| 1 | #include <ATen/Tensor.h> |
|---|---|
| 2 | #include <ATen/core/dispatch/Dispatcher.h> |
| 3 | |
| 4 | // @generated by torchgen/gen.py from Operators.cpp |
| 5 | // NOTE See [Sharded File] comment in VariableType |
| 6 | |
| 7 | #ifndef AT_PER_OPERATOR_HEADERS |
| 8 | #include <ATen/Operators.h> |
| 9 | #else |
| 10 | #include <ATen/ops/_cast_Byte.h> |
| 11 | #include <ATen/ops/_cast_Char.h> |
| 12 | #include <ATen/ops/is_leaf.h> |
| 13 | #include <ATen/ops/requires_grad.h> |
| 14 | #include <ATen/ops/retains_grad.h> |
| 15 | #include <ATen/ops/_unpack_dual.h> |
| 16 | #include <ATen/ops/_has_same_storage_numel.h> |
| 17 | #include <ATen/ops/align_to.h> |
| 18 | #include <ATen/ops/align_to.h> |
| 19 | #include <ATen/ops/_use_cudnn_ctc_loss.h> |
| 20 | #include <ATen/ops/_use_cudnn_ctc_loss.h> |
| 21 | #include <ATen/ops/_cudnn_ctc_loss.h> |
| 22 | #include <ATen/ops/_cudnn_ctc_loss.h> |
| 23 | #include <ATen/ops/_cudnn_rnn.h> |
| 24 | #include <ATen/ops/_debug_has_internal_overlap.h> |
| 25 | #include <ATen/ops/_fused_dropout.h> |
| 26 | #include <ATen/ops/_sobol_engine_initialize_state.h> |
| 27 | #include <ATen/ops/_shape_as_tensor.h> |
| 28 | #include <ATen/ops/dropout.h> |
| 29 | #include <ATen/ops/dropout.h> |
| 30 | #include <ATen/ops/sgn.h> |
| 31 | #include <ATen/ops/sgn.h> |
| 32 | #include <ATen/ops/sgn.h> |
| 33 | #include <ATen/ops/real.h> |
| 34 | #include <ATen/ops/_conj.h> |
| 35 | #include <ATen/ops/_conj_physical.h> |
| 36 | #include <ATen/ops/_neg_view.h> |
| 37 | #include <ATen/ops/avg_pool1d.h> |
| 38 | #include <ATen/ops/adaptive_avg_pool1d.h> |
| 39 | #include <ATen/ops/_is_all_true.h> |
| 40 | #include <ATen/ops/_test_check_tensor.h> |
| 41 | #include <ATen/ops/allclose.h> |
| 42 | #include <ATen/ops/argmax.h> |
| 43 | #include <ATen/ops/argmax.h> |
| 44 | #include <ATen/ops/acosh.h> |
| 45 | #include <ATen/ops/acosh.h> |
| 46 | #include <ATen/ops/acosh.h> |
| 47 | #include <ATen/ops/arctanh.h> |
| 48 | #include <ATen/ops/arctanh.h> |
| 49 | #include <ATen/ops/arctanh.h> |
| 50 | #include <ATen/ops/as_strided.h> |
| 51 | #include <ATen/ops/as_strided.h> |
| 52 | #include <ATen/ops/atleast_3d.h> |
| 53 | #include <ATen/ops/atleast_3d.h> |
| 54 | #include <ATen/ops/_batch_norm_impl_index.h> |
| 55 | #include <ATen/ops/_batch_norm_impl_index_backward.h> |
| 56 | #include <ATen/ops/logical_or.h> |
| 57 | #include <ATen/ops/logical_or.h> |
| 58 | #include <ATen/ops/logical_or.h> |
| 59 | #include <ATen/ops/blackman_window.h> |
| 60 | #include <ATen/ops/blackman_window.h> |
| 61 | #include <ATen/ops/broadcast_tensors.h> |
| 62 | #include <ATen/ops/cat.h> |
| 63 | #include <ATen/ops/cat.h> |
| 64 | #include <ATen/ops/cat.h> |
| 65 | #include <ATen/ops/cat.h> |
| 66 | #include <ATen/ops/convolution.h> |
| 67 | #include <ATen/ops/convolution_backward_overrideable.h> |
| 68 | #include <ATen/ops/_convolution.h> |
| 69 | #include <ATen/ops/_convolution.h> |
| 70 | #include <ATen/ops/conv_transpose1d.h> |
| 71 | #include <ATen/ops/cos.h> |
| 72 | #include <ATen/ops/cos.h> |
| 73 | #include <ATen/ops/cos.h> |
| 74 | #include <ATen/ops/cudnn_affine_grid_generator.h> |
| 75 | #include <ATen/ops/cudnn_batch_norm_backward.h> |
| 76 | #include <ATen/ops/cudnn_convolution_transpose.h> |
| 77 | #include <ATen/ops/cudnn_grid_sampler_backward.h> |
| 78 | #include <ATen/ops/cumsum.h> |
| 79 | #include <ATen/ops/cumsum.h> |
| 80 | #include <ATen/ops/cumsum.h> |
| 81 | #include <ATen/ops/cumsum.h> |
| 82 | #include <ATen/ops/cumsum.h> |
| 83 | #include <ATen/ops/cumsum.h> |
| 84 | #include <ATen/ops/_ctc_loss.h> |
| 85 | #include <ATen/ops/_ctc_loss.h> |
| 86 | #include <ATen/ops/diagflat.h> |
| 87 | #include <ATen/ops/linalg_diagonal.h> |
| 88 | #include <ATen/ops/true_divide.h> |
| 89 | #include <ATen/ops/true_divide.h> |
| 90 | #include <ATen/ops/true_divide.h> |
| 91 | #include <ATen/ops/true_divide.h> |
| 92 | #include <ATen/ops/true_divide.h> |
| 93 | #include <ATen/ops/vdot.h> |
| 94 | #include <ATen/ops/vdot.h> |
| 95 | #include <ATen/ops/embedding_backward.h> |
| 96 | #include <ATen/ops/embedding_dense_backward.h> |
| 97 | #include <ATen/ops/_embedding_bag.h> |
| 98 | #include <ATen/ops/_embedding_bag_sparse_backward.h> |
| 99 | #include <ATen/ops/new_empty.h> |
| 100 | #include <ATen/ops/expm1.h> |
| 101 | #include <ATen/ops/expm1.h> |
| 102 | #include <ATen/ops/expm1.h> |
| 103 | #include <ATen/ops/expand_as.h> |
| 104 | #include <ATen/ops/unflatten.h> |
| 105 | #include <ATen/ops/unflatten.h> |
| 106 | #include <ATen/ops/fill.h> |
| 107 | #include <ATen/ops/fill.h> |
| 108 | #include <ATen/ops/fill.h> |
| 109 | #include <ATen/ops/fill.h> |
| 110 | #include <ATen/ops/lcm.h> |
| 111 | #include <ATen/ops/lcm.h> |
| 112 | #include <ATen/ops/lcm.h> |
| 113 | #include <ATen/ops/grid_sampler_2d_backward.h> |
| 114 | #include <ATen/ops/group_norm.h> |
| 115 | #include <ATen/ops/index_copy.h> |
| 116 | #include <ATen/ops/index_copy.h> |
| 117 | #include <ATen/ops/index_copy.h> |
| 118 | #include <ATen/ops/index_copy.h> |
| 119 | #include <ATen/ops/index_copy.h> |
| 120 | #include <ATen/ops/_index_put_impl.h> |
| 121 | #include <ATen/ops/is_distributed.h> |
| 122 | #include <ATen/ops/is_inference.h> |
| 123 | #include <ATen/ops/kron.h> |
| 124 | #include <ATen/ops/kron.h> |
| 125 | #include <ATen/ops/linear.h> |
| 126 | #include <ATen/ops/linear.h> |
| 127 | #include <ATen/ops/mkldnn_linear.h> |
| 128 | #include <ATen/ops/mkldnn_linear_backward_weights.h> |
| 129 | #include <ATen/ops/fbgemm_linear_quantize_weight.h> |
| 130 | #include <ATen/ops/linspace.h> |
| 131 | #include <ATen/ops/linspace.h> |
| 132 | #include <ATen/ops/log10.h> |
| 133 | #include <ATen/ops/log10.h> |
| 134 | #include <ATen/ops/log10.h> |
| 135 | #include <ATen/ops/log1p.h> |
| 136 | #include <ATen/ops/log1p.h> |
| 137 | #include <ATen/ops/log1p.h> |
| 138 | #include <ATen/ops/logaddexp2.h> |
| 139 | #include <ATen/ops/logaddexp2.h> |
| 140 | #include <ATen/ops/_log_softmax.h> |
| 141 | #include <ATen/ops/_log_softmax.h> |
| 142 | #include <ATen/ops/logsumexp.h> |
| 143 | #include <ATen/ops/logsumexp.h> |
| 144 | #include <ATen/ops/logsumexp.h> |
| 145 | #include <ATen/ops/logsumexp.h> |
| 146 | #include <ATen/ops/_aminmax.h> |
| 147 | #include <ATen/ops/_aminmax.h> |
| 148 | #include <ATen/ops/aminmax.h> |
| 149 | #include <ATen/ops/aminmax.h> |
| 150 | #include <ATen/ops/max.h> |
| 151 | #include <ATen/ops/max.h> |
| 152 | #include <ATen/ops/max.h> |
| 153 | #include <ATen/ops/max.h> |
| 154 | #include <ATen/ops/max_pool1d_with_indices.h> |
| 155 | #include <ATen/ops/mkldnn_max_pool3d_backward.h> |
| 156 | #include <ATen/ops/quantized_max_pool1d.h> |
| 157 | #include <ATen/ops/mkldnn_convolution.h> |
| 158 | #include <ATen/ops/miopen_batch_norm_backward.h> |
| 159 | #include <ATen/ops/miopen_convolution_relu.h> |
| 160 | #include <ATen/ops/mode.h> |
| 161 | #include <ATen/ops/mode.h> |
| 162 | #include <ATen/ops/mode.h> |
| 163 | #include <ATen/ops/mode.h> |
| 164 | #include <ATen/ops/mul.h> |
| 165 | #include <ATen/ops/mul.h> |
| 166 | #include <ATen/ops/mul.h> |
| 167 | #include <ATen/ops/mul.h> |
| 168 | #include <ATen/ops/mul.h> |
| 169 | #include <ATen/ops/mvlgamma.h> |
| 170 | #include <ATen/ops/mvlgamma.h> |
| 171 | #include <ATen/ops/mvlgamma.h> |
| 172 | #include <ATen/ops/narrow.h> |
| 173 | #include <ATen/ops/narrow.h> |
| 174 | #include <ATen/ops/batch_norm_backward_elemt.h> |
| 175 | #include <ATen/ops/pdist.h> |
| 176 | #include <ATen/ops/moveaxis.h> |
| 177 | #include <ATen/ops/moveaxis.h> |
| 178 | #include <ATen/ops/pixel_unshuffle.h> |
| 179 | #include <ATen/ops/is_pinned.h> |
| 180 | #include <ATen/ops/pin_memory.h> |
| 181 | #include <ATen/ops/_pin_memory.h> |
| 182 | #include <ATen/ops/randn.h> |
| 183 | #include <ATen/ops/randn.h> |
| 184 | #include <ATen/ops/randn.h> |
| 185 | #include <ATen/ops/randn.h> |
| 186 | #include <ATen/ops/randn.h> |
| 187 | #include <ATen/ops/randn.h> |
| 188 | #include <ATen/ops/range.h> |
| 189 | #include <ATen/ops/range.h> |
| 190 | #include <ATen/ops/range.h> |
| 191 | #include <ATen/ops/range.h> |
| 192 | #include <ATen/ops/ravel.h> |
| 193 | #include <ATen/ops/reciprocal.h> |
| 194 | #include <ATen/ops/reciprocal.h> |
| 195 | #include <ATen/ops/reciprocal.h> |
| 196 | #include <ATen/ops/neg.h> |
| 197 | #include <ATen/ops/neg.h> |
| 198 | #include <ATen/ops/neg.h> |
| 199 | #include <ATen/ops/reshape_as.h> |
| 200 | #include <ATen/ops/rrelu.h> |
| 201 | #include <ATen/ops/rrelu.h> |
| 202 | #include <ATen/ops/relu6.h> |
| 203 | #include <ATen/ops/relu6.h> |
| 204 | #include <ATen/ops/prelu.h> |
| 205 | #include <ATen/ops/_prelu_kernel_backward.h> |
| 206 | #include <ATen/ops/gelu_backward.h> |
| 207 | #include <ATen/ops/gelu_backward.h> |
| 208 | #include <ATen/ops/selu.h> |
| 209 | #include <ATen/ops/selu.h> |
| 210 | #include <ATen/ops/silu_backward.h> |
| 211 | #include <ATen/ops/silu_backward.h> |
| 212 | #include <ATen/ops/sin.h> |
| 213 | #include <ATen/ops/sin.h> |
| 214 | #include <ATen/ops/sin.h> |
| 215 | #include <ATen/ops/diagonal_scatter.h> |
| 216 | #include <ATen/ops/as_strided_scatter.h> |
| 217 | #include <ATen/ops/split.h> |
| 218 | #include <ATen/ops/split.h> |
| 219 | #include <ATen/ops/squeeze.h> |
| 220 | #include <ATen/ops/squeeze.h> |
| 221 | #include <ATen/ops/squeeze.h> |
| 222 | #include <ATen/ops/squeeze.h> |
| 223 | #include <ATen/ops/squeeze.h> |
| 224 | #include <ATen/ops/squeeze.h> |
| 225 | #include <ATen/ops/squeeze.h> |
| 226 | #include <ATen/ops/squeeze.h> |
| 227 | #include <ATen/ops/sspaddmm.h> |
| 228 | #include <ATen/ops/sspaddmm.h> |
| 229 | #include <ATen/ops/stride.h> |
| 230 | #include <ATen/ops/stride.h> |
| 231 | #include <ATen/ops/threshold_backward.h> |
| 232 | #include <ATen/ops/threshold_backward.h> |
| 233 | #include <ATen/ops/one_hot.h> |
| 234 | #include <ATen/ops/_transform_bias_rescale_qkv.h> |
| 235 | #include <ATen/ops/_unique.h> |
| 236 | #include <ATen/ops/where.h> |
| 237 | #include <ATen/ops/where.h> |
| 238 | #include <ATen/ops/where.h> |
| 239 | #include <ATen/ops/where.h> |
| 240 | #include <ATen/ops/where.h> |
| 241 | #include <ATen/ops/where.h> |
| 242 | #include <ATen/ops/_weight_norm.h> |
| 243 | #include <ATen/ops/_weight_norm_interface.h> |
| 244 | #include <ATen/ops/_weight_norm_differentiable_backward.h> |
| 245 | #include <ATen/ops/zeros.h> |
| 246 | #include <ATen/ops/zeros.h> |
| 247 | #include <ATen/ops/zeros.h> |
| 248 | #include <ATen/ops/_standard_gamma.h> |
| 249 | #include <ATen/ops/_sample_dirichlet.h> |
| 250 | #include <ATen/ops/binomial.h> |
| 251 | #include <ATen/ops/_sparse_sum.h> |
| 252 | #include <ATen/ops/_sparse_sum.h> |
| 253 | #include <ATen/ops/_sparse_sum.h> |
| 254 | #include <ATen/ops/_sparse_sum.h> |
| 255 | #include <ATen/ops/_sparse_addmm.h> |
| 256 | #include <ATen/ops/_sparse_mm_reduce_impl_backward.h> |
| 257 | #include <ATen/ops/addmm.h> |
| 258 | #include <ATen/ops/addmm.h> |
| 259 | #include <ATen/ops/addmm.h> |
| 260 | #include <ATen/ops/sparse_csc_tensor.h> |
| 261 | #include <ATen/ops/sparse_bsc_tensor.h> |
| 262 | #include <ATen/ops/sparse_csc_tensor.h> |
| 263 | #include <ATen/ops/sparse_bsc_tensor.h> |
| 264 | #include <ATen/ops/_sparse_compressed_tensor_unsafe.h> |
| 265 | #include <ATen/ops/_sparse_csr_tensor_unsafe.h> |
| 266 | #include <ATen/ops/_sparse_coo_tensor_unsafe.h> |
| 267 | #include <ATen/ops/_validate_sparse_csr_tensor_args.h> |
| 268 | #include <ATen/ops/_validate_sparse_bsr_tensor_args.h> |
| 269 | #include <ATen/ops/_validate_sparse_bsc_tensor_args.h> |
| 270 | #include <ATen/ops/sparse_resize.h> |
| 271 | #include <ATen/ops/sparse_mask.h> |
| 272 | #include <ATen/ops/_to_cpu.h> |
| 273 | #include <ATen/ops/values.h> |
| 274 | #include <ATen/ops/row_indices.h> |
| 275 | #include <ATen/ops/copy_sparse_to_sparse.h> |
| 276 | #include <ATen/ops/unbind.h> |
| 277 | #include <ATen/ops/unbind.h> |
| 278 | #include <ATen/ops/to_sparse.h> |
| 279 | #include <ATen/ops/to_sparse.h> |
| 280 | #include <ATen/ops/to_mkldnn.h> |
| 281 | #include <ATen/ops/to_mkldnn_backward.h> |
| 282 | #include <ATen/ops/int_repr.h> |
| 283 | #include <ATen/ops/qscheme.h> |
| 284 | #include <ATen/ops/fake_quantize_per_channel_affine.h> |
| 285 | #include <ATen/ops/fake_quantize_per_channel_affine_cachemask.h> |
| 286 | #include <ATen/ops/_fused_moving_avg_obs_fq_helper.h> |
| 287 | #include <ATen/ops/_to_copy.h> |
| 288 | #include <ATen/ops/_thnn_differentiable_lstm_cell_backward.h> |
| 289 | #include <ATen/ops/_thnn_differentiable_gru_cell_backward.h> |
| 290 | #include <ATen/ops/rnn_tanh_cell.h> |
| 291 | #include <ATen/ops/quantized_gru_cell.h> |
| 292 | #include <ATen/ops/_pack_padded_sequence_backward.h> |
| 293 | #include <ATen/ops/lift.h> |
| 294 | #include <ATen/ops/lift_fresh.h> |
| 295 | #include <ATen/ops/eq.h> |
| 296 | #include <ATen/ops/eq.h> |
| 297 | #include <ATen/ops/bitwise_and.h> |
| 298 | #include <ATen/ops/bitwise_and.h> |
| 299 | #include <ATen/ops/bitwise_and.h> |
| 300 | #include <ATen/ops/bitwise_and.h> |
| 301 | #include <ATen/ops/bitwise_and.h> |
| 302 | #include <ATen/ops/bitwise_and.h> |
| 303 | #include <ATen/ops/bitwise_and.h> |
| 304 | #include <ATen/ops/or.h> |
| 305 | #include <ATen/ops/or.h> |
| 306 | #include <ATen/ops/or.h> |
| 307 | #include <ATen/ops/or.h> |
| 308 | #include <ATen/ops/bitwise_xor.h> |
| 309 | #include <ATen/ops/bitwise_xor.h> |
| 310 | #include <ATen/ops/bitwise_xor.h> |
| 311 | #include <ATen/ops/bitwise_xor.h> |
| 312 | #include <ATen/ops/bitwise_xor.h> |
| 313 | #include <ATen/ops/bitwise_xor.h> |
| 314 | #include <ATen/ops/bitwise_xor.h> |
| 315 | #include <ATen/ops/lshift.h> |
| 316 | #include <ATen/ops/lshift.h> |
| 317 | #include <ATen/ops/lshift.h> |
| 318 | #include <ATen/ops/lshift.h> |
| 319 | #include <ATen/ops/bitwise_left_shift.h> |
| 320 | #include <ATen/ops/bitwise_left_shift.h> |
| 321 | #include <ATen/ops/bitwise_left_shift.h> |
| 322 | #include <ATen/ops/bitwise_left_shift.h> |
| 323 | #include <ATen/ops/bitwise_left_shift.h> |
| 324 | #include <ATen/ops/bitwise_left_shift.h> |
| 325 | #include <ATen/ops/bitwise_left_shift.h> |
| 326 | #include <ATen/ops/rshift.h> |
| 327 | #include <ATen/ops/rshift.h> |
| 328 | #include <ATen/ops/rshift.h> |
| 329 | #include <ATen/ops/rshift.h> |
| 330 | #include <ATen/ops/bitwise_right_shift.h> |
| 331 | #include <ATen/ops/bitwise_right_shift.h> |
| 332 | #include <ATen/ops/bitwise_right_shift.h> |
| 333 | #include <ATen/ops/bitwise_right_shift.h> |
| 334 | #include <ATen/ops/bitwise_right_shift.h> |
| 335 | #include <ATen/ops/bitwise_right_shift.h> |
| 336 | #include <ATen/ops/bitwise_right_shift.h> |
| 337 | #include <ATen/ops/exponential.h> |
| 338 | #include <ATen/ops/geometric.h> |
| 339 | #include <ATen/ops/trace_backward.h> |
| 340 | #include <ATen/ops/eq.h> |
| 341 | #include <ATen/ops/eq.h> |
| 342 | #include <ATen/ops/eq.h> |
| 343 | #include <ATen/ops/eq.h> |
| 344 | #include <ATen/ops/le.h> |
| 345 | #include <ATen/ops/le.h> |
| 346 | #include <ATen/ops/le.h> |
| 347 | #include <ATen/ops/le.h> |
| 348 | #include <ATen/ops/le.h> |
| 349 | #include <ATen/ops/le.h> |
| 350 | #include <ATen/ops/take_along_dim.h> |
| 351 | #include <ATen/ops/take_along_dim.h> |
| 352 | #include <ATen/ops/index_select.h> |
| 353 | #include <ATen/ops/index_select.h> |
| 354 | #include <ATen/ops/index_select.h> |
| 355 | #include <ATen/ops/index_select.h> |
| 356 | #include <ATen/ops/masked_select_backward.h> |
| 357 | #include <ATen/ops/nonzero.h> |
| 358 | #include <ATen/ops/nonzero.h> |
| 359 | #include <ATen/ops/nonzero_numpy.h> |
| 360 | #include <ATen/ops/addcmul.h> |
| 361 | #include <ATen/ops/addcmul.h> |
| 362 | #include <ATen/ops/addcmul.h> |
| 363 | #include <ATen/ops/swapdims.h> |
| 364 | #include <ATen/ops/swapdims.h> |
| 365 | #include <ATen/ops/cholesky.h> |
| 366 | #include <ATen/ops/cholesky.h> |
| 367 | #include <ATen/ops/lu_solve.h> |
| 368 | #include <ATen/ops/lu_solve.h> |
| 369 | #include <ATen/ops/lu_unpack.h> |
| 370 | #include <ATen/ops/lu_unpack.h> |
| 371 | #include <ATen/ops/multinomial.h> |
| 372 | #include <ATen/ops/multinomial.h> |
| 373 | #include <ATen/ops/lgamma.h> |
| 374 | #include <ATen/ops/lgamma.h> |
| 375 | #include <ATen/ops/lgamma.h> |
| 376 | #include <ATen/ops/arctan2.h> |
| 377 | #include <ATen/ops/arctan2.h> |
| 378 | #include <ATen/ops/arctan2.h> |
| 379 | #include <ATen/ops/histogram.h> |
| 380 | #include <ATen/ops/histogram.h> |
| 381 | #include <ATen/ops/histogram.h> |
| 382 | #include <ATen/ops/histogram.h> |
| 383 | #include <ATen/ops/igamma.h> |
| 384 | #include <ATen/ops/igamma.h> |
| 385 | #include <ATen/ops/igamma.h> |
| 386 | #include <ATen/ops/max.h> |
| 387 | #include <ATen/ops/max.h> |
| 388 | #include <ATen/ops/max.h> |
| 389 | #include <ATen/ops/max.h> |
| 390 | #include <ATen/ops/pow.h> |
| 391 | #include <ATen/ops/pow.h> |
| 392 | #include <ATen/ops/pow.h> |
| 393 | #include <ATen/ops/pow.h> |
| 394 | #include <ATen/ops/pow.h> |
| 395 | #include <ATen/ops/pow.h> |
| 396 | #include <ATen/ops/pow.h> |
| 397 | #include <ATen/ops/pow.h> |
| 398 | #include <ATen/ops/_amp_foreach_non_finite_check_and_unscale.h> |
| 399 | #include <ATen/ops/_foreach_add.h> |
| 400 | #include <ATen/ops/_foreach_add.h> |
| 401 | #include <ATen/ops/_foreach_clamp_min.h> |
| 402 | #include <ATen/ops/_foreach_clamp_min.h> |
| 403 | #include <ATen/ops/_foreach_minimum.h> |
| 404 | #include <ATen/ops/_foreach_minimum.h> |
| 405 | #include <ATen/ops/_foreach_add.h> |
| 406 | #include <ATen/ops/_foreach_add.h> |
| 407 | #include <ATen/ops/_foreach_clamp_min.h> |
| 408 | #include <ATen/ops/_foreach_clamp_min.h> |
| 409 | #include <ATen/ops/_foreach_minimum.h> |
| 410 | #include <ATen/ops/_foreach_minimum.h> |
| 411 | #include <ATen/ops/_foreach_add.h> |
| 412 | #include <ATen/ops/_foreach_add.h> |
| 413 | #include <ATen/ops/_foreach_clamp_min.h> |
| 414 | #include <ATen/ops/_foreach_clamp_min.h> |
| 415 | #include <ATen/ops/_foreach_minimum.h> |
| 416 | #include <ATen/ops/_foreach_minimum.h> |
| 417 | #include <ATen/ops/_foreach_cosh.h> |
| 418 | #include <ATen/ops/_foreach_cosh.h> |
| 419 | #include <ATen/ops/_foreach_erfc.h> |
| 420 | #include <ATen/ops/_foreach_erfc.h> |
| 421 | #include <ATen/ops/_foreach_round.h> |
| 422 | #include <ATen/ops/_foreach_round.h> |
| 423 | #include <ATen/ops/_foreach_lgamma.h> |
| 424 | #include <ATen/ops/_foreach_lgamma.h> |
| 425 | #include <ATen/ops/_foreach_frac.h> |
| 426 | #include <ATen/ops/_foreach_frac.h> |
| 427 | #include <ATen/ops/_foreach_trunc.h> |
| 428 | #include <ATen/ops/_foreach_trunc.h> |
| 429 | #include <ATen/ops/_foreach_lerp.h> |
| 430 | #include <ATen/ops/_foreach_lerp.h> |
| 431 | #include <ATen/ops/_foreach_lerp.h> |
| 432 | #include <ATen/ops/_foreach_lerp.h> |
| 433 | #include <ATen/ops/mse_loss_backward.h> |
| 434 | #include <ATen/ops/mse_loss_backward.h> |
| 435 | #include <ATen/ops/multi_margin_loss_backward.h> |
| 436 | #include <ATen/ops/multi_margin_loss_backward.h> |
| 437 | #include <ATen/ops/multilabel_margin_loss_backward.h> |
| 438 | #include <ATen/ops/multilabel_margin_loss_backward.h> |
| 439 | #include <ATen/ops/elu_backward.h> |
| 440 | #include <ATen/ops/elu_backward.h> |
| 441 | #include <ATen/ops/hardsigmoid_backward.h> |
| 442 | #include <ATen/ops/hardsigmoid_backward.h> |
| 443 | #include <ATen/ops/rrelu_with_noise_backward.h> |
| 444 | #include <ATen/ops/softplus_backward.h> |
| 445 | #include <ATen/ops/softplus_backward.h> |
| 446 | #include <ATen/ops/mkldnn_adaptive_avg_pool2d_backward.h> |
| 447 | #include <ATen/ops/fractional_max_pool3d_backward.h> |
| 448 | #include <ATen/ops/fractional_max_pool3d_backward.h> |
| 449 | #include <ATen/ops/max_pool2d_with_indices.h> |
| 450 | #include <ATen/ops/max_pool2d_with_indices.h> |
| 451 | #include <ATen/ops/reflection_pad1d.h> |
| 452 | #include <ATen/ops/reflection_pad1d.h> |
| 453 | #include <ATen/ops/_pad_enum.h> |
| 454 | #include <ATen/ops/upsample_trilinear3d.h> |
| 455 | #include <ATen/ops/_upsample_bicubic2d_aa.h> |
| 456 | #include <ATen/ops/upsample_nearest3d.h> |
| 457 | #include <ATen/ops/_upsample_bilinear2d_aa_backward.h> |
| 458 | #include <ATen/ops/_upsample_bilinear2d_aa_backward.h> |
| 459 | #include <ATen/ops/_upsample_bicubic2d_aa.h> |
| 460 | #include <ATen/ops/_upsample_bicubic2d_aa.h> |
| 461 | #include <ATen/ops/upsample_trilinear3d.h> |
| 462 | #include <ATen/ops/upsample_trilinear3d.h> |
| 463 | #include <ATen/ops/upsample_nearest3d.h> |
| 464 | #include <ATen/ops/upsample_nearest3d.h> |
| 465 | #include <ATen/ops/sigmoid_backward.h> |
| 466 | #include <ATen/ops/sigmoid_backward.h> |
| 467 | #include <ATen/ops/tanh_backward.h> |
| 468 | #include <ATen/ops/tanh_backward.h> |
| 469 | #include <ATen/ops/thnn_conv2d.h> |
| 470 | #include <ATen/ops/thnn_conv2d.h> |
| 471 | #include <ATen/ops/_slow_conv2d_forward.h> |
| 472 | #include <ATen/ops/_slow_conv2d_forward.h> |
| 473 | #include <ATen/ops/column_stack.h> |
| 474 | #include <ATen/ops/column_stack.h> |
| 475 | #include <ATen/ops/special_entr.h> |
| 476 | #include <ATen/ops/special_entr.h> |
| 477 | #include <ATen/ops/special_ndtri.h> |
| 478 | #include <ATen/ops/special_ndtri.h> |
| 479 | #include <ATen/ops/special_erfc.h> |
| 480 | #include <ATen/ops/special_erfc.h> |
| 481 | #include <ATen/ops/special_i1e.h> |
| 482 | #include <ATen/ops/special_i1e.h> |
| 483 | #include <ATen/ops/special_logsumexp.h> |
| 484 | #include <ATen/ops/special_logsumexp.h> |
| 485 | #include <ATen/ops/special_gammainc.h> |
| 486 | #include <ATen/ops/special_gammainc.h> |
| 487 | #include <ATen/ops/fft_rfft2.h> |
| 488 | #include <ATen/ops/fft_rfft2.h> |
| 489 | #include <ATen/ops/fft_hfftn.h> |
| 490 | #include <ATen/ops/fft_hfftn.h> |
| 491 | #include <ATen/ops/linalg_lu.h> |
| 492 | #include <ATen/ops/linalg_lu.h> |
| 493 | #include <ATen/ops/linalg_ldl_factor_ex.h> |
| 494 | #include <ATen/ops/linalg_ldl_factor_ex.h> |
| 495 | #include <ATen/ops/linalg_ldl_solve.h> |
| 496 | #include <ATen/ops/linalg_ldl_solve.h> |
| 497 | #include <ATen/ops/linalg_lstsq.h> |
| 498 | #include <ATen/ops/linalg_lstsq.h> |
| 499 | #include <ATen/ops/linalg_vecdot.h> |
| 500 | #include <ATen/ops/linalg_vecdot.h> |
| 501 | #include <ATen/ops/linalg_matrix_exp.h> |
| 502 | #include <ATen/ops/_linalg_eigh.h> |
| 503 | #include <ATen/ops/_linalg_eigh.h> |
| 504 | #include <ATen/ops/linalg_norm.h> |
| 505 | #include <ATen/ops/linalg_norm.h> |
| 506 | #include <ATen/ops/linalg_norm.h> |
| 507 | #include <ATen/ops/linalg_norm.h> |
| 508 | #include <ATen/ops/linalg_svdvals.h> |
| 509 | #include <ATen/ops/linalg_svdvals.h> |
| 510 | #include <ATen/ops/linalg_matrix_power.h> |
| 511 | #include <ATen/ops/linalg_matrix_power.h> |
| 512 | #include <ATen/ops/_test_serialization_subcmul.h> |
| 513 | #include <ATen/ops/_test_optional_intlist.h> |
| 514 | #include <ATen/ops/_test_ambiguous_defaults.h> |
| 515 | #include <ATen/ops/_test_ambiguous_defaults.h> |
| 516 | #include <ATen/ops/_test_autograd_multiple_dispatch.h> |
| 517 | #include <ATen/ops/_test_autograd_multiple_dispatch.h> |
| 518 | #include <ATen/ops/segment_reduce.h> |
| 519 | #include <ATen/ops/_segment_reduce_backward.h> |
| 520 | #include <ATen/ops/_make_dual_copy.h> |
| 521 | #include <ATen/ops/view_as_complex_copy.h> |
| 522 | #include <ATen/ops/_neg_view_copy.h> |
| 523 | #include <ATen/ops/expand_copy.h> |
| 524 | #include <ATen/ops/unsqueeze_copy.h> |
| 525 | #include <ATen/ops/crow_indices_copy.h> |
| 526 | #include <ATen/ops/to_padded_tensor.h> |
| 527 | #include <ATen/ops/_nested_tensor_softmax_with_shape.h> |
| 528 | #include <ATen/ops/_flash_attention_forward.h> |
| 529 | #include <ATen/ops/special_bessel_j0.h> |
| 530 | #include <ATen/ops/special_bessel_j0.h> |
| 531 | #include <ATen/ops/special_bessel_y0.h> |
| 532 | #include <ATen/ops/special_bessel_y0.h> |
| 533 | #include <ATen/ops/special_chebyshev_polynomial_u.h> |
| 534 | #include <ATen/ops/special_chebyshev_polynomial_u.h> |
| 535 | #include <ATen/ops/special_chebyshev_polynomial_u.h> |
| 536 | #include <ATen/ops/special_chebyshev_polynomial_u.h> |
| 537 | #include <ATen/ops/special_chebyshev_polynomial_u.h> |
| 538 | #include <ATen/ops/special_chebyshev_polynomial_u.h> |
| 539 | #include <ATen/ops/special_hermite_polynomial_he.h> |
| 540 | #include <ATen/ops/special_hermite_polynomial_he.h> |
| 541 | #include <ATen/ops/special_hermite_polynomial_he.h> |
| 542 | #include <ATen/ops/special_hermite_polynomial_he.h> |
| 543 | #include <ATen/ops/special_hermite_polynomial_he.h> |
| 544 | #include <ATen/ops/special_hermite_polynomial_he.h> |
| 545 | #include <ATen/ops/special_modified_bessel_i1.h> |
| 546 | #include <ATen/ops/special_modified_bessel_i1.h> |
| 547 | #include <ATen/ops/special_shifted_chebyshev_polynomial_v.h> |
| 548 | #include <ATen/ops/special_shifted_chebyshev_polynomial_v.h> |
| 549 | #include <ATen/ops/special_shifted_chebyshev_polynomial_v.h> |
| 550 | #include <ATen/ops/special_shifted_chebyshev_polynomial_v.h> |
| 551 | #include <ATen/ops/special_shifted_chebyshev_polynomial_v.h> |
| 552 | #include <ATen/ops/special_shifted_chebyshev_polynomial_v.h> |
| 553 | #include <ATen/ops/special_shifted_chebyshev_polynomial_w.h> |
| 554 | #include <ATen/ops/special_shifted_chebyshev_polynomial_w.h> |
| 555 | #include <ATen/ops/special_shifted_chebyshev_polynomial_w.h> |
| 556 | #include <ATen/ops/special_shifted_chebyshev_polynomial_w.h> |
| 557 | #include <ATen/ops/special_shifted_chebyshev_polynomial_w.h> |
| 558 | #include <ATen/ops/special_shifted_chebyshev_polynomial_w.h> |
| 559 | #include <ATen/ops/special_spherical_bessel_j0.h> |
| 560 | #include <ATen/ops/special_spherical_bessel_j0.h> |
| 561 | #include <ATen/ops/_cudnn_ctc_loss.h> |
| 562 | #include <ATen/ops/_cudnn_rnn.h> |
| 563 | #include <ATen/ops/_fused_dropout.h> |
| 564 | #include <ATen/ops/_conj_physical.h> |
| 565 | #include <ATen/ops/blackman_window.h> |
| 566 | #include <ATen/ops/blackman_window.h> |
| 567 | #include <ATen/ops/convolution.h> |
| 568 | #include <ATen/ops/convolution_backward_overrideable.h> |
| 569 | #include <ATen/ops/_convolution.h> |
| 570 | #include <ATen/ops/cudnn_affine_grid_generator.h> |
| 571 | #include <ATen/ops/cudnn_batch_norm_backward.h> |
| 572 | #include <ATen/ops/cudnn_convolution_transpose.h> |
| 573 | #include <ATen/ops/cudnn_grid_sampler_backward.h> |
| 574 | #include <ATen/ops/_ctc_loss.h> |
| 575 | #include <ATen/ops/_ctc_loss.h> |
| 576 | #include <ATen/ops/embedding_dense_backward.h> |
| 577 | #include <ATen/ops/_embedding_bag.h> |
| 578 | #include <ATen/ops/new_empty.h> |
| 579 | #include <ATen/ops/fill.h> |
| 580 | #include <ATen/ops/fill.h> |
| 581 | #include <ATen/ops/grid_sampler_2d_backward.h> |
| 582 | #include <ATen/ops/_index_put_impl.h> |
| 583 | #include <ATen/ops/_index_put_impl.h> |
| 584 | #include <ATen/ops/mkldnn_linear.h> |
| 585 | #include <ATen/ops/mkldnn_linear_backward_weights.h> |
| 586 | #include <ATen/ops/_aminmax.h> |
| 587 | #include <ATen/ops/_aminmax.h> |
| 588 | #include <ATen/ops/mkldnn_max_pool3d_backward.h> |
| 589 | #include <ATen/ops/quantized_max_pool1d.h> |
| 590 | #include <ATen/ops/mkldnn_convolution.h> |
| 591 | #include <ATen/ops/miopen_batch_norm_backward.h> |
| 592 | #include <ATen/ops/mul.h> |
| 593 | #include <ATen/ops/batch_norm_backward_elemt.h> |
| 594 | #include <ATen/ops/pixel_unshuffle.h> |
| 595 | #include <ATen/ops/_pin_memory.h> |
| 596 | #include <ATen/ops/randn.h> |
| 597 | #include <ATen/ops/randn.h> |
| 598 | #include <ATen/ops/diagonal_scatter.h> |
| 599 | #include <ATen/ops/as_strided_scatter.h> |
| 600 | #include <ATen/ops/_transform_bias_rescale_qkv.h> |
| 601 | #include <ATen/ops/_unique.h> |
| 602 | #include <ATen/ops/_weight_norm_interface.h> |
| 603 | #include <ATen/ops/zeros.h> |
| 604 | #include <ATen/ops/_standard_gamma.h> |
| 605 | #include <ATen/ops/_sample_dirichlet.h> |
| 606 | #include <ATen/ops/binomial.h> |
| 607 | #include <ATen/ops/_sparse_sum.h> |
| 608 | #include <ATen/ops/_sparse_addmm.h> |
| 609 | #include <ATen/ops/sparse_resize.h> |
| 610 | #include <ATen/ops/sparse_resize.h> |
| 611 | #include <ATen/ops/sparse_mask.h> |
| 612 | #include <ATen/ops/copy_sparse_to_sparse.h> |
| 613 | #include <ATen/ops/copy_sparse_to_sparse.h> |
| 614 | #include <ATen/ops/to_sparse.h> |
| 615 | #include <ATen/ops/to_sparse.h> |
| 616 | #include <ATen/ops/to_mkldnn.h> |
| 617 | #include <ATen/ops/int_repr.h> |
| 618 | #include <ATen/ops/fake_quantize_per_channel_affine_cachemask.h> |
| 619 | #include <ATen/ops/_fused_moving_avg_obs_fq_helper.h> |
| 620 | #include <ATen/ops/_fused_moving_avg_obs_fq_helper.h> |
| 621 | #include <ATen/ops/_to_copy.h> |
| 622 | #include <ATen/ops/lift.h> |
| 623 | #include <ATen/ops/bitwise_and.h> |
| 624 | #include <ATen/ops/bitwise_xor.h> |
| 625 | #include <ATen/ops/lshift.h> |
| 626 | #include <ATen/ops/lshift.h> |
| 627 | #include <ATen/ops/bitwise_left_shift.h> |
| 628 | #include <ATen/ops/rshift.h> |
| 629 | #include <ATen/ops/rshift.h> |
| 630 | #include <ATen/ops/bitwise_right_shift.h> |
| 631 | #include <ATen/ops/exponential.h> |
| 632 | #include <ATen/ops/exponential.h> |
| 633 | #include <ATen/ops/geometric.h> |
| 634 | #include <ATen/ops/geometric.h> |
| 635 | #include <ATen/ops/_amp_foreach_non_finite_check_and_unscale.h> |
| 636 | #include <ATen/ops/_amp_foreach_non_finite_check_and_unscale.h> |
| 637 | #include <ATen/ops/_foreach_add.h> |
| 638 | #include <ATen/ops/_foreach_clamp_min.h> |
| 639 | #include <ATen/ops/_foreach_minimum.h> |
| 640 | #include <ATen/ops/_foreach_add.h> |
| 641 | #include <ATen/ops/_foreach_clamp_min.h> |
| 642 | #include <ATen/ops/_foreach_minimum.h> |
| 643 | #include <ATen/ops/_foreach_add.h> |
| 644 | #include <ATen/ops/_foreach_clamp_min.h> |
| 645 | #include <ATen/ops/_foreach_minimum.h> |
| 646 | #include <ATen/ops/_foreach_cosh.h> |
| 647 | #include <ATen/ops/_foreach_erfc.h> |
| 648 | #include <ATen/ops/_foreach_round.h> |
| 649 | #include <ATen/ops/_foreach_lgamma.h> |
| 650 | #include <ATen/ops/_foreach_frac.h> |
| 651 | #include <ATen/ops/_foreach_trunc.h> |
| 652 | #include <ATen/ops/_foreach_lerp.h> |
| 653 | #include <ATen/ops/_foreach_lerp.h> |
| 654 | #include <ATen/ops/rrelu_with_noise_backward.h> |
| 655 | #include <ATen/ops/mkldnn_adaptive_avg_pool2d_backward.h> |
| 656 | #include <ATen/ops/linalg_matrix_exp.h> |
| 657 | #include <ATen/ops/_test_optional_intlist.h> |
| 658 | #include <ATen/ops/_test_autograd_multiple_dispatch.h> |
| 659 | #include <ATen/ops/segment_reduce.h> |
| 660 | #include <ATen/ops/_segment_reduce_backward.h> |
| 661 | #include <ATen/ops/_make_dual_copy.h> |
| 662 | #include <ATen/ops/view_as_complex_copy.h> |
| 663 | #include <ATen/ops/_neg_view_copy.h> |
| 664 | #include <ATen/ops/expand_copy.h> |
| 665 | #include <ATen/ops/unsqueeze_copy.h> |
| 666 | #include <ATen/ops/crow_indices_copy.h> |
| 667 | #include <ATen/ops/to_padded_tensor.h> |
| 668 | #endif |
| 669 | |
| 670 | |
| 671 | |
| 672 | namespace at { namespace _ops { |
| 673 | |
| 674 | |
| 675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Byte, name, "aten::_cast_Byte") |
| 676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Byte, overload_name, "") |
| 677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Byte, schema_str, "_cast_Byte(Tensor self, bool non_blocking=False) -> Tensor") |
| 678 | |
| 679 | // aten::_cast_Byte(Tensor self, bool non_blocking=False) -> Tensor |
| 680 | static C10_NOINLINE c10::TypedOperatorHandle<_cast_Byte::schema> create__cast_Byte_typed_handle() { |
| 681 | return c10::Dispatcher::singleton() |
| 682 | .findSchemaOrThrow(_cast_Byte::name, _cast_Byte::overload_name) |
| 683 | .typed<_cast_Byte::schema>(); |
| 684 | } |
| 685 | |
| 686 | // aten::_cast_Byte(Tensor self, bool non_blocking=False) -> Tensor |
| 687 | at::Tensor _cast_Byte::call(const at::Tensor & self, bool non_blocking) { |
| 688 | |
| 689 | static auto op = create__cast_Byte_typed_handle(); |
| 690 | return op.call(self, non_blocking); |
| 691 | } |
| 692 | |
| 693 | // aten::_cast_Byte(Tensor self, bool non_blocking=False) -> Tensor |
| 694 | at::Tensor _cast_Byte::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking) { |
| 695 | |
| 696 | static auto op = create__cast_Byte_typed_handle(); |
| 697 | return op.redispatch(dispatchKeySet, self, non_blocking); |
| 698 | } |
| 699 | |
| 700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Char, name, "aten::_cast_Char") |
| 701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Char, overload_name, "") |
| 702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Char, schema_str, "_cast_Char(Tensor self, bool non_blocking=False) -> Tensor") |
| 703 | |
| 704 | // aten::_cast_Char(Tensor self, bool non_blocking=False) -> Tensor |
| 705 | static C10_NOINLINE c10::TypedOperatorHandle<_cast_Char::schema> create__cast_Char_typed_handle() { |
| 706 | return c10::Dispatcher::singleton() |
| 707 | .findSchemaOrThrow(_cast_Char::name, _cast_Char::overload_name) |
| 708 | .typed<_cast_Char::schema>(); |
| 709 | } |
| 710 | |
| 711 | // aten::_cast_Char(Tensor self, bool non_blocking=False) -> Tensor |
| 712 | at::Tensor _cast_Char::call(const at::Tensor & self, bool non_blocking) { |
| 713 | |
| 714 | static auto op = create__cast_Char_typed_handle(); |
| 715 | return op.call(self, non_blocking); |
| 716 | } |
| 717 | |
| 718 | // aten::_cast_Char(Tensor self, bool non_blocking=False) -> Tensor |
| 719 | at::Tensor _cast_Char::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking) { |
| 720 | |
| 721 | static auto op = create__cast_Char_typed_handle(); |
| 722 | return op.redispatch(dispatchKeySet, self, non_blocking); |
| 723 | } |
| 724 | |
| 725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_leaf, name, "aten::is_leaf") |
| 726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_leaf, overload_name, "") |
| 727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_leaf, schema_str, "is_leaf(Tensor self) -> bool") |
| 728 | |
| 729 | // aten::is_leaf(Tensor self) -> bool |
| 730 | static C10_NOINLINE c10::TypedOperatorHandle<is_leaf::schema> create_is_leaf_typed_handle() { |
| 731 | return c10::Dispatcher::singleton() |
| 732 | .findSchemaOrThrow(is_leaf::name, is_leaf::overload_name) |
| 733 | .typed<is_leaf::schema>(); |
| 734 | } |
| 735 | |
| 736 | // aten::is_leaf(Tensor self) -> bool |
| 737 | bool is_leaf::call(const at::Tensor & self) { |
| 738 | |
| 739 | static auto op = create_is_leaf_typed_handle(); |
| 740 | return op.call(self); |
| 741 | } |
| 742 | |
| 743 | // aten::is_leaf(Tensor self) -> bool |
| 744 | bool is_leaf::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 745 | |
| 746 | static auto op = create_is_leaf_typed_handle(); |
| 747 | return op.redispatch(dispatchKeySet, self); |
| 748 | } |
| 749 | |
| 750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(requires_grad_, name, "aten::requires_grad_") |
| 751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(requires_grad_, overload_name, "") |
| 752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(requires_grad_, schema_str, "requires_grad_(Tensor(a!) self, bool requires_grad=True) -> Tensor(a!)") |
| 753 | |
| 754 | // aten::requires_grad_(Tensor(a!) self, bool requires_grad=True) -> Tensor(a!) |
| 755 | static C10_NOINLINE c10::TypedOperatorHandle<requires_grad_::schema> create_requires_grad__typed_handle() { |
| 756 | return c10::Dispatcher::singleton() |
| 757 | .findSchemaOrThrow(requires_grad_::name, requires_grad_::overload_name) |
| 758 | .typed<requires_grad_::schema>(); |
| 759 | } |
| 760 | |
| 761 | // aten::requires_grad_(Tensor(a!) self, bool requires_grad=True) -> Tensor(a!) |
| 762 | at::Tensor & requires_grad_::call(at::Tensor & self, bool requires_grad) { |
| 763 | |
| 764 | static auto op = create_requires_grad__typed_handle(); |
| 765 | return op.call(self, requires_grad); |
| 766 | } |
| 767 | |
| 768 | // aten::requires_grad_(Tensor(a!) self, bool requires_grad=True) -> Tensor(a!) |
| 769 | at::Tensor & requires_grad_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, bool requires_grad) { |
| 770 | |
| 771 | static auto op = create_requires_grad__typed_handle(); |
| 772 | return op.redispatch(dispatchKeySet, self, requires_grad); |
| 773 | } |
| 774 | |
| 775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(retains_grad, name, "aten::retains_grad") |
| 776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(retains_grad, overload_name, "") |
| 777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(retains_grad, schema_str, "retains_grad(Tensor self) -> bool") |
| 778 | |
| 779 | // aten::retains_grad(Tensor self) -> bool |
| 780 | static C10_NOINLINE c10::TypedOperatorHandle<retains_grad::schema> create_retains_grad_typed_handle() { |
| 781 | return c10::Dispatcher::singleton() |
| 782 | .findSchemaOrThrow(retains_grad::name, retains_grad::overload_name) |
| 783 | .typed<retains_grad::schema>(); |
| 784 | } |
| 785 | |
| 786 | // aten::retains_grad(Tensor self) -> bool |
| 787 | bool retains_grad::call(const at::Tensor & self) { |
| 788 | |
| 789 | static auto op = create_retains_grad_typed_handle(); |
| 790 | return op.call(self); |
| 791 | } |
| 792 | |
| 793 | // aten::retains_grad(Tensor self) -> bool |
| 794 | bool retains_grad::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 795 | |
| 796 | static auto op = create_retains_grad_typed_handle(); |
| 797 | return op.redispatch(dispatchKeySet, self); |
| 798 | } |
| 799 | |
| 800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unpack_dual, name, "aten::_unpack_dual") |
| 801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unpack_dual, overload_name, "") |
| 802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unpack_dual, schema_str, "_unpack_dual(Tensor(a) dual, int level) -> (Tensor(a) primal, Tensor tangent)") |
| 803 | |
| 804 | // aten::_unpack_dual(Tensor(a) dual, int level) -> (Tensor(a) primal, Tensor tangent) |
| 805 | static C10_NOINLINE c10::TypedOperatorHandle<_unpack_dual::schema> create__unpack_dual_typed_handle() { |
| 806 | return c10::Dispatcher::singleton() |
| 807 | .findSchemaOrThrow(_unpack_dual::name, _unpack_dual::overload_name) |
| 808 | .typed<_unpack_dual::schema>(); |
| 809 | } |
| 810 | |
| 811 | // aten::_unpack_dual(Tensor(a) dual, int level) -> (Tensor(a) primal, Tensor tangent) |
| 812 | ::std::tuple<at::Tensor,at::Tensor> _unpack_dual::call(const at::Tensor & dual, int64_t level) { |
| 813 | |
| 814 | static auto op = create__unpack_dual_typed_handle(); |
| 815 | return op.call(dual, level); |
| 816 | } |
| 817 | |
| 818 | // aten::_unpack_dual(Tensor(a) dual, int level) -> (Tensor(a) primal, Tensor tangent) |
| 819 | ::std::tuple<at::Tensor,at::Tensor> _unpack_dual::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & dual, int64_t level) { |
| 820 | |
| 821 | static auto op = create__unpack_dual_typed_handle(); |
| 822 | return op.redispatch(dispatchKeySet, dual, level); |
| 823 | } |
| 824 | |
| 825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_has_same_storage_numel, name, "aten::_has_same_storage_numel") |
| 826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_has_same_storage_numel, overload_name, "") |
| 827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_has_same_storage_numel, schema_str, "_has_same_storage_numel(Tensor self, Tensor other) -> bool") |
| 828 | |
| 829 | // aten::_has_same_storage_numel(Tensor self, Tensor other) -> bool |
| 830 | static C10_NOINLINE c10::TypedOperatorHandle<_has_same_storage_numel::schema> create__has_same_storage_numel_typed_handle() { |
| 831 | return c10::Dispatcher::singleton() |
| 832 | .findSchemaOrThrow(_has_same_storage_numel::name, _has_same_storage_numel::overload_name) |
| 833 | .typed<_has_same_storage_numel::schema>(); |
| 834 | } |
| 835 | |
| 836 | // aten::_has_same_storage_numel(Tensor self, Tensor other) -> bool |
| 837 | bool _has_same_storage_numel::call(const at::Tensor & self, const at::Tensor & other) { |
| 838 | |
| 839 | static auto op = create__has_same_storage_numel_typed_handle(); |
| 840 | return op.call(self, other); |
| 841 | } |
| 842 | |
| 843 | // aten::_has_same_storage_numel(Tensor self, Tensor other) -> bool |
| 844 | bool _has_same_storage_numel::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 845 | |
| 846 | static auto op = create__has_same_storage_numel_typed_handle(); |
| 847 | return op.redispatch(dispatchKeySet, self, other); |
| 848 | } |
| 849 | |
| 850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_to, name, "aten::align_to") |
| 851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_to, overload_name, "") |
| 852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_to, schema_str, "align_to(Tensor(a) self, Dimname[] names) -> Tensor(a)") |
| 853 | |
| 854 | // aten::align_to(Tensor(a) self, Dimname[] names) -> Tensor(a) |
| 855 | static C10_NOINLINE c10::TypedOperatorHandle<align_to::schema> create_align_to_typed_handle() { |
| 856 | return c10::Dispatcher::singleton() |
| 857 | .findSchemaOrThrow(align_to::name, align_to::overload_name) |
| 858 | .typed<align_to::schema>(); |
| 859 | } |
| 860 | |
| 861 | // aten::align_to(Tensor(a) self, Dimname[] names) -> Tensor(a) |
| 862 | at::Tensor align_to::call(const at::Tensor & self, at::DimnameList names) { |
| 863 | |
| 864 | static auto op = create_align_to_typed_handle(); |
| 865 | return op.call(self, names); |
| 866 | } |
| 867 | |
| 868 | // aten::align_to(Tensor(a) self, Dimname[] names) -> Tensor(a) |
| 869 | at::Tensor align_to::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList names) { |
| 870 | |
| 871 | static auto op = create_align_to_typed_handle(); |
| 872 | return op.redispatch(dispatchKeySet, self, names); |
| 873 | } |
| 874 | |
| 875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_to_ellipsis_idx, name, "aten::align_to") |
| 876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_to_ellipsis_idx, overload_name, "ellipsis_idx") |
| 877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_to_ellipsis_idx, schema_str, "align_to.ellipsis_idx(Tensor(a) self, Dimname[] order, int ellipsis_idx) -> Tensor(a)") |
| 878 | |
| 879 | // aten::align_to.ellipsis_idx(Tensor(a) self, Dimname[] order, int ellipsis_idx) -> Tensor(a) |
| 880 | static C10_NOINLINE c10::TypedOperatorHandle<align_to_ellipsis_idx::schema> create_align_to_ellipsis_idx_typed_handle() { |
| 881 | return c10::Dispatcher::singleton() |
| 882 | .findSchemaOrThrow(align_to_ellipsis_idx::name, align_to_ellipsis_idx::overload_name) |
| 883 | .typed<align_to_ellipsis_idx::schema>(); |
| 884 | } |
| 885 | |
| 886 | // aten::align_to.ellipsis_idx(Tensor(a) self, Dimname[] order, int ellipsis_idx) -> Tensor(a) |
| 887 | at::Tensor align_to_ellipsis_idx::call(const at::Tensor & self, at::DimnameList order, int64_t ellipsis_idx) { |
| 888 | |
| 889 | static auto op = create_align_to_ellipsis_idx_typed_handle(); |
| 890 | return op.call(self, order, ellipsis_idx); |
| 891 | } |
| 892 | |
| 893 | // aten::align_to.ellipsis_idx(Tensor(a) self, Dimname[] order, int ellipsis_idx) -> Tensor(a) |
| 894 | at::Tensor align_to_ellipsis_idx::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList order, int64_t ellipsis_idx) { |
| 895 | |
| 896 | static auto op = create_align_to_ellipsis_idx_typed_handle(); |
| 897 | return op.redispatch(dispatchKeySet, self, order, ellipsis_idx); |
| 898 | } |
| 899 | |
| 900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_use_cudnn_ctc_loss, name, "aten::_use_cudnn_ctc_loss") |
| 901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_use_cudnn_ctc_loss, overload_name, "") |
| 902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_use_cudnn_ctc_loss, schema_str, "_use_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank) -> bool") |
| 903 | |
| 904 | // aten::_use_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank) -> bool |
| 905 | static C10_NOINLINE c10::TypedOperatorHandle<_use_cudnn_ctc_loss::schema> create__use_cudnn_ctc_loss_typed_handle() { |
| 906 | return c10::Dispatcher::singleton() |
| 907 | .findSchemaOrThrow(_use_cudnn_ctc_loss::name, _use_cudnn_ctc_loss::overload_name) |
| 908 | .typed<_use_cudnn_ctc_loss::schema>(); |
| 909 | } |
| 910 | |
| 911 | // aten::_use_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank) -> bool |
| 912 | bool _use_cudnn_ctc_loss::call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank) { |
| 913 | |
| 914 | static auto op = create__use_cudnn_ctc_loss_typed_handle(); |
| 915 | return op.call(log_probs, targets, input_lengths, target_lengths, blank); |
| 916 | } |
| 917 | |
| 918 | // aten::_use_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank) -> bool |
| 919 | bool _use_cudnn_ctc_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank) { |
| 920 | |
| 921 | static auto op = create__use_cudnn_ctc_loss_typed_handle(); |
| 922 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank); |
| 923 | } |
| 924 | |
| 925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_use_cudnn_ctc_loss_Tensor, name, "aten::_use_cudnn_ctc_loss") |
| 926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_use_cudnn_ctc_loss_Tensor, overload_name, "Tensor") |
| 927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_use_cudnn_ctc_loss_Tensor, schema_str, "_use_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank) -> bool") |
| 928 | |
| 929 | // aten::_use_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank) -> bool |
| 930 | static C10_NOINLINE c10::TypedOperatorHandle<_use_cudnn_ctc_loss_Tensor::schema> create__use_cudnn_ctc_loss_Tensor_typed_handle() { |
| 931 | return c10::Dispatcher::singleton() |
| 932 | .findSchemaOrThrow(_use_cudnn_ctc_loss_Tensor::name, _use_cudnn_ctc_loss_Tensor::overload_name) |
| 933 | .typed<_use_cudnn_ctc_loss_Tensor::schema>(); |
| 934 | } |
| 935 | |
| 936 | // aten::_use_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank) -> bool |
| 937 | bool _use_cudnn_ctc_loss_Tensor::call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank) { |
| 938 | |
| 939 | static auto op = create__use_cudnn_ctc_loss_Tensor_typed_handle(); |
| 940 | return op.call(log_probs, targets, input_lengths, target_lengths, blank); |
| 941 | } |
| 942 | |
| 943 | // aten::_use_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank) -> bool |
| 944 | bool _use_cudnn_ctc_loss_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank) { |
| 945 | |
| 946 | static auto op = create__use_cudnn_ctc_loss_Tensor_typed_handle(); |
| 947 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank); |
| 948 | } |
| 949 | |
| 950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss, name, "aten::_cudnn_ctc_loss") |
| 951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss, overload_name, "") |
| 952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss, schema_str, "_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor)") |
| 953 | |
| 954 | // aten::_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) |
| 955 | static C10_NOINLINE c10::TypedOperatorHandle<_cudnn_ctc_loss::schema> create__cudnn_ctc_loss_typed_handle() { |
| 956 | return c10::Dispatcher::singleton() |
| 957 | .findSchemaOrThrow(_cudnn_ctc_loss::name, _cudnn_ctc_loss::overload_name) |
| 958 | .typed<_cudnn_ctc_loss::schema>(); |
| 959 | } |
| 960 | |
| 961 | // aten::_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) |
| 962 | ::std::tuple<at::Tensor,at::Tensor> _cudnn_ctc_loss::call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity) { |
| 963 | |
| 964 | static auto op = create__cudnn_ctc_loss_typed_handle(); |
| 965 | return op.call(log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity); |
| 966 | } |
| 967 | |
| 968 | // aten::_cudnn_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) |
| 969 | ::std::tuple<at::Tensor,at::Tensor> _cudnn_ctc_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity) { |
| 970 | |
| 971 | static auto op = create__cudnn_ctc_loss_typed_handle(); |
| 972 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity); |
| 973 | } |
| 974 | |
| 975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss_Tensor, name, "aten::_cudnn_ctc_loss") |
| 976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss_Tensor, overload_name, "Tensor") |
| 977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss_Tensor, schema_str, "_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor)") |
| 978 | |
| 979 | // aten::_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) |
| 980 | static C10_NOINLINE c10::TypedOperatorHandle<_cudnn_ctc_loss_Tensor::schema> create__cudnn_ctc_loss_Tensor_typed_handle() { |
| 981 | return c10::Dispatcher::singleton() |
| 982 | .findSchemaOrThrow(_cudnn_ctc_loss_Tensor::name, _cudnn_ctc_loss_Tensor::overload_name) |
| 983 | .typed<_cudnn_ctc_loss_Tensor::schema>(); |
| 984 | } |
| 985 | |
| 986 | // aten::_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) |
| 987 | ::std::tuple<at::Tensor,at::Tensor> _cudnn_ctc_loss_Tensor::call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool deterministic, bool zero_infinity) { |
| 988 | |
| 989 | static auto op = create__cudnn_ctc_loss_Tensor_typed_handle(); |
| 990 | return op.call(log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity); |
| 991 | } |
| 992 | |
| 993 | // aten::_cudnn_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank, bool deterministic, bool zero_infinity) -> (Tensor, Tensor) |
| 994 | ::std::tuple<at::Tensor,at::Tensor> _cudnn_ctc_loss_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool deterministic, bool zero_infinity) { |
| 995 | |
| 996 | static auto op = create__cudnn_ctc_loss_Tensor_typed_handle(); |
| 997 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity); |
| 998 | } |
| 999 | |
| 1000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_rnn, name, "aten::_cudnn_rnn") |
| 1001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_rnn, overload_name, "") |
| 1002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_rnn, schema_str, "_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") |
| 1003 | |
| 1004 | // aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 1005 | static C10_NOINLINE c10::TypedOperatorHandle<_cudnn_rnn::schema> create__cudnn_rnn_typed_handle() { |
| 1006 | return c10::Dispatcher::singleton() |
| 1007 | .findSchemaOrThrow(_cudnn_rnn::name, _cudnn_rnn::overload_name) |
| 1008 | .typed<_cudnn_rnn::schema>(); |
| 1009 | } |
| 1010 | |
| 1011 | // aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 1012 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _cudnn_rnn::call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional<at::Tensor> & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state) { |
| 1013 | |
| 1014 | static auto op = create__cudnn_rnn_typed_handle(); |
| 1015 | return op.call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); |
| 1016 | } |
| 1017 | |
| 1018 | // aten::_cudnn_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 1019 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _cudnn_rnn::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional<at::Tensor> & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state) { |
| 1020 | |
| 1021 | static auto op = create__cudnn_rnn_typed_handle(); |
| 1022 | return op.redispatch(dispatchKeySet, input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); |
| 1023 | } |
| 1024 | |
| 1025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_debug_has_internal_overlap, name, "aten::_debug_has_internal_overlap") |
| 1026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_debug_has_internal_overlap, overload_name, "") |
| 1027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_debug_has_internal_overlap, schema_str, "_debug_has_internal_overlap(Tensor self) -> int") |
| 1028 | |
| 1029 | // aten::_debug_has_internal_overlap(Tensor self) -> int |
| 1030 | static C10_NOINLINE c10::TypedOperatorHandle<_debug_has_internal_overlap::schema> create__debug_has_internal_overlap_typed_handle() { |
| 1031 | return c10::Dispatcher::singleton() |
| 1032 | .findSchemaOrThrow(_debug_has_internal_overlap::name, _debug_has_internal_overlap::overload_name) |
| 1033 | .typed<_debug_has_internal_overlap::schema>(); |
| 1034 | } |
| 1035 | |
| 1036 | // aten::_debug_has_internal_overlap(Tensor self) -> int |
| 1037 | int64_t _debug_has_internal_overlap::call(const at::Tensor & self) { |
| 1038 | |
| 1039 | static auto op = create__debug_has_internal_overlap_typed_handle(); |
| 1040 | return op.call(self); |
| 1041 | } |
| 1042 | |
| 1043 | // aten::_debug_has_internal_overlap(Tensor self) -> int |
| 1044 | int64_t _debug_has_internal_overlap::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1045 | |
| 1046 | static auto op = create__debug_has_internal_overlap_typed_handle(); |
| 1047 | return op.redispatch(dispatchKeySet, self); |
| 1048 | } |
| 1049 | |
| 1050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_dropout, name, "aten::_fused_dropout") |
| 1051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_dropout, overload_name, "") |
| 1052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_dropout, schema_str, "_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor)") |
| 1053 | |
| 1054 | // aten::_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor) |
| 1055 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_dropout::schema> create__fused_dropout_typed_handle() { |
| 1056 | return c10::Dispatcher::singleton() |
| 1057 | .findSchemaOrThrow(_fused_dropout::name, _fused_dropout::overload_name) |
| 1058 | .typed<_fused_dropout::schema>(); |
| 1059 | } |
| 1060 | |
| 1061 | // aten::_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor) |
| 1062 | ::std::tuple<at::Tensor,at::Tensor> _fused_dropout::call(const at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
| 1063 | |
| 1064 | static auto op = create__fused_dropout_typed_handle(); |
| 1065 | return op.call(self, p, generator); |
| 1066 | } |
| 1067 | |
| 1068 | // aten::_fused_dropout(Tensor self, float p, Generator? generator=None) -> (Tensor, Tensor) |
| 1069 | ::std::tuple<at::Tensor,at::Tensor> _fused_dropout::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
| 1070 | |
| 1071 | static auto op = create__fused_dropout_typed_handle(); |
| 1072 | return op.redispatch(dispatchKeySet, self, p, generator); |
| 1073 | } |
| 1074 | |
| 1075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sobol_engine_initialize_state_, name, "aten::_sobol_engine_initialize_state_") |
| 1076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sobol_engine_initialize_state_, overload_name, "") |
| 1077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sobol_engine_initialize_state_, schema_str, "_sobol_engine_initialize_state_(Tensor(a!) self, int dimension) -> Tensor(a!)") |
| 1078 | |
| 1079 | // aten::_sobol_engine_initialize_state_(Tensor(a!) self, int dimension) -> Tensor(a!) |
| 1080 | static C10_NOINLINE c10::TypedOperatorHandle<_sobol_engine_initialize_state_::schema> create__sobol_engine_initialize_state__typed_handle() { |
| 1081 | return c10::Dispatcher::singleton() |
| 1082 | .findSchemaOrThrow(_sobol_engine_initialize_state_::name, _sobol_engine_initialize_state_::overload_name) |
| 1083 | .typed<_sobol_engine_initialize_state_::schema>(); |
| 1084 | } |
| 1085 | |
| 1086 | // aten::_sobol_engine_initialize_state_(Tensor(a!) self, int dimension) -> Tensor(a!) |
| 1087 | at::Tensor & _sobol_engine_initialize_state_::call(at::Tensor & self, int64_t dimension) { |
| 1088 | |
| 1089 | static auto op = create__sobol_engine_initialize_state__typed_handle(); |
| 1090 | return op.call(self, dimension); |
| 1091 | } |
| 1092 | |
| 1093 | // aten::_sobol_engine_initialize_state_(Tensor(a!) self, int dimension) -> Tensor(a!) |
| 1094 | at::Tensor & _sobol_engine_initialize_state_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dimension) { |
| 1095 | |
| 1096 | static auto op = create__sobol_engine_initialize_state__typed_handle(); |
| 1097 | return op.redispatch(dispatchKeySet, self, dimension); |
| 1098 | } |
| 1099 | |
| 1100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_shape_as_tensor, name, "aten::_shape_as_tensor") |
| 1101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_shape_as_tensor, overload_name, "") |
| 1102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_shape_as_tensor, schema_str, "_shape_as_tensor(Tensor self) -> Tensor") |
| 1103 | |
| 1104 | // aten::_shape_as_tensor(Tensor self) -> Tensor |
| 1105 | static C10_NOINLINE c10::TypedOperatorHandle<_shape_as_tensor::schema> create__shape_as_tensor_typed_handle() { |
| 1106 | return c10::Dispatcher::singleton() |
| 1107 | .findSchemaOrThrow(_shape_as_tensor::name, _shape_as_tensor::overload_name) |
| 1108 | .typed<_shape_as_tensor::schema>(); |
| 1109 | } |
| 1110 | |
| 1111 | // aten::_shape_as_tensor(Tensor self) -> Tensor |
| 1112 | at::Tensor _shape_as_tensor::call(const at::Tensor & self) { |
| 1113 | |
| 1114 | static auto op = create__shape_as_tensor_typed_handle(); |
| 1115 | return op.call(self); |
| 1116 | } |
| 1117 | |
| 1118 | // aten::_shape_as_tensor(Tensor self) -> Tensor |
| 1119 | at::Tensor _shape_as_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1120 | |
| 1121 | static auto op = create__shape_as_tensor_typed_handle(); |
| 1122 | return op.redispatch(dispatchKeySet, self); |
| 1123 | } |
| 1124 | |
| 1125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dropout, name, "aten::dropout") |
| 1126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dropout, overload_name, "") |
| 1127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dropout, schema_str, "dropout(Tensor input, float p, bool train) -> Tensor") |
| 1128 | |
| 1129 | // aten::dropout(Tensor input, float p, bool train) -> Tensor |
| 1130 | static C10_NOINLINE c10::TypedOperatorHandle<dropout::schema> create_dropout_typed_handle() { |
| 1131 | return c10::Dispatcher::singleton() |
| 1132 | .findSchemaOrThrow(dropout::name, dropout::overload_name) |
| 1133 | .typed<dropout::schema>(); |
| 1134 | } |
| 1135 | |
| 1136 | // aten::dropout(Tensor input, float p, bool train) -> Tensor |
| 1137 | at::Tensor dropout::call(const at::Tensor & input, double p, bool train) { |
| 1138 | |
| 1139 | static auto op = create_dropout_typed_handle(); |
| 1140 | return op.call(input, p, train); |
| 1141 | } |
| 1142 | |
| 1143 | // aten::dropout(Tensor input, float p, bool train) -> Tensor |
| 1144 | at::Tensor dropout::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, bool train) { |
| 1145 | |
| 1146 | static auto op = create_dropout_typed_handle(); |
| 1147 | return op.redispatch(dispatchKeySet, input, p, train); |
| 1148 | } |
| 1149 | |
| 1150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dropout_, name, "aten::dropout_") |
| 1151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dropout_, overload_name, "") |
| 1152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dropout_, schema_str, "dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)") |
| 1153 | |
| 1154 | // aten::dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) |
| 1155 | static C10_NOINLINE c10::TypedOperatorHandle<dropout_::schema> create_dropout__typed_handle() { |
| 1156 | return c10::Dispatcher::singleton() |
| 1157 | .findSchemaOrThrow(dropout_::name, dropout_::overload_name) |
| 1158 | .typed<dropout_::schema>(); |
| 1159 | } |
| 1160 | |
| 1161 | // aten::dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) |
| 1162 | at::Tensor & dropout_::call(at::Tensor & self, double p, bool train) { |
| 1163 | |
| 1164 | static auto op = create_dropout__typed_handle(); |
| 1165 | return op.call(self, p, train); |
| 1166 | } |
| 1167 | |
| 1168 | // aten::dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) |
| 1169 | at::Tensor & dropout_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, bool train) { |
| 1170 | |
| 1171 | static auto op = create_dropout__typed_handle(); |
| 1172 | return op.redispatch(dispatchKeySet, self, p, train); |
| 1173 | } |
| 1174 | |
| 1175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn, name, "aten::sgn") |
| 1176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn, overload_name, "") |
| 1177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn, schema_str, "sgn(Tensor self) -> Tensor") |
| 1178 | |
| 1179 | // aten::sgn(Tensor self) -> Tensor |
| 1180 | static C10_NOINLINE c10::TypedOperatorHandle<sgn::schema> create_sgn_typed_handle() { |
| 1181 | return c10::Dispatcher::singleton() |
| 1182 | .findSchemaOrThrow(sgn::name, sgn::overload_name) |
| 1183 | .typed<sgn::schema>(); |
| 1184 | } |
| 1185 | |
| 1186 | // aten::sgn(Tensor self) -> Tensor |
| 1187 | at::Tensor sgn::call(const at::Tensor & self) { |
| 1188 | |
| 1189 | static auto op = create_sgn_typed_handle(); |
| 1190 | return op.call(self); |
| 1191 | } |
| 1192 | |
| 1193 | // aten::sgn(Tensor self) -> Tensor |
| 1194 | at::Tensor sgn::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1195 | |
| 1196 | static auto op = create_sgn_typed_handle(); |
| 1197 | return op.redispatch(dispatchKeySet, self); |
| 1198 | } |
| 1199 | |
| 1200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn_, name, "aten::sgn_") |
| 1201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn_, overload_name, "") |
| 1202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn_, schema_str, "sgn_(Tensor(a!) self) -> Tensor(a!)") |
| 1203 | |
| 1204 | // aten::sgn_(Tensor(a!) self) -> Tensor(a!) |
| 1205 | static C10_NOINLINE c10::TypedOperatorHandle<sgn_::schema> create_sgn__typed_handle() { |
| 1206 | return c10::Dispatcher::singleton() |
| 1207 | .findSchemaOrThrow(sgn_::name, sgn_::overload_name) |
| 1208 | .typed<sgn_::schema>(); |
| 1209 | } |
| 1210 | |
| 1211 | // aten::sgn_(Tensor(a!) self) -> Tensor(a!) |
| 1212 | at::Tensor & sgn_::call(at::Tensor & self) { |
| 1213 | |
| 1214 | static auto op = create_sgn__typed_handle(); |
| 1215 | return op.call(self); |
| 1216 | } |
| 1217 | |
| 1218 | // aten::sgn_(Tensor(a!) self) -> Tensor(a!) |
| 1219 | at::Tensor & sgn_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 1220 | |
| 1221 | static auto op = create_sgn__typed_handle(); |
| 1222 | return op.redispatch(dispatchKeySet, self); |
| 1223 | } |
| 1224 | |
| 1225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn_out, name, "aten::sgn") |
| 1226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn_out, overload_name, "out") |
| 1227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sgn_out, schema_str, "sgn.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 1228 | |
| 1229 | // aten::sgn.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1230 | static C10_NOINLINE c10::TypedOperatorHandle<sgn_out::schema> create_sgn_out_typed_handle() { |
| 1231 | return c10::Dispatcher::singleton() |
| 1232 | .findSchemaOrThrow(sgn_out::name, sgn_out::overload_name) |
| 1233 | .typed<sgn_out::schema>(); |
| 1234 | } |
| 1235 | |
| 1236 | // aten::sgn.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1237 | at::Tensor & sgn_out::call(const at::Tensor & self, at::Tensor & out) { |
| 1238 | |
| 1239 | static auto op = create_sgn_out_typed_handle(); |
| 1240 | return op.call(self, out); |
| 1241 | } |
| 1242 | |
| 1243 | // aten::sgn.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1244 | at::Tensor & sgn_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 1245 | |
| 1246 | static auto op = create_sgn_out_typed_handle(); |
| 1247 | return op.redispatch(dispatchKeySet, self, out); |
| 1248 | } |
| 1249 | |
| 1250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(real, name, "aten::real") |
| 1251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(real, overload_name, "") |
| 1252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(real, schema_str, "real(Tensor(a) self) -> Tensor(a)") |
| 1253 | |
| 1254 | // aten::real(Tensor(a) self) -> Tensor(a) |
| 1255 | static C10_NOINLINE c10::TypedOperatorHandle<real::schema> create_real_typed_handle() { |
| 1256 | return c10::Dispatcher::singleton() |
| 1257 | .findSchemaOrThrow(real::name, real::overload_name) |
| 1258 | .typed<real::schema>(); |
| 1259 | } |
| 1260 | |
| 1261 | // aten::real(Tensor(a) self) -> Tensor(a) |
| 1262 | at::Tensor real::call(const at::Tensor & self) { |
| 1263 | |
| 1264 | static auto op = create_real_typed_handle(); |
| 1265 | return op.call(self); |
| 1266 | } |
| 1267 | |
| 1268 | // aten::real(Tensor(a) self) -> Tensor(a) |
| 1269 | at::Tensor real::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1270 | |
| 1271 | static auto op = create_real_typed_handle(); |
| 1272 | return op.redispatch(dispatchKeySet, self); |
| 1273 | } |
| 1274 | |
| 1275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj, name, "aten::_conj") |
| 1276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj, overload_name, "") |
| 1277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj, schema_str, "_conj(Tensor(a) self) -> Tensor(a)") |
| 1278 | |
| 1279 | // aten::_conj(Tensor(a) self) -> Tensor(a) |
| 1280 | static C10_NOINLINE c10::TypedOperatorHandle<_conj::schema> create__conj_typed_handle() { |
| 1281 | return c10::Dispatcher::singleton() |
| 1282 | .findSchemaOrThrow(_conj::name, _conj::overload_name) |
| 1283 | .typed<_conj::schema>(); |
| 1284 | } |
| 1285 | |
| 1286 | // aten::_conj(Tensor(a) self) -> Tensor(a) |
| 1287 | at::Tensor _conj::call(const at::Tensor & self) { |
| 1288 | |
| 1289 | static auto op = create__conj_typed_handle(); |
| 1290 | return op.call(self); |
| 1291 | } |
| 1292 | |
| 1293 | // aten::_conj(Tensor(a) self) -> Tensor(a) |
| 1294 | at::Tensor _conj::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1295 | |
| 1296 | static auto op = create__conj_typed_handle(); |
| 1297 | return op.redispatch(dispatchKeySet, self); |
| 1298 | } |
| 1299 | |
| 1300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj_physical, name, "aten::_conj_physical") |
| 1301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj_physical, overload_name, "") |
| 1302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj_physical, schema_str, "_conj_physical(Tensor self) -> Tensor") |
| 1303 | |
| 1304 | // aten::_conj_physical(Tensor self) -> Tensor |
| 1305 | static C10_NOINLINE c10::TypedOperatorHandle<_conj_physical::schema> create__conj_physical_typed_handle() { |
| 1306 | return c10::Dispatcher::singleton() |
| 1307 | .findSchemaOrThrow(_conj_physical::name, _conj_physical::overload_name) |
| 1308 | .typed<_conj_physical::schema>(); |
| 1309 | } |
| 1310 | |
| 1311 | // aten::_conj_physical(Tensor self) -> Tensor |
| 1312 | at::Tensor _conj_physical::call(const at::Tensor & self) { |
| 1313 | |
| 1314 | static auto op = create__conj_physical_typed_handle(); |
| 1315 | return op.call(self); |
| 1316 | } |
| 1317 | |
| 1318 | // aten::_conj_physical(Tensor self) -> Tensor |
| 1319 | at::Tensor _conj_physical::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1320 | |
| 1321 | static auto op = create__conj_physical_typed_handle(); |
| 1322 | return op.redispatch(dispatchKeySet, self); |
| 1323 | } |
| 1324 | |
| 1325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view, name, "aten::_neg_view") |
| 1326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view, overload_name, "") |
| 1327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view, schema_str, "_neg_view(Tensor(a) self) -> Tensor(a)") |
| 1328 | |
| 1329 | // aten::_neg_view(Tensor(a) self) -> Tensor(a) |
| 1330 | static C10_NOINLINE c10::TypedOperatorHandle<_neg_view::schema> create__neg_view_typed_handle() { |
| 1331 | return c10::Dispatcher::singleton() |
| 1332 | .findSchemaOrThrow(_neg_view::name, _neg_view::overload_name) |
| 1333 | .typed<_neg_view::schema>(); |
| 1334 | } |
| 1335 | |
| 1336 | // aten::_neg_view(Tensor(a) self) -> Tensor(a) |
| 1337 | at::Tensor _neg_view::call(const at::Tensor & self) { |
| 1338 | |
| 1339 | static auto op = create__neg_view_typed_handle(); |
| 1340 | return op.call(self); |
| 1341 | } |
| 1342 | |
| 1343 | // aten::_neg_view(Tensor(a) self) -> Tensor(a) |
| 1344 | at::Tensor _neg_view::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1345 | |
| 1346 | static auto op = create__neg_view_typed_handle(); |
| 1347 | return op.redispatch(dispatchKeySet, self); |
| 1348 | } |
| 1349 | |
| 1350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool1d, name, "aten::avg_pool1d") |
| 1351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool1d, overload_name, "") |
| 1352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool1d, schema_str, "avg_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True) -> Tensor") |
| 1353 | |
| 1354 | // aten::avg_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True) -> Tensor |
| 1355 | static C10_NOINLINE c10::TypedOperatorHandle<avg_pool1d::schema> create_avg_pool1d_typed_handle() { |
| 1356 | return c10::Dispatcher::singleton() |
| 1357 | .findSchemaOrThrow(avg_pool1d::name, avg_pool1d::overload_name) |
| 1358 | .typed<avg_pool1d::schema>(); |
| 1359 | } |
| 1360 | |
| 1361 | // aten::avg_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True) -> Tensor |
| 1362 | at::Tensor avg_pool1d::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad) { |
| 1363 | |
| 1364 | static auto op = create_avg_pool1d_typed_handle(); |
| 1365 | return op.call(self, kernel_size, stride, padding, ceil_mode, count_include_pad); |
| 1366 | } |
| 1367 | |
| 1368 | // aten::avg_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, bool ceil_mode=False, bool count_include_pad=True) -> Tensor |
| 1369 | at::Tensor avg_pool1d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad) { |
| 1370 | |
| 1371 | static auto op = create_avg_pool1d_typed_handle(); |
| 1372 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, ceil_mode, count_include_pad); |
| 1373 | } |
| 1374 | |
| 1375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(adaptive_avg_pool1d, name, "aten::adaptive_avg_pool1d") |
| 1376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(adaptive_avg_pool1d, overload_name, "") |
| 1377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(adaptive_avg_pool1d, schema_str, "adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor") |
| 1378 | |
| 1379 | // aten::adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor |
| 1380 | static C10_NOINLINE c10::TypedOperatorHandle<adaptive_avg_pool1d::schema> create_adaptive_avg_pool1d_typed_handle() { |
| 1381 | return c10::Dispatcher::singleton() |
| 1382 | .findSchemaOrThrow(adaptive_avg_pool1d::name, adaptive_avg_pool1d::overload_name) |
| 1383 | .typed<adaptive_avg_pool1d::schema>(); |
| 1384 | } |
| 1385 | |
| 1386 | // aten::adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor |
| 1387 | at::Tensor adaptive_avg_pool1d::call(const at::Tensor & self, at::IntArrayRef output_size) { |
| 1388 | |
| 1389 | static auto op = create_adaptive_avg_pool1d_typed_handle(); |
| 1390 | return op.call(self, output_size); |
| 1391 | } |
| 1392 | |
| 1393 | // aten::adaptive_avg_pool1d(Tensor self, int[1] output_size) -> Tensor |
| 1394 | at::Tensor adaptive_avg_pool1d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size) { |
| 1395 | |
| 1396 | static auto op = create_adaptive_avg_pool1d_typed_handle(); |
| 1397 | return op.redispatch(dispatchKeySet, self, output_size); |
| 1398 | } |
| 1399 | |
| 1400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_is_all_true, name, "aten::_is_all_true") |
| 1401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_is_all_true, overload_name, "") |
| 1402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_is_all_true, schema_str, "_is_all_true(Tensor self) -> Tensor") |
| 1403 | |
| 1404 | // aten::_is_all_true(Tensor self) -> Tensor |
| 1405 | static C10_NOINLINE c10::TypedOperatorHandle<_is_all_true::schema> create__is_all_true_typed_handle() { |
| 1406 | return c10::Dispatcher::singleton() |
| 1407 | .findSchemaOrThrow(_is_all_true::name, _is_all_true::overload_name) |
| 1408 | .typed<_is_all_true::schema>(); |
| 1409 | } |
| 1410 | |
| 1411 | // aten::_is_all_true(Tensor self) -> Tensor |
| 1412 | at::Tensor _is_all_true::call(const at::Tensor & self) { |
| 1413 | |
| 1414 | static auto op = create__is_all_true_typed_handle(); |
| 1415 | return op.call(self); |
| 1416 | } |
| 1417 | |
| 1418 | // aten::_is_all_true(Tensor self) -> Tensor |
| 1419 | at::Tensor _is_all_true::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1420 | |
| 1421 | static auto op = create__is_all_true_typed_handle(); |
| 1422 | return op.redispatch(dispatchKeySet, self); |
| 1423 | } |
| 1424 | |
| 1425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_check_tensor, name, "aten::_test_check_tensor") |
| 1426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_check_tensor, overload_name, "") |
| 1427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_check_tensor, schema_str, "_test_check_tensor(Tensor self) -> Tensor") |
| 1428 | |
| 1429 | // aten::_test_check_tensor(Tensor self) -> Tensor |
| 1430 | static C10_NOINLINE c10::TypedOperatorHandle<_test_check_tensor::schema> create__test_check_tensor_typed_handle() { |
| 1431 | return c10::Dispatcher::singleton() |
| 1432 | .findSchemaOrThrow(_test_check_tensor::name, _test_check_tensor::overload_name) |
| 1433 | .typed<_test_check_tensor::schema>(); |
| 1434 | } |
| 1435 | |
| 1436 | // aten::_test_check_tensor(Tensor self) -> Tensor |
| 1437 | at::Tensor _test_check_tensor::call(const at::Tensor & self) { |
| 1438 | |
| 1439 | static auto op = create__test_check_tensor_typed_handle(); |
| 1440 | return op.call(self); |
| 1441 | } |
| 1442 | |
| 1443 | // aten::_test_check_tensor(Tensor self) -> Tensor |
| 1444 | at::Tensor _test_check_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1445 | |
| 1446 | static auto op = create__test_check_tensor_typed_handle(); |
| 1447 | return op.redispatch(dispatchKeySet, self); |
| 1448 | } |
| 1449 | |
| 1450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(allclose, name, "aten::allclose") |
| 1451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(allclose, overload_name, "") |
| 1452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(allclose, schema_str, "allclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> bool") |
| 1453 | |
| 1454 | // aten::allclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> bool |
| 1455 | static C10_NOINLINE c10::TypedOperatorHandle<allclose::schema> create_allclose_typed_handle() { |
| 1456 | return c10::Dispatcher::singleton() |
| 1457 | .findSchemaOrThrow(allclose::name, allclose::overload_name) |
| 1458 | .typed<allclose::schema>(); |
| 1459 | } |
| 1460 | |
| 1461 | // aten::allclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> bool |
| 1462 | bool allclose::call(const at::Tensor & self, const at::Tensor & other, double rtol, double atol, bool equal_nan) { |
| 1463 | |
| 1464 | static auto op = create_allclose_typed_handle(); |
| 1465 | return op.call(self, other, rtol, atol, equal_nan); |
| 1466 | } |
| 1467 | |
| 1468 | // aten::allclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> bool |
| 1469 | bool allclose::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, double rtol, double atol, bool equal_nan) { |
| 1470 | |
| 1471 | static auto op = create_allclose_typed_handle(); |
| 1472 | return op.redispatch(dispatchKeySet, self, other, rtol, atol, equal_nan); |
| 1473 | } |
| 1474 | |
| 1475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argmax, name, "aten::argmax") |
| 1476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argmax, overload_name, "") |
| 1477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argmax, schema_str, "argmax(Tensor self, int? dim=None, bool keepdim=False) -> Tensor") |
| 1478 | |
| 1479 | // aten::argmax(Tensor self, int? dim=None, bool keepdim=False) -> Tensor |
| 1480 | static C10_NOINLINE c10::TypedOperatorHandle<argmax::schema> create_argmax_typed_handle() { |
| 1481 | return c10::Dispatcher::singleton() |
| 1482 | .findSchemaOrThrow(argmax::name, argmax::overload_name) |
| 1483 | .typed<argmax::schema>(); |
| 1484 | } |
| 1485 | |
| 1486 | // aten::argmax(Tensor self, int? dim=None, bool keepdim=False) -> Tensor |
| 1487 | at::Tensor argmax::call(const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim) { |
| 1488 | |
| 1489 | static auto op = create_argmax_typed_handle(); |
| 1490 | return op.call(self, dim, keepdim); |
| 1491 | } |
| 1492 | |
| 1493 | // aten::argmax(Tensor self, int? dim=None, bool keepdim=False) -> Tensor |
| 1494 | at::Tensor argmax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim) { |
| 1495 | |
| 1496 | static auto op = create_argmax_typed_handle(); |
| 1497 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 1498 | } |
| 1499 | |
| 1500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argmax_out, name, "aten::argmax") |
| 1501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argmax_out, overload_name, "out") |
| 1502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argmax_out, schema_str, "argmax.out(Tensor self, int? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 1503 | |
| 1504 | // aten::argmax.out(Tensor self, int? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1505 | static C10_NOINLINE c10::TypedOperatorHandle<argmax_out::schema> create_argmax_out_typed_handle() { |
| 1506 | return c10::Dispatcher::singleton() |
| 1507 | .findSchemaOrThrow(argmax_out::name, argmax_out::overload_name) |
| 1508 | .typed<argmax_out::schema>(); |
| 1509 | } |
| 1510 | |
| 1511 | // aten::argmax.out(Tensor self, int? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1512 | at::Tensor & argmax_out::call(const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim, at::Tensor & out) { |
| 1513 | |
| 1514 | static auto op = create_argmax_out_typed_handle(); |
| 1515 | return op.call(self, dim, keepdim, out); |
| 1516 | } |
| 1517 | |
| 1518 | // aten::argmax.out(Tensor self, int? dim=None, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1519 | at::Tensor & argmax_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim, at::Tensor & out) { |
| 1520 | |
| 1521 | static auto op = create_argmax_out_typed_handle(); |
| 1522 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
| 1523 | } |
| 1524 | |
| 1525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh, name, "aten::acosh") |
| 1526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh, overload_name, "") |
| 1527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh, schema_str, "acosh(Tensor self) -> Tensor") |
| 1528 | |
| 1529 | // aten::acosh(Tensor self) -> Tensor |
| 1530 | static C10_NOINLINE c10::TypedOperatorHandle<acosh::schema> create_acosh_typed_handle() { |
| 1531 | return c10::Dispatcher::singleton() |
| 1532 | .findSchemaOrThrow(acosh::name, acosh::overload_name) |
| 1533 | .typed<acosh::schema>(); |
| 1534 | } |
| 1535 | |
| 1536 | // aten::acosh(Tensor self) -> Tensor |
| 1537 | at::Tensor acosh::call(const at::Tensor & self) { |
| 1538 | |
| 1539 | static auto op = create_acosh_typed_handle(); |
| 1540 | return op.call(self); |
| 1541 | } |
| 1542 | |
| 1543 | // aten::acosh(Tensor self) -> Tensor |
| 1544 | at::Tensor acosh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1545 | |
| 1546 | static auto op = create_acosh_typed_handle(); |
| 1547 | return op.redispatch(dispatchKeySet, self); |
| 1548 | } |
| 1549 | |
| 1550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh_, name, "aten::acosh_") |
| 1551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh_, overload_name, "") |
| 1552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh_, schema_str, "acosh_(Tensor(a!) self) -> Tensor(a!)") |
| 1553 | |
| 1554 | // aten::acosh_(Tensor(a!) self) -> Tensor(a!) |
| 1555 | static C10_NOINLINE c10::TypedOperatorHandle<acosh_::schema> create_acosh__typed_handle() { |
| 1556 | return c10::Dispatcher::singleton() |
| 1557 | .findSchemaOrThrow(acosh_::name, acosh_::overload_name) |
| 1558 | .typed<acosh_::schema>(); |
| 1559 | } |
| 1560 | |
| 1561 | // aten::acosh_(Tensor(a!) self) -> Tensor(a!) |
| 1562 | at::Tensor & acosh_::call(at::Tensor & self) { |
| 1563 | |
| 1564 | static auto op = create_acosh__typed_handle(); |
| 1565 | return op.call(self); |
| 1566 | } |
| 1567 | |
| 1568 | // aten::acosh_(Tensor(a!) self) -> Tensor(a!) |
| 1569 | at::Tensor & acosh_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 1570 | |
| 1571 | static auto op = create_acosh__typed_handle(); |
| 1572 | return op.redispatch(dispatchKeySet, self); |
| 1573 | } |
| 1574 | |
| 1575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh_out, name, "aten::acosh") |
| 1576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh_out, overload_name, "out") |
| 1577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acosh_out, schema_str, "acosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 1578 | |
| 1579 | // aten::acosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1580 | static C10_NOINLINE c10::TypedOperatorHandle<acosh_out::schema> create_acosh_out_typed_handle() { |
| 1581 | return c10::Dispatcher::singleton() |
| 1582 | .findSchemaOrThrow(acosh_out::name, acosh_out::overload_name) |
| 1583 | .typed<acosh_out::schema>(); |
| 1584 | } |
| 1585 | |
| 1586 | // aten::acosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1587 | at::Tensor & acosh_out::call(const at::Tensor & self, at::Tensor & out) { |
| 1588 | |
| 1589 | static auto op = create_acosh_out_typed_handle(); |
| 1590 | return op.call(self, out); |
| 1591 | } |
| 1592 | |
| 1593 | // aten::acosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1594 | at::Tensor & acosh_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 1595 | |
| 1596 | static auto op = create_acosh_out_typed_handle(); |
| 1597 | return op.redispatch(dispatchKeySet, self, out); |
| 1598 | } |
| 1599 | |
| 1600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh, name, "aten::arctanh") |
| 1601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh, overload_name, "") |
| 1602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh, schema_str, "arctanh(Tensor self) -> Tensor") |
| 1603 | |
| 1604 | // aten::arctanh(Tensor self) -> Tensor |
| 1605 | static C10_NOINLINE c10::TypedOperatorHandle<arctanh::schema> create_arctanh_typed_handle() { |
| 1606 | return c10::Dispatcher::singleton() |
| 1607 | .findSchemaOrThrow(arctanh::name, arctanh::overload_name) |
| 1608 | .typed<arctanh::schema>(); |
| 1609 | } |
| 1610 | |
| 1611 | // aten::arctanh(Tensor self) -> Tensor |
| 1612 | at::Tensor arctanh::call(const at::Tensor & self) { |
| 1613 | |
| 1614 | static auto op = create_arctanh_typed_handle(); |
| 1615 | return op.call(self); |
| 1616 | } |
| 1617 | |
| 1618 | // aten::arctanh(Tensor self) -> Tensor |
| 1619 | at::Tensor arctanh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1620 | |
| 1621 | static auto op = create_arctanh_typed_handle(); |
| 1622 | return op.redispatch(dispatchKeySet, self); |
| 1623 | } |
| 1624 | |
| 1625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh_, name, "aten::arctanh_") |
| 1626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh_, overload_name, "") |
| 1627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh_, schema_str, "arctanh_(Tensor(a!) self) -> Tensor(a!)") |
| 1628 | |
| 1629 | // aten::arctanh_(Tensor(a!) self) -> Tensor(a!) |
| 1630 | static C10_NOINLINE c10::TypedOperatorHandle<arctanh_::schema> create_arctanh__typed_handle() { |
| 1631 | return c10::Dispatcher::singleton() |
| 1632 | .findSchemaOrThrow(arctanh_::name, arctanh_::overload_name) |
| 1633 | .typed<arctanh_::schema>(); |
| 1634 | } |
| 1635 | |
| 1636 | // aten::arctanh_(Tensor(a!) self) -> Tensor(a!) |
| 1637 | at::Tensor & arctanh_::call(at::Tensor & self) { |
| 1638 | |
| 1639 | static auto op = create_arctanh__typed_handle(); |
| 1640 | return op.call(self); |
| 1641 | } |
| 1642 | |
| 1643 | // aten::arctanh_(Tensor(a!) self) -> Tensor(a!) |
| 1644 | at::Tensor & arctanh_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 1645 | |
| 1646 | static auto op = create_arctanh__typed_handle(); |
| 1647 | return op.redispatch(dispatchKeySet, self); |
| 1648 | } |
| 1649 | |
| 1650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh_out, name, "aten::arctanh") |
| 1651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh_out, overload_name, "out") |
| 1652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctanh_out, schema_str, "arctanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 1653 | |
| 1654 | // aten::arctanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1655 | static C10_NOINLINE c10::TypedOperatorHandle<arctanh_out::schema> create_arctanh_out_typed_handle() { |
| 1656 | return c10::Dispatcher::singleton() |
| 1657 | .findSchemaOrThrow(arctanh_out::name, arctanh_out::overload_name) |
| 1658 | .typed<arctanh_out::schema>(); |
| 1659 | } |
| 1660 | |
| 1661 | // aten::arctanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1662 | at::Tensor & arctanh_out::call(const at::Tensor & self, at::Tensor & out) { |
| 1663 | |
| 1664 | static auto op = create_arctanh_out_typed_handle(); |
| 1665 | return op.call(self, out); |
| 1666 | } |
| 1667 | |
| 1668 | // aten::arctanh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1669 | at::Tensor & arctanh_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 1670 | |
| 1671 | static auto op = create_arctanh_out_typed_handle(); |
| 1672 | return op.redispatch(dispatchKeySet, self, out); |
| 1673 | } |
| 1674 | |
| 1675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided, name, "aten::as_strided") |
| 1676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided, overload_name, "") |
| 1677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided, schema_str, "as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a)") |
| 1678 | |
| 1679 | // aten::as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a) |
| 1680 | static C10_NOINLINE c10::TypedOperatorHandle<as_strided::schema> create_as_strided_typed_handle() { |
| 1681 | return c10::Dispatcher::singleton() |
| 1682 | .findSchemaOrThrow(as_strided::name, as_strided::overload_name) |
| 1683 | .typed<as_strided::schema>(); |
| 1684 | } |
| 1685 | |
| 1686 | // aten::as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a) |
| 1687 | at::Tensor as_strided::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset) { |
| 1688 | |
| 1689 | static auto op = create_as_strided_typed_handle(); |
| 1690 | return op.call(self, size, stride, storage_offset); |
| 1691 | } |
| 1692 | |
| 1693 | // aten::as_strided(Tensor(a) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a) |
| 1694 | at::Tensor as_strided::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset) { |
| 1695 | |
| 1696 | static auto op = create_as_strided_typed_handle(); |
| 1697 | return op.redispatch(dispatchKeySet, self, size, stride, storage_offset); |
| 1698 | } |
| 1699 | |
| 1700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_, name, "aten::as_strided_") |
| 1701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_, overload_name, "") |
| 1702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_, schema_str, "as_strided_(Tensor(a!) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a!)") |
| 1703 | |
| 1704 | // aten::as_strided_(Tensor(a!) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a!) |
| 1705 | static C10_NOINLINE c10::TypedOperatorHandle<as_strided_::schema> create_as_strided__typed_handle() { |
| 1706 | return c10::Dispatcher::singleton() |
| 1707 | .findSchemaOrThrow(as_strided_::name, as_strided_::overload_name) |
| 1708 | .typed<as_strided_::schema>(); |
| 1709 | } |
| 1710 | |
| 1711 | // aten::as_strided_(Tensor(a!) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a!) |
| 1712 | const at::Tensor & as_strided_::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset) { |
| 1713 | |
| 1714 | static auto op = create_as_strided__typed_handle(); |
| 1715 | return op.call(self, size, stride, storage_offset); |
| 1716 | } |
| 1717 | |
| 1718 | // aten::as_strided_(Tensor(a!) self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor(a!) |
| 1719 | const at::Tensor & as_strided_::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset) { |
| 1720 | |
| 1721 | static auto op = create_as_strided__typed_handle(); |
| 1722 | return op.redispatch(dispatchKeySet, self, size, stride, storage_offset); |
| 1723 | } |
| 1724 | |
| 1725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_3d, name, "aten::atleast_3d") |
| 1726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_3d, overload_name, "") |
| 1727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_3d, schema_str, "atleast_3d(Tensor self) -> Tensor") |
| 1728 | |
| 1729 | // aten::atleast_3d(Tensor self) -> Tensor |
| 1730 | static C10_NOINLINE c10::TypedOperatorHandle<atleast_3d::schema> create_atleast_3d_typed_handle() { |
| 1731 | return c10::Dispatcher::singleton() |
| 1732 | .findSchemaOrThrow(atleast_3d::name, atleast_3d::overload_name) |
| 1733 | .typed<atleast_3d::schema>(); |
| 1734 | } |
| 1735 | |
| 1736 | // aten::atleast_3d(Tensor self) -> Tensor |
| 1737 | at::Tensor atleast_3d::call(const at::Tensor & self) { |
| 1738 | |
| 1739 | static auto op = create_atleast_3d_typed_handle(); |
| 1740 | return op.call(self); |
| 1741 | } |
| 1742 | |
| 1743 | // aten::atleast_3d(Tensor self) -> Tensor |
| 1744 | at::Tensor atleast_3d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1745 | |
| 1746 | static auto op = create_atleast_3d_typed_handle(); |
| 1747 | return op.redispatch(dispatchKeySet, self); |
| 1748 | } |
| 1749 | |
| 1750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_3d_Sequence, name, "aten::atleast_3d") |
| 1751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_3d_Sequence, overload_name, "Sequence") |
| 1752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_3d_Sequence, schema_str, "atleast_3d.Sequence(Tensor[] tensors) -> Tensor[]") |
| 1753 | |
| 1754 | // aten::atleast_3d.Sequence(Tensor[] tensors) -> Tensor[] |
| 1755 | static C10_NOINLINE c10::TypedOperatorHandle<atleast_3d_Sequence::schema> create_atleast_3d_Sequence_typed_handle() { |
| 1756 | return c10::Dispatcher::singleton() |
| 1757 | .findSchemaOrThrow(atleast_3d_Sequence::name, atleast_3d_Sequence::overload_name) |
| 1758 | .typed<atleast_3d_Sequence::schema>(); |
| 1759 | } |
| 1760 | |
| 1761 | // aten::atleast_3d.Sequence(Tensor[] tensors) -> Tensor[] |
| 1762 | ::std::vector<at::Tensor> atleast_3d_Sequence::call(at::TensorList tensors) { |
| 1763 | |
| 1764 | static auto op = create_atleast_3d_Sequence_typed_handle(); |
| 1765 | return op.call(tensors); |
| 1766 | } |
| 1767 | |
| 1768 | // aten::atleast_3d.Sequence(Tensor[] tensors) -> Tensor[] |
| 1769 | ::std::vector<at::Tensor> atleast_3d_Sequence::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 1770 | |
| 1771 | static auto op = create_atleast_3d_Sequence_typed_handle(); |
| 1772 | return op.redispatch(dispatchKeySet, tensors); |
| 1773 | } |
| 1774 | |
| 1775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_batch_norm_impl_index, name, "aten::_batch_norm_impl_index") |
| 1776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_batch_norm_impl_index, overload_name, "") |
| 1777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_batch_norm_impl_index, schema_str, "_batch_norm_impl_index(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> (Tensor, Tensor, Tensor, Tensor, int)") |
| 1778 | |
| 1779 | // aten::_batch_norm_impl_index(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> (Tensor, Tensor, Tensor, Tensor, int) |
| 1780 | static C10_NOINLINE c10::TypedOperatorHandle<_batch_norm_impl_index::schema> create__batch_norm_impl_index_typed_handle() { |
| 1781 | return c10::Dispatcher::singleton() |
| 1782 | .findSchemaOrThrow(_batch_norm_impl_index::name, _batch_norm_impl_index::overload_name) |
| 1783 | .typed<_batch_norm_impl_index::schema>(); |
| 1784 | } |
| 1785 | |
| 1786 | // aten::_batch_norm_impl_index(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> (Tensor, Tensor, Tensor, Tensor, int) |
| 1787 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,int64_t> _batch_norm_impl_index::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled) { |
| 1788 | |
| 1789 | static auto op = create__batch_norm_impl_index_typed_handle(); |
| 1790 | return op.call(input, weight, bias, running_mean, running_var, training, momentum, eps, cudnn_enabled); |
| 1791 | } |
| 1792 | |
| 1793 | // aten::_batch_norm_impl_index(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> (Tensor, Tensor, Tensor, Tensor, int) |
| 1794 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,int64_t> _batch_norm_impl_index::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, bool training, double momentum, double eps, bool cudnn_enabled) { |
| 1795 | |
| 1796 | static auto op = create__batch_norm_impl_index_typed_handle(); |
| 1797 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, momentum, eps, cudnn_enabled); |
| 1798 | } |
| 1799 | |
| 1800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_batch_norm_impl_index_backward, name, "aten::_batch_norm_impl_index_backward") |
| 1801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_batch_norm_impl_index_backward, overload_name, "") |
| 1802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_batch_norm_impl_index_backward, schema_str, "_batch_norm_impl_index_backward(int impl_index, Tensor input, Tensor grad_output, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var_transform, bool train, float eps, bool[3] output_mask, Tensor reservedSpace) -> (Tensor, Tensor, Tensor)") |
| 1803 | |
| 1804 | // aten::_batch_norm_impl_index_backward(int impl_index, Tensor input, Tensor grad_output, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var_transform, bool train, float eps, bool[3] output_mask, Tensor reservedSpace) -> (Tensor, Tensor, Tensor) |
| 1805 | static C10_NOINLINE c10::TypedOperatorHandle<_batch_norm_impl_index_backward::schema> create__batch_norm_impl_index_backward_typed_handle() { |
| 1806 | return c10::Dispatcher::singleton() |
| 1807 | .findSchemaOrThrow(_batch_norm_impl_index_backward::name, _batch_norm_impl_index_backward::overload_name) |
| 1808 | .typed<_batch_norm_impl_index_backward::schema>(); |
| 1809 | } |
| 1810 | |
| 1811 | // aten::_batch_norm_impl_index_backward(int impl_index, Tensor input, Tensor grad_output, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var_transform, bool train, float eps, bool[3] output_mask, Tensor reservedSpace) -> (Tensor, Tensor, Tensor) |
| 1812 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _batch_norm_impl_index_backward::call(int64_t impl_index, const at::Tensor & input, const at::Tensor & grad_output, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var_transform, bool train, double eps, ::std::array<bool,3> output_mask, const at::Tensor & reservedSpace) { |
| 1813 | |
| 1814 | static auto op = create__batch_norm_impl_index_backward_typed_handle(); |
| 1815 | return op.call(impl_index, input, grad_output, weight, running_mean, running_var, save_mean, save_var_transform, train, eps, output_mask, reservedSpace); |
| 1816 | } |
| 1817 | |
| 1818 | // aten::_batch_norm_impl_index_backward(int impl_index, Tensor input, Tensor grad_output, Tensor? weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var_transform, bool train, float eps, bool[3] output_mask, Tensor reservedSpace) -> (Tensor, Tensor, Tensor) |
| 1819 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _batch_norm_impl_index_backward::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t impl_index, const at::Tensor & input, const at::Tensor & grad_output, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var_transform, bool train, double eps, ::std::array<bool,3> output_mask, const at::Tensor & reservedSpace) { |
| 1820 | |
| 1821 | static auto op = create__batch_norm_impl_index_backward_typed_handle(); |
| 1822 | return op.redispatch(dispatchKeySet, impl_index, input, grad_output, weight, running_mean, running_var, save_mean, save_var_transform, train, eps, output_mask, reservedSpace); |
| 1823 | } |
| 1824 | |
| 1825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or, name, "aten::logical_or") |
| 1826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or, overload_name, "") |
| 1827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or, schema_str, "logical_or(Tensor self, Tensor other) -> Tensor") |
| 1828 | |
| 1829 | // aten::logical_or(Tensor self, Tensor other) -> Tensor |
| 1830 | static C10_NOINLINE c10::TypedOperatorHandle<logical_or::schema> create_logical_or_typed_handle() { |
| 1831 | return c10::Dispatcher::singleton() |
| 1832 | .findSchemaOrThrow(logical_or::name, logical_or::overload_name) |
| 1833 | .typed<logical_or::schema>(); |
| 1834 | } |
| 1835 | |
| 1836 | // aten::logical_or(Tensor self, Tensor other) -> Tensor |
| 1837 | at::Tensor logical_or::call(const at::Tensor & self, const at::Tensor & other) { |
| 1838 | |
| 1839 | static auto op = create_logical_or_typed_handle(); |
| 1840 | return op.call(self, other); |
| 1841 | } |
| 1842 | |
| 1843 | // aten::logical_or(Tensor self, Tensor other) -> Tensor |
| 1844 | at::Tensor logical_or::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 1845 | |
| 1846 | static auto op = create_logical_or_typed_handle(); |
| 1847 | return op.redispatch(dispatchKeySet, self, other); |
| 1848 | } |
| 1849 | |
| 1850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or_, name, "aten::logical_or_") |
| 1851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or_, overload_name, "") |
| 1852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or_, schema_str, "logical_or_(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 1853 | |
| 1854 | // aten::logical_or_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1855 | static C10_NOINLINE c10::TypedOperatorHandle<logical_or_::schema> create_logical_or__typed_handle() { |
| 1856 | return c10::Dispatcher::singleton() |
| 1857 | .findSchemaOrThrow(logical_or_::name, logical_or_::overload_name) |
| 1858 | .typed<logical_or_::schema>(); |
| 1859 | } |
| 1860 | |
| 1861 | // aten::logical_or_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1862 | at::Tensor & logical_or_::call(at::Tensor & self, const at::Tensor & other) { |
| 1863 | |
| 1864 | static auto op = create_logical_or__typed_handle(); |
| 1865 | return op.call(self, other); |
| 1866 | } |
| 1867 | |
| 1868 | // aten::logical_or_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1869 | at::Tensor & logical_or_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 1870 | |
| 1871 | static auto op = create_logical_or__typed_handle(); |
| 1872 | return op.redispatch(dispatchKeySet, self, other); |
| 1873 | } |
| 1874 | |
| 1875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or_out, name, "aten::logical_or") |
| 1876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or_out, overload_name, "out") |
| 1877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_or_out, schema_str, "logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 1878 | |
| 1879 | // aten::logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1880 | static C10_NOINLINE c10::TypedOperatorHandle<logical_or_out::schema> create_logical_or_out_typed_handle() { |
| 1881 | return c10::Dispatcher::singleton() |
| 1882 | .findSchemaOrThrow(logical_or_out::name, logical_or_out::overload_name) |
| 1883 | .typed<logical_or_out::schema>(); |
| 1884 | } |
| 1885 | |
| 1886 | // aten::logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1887 | at::Tensor & logical_or_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 1888 | |
| 1889 | static auto op = create_logical_or_out_typed_handle(); |
| 1890 | return op.call(self, other, out); |
| 1891 | } |
| 1892 | |
| 1893 | // aten::logical_or.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1894 | at::Tensor & logical_or_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 1895 | |
| 1896 | static auto op = create_logical_or_out_typed_handle(); |
| 1897 | return op.redispatch(dispatchKeySet, self, other, out); |
| 1898 | } |
| 1899 | |
| 1900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window, name, "aten::blackman_window") |
| 1901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window, overload_name, "") |
| 1902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window, schema_str, "blackman_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 1903 | |
| 1904 | // aten::blackman_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 1905 | static C10_NOINLINE c10::TypedOperatorHandle<blackman_window::schema> create_blackman_window_typed_handle() { |
| 1906 | return c10::Dispatcher::singleton() |
| 1907 | .findSchemaOrThrow(blackman_window::name, blackman_window::overload_name) |
| 1908 | .typed<blackman_window::schema>(); |
| 1909 | } |
| 1910 | |
| 1911 | // aten::blackman_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 1912 | at::Tensor blackman_window::call(int64_t window_length, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 1913 | |
| 1914 | static auto op = create_blackman_window_typed_handle(); |
| 1915 | return op.call(window_length, dtype, layout, device, pin_memory); |
| 1916 | } |
| 1917 | |
| 1918 | // aten::blackman_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 1919 | at::Tensor blackman_window::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 1920 | |
| 1921 | static auto op = create_blackman_window_typed_handle(); |
| 1922 | return op.redispatch(dispatchKeySet, window_length, dtype, layout, device, pin_memory); |
| 1923 | } |
| 1924 | |
| 1925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_periodic, name, "aten::blackman_window") |
| 1926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_periodic, overload_name, "periodic") |
| 1927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_periodic, schema_str, "blackman_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 1928 | |
| 1929 | // aten::blackman_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 1930 | static C10_NOINLINE c10::TypedOperatorHandle<blackman_window_periodic::schema> create_blackman_window_periodic_typed_handle() { |
| 1931 | return c10::Dispatcher::singleton() |
| 1932 | .findSchemaOrThrow(blackman_window_periodic::name, blackman_window_periodic::overload_name) |
| 1933 | .typed<blackman_window_periodic::schema>(); |
| 1934 | } |
| 1935 | |
| 1936 | // aten::blackman_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 1937 | at::Tensor blackman_window_periodic::call(int64_t window_length, bool periodic, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 1938 | |
| 1939 | static auto op = create_blackman_window_periodic_typed_handle(); |
| 1940 | return op.call(window_length, periodic, dtype, layout, device, pin_memory); |
| 1941 | } |
| 1942 | |
| 1943 | // aten::blackman_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 1944 | at::Tensor blackman_window_periodic::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 1945 | |
| 1946 | static auto op = create_blackman_window_periodic_typed_handle(); |
| 1947 | return op.redispatch(dispatchKeySet, window_length, periodic, dtype, layout, device, pin_memory); |
| 1948 | } |
| 1949 | |
| 1950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(broadcast_tensors, name, "aten::broadcast_tensors") |
| 1951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(broadcast_tensors, overload_name, "") |
| 1952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(broadcast_tensors, schema_str, "broadcast_tensors(Tensor[] tensors) -> Tensor[]") |
| 1953 | |
| 1954 | // aten::broadcast_tensors(Tensor[] tensors) -> Tensor[] |
| 1955 | static C10_NOINLINE c10::TypedOperatorHandle<broadcast_tensors::schema> create_broadcast_tensors_typed_handle() { |
| 1956 | return c10::Dispatcher::singleton() |
| 1957 | .findSchemaOrThrow(broadcast_tensors::name, broadcast_tensors::overload_name) |
| 1958 | .typed<broadcast_tensors::schema>(); |
| 1959 | } |
| 1960 | |
| 1961 | // aten::broadcast_tensors(Tensor[] tensors) -> Tensor[] |
| 1962 | ::std::vector<at::Tensor> broadcast_tensors::call(at::TensorList tensors) { |
| 1963 | |
| 1964 | static auto op = create_broadcast_tensors_typed_handle(); |
| 1965 | return op.call(tensors); |
| 1966 | } |
| 1967 | |
| 1968 | // aten::broadcast_tensors(Tensor[] tensors) -> Tensor[] |
| 1969 | ::std::vector<at::Tensor> broadcast_tensors::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 1970 | |
| 1971 | static auto op = create_broadcast_tensors_typed_handle(); |
| 1972 | return op.redispatch(dispatchKeySet, tensors); |
| 1973 | } |
| 1974 | |
| 1975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat, name, "aten::cat") |
| 1976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat, overload_name, "") |
| 1977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat, schema_str, "cat(Tensor[] tensors, int dim=0) -> Tensor") |
| 1978 | |
| 1979 | // aten::cat(Tensor[] tensors, int dim=0) -> Tensor |
| 1980 | static C10_NOINLINE c10::TypedOperatorHandle<cat::schema> create_cat_typed_handle() { |
| 1981 | return c10::Dispatcher::singleton() |
| 1982 | .findSchemaOrThrow(cat::name, cat::overload_name) |
| 1983 | .typed<cat::schema>(); |
| 1984 | } |
| 1985 | |
| 1986 | // aten::cat(Tensor[] tensors, int dim=0) -> Tensor |
| 1987 | at::Tensor cat::call(const at::ITensorListRef & tensors, int64_t dim) { |
| 1988 | |
| 1989 | static auto op = create_cat_typed_handle(); |
| 1990 | return op.call(tensors, dim); |
| 1991 | } |
| 1992 | |
| 1993 | // aten::cat(Tensor[] tensors, int dim=0) -> Tensor |
| 1994 | at::Tensor cat::redispatch(c10::DispatchKeySet dispatchKeySet, const at::ITensorListRef & tensors, int64_t dim) { |
| 1995 | |
| 1996 | static auto op = create_cat_typed_handle(); |
| 1997 | return op.redispatch(dispatchKeySet, tensors, dim); |
| 1998 | } |
| 1999 | |
| 2000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_out, name, "aten::cat") |
| 2001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_out, overload_name, "out") |
| 2002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_out, schema_str, "cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!)") |
| 2003 | |
| 2004 | // aten::cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!) |
| 2005 | static C10_NOINLINE c10::TypedOperatorHandle<cat_out::schema> create_cat_out_typed_handle() { |
| 2006 | return c10::Dispatcher::singleton() |
| 2007 | .findSchemaOrThrow(cat_out::name, cat_out::overload_name) |
| 2008 | .typed<cat_out::schema>(); |
| 2009 | } |
| 2010 | |
| 2011 | // aten::cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!) |
| 2012 | at::Tensor & cat_out::call(const at::ITensorListRef & tensors, int64_t dim, at::Tensor & out) { |
| 2013 | |
| 2014 | static auto op = create_cat_out_typed_handle(); |
| 2015 | return op.call(tensors, dim, out); |
| 2016 | } |
| 2017 | |
| 2018 | // aten::cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> Tensor(a!) |
| 2019 | at::Tensor & cat_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::ITensorListRef & tensors, int64_t dim, at::Tensor & out) { |
| 2020 | |
| 2021 | static auto op = create_cat_out_typed_handle(); |
| 2022 | return op.redispatch(dispatchKeySet, tensors, dim, out); |
| 2023 | } |
| 2024 | |
| 2025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_names, name, "aten::cat") |
| 2026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_names, overload_name, "names") |
| 2027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_names, schema_str, "cat.names(Tensor[] tensors, Dimname dim) -> Tensor") |
| 2028 | |
| 2029 | // aten::cat.names(Tensor[] tensors, Dimname dim) -> Tensor |
| 2030 | static C10_NOINLINE c10::TypedOperatorHandle<cat_names::schema> create_cat_names_typed_handle() { |
| 2031 | return c10::Dispatcher::singleton() |
| 2032 | .findSchemaOrThrow(cat_names::name, cat_names::overload_name) |
| 2033 | .typed<cat_names::schema>(); |
| 2034 | } |
| 2035 | |
| 2036 | // aten::cat.names(Tensor[] tensors, Dimname dim) -> Tensor |
| 2037 | at::Tensor cat_names::call(at::TensorList tensors, at::Dimname dim) { |
| 2038 | |
| 2039 | static auto op = create_cat_names_typed_handle(); |
| 2040 | return op.call(tensors, dim); |
| 2041 | } |
| 2042 | |
| 2043 | // aten::cat.names(Tensor[] tensors, Dimname dim) -> Tensor |
| 2044 | at::Tensor cat_names::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Dimname dim) { |
| 2045 | |
| 2046 | static auto op = create_cat_names_typed_handle(); |
| 2047 | return op.redispatch(dispatchKeySet, tensors, dim); |
| 2048 | } |
| 2049 | |
| 2050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_names_out, name, "aten::cat") |
| 2051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_names_out, overload_name, "names_out") |
| 2052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cat_names_out, schema_str, "cat.names_out(Tensor[] tensors, Dimname dim, *, Tensor(a!) out) -> Tensor(a!)") |
| 2053 | |
| 2054 | // aten::cat.names_out(Tensor[] tensors, Dimname dim, *, Tensor(a!) out) -> Tensor(a!) |
| 2055 | static C10_NOINLINE c10::TypedOperatorHandle<cat_names_out::schema> create_cat_names_out_typed_handle() { |
| 2056 | return c10::Dispatcher::singleton() |
| 2057 | .findSchemaOrThrow(cat_names_out::name, cat_names_out::overload_name) |
| 2058 | .typed<cat_names_out::schema>(); |
| 2059 | } |
| 2060 | |
| 2061 | // aten::cat.names_out(Tensor[] tensors, Dimname dim, *, Tensor(a!) out) -> Tensor(a!) |
| 2062 | at::Tensor & cat_names_out::call(at::TensorList tensors, at::Dimname dim, at::Tensor & out) { |
| 2063 | |
| 2064 | static auto op = create_cat_names_out_typed_handle(); |
| 2065 | return op.call(tensors, dim, out); |
| 2066 | } |
| 2067 | |
| 2068 | // aten::cat.names_out(Tensor[] tensors, Dimname dim, *, Tensor(a!) out) -> Tensor(a!) |
| 2069 | at::Tensor & cat_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Dimname dim, at::Tensor & out) { |
| 2070 | |
| 2071 | static auto op = create_cat_names_out_typed_handle(); |
| 2072 | return op.redispatch(dispatchKeySet, tensors, dim, out); |
| 2073 | } |
| 2074 | |
| 2075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution, name, "aten::convolution") |
| 2076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution, overload_name, "") |
| 2077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution, schema_str, "convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor") |
| 2078 | |
| 2079 | // aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor |
| 2080 | static C10_NOINLINE c10::TypedOperatorHandle<convolution::schema> create_convolution_typed_handle() { |
| 2081 | return c10::Dispatcher::singleton() |
| 2082 | .findSchemaOrThrow(convolution::name, convolution::overload_name) |
| 2083 | .typed<convolution::schema>(); |
| 2084 | } |
| 2085 | |
| 2086 | // aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor |
| 2087 | at::Tensor convolution::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups) { |
| 2088 | |
| 2089 | static auto op = create_convolution_typed_handle(); |
| 2090 | return op.call(input, weight, bias, stride, padding, dilation, transposed, output_padding, groups); |
| 2091 | } |
| 2092 | |
| 2093 | // aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor |
| 2094 | at::Tensor convolution::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups) { |
| 2095 | |
| 2096 | static auto op = create_convolution_typed_handle(); |
| 2097 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, transposed, output_padding, groups); |
| 2098 | } |
| 2099 | |
| 2100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_overrideable, name, "aten::convolution_backward_overrideable") |
| 2101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_overrideable, overload_name, "") |
| 2102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_overrideable, schema_str, "convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias)") |
| 2103 | |
| 2104 | // aten::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) |
| 2105 | static C10_NOINLINE c10::TypedOperatorHandle<convolution_backward_overrideable::schema> create_convolution_backward_overrideable_typed_handle() { |
| 2106 | return c10::Dispatcher::singleton() |
| 2107 | .findSchemaOrThrow(convolution_backward_overrideable::name, convolution_backward_overrideable::overload_name) |
| 2108 | .typed<convolution_backward_overrideable::schema>(); |
| 2109 | } |
| 2110 | |
| 2111 | // aten::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) |
| 2112 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> convolution_backward_overrideable::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask) { |
| 2113 | |
| 2114 | static auto op = create_convolution_backward_overrideable_typed_handle(); |
| 2115 | return op.call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask); |
| 2116 | } |
| 2117 | |
| 2118 | // aten::convolution_backward_overrideable(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor grad_input, Tensor grad_weight, Tensor grad_bias) |
| 2119 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> convolution_backward_overrideable::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask) { |
| 2120 | |
| 2121 | static auto op = create_convolution_backward_overrideable_typed_handle(); |
| 2122 | return op.redispatch(dispatchKeySet, grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask); |
| 2123 | } |
| 2124 | |
| 2125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution, name, "aten::_convolution") |
| 2126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution, overload_name, "") |
| 2127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution, schema_str, "_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor") |
| 2128 | |
| 2129 | // aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor |
| 2130 | static C10_NOINLINE c10::TypedOperatorHandle<_convolution::schema> create__convolution_typed_handle() { |
| 2131 | return c10::Dispatcher::singleton() |
| 2132 | .findSchemaOrThrow(_convolution::name, _convolution::overload_name) |
| 2133 | .typed<_convolution::schema>(); |
| 2134 | } |
| 2135 | |
| 2136 | // aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor |
| 2137 | at::Tensor _convolution::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) { |
| 2138 | |
| 2139 | static auto op = create__convolution_typed_handle(); |
| 2140 | return op.call(input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, benchmark, deterministic, cudnn_enabled, allow_tf32); |
| 2141 | } |
| 2142 | |
| 2143 | // aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor |
| 2144 | at::Tensor _convolution::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) { |
| 2145 | |
| 2146 | static auto op = create__convolution_typed_handle(); |
| 2147 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, benchmark, deterministic, cudnn_enabled, allow_tf32); |
| 2148 | } |
| 2149 | |
| 2150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_deprecated, name, "aten::_convolution") |
| 2151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_deprecated, overload_name, "deprecated") |
| 2152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_deprecated, schema_str, "_convolution.deprecated(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor") |
| 2153 | |
| 2154 | // aten::_convolution.deprecated(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor |
| 2155 | static C10_NOINLINE c10::TypedOperatorHandle<_convolution_deprecated::schema> create__convolution_deprecated_typed_handle() { |
| 2156 | return c10::Dispatcher::singleton() |
| 2157 | .findSchemaOrThrow(_convolution_deprecated::name, _convolution_deprecated::overload_name) |
| 2158 | .typed<_convolution_deprecated::schema>(); |
| 2159 | } |
| 2160 | |
| 2161 | // aten::_convolution.deprecated(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor |
| 2162 | at::Tensor _convolution_deprecated::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled) { |
| 2163 | |
| 2164 | static auto op = create__convolution_deprecated_typed_handle(); |
| 2165 | return op.call(input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, benchmark, deterministic, cudnn_enabled); |
| 2166 | } |
| 2167 | |
| 2168 | // aten::_convolution.deprecated(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled) -> Tensor |
| 2169 | at::Tensor _convolution_deprecated::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled) { |
| 2170 | |
| 2171 | static auto op = create__convolution_deprecated_typed_handle(); |
| 2172 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, benchmark, deterministic, cudnn_enabled); |
| 2173 | } |
| 2174 | |
| 2175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv_transpose1d, name, "aten::conv_transpose1d") |
| 2176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv_transpose1d, overload_name, "") |
| 2177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv_transpose1d, schema_str, "conv_transpose1d(Tensor input, Tensor weight, Tensor? bias=None, int[1] stride=1, int[1] padding=0, int[1] output_padding=0, int groups=1, int[1] dilation=1) -> Tensor") |
| 2178 | |
| 2179 | // aten::conv_transpose1d(Tensor input, Tensor weight, Tensor? bias=None, int[1] stride=1, int[1] padding=0, int[1] output_padding=0, int groups=1, int[1] dilation=1) -> Tensor |
| 2180 | static C10_NOINLINE c10::TypedOperatorHandle<conv_transpose1d::schema> create_conv_transpose1d_typed_handle() { |
| 2181 | return c10::Dispatcher::singleton() |
| 2182 | .findSchemaOrThrow(conv_transpose1d::name, conv_transpose1d::overload_name) |
| 2183 | .typed<conv_transpose1d::schema>(); |
| 2184 | } |
| 2185 | |
| 2186 | // aten::conv_transpose1d(Tensor input, Tensor weight, Tensor? bias=None, int[1] stride=1, int[1] padding=0, int[1] output_padding=0, int groups=1, int[1] dilation=1) -> Tensor |
| 2187 | at::Tensor conv_transpose1d::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, int64_t groups, at::IntArrayRef dilation) { |
| 2188 | |
| 2189 | static auto op = create_conv_transpose1d_typed_handle(); |
| 2190 | return op.call(input, weight, bias, stride, padding, output_padding, groups, dilation); |
| 2191 | } |
| 2192 | |
| 2193 | // aten::conv_transpose1d(Tensor input, Tensor weight, Tensor? bias=None, int[1] stride=1, int[1] padding=0, int[1] output_padding=0, int groups=1, int[1] dilation=1) -> Tensor |
| 2194 | at::Tensor conv_transpose1d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, int64_t groups, at::IntArrayRef dilation) { |
| 2195 | |
| 2196 | static auto op = create_conv_transpose1d_typed_handle(); |
| 2197 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, output_padding, groups, dilation); |
| 2198 | } |
| 2199 | |
| 2200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos, name, "aten::cos") |
| 2201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos, overload_name, "") |
| 2202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos, schema_str, "cos(Tensor self) -> Tensor") |
| 2203 | |
| 2204 | // aten::cos(Tensor self) -> Tensor |
| 2205 | static C10_NOINLINE c10::TypedOperatorHandle<cos::schema> create_cos_typed_handle() { |
| 2206 | return c10::Dispatcher::singleton() |
| 2207 | .findSchemaOrThrow(cos::name, cos::overload_name) |
| 2208 | .typed<cos::schema>(); |
| 2209 | } |
| 2210 | |
| 2211 | // aten::cos(Tensor self) -> Tensor |
| 2212 | at::Tensor cos::call(const at::Tensor & self) { |
| 2213 | |
| 2214 | static auto op = create_cos_typed_handle(); |
| 2215 | return op.call(self); |
| 2216 | } |
| 2217 | |
| 2218 | // aten::cos(Tensor self) -> Tensor |
| 2219 | at::Tensor cos::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 2220 | |
| 2221 | static auto op = create_cos_typed_handle(); |
| 2222 | return op.redispatch(dispatchKeySet, self); |
| 2223 | } |
| 2224 | |
| 2225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos_, name, "aten::cos_") |
| 2226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos_, overload_name, "") |
| 2227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos_, schema_str, "cos_(Tensor(a!) self) -> Tensor(a!)") |
| 2228 | |
| 2229 | // aten::cos_(Tensor(a!) self) -> Tensor(a!) |
| 2230 | static C10_NOINLINE c10::TypedOperatorHandle<cos_::schema> create_cos__typed_handle() { |
| 2231 | return c10::Dispatcher::singleton() |
| 2232 | .findSchemaOrThrow(cos_::name, cos_::overload_name) |
| 2233 | .typed<cos_::schema>(); |
| 2234 | } |
| 2235 | |
| 2236 | // aten::cos_(Tensor(a!) self) -> Tensor(a!) |
| 2237 | at::Tensor & cos_::call(at::Tensor & self) { |
| 2238 | |
| 2239 | static auto op = create_cos__typed_handle(); |
| 2240 | return op.call(self); |
| 2241 | } |
| 2242 | |
| 2243 | // aten::cos_(Tensor(a!) self) -> Tensor(a!) |
| 2244 | at::Tensor & cos_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 2245 | |
| 2246 | static auto op = create_cos__typed_handle(); |
| 2247 | return op.redispatch(dispatchKeySet, self); |
| 2248 | } |
| 2249 | |
| 2250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos_out, name, "aten::cos") |
| 2251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos_out, overload_name, "out") |
| 2252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cos_out, schema_str, "cos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 2253 | |
| 2254 | // aten::cos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2255 | static C10_NOINLINE c10::TypedOperatorHandle<cos_out::schema> create_cos_out_typed_handle() { |
| 2256 | return c10::Dispatcher::singleton() |
| 2257 | .findSchemaOrThrow(cos_out::name, cos_out::overload_name) |
| 2258 | .typed<cos_out::schema>(); |
| 2259 | } |
| 2260 | |
| 2261 | // aten::cos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2262 | at::Tensor & cos_out::call(const at::Tensor & self, at::Tensor & out) { |
| 2263 | |
| 2264 | static auto op = create_cos_out_typed_handle(); |
| 2265 | return op.call(self, out); |
| 2266 | } |
| 2267 | |
| 2268 | // aten::cos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2269 | at::Tensor & cos_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 2270 | |
| 2271 | static auto op = create_cos_out_typed_handle(); |
| 2272 | return op.redispatch(dispatchKeySet, self, out); |
| 2273 | } |
| 2274 | |
| 2275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_affine_grid_generator, name, "aten::cudnn_affine_grid_generator") |
| 2276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_affine_grid_generator, overload_name, "") |
| 2277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_affine_grid_generator, schema_str, "cudnn_affine_grid_generator(Tensor theta, int N, int C, int H, int W) -> Tensor grid") |
| 2278 | |
| 2279 | // aten::cudnn_affine_grid_generator(Tensor theta, int N, int C, int H, int W) -> Tensor grid |
| 2280 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_affine_grid_generator::schema> create_cudnn_affine_grid_generator_typed_handle() { |
| 2281 | return c10::Dispatcher::singleton() |
| 2282 | .findSchemaOrThrow(cudnn_affine_grid_generator::name, cudnn_affine_grid_generator::overload_name) |
| 2283 | .typed<cudnn_affine_grid_generator::schema>(); |
| 2284 | } |
| 2285 | |
| 2286 | // aten::cudnn_affine_grid_generator(Tensor theta, int N, int C, int H, int W) -> Tensor grid |
| 2287 | at::Tensor cudnn_affine_grid_generator::call(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W) { |
| 2288 | |
| 2289 | static auto op = create_cudnn_affine_grid_generator_typed_handle(); |
| 2290 | return op.call(theta, N, C, H, W); |
| 2291 | } |
| 2292 | |
| 2293 | // aten::cudnn_affine_grid_generator(Tensor theta, int N, int C, int H, int W) -> Tensor grid |
| 2294 | at::Tensor cudnn_affine_grid_generator::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W) { |
| 2295 | |
| 2296 | static auto op = create_cudnn_affine_grid_generator_typed_handle(); |
| 2297 | return op.redispatch(dispatchKeySet, theta, N, C, H, W); |
| 2298 | } |
| 2299 | |
| 2300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_backward, name, "aten::cudnn_batch_norm_backward") |
| 2301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_backward, overload_name, "") |
| 2302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_backward, schema_str, "cudnn_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace) -> (Tensor, Tensor, Tensor)") |
| 2303 | |
| 2304 | // aten::cudnn_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace) -> (Tensor, Tensor, Tensor) |
| 2305 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_batch_norm_backward::schema> create_cudnn_batch_norm_backward_typed_handle() { |
| 2306 | return c10::Dispatcher::singleton() |
| 2307 | .findSchemaOrThrow(cudnn_batch_norm_backward::name, cudnn_batch_norm_backward::overload_name) |
| 2308 | .typed<cudnn_batch_norm_backward::schema>(); |
| 2309 | } |
| 2310 | |
| 2311 | // aten::cudnn_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace) -> (Tensor, Tensor, Tensor) |
| 2312 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> cudnn_batch_norm_backward::call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon, const at::Tensor & reserveSpace) { |
| 2313 | |
| 2314 | static auto op = create_cudnn_batch_norm_backward_typed_handle(); |
| 2315 | return op.call(input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon, reserveSpace); |
| 2316 | } |
| 2317 | |
| 2318 | // aten::cudnn_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace) -> (Tensor, Tensor, Tensor) |
| 2319 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> cudnn_batch_norm_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon, const at::Tensor & reserveSpace) { |
| 2320 | |
| 2321 | static auto op = create_cudnn_batch_norm_backward_typed_handle(); |
| 2322 | return op.redispatch(dispatchKeySet, input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon, reserveSpace); |
| 2323 | } |
| 2324 | |
| 2325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_transpose, name, "aten::cudnn_convolution_transpose") |
| 2326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_transpose, overload_name, "") |
| 2327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_transpose, schema_str, "cudnn_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor") |
| 2328 | |
| 2329 | // aten::cudnn_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor |
| 2330 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_convolution_transpose::schema> create_cudnn_convolution_transpose_typed_handle() { |
| 2331 | return c10::Dispatcher::singleton() |
| 2332 | .findSchemaOrThrow(cudnn_convolution_transpose::name, cudnn_convolution_transpose::overload_name) |
| 2333 | .typed<cudnn_convolution_transpose::schema>(); |
| 2334 | } |
| 2335 | |
| 2336 | // aten::cudnn_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor |
| 2337 | at::Tensor cudnn_convolution_transpose::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { |
| 2338 | |
| 2339 | static auto op = create_cudnn_convolution_transpose_typed_handle(); |
| 2340 | return op.call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32); |
| 2341 | } |
| 2342 | |
| 2343 | // aten::cudnn_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32) -> Tensor |
| 2344 | at::Tensor cudnn_convolution_transpose::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32) { |
| 2345 | |
| 2346 | static auto op = create_cudnn_convolution_transpose_typed_handle(); |
| 2347 | return op.redispatch(dispatchKeySet, self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32); |
| 2348 | } |
| 2349 | |
| 2350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_grid_sampler_backward, name, "aten::cudnn_grid_sampler_backward") |
| 2351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_grid_sampler_backward, overload_name, "") |
| 2352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_grid_sampler_backward, schema_str, "cudnn_grid_sampler_backward(Tensor self, Tensor grid, Tensor grad_output) -> (Tensor grad_self, Tensor grad_grid)") |
| 2353 | |
| 2354 | // aten::cudnn_grid_sampler_backward(Tensor self, Tensor grid, Tensor grad_output) -> (Tensor grad_self, Tensor grad_grid) |
| 2355 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_grid_sampler_backward::schema> create_cudnn_grid_sampler_backward_typed_handle() { |
| 2356 | return c10::Dispatcher::singleton() |
| 2357 | .findSchemaOrThrow(cudnn_grid_sampler_backward::name, cudnn_grid_sampler_backward::overload_name) |
| 2358 | .typed<cudnn_grid_sampler_backward::schema>(); |
| 2359 | } |
| 2360 | |
| 2361 | // aten::cudnn_grid_sampler_backward(Tensor self, Tensor grid, Tensor grad_output) -> (Tensor grad_self, Tensor grad_grid) |
| 2362 | ::std::tuple<at::Tensor,at::Tensor> cudnn_grid_sampler_backward::call(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output) { |
| 2363 | |
| 2364 | static auto op = create_cudnn_grid_sampler_backward_typed_handle(); |
| 2365 | return op.call(self, grid, grad_output); |
| 2366 | } |
| 2367 | |
| 2368 | // aten::cudnn_grid_sampler_backward(Tensor self, Tensor grid, Tensor grad_output) -> (Tensor grad_self, Tensor grad_grid) |
| 2369 | ::std::tuple<at::Tensor,at::Tensor> cudnn_grid_sampler_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output) { |
| 2370 | |
| 2371 | static auto op = create_cudnn_grid_sampler_backward_typed_handle(); |
| 2372 | return op.redispatch(dispatchKeySet, self, grid, grad_output); |
| 2373 | } |
| 2374 | |
| 2375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum, name, "aten::cumsum") |
| 2376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum, overload_name, "") |
| 2377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum, schema_str, "cumsum(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor") |
| 2378 | |
| 2379 | // aten::cumsum(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor |
| 2380 | static C10_NOINLINE c10::TypedOperatorHandle<cumsum::schema> create_cumsum_typed_handle() { |
| 2381 | return c10::Dispatcher::singleton() |
| 2382 | .findSchemaOrThrow(cumsum::name, cumsum::overload_name) |
| 2383 | .typed<cumsum::schema>(); |
| 2384 | } |
| 2385 | |
| 2386 | // aten::cumsum(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor |
| 2387 | at::Tensor cumsum::call(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
| 2388 | |
| 2389 | static auto op = create_cumsum_typed_handle(); |
| 2390 | return op.call(self, dim, dtype); |
| 2391 | } |
| 2392 | |
| 2393 | // aten::cumsum(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor |
| 2394 | at::Tensor cumsum::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
| 2395 | |
| 2396 | static auto op = create_cumsum_typed_handle(); |
| 2397 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
| 2398 | } |
| 2399 | |
| 2400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_, name, "aten::cumsum_") |
| 2401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_, overload_name, "") |
| 2402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_, schema_str, "cumsum_(Tensor(a!) self, int dim, *, ScalarType? dtype=None) -> Tensor(a!)") |
| 2403 | |
| 2404 | // aten::cumsum_(Tensor(a!) self, int dim, *, ScalarType? dtype=None) -> Tensor(a!) |
| 2405 | static C10_NOINLINE c10::TypedOperatorHandle<cumsum_::schema> create_cumsum__typed_handle() { |
| 2406 | return c10::Dispatcher::singleton() |
| 2407 | .findSchemaOrThrow(cumsum_::name, cumsum_::overload_name) |
| 2408 | .typed<cumsum_::schema>(); |
| 2409 | } |
| 2410 | |
| 2411 | // aten::cumsum_(Tensor(a!) self, int dim, *, ScalarType? dtype=None) -> Tensor(a!) |
| 2412 | at::Tensor & cumsum_::call(at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
| 2413 | |
| 2414 | static auto op = create_cumsum__typed_handle(); |
| 2415 | return op.call(self, dim, dtype); |
| 2416 | } |
| 2417 | |
| 2418 | // aten::cumsum_(Tensor(a!) self, int dim, *, ScalarType? dtype=None) -> Tensor(a!) |
| 2419 | at::Tensor & cumsum_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
| 2420 | |
| 2421 | static auto op = create_cumsum__typed_handle(); |
| 2422 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
| 2423 | } |
| 2424 | |
| 2425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_out, name, "aten::cumsum") |
| 2426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_out, overload_name, "out") |
| 2427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_out, schema_str, "cumsum.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") |
| 2428 | |
| 2429 | // aten::cumsum.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 2430 | static C10_NOINLINE c10::TypedOperatorHandle<cumsum_out::schema> create_cumsum_out_typed_handle() { |
| 2431 | return c10::Dispatcher::singleton() |
| 2432 | .findSchemaOrThrow(cumsum_out::name, cumsum_out::overload_name) |
| 2433 | .typed<cumsum_out::schema>(); |
| 2434 | } |
| 2435 | |
| 2436 | // aten::cumsum.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 2437 | at::Tensor & cumsum_out::call(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 2438 | |
| 2439 | static auto op = create_cumsum_out_typed_handle(); |
| 2440 | return op.call(self, dim, dtype, out); |
| 2441 | } |
| 2442 | |
| 2443 | // aten::cumsum.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 2444 | at::Tensor & cumsum_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 2445 | |
| 2446 | static auto op = create_cumsum_out_typed_handle(); |
| 2447 | return op.redispatch(dispatchKeySet, self, dim, dtype, out); |
| 2448 | } |
| 2449 | |
| 2450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_dimname, name, "aten::cumsum") |
| 2451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_dimname, overload_name, "dimname") |
| 2452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_dimname, schema_str, "cumsum.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor") |
| 2453 | |
| 2454 | // aten::cumsum.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
| 2455 | static C10_NOINLINE c10::TypedOperatorHandle<cumsum_dimname::schema> create_cumsum_dimname_typed_handle() { |
| 2456 | return c10::Dispatcher::singleton() |
| 2457 | .findSchemaOrThrow(cumsum_dimname::name, cumsum_dimname::overload_name) |
| 2458 | .typed<cumsum_dimname::schema>(); |
| 2459 | } |
| 2460 | |
| 2461 | // aten::cumsum.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
| 2462 | at::Tensor cumsum_dimname::call(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
| 2463 | |
| 2464 | static auto op = create_cumsum_dimname_typed_handle(); |
| 2465 | return op.call(self, dim, dtype); |
| 2466 | } |
| 2467 | |
| 2468 | // aten::cumsum.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
| 2469 | at::Tensor cumsum_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
| 2470 | |
| 2471 | static auto op = create_cumsum_dimname_typed_handle(); |
| 2472 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
| 2473 | } |
| 2474 | |
| 2475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum__dimname, name, "aten::cumsum_") |
| 2476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum__dimname, overload_name, "dimname") |
| 2477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum__dimname, schema_str, "cumsum_.dimname(Tensor(a!) self, Dimname dim, *, ScalarType? dtype=None) -> Tensor(a!)") |
| 2478 | |
| 2479 | // aten::cumsum_.dimname(Tensor(a!) self, Dimname dim, *, ScalarType? dtype=None) -> Tensor(a!) |
| 2480 | static C10_NOINLINE c10::TypedOperatorHandle<cumsum__dimname::schema> create_cumsum__dimname_typed_handle() { |
| 2481 | return c10::Dispatcher::singleton() |
| 2482 | .findSchemaOrThrow(cumsum__dimname::name, cumsum__dimname::overload_name) |
| 2483 | .typed<cumsum__dimname::schema>(); |
| 2484 | } |
| 2485 | |
| 2486 | // aten::cumsum_.dimname(Tensor(a!) self, Dimname dim, *, ScalarType? dtype=None) -> Tensor(a!) |
| 2487 | at::Tensor & cumsum__dimname::call(at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
| 2488 | |
| 2489 | static auto op = create_cumsum__dimname_typed_handle(); |
| 2490 | return op.call(self, dim, dtype); |
| 2491 | } |
| 2492 | |
| 2493 | // aten::cumsum_.dimname(Tensor(a!) self, Dimname dim, *, ScalarType? dtype=None) -> Tensor(a!) |
| 2494 | at::Tensor & cumsum__dimname::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
| 2495 | |
| 2496 | static auto op = create_cumsum__dimname_typed_handle(); |
| 2497 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
| 2498 | } |
| 2499 | |
| 2500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_dimname_out, name, "aten::cumsum") |
| 2501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_dimname_out, overload_name, "dimname_out") |
| 2502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumsum_dimname_out, schema_str, "cumsum.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") |
| 2503 | |
| 2504 | // aten::cumsum.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 2505 | static C10_NOINLINE c10::TypedOperatorHandle<cumsum_dimname_out::schema> create_cumsum_dimname_out_typed_handle() { |
| 2506 | return c10::Dispatcher::singleton() |
| 2507 | .findSchemaOrThrow(cumsum_dimname_out::name, cumsum_dimname_out::overload_name) |
| 2508 | .typed<cumsum_dimname_out::schema>(); |
| 2509 | } |
| 2510 | |
| 2511 | // aten::cumsum.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 2512 | at::Tensor & cumsum_dimname_out::call(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 2513 | |
| 2514 | static auto op = create_cumsum_dimname_out_typed_handle(); |
| 2515 | return op.call(self, dim, dtype, out); |
| 2516 | } |
| 2517 | |
| 2518 | // aten::cumsum.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 2519 | at::Tensor & cumsum_dimname_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 2520 | |
| 2521 | static auto op = create_cumsum_dimname_out_typed_handle(); |
| 2522 | return op.redispatch(dispatchKeySet, self, dim, dtype, out); |
| 2523 | } |
| 2524 | |
| 2525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss, name, "aten::_ctc_loss") |
| 2526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss, overload_name, "") |
| 2527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss, schema_str, "_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor)") |
| 2528 | |
| 2529 | // aten::_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) |
| 2530 | static C10_NOINLINE c10::TypedOperatorHandle<_ctc_loss::schema> create__ctc_loss_typed_handle() { |
| 2531 | return c10::Dispatcher::singleton() |
| 2532 | .findSchemaOrThrow(_ctc_loss::name, _ctc_loss::overload_name) |
| 2533 | .typed<_ctc_loss::schema>(); |
| 2534 | } |
| 2535 | |
| 2536 | // aten::_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) |
| 2537 | ::std::tuple<at::Tensor,at::Tensor> _ctc_loss::call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity) { |
| 2538 | |
| 2539 | static auto op = create__ctc_loss_typed_handle(); |
| 2540 | return op.call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); |
| 2541 | } |
| 2542 | |
| 2543 | // aten::_ctc_loss(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) |
| 2544 | ::std::tuple<at::Tensor,at::Tensor> _ctc_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity) { |
| 2545 | |
| 2546 | static auto op = create__ctc_loss_typed_handle(); |
| 2547 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); |
| 2548 | } |
| 2549 | |
| 2550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_Tensor, name, "aten::_ctc_loss") |
| 2551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_Tensor, overload_name, "Tensor") |
| 2552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_Tensor, schema_str, "_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor)") |
| 2553 | |
| 2554 | // aten::_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) |
| 2555 | static C10_NOINLINE c10::TypedOperatorHandle<_ctc_loss_Tensor::schema> create__ctc_loss_Tensor_typed_handle() { |
| 2556 | return c10::Dispatcher::singleton() |
| 2557 | .findSchemaOrThrow(_ctc_loss_Tensor::name, _ctc_loss_Tensor::overload_name) |
| 2558 | .typed<_ctc_loss_Tensor::schema>(); |
| 2559 | } |
| 2560 | |
| 2561 | // aten::_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) |
| 2562 | ::std::tuple<at::Tensor,at::Tensor> _ctc_loss_Tensor::call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity) { |
| 2563 | |
| 2564 | static auto op = create__ctc_loss_Tensor_typed_handle(); |
| 2565 | return op.call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); |
| 2566 | } |
| 2567 | |
| 2568 | // aten::_ctc_loss.Tensor(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False) -> (Tensor, Tensor) |
| 2569 | ::std::tuple<at::Tensor,at::Tensor> _ctc_loss_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity) { |
| 2570 | |
| 2571 | static auto op = create__ctc_loss_Tensor_typed_handle(); |
| 2572 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); |
| 2573 | } |
| 2574 | |
| 2575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagflat, name, "aten::diagflat") |
| 2576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagflat, overload_name, "") |
| 2577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagflat, schema_str, "diagflat(Tensor self, int offset=0) -> Tensor") |
| 2578 | |
| 2579 | // aten::diagflat(Tensor self, int offset=0) -> Tensor |
| 2580 | static C10_NOINLINE c10::TypedOperatorHandle<diagflat::schema> create_diagflat_typed_handle() { |
| 2581 | return c10::Dispatcher::singleton() |
| 2582 | .findSchemaOrThrow(diagflat::name, diagflat::overload_name) |
| 2583 | .typed<diagflat::schema>(); |
| 2584 | } |
| 2585 | |
| 2586 | // aten::diagflat(Tensor self, int offset=0) -> Tensor |
| 2587 | at::Tensor diagflat::call(const at::Tensor & self, int64_t offset) { |
| 2588 | |
| 2589 | static auto op = create_diagflat_typed_handle(); |
| 2590 | return op.call(self, offset); |
| 2591 | } |
| 2592 | |
| 2593 | // aten::diagflat(Tensor self, int offset=0) -> Tensor |
| 2594 | at::Tensor diagflat::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t offset) { |
| 2595 | |
| 2596 | static auto op = create_diagflat_typed_handle(); |
| 2597 | return op.redispatch(dispatchKeySet, self, offset); |
| 2598 | } |
| 2599 | |
| 2600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_diagonal, name, "aten::linalg_diagonal") |
| 2601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_diagonal, overload_name, "") |
| 2602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_diagonal, schema_str, "linalg_diagonal(Tensor(a) A, *, int offset=0, int dim1=-2, int dim2=-1) -> Tensor(a)") |
| 2603 | |
| 2604 | // aten::linalg_diagonal(Tensor(a) A, *, int offset=0, int dim1=-2, int dim2=-1) -> Tensor(a) |
| 2605 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_diagonal::schema> create_linalg_diagonal_typed_handle() { |
| 2606 | return c10::Dispatcher::singleton() |
| 2607 | .findSchemaOrThrow(linalg_diagonal::name, linalg_diagonal::overload_name) |
| 2608 | .typed<linalg_diagonal::schema>(); |
| 2609 | } |
| 2610 | |
| 2611 | // aten::linalg_diagonal(Tensor(a) A, *, int offset=0, int dim1=-2, int dim2=-1) -> Tensor(a) |
| 2612 | at::Tensor linalg_diagonal::call(const at::Tensor & A, int64_t offset, int64_t dim1, int64_t dim2) { |
| 2613 | |
| 2614 | static auto op = create_linalg_diagonal_typed_handle(); |
| 2615 | return op.call(A, offset, dim1, dim2); |
| 2616 | } |
| 2617 | |
| 2618 | // aten::linalg_diagonal(Tensor(a) A, *, int offset=0, int dim1=-2, int dim2=-1) -> Tensor(a) |
| 2619 | at::Tensor linalg_diagonal::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, int64_t offset, int64_t dim1, int64_t dim2) { |
| 2620 | |
| 2621 | static auto op = create_linalg_diagonal_typed_handle(); |
| 2622 | return op.redispatch(dispatchKeySet, A, offset, dim1, dim2); |
| 2623 | } |
| 2624 | |
| 2625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_Tensor, name, "aten::true_divide") |
| 2626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_Tensor, overload_name, "Tensor") |
| 2627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_Tensor, schema_str, "true_divide.Tensor(Tensor self, Tensor other) -> Tensor") |
| 2628 | |
| 2629 | // aten::true_divide.Tensor(Tensor self, Tensor other) -> Tensor |
| 2630 | static C10_NOINLINE c10::TypedOperatorHandle<true_divide_Tensor::schema> create_true_divide_Tensor_typed_handle() { |
| 2631 | return c10::Dispatcher::singleton() |
| 2632 | .findSchemaOrThrow(true_divide_Tensor::name, true_divide_Tensor::overload_name) |
| 2633 | .typed<true_divide_Tensor::schema>(); |
| 2634 | } |
| 2635 | |
| 2636 | // aten::true_divide.Tensor(Tensor self, Tensor other) -> Tensor |
| 2637 | at::Tensor true_divide_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 2638 | |
| 2639 | static auto op = create_true_divide_Tensor_typed_handle(); |
| 2640 | return op.call(self, other); |
| 2641 | } |
| 2642 | |
| 2643 | // aten::true_divide.Tensor(Tensor self, Tensor other) -> Tensor |
| 2644 | at::Tensor true_divide_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 2645 | |
| 2646 | static auto op = create_true_divide_Tensor_typed_handle(); |
| 2647 | return op.redispatch(dispatchKeySet, self, other); |
| 2648 | } |
| 2649 | |
| 2650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide__Tensor, name, "aten::true_divide_") |
| 2651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide__Tensor, overload_name, "Tensor") |
| 2652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide__Tensor, schema_str, "true_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 2653 | |
| 2654 | // aten::true_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 2655 | static C10_NOINLINE c10::TypedOperatorHandle<true_divide__Tensor::schema> create_true_divide__Tensor_typed_handle() { |
| 2656 | return c10::Dispatcher::singleton() |
| 2657 | .findSchemaOrThrow(true_divide__Tensor::name, true_divide__Tensor::overload_name) |
| 2658 | .typed<true_divide__Tensor::schema>(); |
| 2659 | } |
| 2660 | |
| 2661 | // aten::true_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 2662 | at::Tensor & true_divide__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 2663 | |
| 2664 | static auto op = create_true_divide__Tensor_typed_handle(); |
| 2665 | return op.call(self, other); |
| 2666 | } |
| 2667 | |
| 2668 | // aten::true_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 2669 | at::Tensor & true_divide__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 2670 | |
| 2671 | static auto op = create_true_divide__Tensor_typed_handle(); |
| 2672 | return op.redispatch(dispatchKeySet, self, other); |
| 2673 | } |
| 2674 | |
| 2675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_out, name, "aten::true_divide") |
| 2676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_out, overload_name, "out") |
| 2677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_out, schema_str, "true_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 2678 | |
| 2679 | // aten::true_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2680 | static C10_NOINLINE c10::TypedOperatorHandle<true_divide_out::schema> create_true_divide_out_typed_handle() { |
| 2681 | return c10::Dispatcher::singleton() |
| 2682 | .findSchemaOrThrow(true_divide_out::name, true_divide_out::overload_name) |
| 2683 | .typed<true_divide_out::schema>(); |
| 2684 | } |
| 2685 | |
| 2686 | // aten::true_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2687 | at::Tensor & true_divide_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2688 | |
| 2689 | static auto op = create_true_divide_out_typed_handle(); |
| 2690 | return op.call(self, other, out); |
| 2691 | } |
| 2692 | |
| 2693 | // aten::true_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2694 | at::Tensor & true_divide_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2695 | |
| 2696 | static auto op = create_true_divide_out_typed_handle(); |
| 2697 | return op.redispatch(dispatchKeySet, self, other, out); |
| 2698 | } |
| 2699 | |
| 2700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_Scalar, name, "aten::true_divide") |
| 2701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_Scalar, overload_name, "Scalar") |
| 2702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide_Scalar, schema_str, "true_divide.Scalar(Tensor self, Scalar other) -> Tensor") |
| 2703 | |
| 2704 | // aten::true_divide.Scalar(Tensor self, Scalar other) -> Tensor |
| 2705 | static C10_NOINLINE c10::TypedOperatorHandle<true_divide_Scalar::schema> create_true_divide_Scalar_typed_handle() { |
| 2706 | return c10::Dispatcher::singleton() |
| 2707 | .findSchemaOrThrow(true_divide_Scalar::name, true_divide_Scalar::overload_name) |
| 2708 | .typed<true_divide_Scalar::schema>(); |
| 2709 | } |
| 2710 | |
| 2711 | // aten::true_divide.Scalar(Tensor self, Scalar other) -> Tensor |
| 2712 | at::Tensor true_divide_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 2713 | |
| 2714 | static auto op = create_true_divide_Scalar_typed_handle(); |
| 2715 | return op.call(self, other); |
| 2716 | } |
| 2717 | |
| 2718 | // aten::true_divide.Scalar(Tensor self, Scalar other) -> Tensor |
| 2719 | at::Tensor true_divide_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 2720 | |
| 2721 | static auto op = create_true_divide_Scalar_typed_handle(); |
| 2722 | return op.redispatch(dispatchKeySet, self, other); |
| 2723 | } |
| 2724 | |
| 2725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide__Scalar, name, "aten::true_divide_") |
| 2726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide__Scalar, overload_name, "Scalar") |
| 2727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(true_divide__Scalar, schema_str, "true_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 2728 | |
| 2729 | // aten::true_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 2730 | static C10_NOINLINE c10::TypedOperatorHandle<true_divide__Scalar::schema> create_true_divide__Scalar_typed_handle() { |
| 2731 | return c10::Dispatcher::singleton() |
| 2732 | .findSchemaOrThrow(true_divide__Scalar::name, true_divide__Scalar::overload_name) |
| 2733 | .typed<true_divide__Scalar::schema>(); |
| 2734 | } |
| 2735 | |
| 2736 | // aten::true_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 2737 | at::Tensor & true_divide__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 2738 | |
| 2739 | static auto op = create_true_divide__Scalar_typed_handle(); |
| 2740 | return op.call(self, other); |
| 2741 | } |
| 2742 | |
| 2743 | // aten::true_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 2744 | at::Tensor & true_divide__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 2745 | |
| 2746 | static auto op = create_true_divide__Scalar_typed_handle(); |
| 2747 | return op.redispatch(dispatchKeySet, self, other); |
| 2748 | } |
| 2749 | |
| 2750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vdot, name, "aten::vdot") |
| 2751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vdot, overload_name, "") |
| 2752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vdot, schema_str, "vdot(Tensor self, Tensor other) -> Tensor") |
| 2753 | |
| 2754 | // aten::vdot(Tensor self, Tensor other) -> Tensor |
| 2755 | static C10_NOINLINE c10::TypedOperatorHandle<vdot::schema> create_vdot_typed_handle() { |
| 2756 | return c10::Dispatcher::singleton() |
| 2757 | .findSchemaOrThrow(vdot::name, vdot::overload_name) |
| 2758 | .typed<vdot::schema>(); |
| 2759 | } |
| 2760 | |
| 2761 | // aten::vdot(Tensor self, Tensor other) -> Tensor |
| 2762 | at::Tensor vdot::call(const at::Tensor & self, const at::Tensor & other) { |
| 2763 | |
| 2764 | static auto op = create_vdot_typed_handle(); |
| 2765 | return op.call(self, other); |
| 2766 | } |
| 2767 | |
| 2768 | // aten::vdot(Tensor self, Tensor other) -> Tensor |
| 2769 | at::Tensor vdot::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 2770 | |
| 2771 | static auto op = create_vdot_typed_handle(); |
| 2772 | return op.redispatch(dispatchKeySet, self, other); |
| 2773 | } |
| 2774 | |
| 2775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vdot_out, name, "aten::vdot") |
| 2776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vdot_out, overload_name, "out") |
| 2777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vdot_out, schema_str, "vdot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 2778 | |
| 2779 | // aten::vdot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2780 | static C10_NOINLINE c10::TypedOperatorHandle<vdot_out::schema> create_vdot_out_typed_handle() { |
| 2781 | return c10::Dispatcher::singleton() |
| 2782 | .findSchemaOrThrow(vdot_out::name, vdot_out::overload_name) |
| 2783 | .typed<vdot_out::schema>(); |
| 2784 | } |
| 2785 | |
| 2786 | // aten::vdot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2787 | at::Tensor & vdot_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2788 | |
| 2789 | static auto op = create_vdot_out_typed_handle(); |
| 2790 | return op.call(self, other, out); |
| 2791 | } |
| 2792 | |
| 2793 | // aten::vdot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2794 | at::Tensor & vdot_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2795 | |
| 2796 | static auto op = create_vdot_out_typed_handle(); |
| 2797 | return op.redispatch(dispatchKeySet, self, other, out); |
| 2798 | } |
| 2799 | |
| 2800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_backward, name, "aten::embedding_backward") |
| 2801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_backward, overload_name, "") |
| 2802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_backward, schema_str, "embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor") |
| 2803 | |
| 2804 | // aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor |
| 2805 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_backward::schema> create_embedding_backward_typed_handle() { |
| 2806 | return c10::Dispatcher::singleton() |
| 2807 | .findSchemaOrThrow(embedding_backward::name, embedding_backward::overload_name) |
| 2808 | .typed<embedding_backward::schema>(); |
| 2809 | } |
| 2810 | |
| 2811 | // aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor |
| 2812 | at::Tensor embedding_backward::call(const at::Tensor & grad, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse) { |
| 2813 | |
| 2814 | static auto op = create_embedding_backward_typed_handle(); |
| 2815 | return op.call(grad, indices, num_weights, padding_idx, scale_grad_by_freq, sparse); |
| 2816 | } |
| 2817 | |
| 2818 | // aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor |
| 2819 | at::Tensor embedding_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse) { |
| 2820 | |
| 2821 | static auto op = create_embedding_backward_typed_handle(); |
| 2822 | return op.redispatch(dispatchKeySet, grad, indices, num_weights, padding_idx, scale_grad_by_freq, sparse); |
| 2823 | } |
| 2824 | |
| 2825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_dense_backward, name, "aten::embedding_dense_backward") |
| 2826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_dense_backward, overload_name, "") |
| 2827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_dense_backward, schema_str, "embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor") |
| 2828 | |
| 2829 | // aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor |
| 2830 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_dense_backward::schema> create_embedding_dense_backward_typed_handle() { |
| 2831 | return c10::Dispatcher::singleton() |
| 2832 | .findSchemaOrThrow(embedding_dense_backward::name, embedding_dense_backward::overload_name) |
| 2833 | .typed<embedding_dense_backward::schema>(); |
| 2834 | } |
| 2835 | |
| 2836 | // aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor |
| 2837 | at::Tensor embedding_dense_backward::call(const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq) { |
| 2838 | |
| 2839 | static auto op = create_embedding_dense_backward_typed_handle(); |
| 2840 | return op.call(grad_output, indices, num_weights, padding_idx, scale_grad_by_freq); |
| 2841 | } |
| 2842 | |
| 2843 | // aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor |
| 2844 | at::Tensor embedding_dense_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq) { |
| 2845 | |
| 2846 | static auto op = create_embedding_dense_backward_typed_handle(); |
| 2847 | return op.redispatch(dispatchKeySet, grad_output, indices, num_weights, padding_idx, scale_grad_by_freq); |
| 2848 | } |
| 2849 | |
| 2850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag, name, "aten::_embedding_bag") |
| 2851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag, overload_name, "") |
| 2852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag, schema_str, "_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor)") |
| 2853 | |
| 2854 | // aten::_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor) |
| 2855 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag::schema> create__embedding_bag_typed_handle() { |
| 2856 | return c10::Dispatcher::singleton() |
| 2857 | .findSchemaOrThrow(_embedding_bag::name, _embedding_bag::overload_name) |
| 2858 | .typed<_embedding_bag::schema>(); |
| 2859 | } |
| 2860 | |
| 2861 | // aten::_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor) |
| 2862 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _embedding_bag::call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, bool include_last_offset, int64_t padding_idx) { |
| 2863 | |
| 2864 | static auto op = create__embedding_bag_typed_handle(); |
| 2865 | return op.call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx); |
| 2866 | } |
| 2867 | |
| 2868 | // aten::_embedding_bag(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1) -> (Tensor, Tensor, Tensor, Tensor) |
| 2869 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _embedding_bag::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, bool include_last_offset, int64_t padding_idx) { |
| 2870 | |
| 2871 | static auto op = create__embedding_bag_typed_handle(); |
| 2872 | return op.redispatch(dispatchKeySet, weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx); |
| 2873 | } |
| 2874 | |
| 2875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_sparse_backward, name, "aten::_embedding_bag_sparse_backward") |
| 2876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_sparse_backward, overload_name, "") |
| 2877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_sparse_backward, schema_str, "_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor") |
| 2878 | |
| 2879 | // aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2880 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag_sparse_backward::schema> create__embedding_bag_sparse_backward_typed_handle() { |
| 2881 | return c10::Dispatcher::singleton() |
| 2882 | .findSchemaOrThrow(_embedding_bag_sparse_backward::name, _embedding_bag_sparse_backward::overload_name) |
| 2883 | .typed<_embedding_bag_sparse_backward::schema>(); |
| 2884 | } |
| 2885 | |
| 2886 | // aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2887 | at::Tensor _embedding_bag_sparse_backward::call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx) { |
| 2888 | |
| 2889 | static auto op = create__embedding_bag_sparse_backward_typed_handle(); |
| 2890 | return op.call(grad, indices, offsets, offset2bag, bag_size, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); |
| 2891 | } |
| 2892 | |
| 2893 | // aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2894 | at::Tensor _embedding_bag_sparse_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx) { |
| 2895 | |
| 2896 | static auto op = create__embedding_bag_sparse_backward_typed_handle(); |
| 2897 | return op.redispatch(dispatchKeySet, grad, indices, offsets, offset2bag, bag_size, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); |
| 2898 | } |
| 2899 | |
| 2900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty, name, "aten::new_empty") |
| 2901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty, overload_name, "") |
| 2902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty, schema_str, "new_empty(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 2903 | |
| 2904 | // aten::new_empty(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2905 | static C10_NOINLINE c10::TypedOperatorHandle<new_empty::schema> create_new_empty_typed_handle() { |
| 2906 | return c10::Dispatcher::singleton() |
| 2907 | .findSchemaOrThrow(new_empty::name, new_empty::overload_name) |
| 2908 | .typed<new_empty::schema>(); |
| 2909 | } |
| 2910 | |
| 2911 | // aten::new_empty(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2912 | at::Tensor new_empty::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 2913 | |
| 2914 | static auto op = create_new_empty_typed_handle(); |
| 2915 | return op.call(self, size, dtype, layout, device, pin_memory); |
| 2916 | } |
| 2917 | |
| 2918 | // aten::new_empty(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2919 | at::Tensor new_empty::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 2920 | |
| 2921 | static auto op = create_new_empty_typed_handle(); |
| 2922 | return op.redispatch(dispatchKeySet, self, size, dtype, layout, device, pin_memory); |
| 2923 | } |
| 2924 | |
| 2925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1, name, "aten::expm1") |
| 2926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1, overload_name, "") |
| 2927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1, schema_str, "expm1(Tensor self) -> Tensor") |
| 2928 | |
| 2929 | // aten::expm1(Tensor self) -> Tensor |
| 2930 | static C10_NOINLINE c10::TypedOperatorHandle<expm1::schema> create_expm1_typed_handle() { |
| 2931 | return c10::Dispatcher::singleton() |
| 2932 | .findSchemaOrThrow(expm1::name, expm1::overload_name) |
| 2933 | .typed<expm1::schema>(); |
| 2934 | } |
| 2935 | |
| 2936 | // aten::expm1(Tensor self) -> Tensor |
| 2937 | at::Tensor expm1::call(const at::Tensor & self) { |
| 2938 | |
| 2939 | static auto op = create_expm1_typed_handle(); |
| 2940 | return op.call(self); |
| 2941 | } |
| 2942 | |
| 2943 | // aten::expm1(Tensor self) -> Tensor |
| 2944 | at::Tensor expm1::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 2945 | |
| 2946 | static auto op = create_expm1_typed_handle(); |
| 2947 | return op.redispatch(dispatchKeySet, self); |
| 2948 | } |
| 2949 | |
| 2950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1_, name, "aten::expm1_") |
| 2951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1_, overload_name, "") |
| 2952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1_, schema_str, "expm1_(Tensor(a!) self) -> Tensor(a!)") |
| 2953 | |
| 2954 | // aten::expm1_(Tensor(a!) self) -> Tensor(a!) |
| 2955 | static C10_NOINLINE c10::TypedOperatorHandle<expm1_::schema> create_expm1__typed_handle() { |
| 2956 | return c10::Dispatcher::singleton() |
| 2957 | .findSchemaOrThrow(expm1_::name, expm1_::overload_name) |
| 2958 | .typed<expm1_::schema>(); |
| 2959 | } |
| 2960 | |
| 2961 | // aten::expm1_(Tensor(a!) self) -> Tensor(a!) |
| 2962 | at::Tensor & expm1_::call(at::Tensor & self) { |
| 2963 | |
| 2964 | static auto op = create_expm1__typed_handle(); |
| 2965 | return op.call(self); |
| 2966 | } |
| 2967 | |
| 2968 | // aten::expm1_(Tensor(a!) self) -> Tensor(a!) |
| 2969 | at::Tensor & expm1_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 2970 | |
| 2971 | static auto op = create_expm1__typed_handle(); |
| 2972 | return op.redispatch(dispatchKeySet, self); |
| 2973 | } |
| 2974 | |
| 2975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1_out, name, "aten::expm1") |
| 2976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1_out, overload_name, "out") |
| 2977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expm1_out, schema_str, "expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 2978 | |
| 2979 | // aten::expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2980 | static C10_NOINLINE c10::TypedOperatorHandle<expm1_out::schema> create_expm1_out_typed_handle() { |
| 2981 | return c10::Dispatcher::singleton() |
| 2982 | .findSchemaOrThrow(expm1_out::name, expm1_out::overload_name) |
| 2983 | .typed<expm1_out::schema>(); |
| 2984 | } |
| 2985 | |
| 2986 | // aten::expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2987 | at::Tensor & expm1_out::call(const at::Tensor & self, at::Tensor & out) { |
| 2988 | |
| 2989 | static auto op = create_expm1_out_typed_handle(); |
| 2990 | return op.call(self, out); |
| 2991 | } |
| 2992 | |
| 2993 | // aten::expm1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2994 | at::Tensor & expm1_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 2995 | |
| 2996 | static auto op = create_expm1_out_typed_handle(); |
| 2997 | return op.redispatch(dispatchKeySet, self, out); |
| 2998 | } |
| 2999 | |
| 3000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_as, name, "aten::expand_as") |
| 3001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_as, overload_name, "") |
| 3002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_as, schema_str, "expand_as(Tensor(a) self, Tensor other) -> Tensor(a)") |
| 3003 | |
| 3004 | // aten::expand_as(Tensor(a) self, Tensor other) -> Tensor(a) |
| 3005 | static C10_NOINLINE c10::TypedOperatorHandle<expand_as::schema> create_expand_as_typed_handle() { |
| 3006 | return c10::Dispatcher::singleton() |
| 3007 | .findSchemaOrThrow(expand_as::name, expand_as::overload_name) |
| 3008 | .typed<expand_as::schema>(); |
| 3009 | } |
| 3010 | |
| 3011 | // aten::expand_as(Tensor(a) self, Tensor other) -> Tensor(a) |
| 3012 | at::Tensor expand_as::call(const at::Tensor & self, const at::Tensor & other) { |
| 3013 | |
| 3014 | static auto op = create_expand_as_typed_handle(); |
| 3015 | return op.call(self, other); |
| 3016 | } |
| 3017 | |
| 3018 | // aten::expand_as(Tensor(a) self, Tensor other) -> Tensor(a) |
| 3019 | at::Tensor expand_as::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 3020 | |
| 3021 | static auto op = create_expand_as_typed_handle(); |
| 3022 | return op.redispatch(dispatchKeySet, self, other); |
| 3023 | } |
| 3024 | |
| 3025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_int, name, "aten::unflatten") |
| 3026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_int, overload_name, "int") |
| 3027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_int, schema_str, "unflatten.int(Tensor(a) self, int dim, int[] sizes) -> Tensor(a)") |
| 3028 | |
| 3029 | // aten::unflatten.int(Tensor(a) self, int dim, int[] sizes) -> Tensor(a) |
| 3030 | static C10_NOINLINE c10::TypedOperatorHandle<unflatten_int::schema> create_unflatten_int_typed_handle() { |
| 3031 | return c10::Dispatcher::singleton() |
| 3032 | .findSchemaOrThrow(unflatten_int::name, unflatten_int::overload_name) |
| 3033 | .typed<unflatten_int::schema>(); |
| 3034 | } |
| 3035 | |
| 3036 | // aten::unflatten.int(Tensor(a) self, int dim, int[] sizes) -> Tensor(a) |
| 3037 | at::Tensor unflatten_int::call(const at::Tensor & self, int64_t dim, at::IntArrayRef sizes) { |
| 3038 | |
| 3039 | static auto op = create_unflatten_int_typed_handle(); |
| 3040 | return op.call(self, dim, sizes); |
| 3041 | } |
| 3042 | |
| 3043 | // aten::unflatten.int(Tensor(a) self, int dim, int[] sizes) -> Tensor(a) |
| 3044 | at::Tensor unflatten_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::IntArrayRef sizes) { |
| 3045 | |
| 3046 | static auto op = create_unflatten_int_typed_handle(); |
| 3047 | return op.redispatch(dispatchKeySet, self, dim, sizes); |
| 3048 | } |
| 3049 | |
| 3050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_Dimname, name, "aten::unflatten") |
| 3051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_Dimname, overload_name, "Dimname") |
| 3052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_Dimname, schema_str, "unflatten.Dimname(Tensor(a) self, Dimname dim, int[] sizes, Dimname[] names) -> Tensor(a)") |
| 3053 | |
| 3054 | // aten::unflatten.Dimname(Tensor(a) self, Dimname dim, int[] sizes, Dimname[] names) -> Tensor(a) |
| 3055 | static C10_NOINLINE c10::TypedOperatorHandle<unflatten_Dimname::schema> create_unflatten_Dimname_typed_handle() { |
| 3056 | return c10::Dispatcher::singleton() |
| 3057 | .findSchemaOrThrow(unflatten_Dimname::name, unflatten_Dimname::overload_name) |
| 3058 | .typed<unflatten_Dimname::schema>(); |
| 3059 | } |
| 3060 | |
| 3061 | // aten::unflatten.Dimname(Tensor(a) self, Dimname dim, int[] sizes, Dimname[] names) -> Tensor(a) |
| 3062 | at::Tensor unflatten_Dimname::call(const at::Tensor & self, at::Dimname dim, at::IntArrayRef sizes, at::DimnameList names) { |
| 3063 | |
| 3064 | static auto op = create_unflatten_Dimname_typed_handle(); |
| 3065 | return op.call(self, dim, sizes, names); |
| 3066 | } |
| 3067 | |
| 3068 | // aten::unflatten.Dimname(Tensor(a) self, Dimname dim, int[] sizes, Dimname[] names) -> Tensor(a) |
| 3069 | at::Tensor unflatten_Dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, at::IntArrayRef sizes, at::DimnameList names) { |
| 3070 | |
| 3071 | static auto op = create_unflatten_Dimname_typed_handle(); |
| 3072 | return op.redispatch(dispatchKeySet, self, dim, sizes, names); |
| 3073 | } |
| 3074 | |
| 3075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Scalar, name, "aten::fill") |
| 3076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Scalar, overload_name, "Scalar") |
| 3077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Scalar, schema_str, "fill.Scalar(Tensor self, Scalar value) -> Tensor") |
| 3078 | |
| 3079 | // aten::fill.Scalar(Tensor self, Scalar value) -> Tensor |
| 3080 | static C10_NOINLINE c10::TypedOperatorHandle<fill_Scalar::schema> create_fill_Scalar_typed_handle() { |
| 3081 | return c10::Dispatcher::singleton() |
| 3082 | .findSchemaOrThrow(fill_Scalar::name, fill_Scalar::overload_name) |
| 3083 | .typed<fill_Scalar::schema>(); |
| 3084 | } |
| 3085 | |
| 3086 | // aten::fill.Scalar(Tensor self, Scalar value) -> Tensor |
| 3087 | at::Tensor fill_Scalar::call(const at::Tensor & self, const at::Scalar & value) { |
| 3088 | |
| 3089 | static auto op = create_fill_Scalar_typed_handle(); |
| 3090 | return op.call(self, value); |
| 3091 | } |
| 3092 | |
| 3093 | // aten::fill.Scalar(Tensor self, Scalar value) -> Tensor |
| 3094 | at::Tensor fill_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & value) { |
| 3095 | |
| 3096 | static auto op = create_fill_Scalar_typed_handle(); |
| 3097 | return op.redispatch(dispatchKeySet, self, value); |
| 3098 | } |
| 3099 | |
| 3100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Tensor, name, "aten::fill") |
| 3101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Tensor, overload_name, "Tensor") |
| 3102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Tensor, schema_str, "fill.Tensor(Tensor self, Tensor value) -> Tensor") |
| 3103 | |
| 3104 | // aten::fill.Tensor(Tensor self, Tensor value) -> Tensor |
| 3105 | static C10_NOINLINE c10::TypedOperatorHandle<fill_Tensor::schema> create_fill_Tensor_typed_handle() { |
| 3106 | return c10::Dispatcher::singleton() |
| 3107 | .findSchemaOrThrow(fill_Tensor::name, fill_Tensor::overload_name) |
| 3108 | .typed<fill_Tensor::schema>(); |
| 3109 | } |
| 3110 | |
| 3111 | // aten::fill.Tensor(Tensor self, Tensor value) -> Tensor |
| 3112 | at::Tensor fill_Tensor::call(const at::Tensor & self, const at::Tensor & value) { |
| 3113 | |
| 3114 | static auto op = create_fill_Tensor_typed_handle(); |
| 3115 | return op.call(self, value); |
| 3116 | } |
| 3117 | |
| 3118 | // aten::fill.Tensor(Tensor self, Tensor value) -> Tensor |
| 3119 | at::Tensor fill_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & value) { |
| 3120 | |
| 3121 | static auto op = create_fill_Tensor_typed_handle(); |
| 3122 | return op.redispatch(dispatchKeySet, self, value); |
| 3123 | } |
| 3124 | |
| 3125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill__Scalar, name, "aten::fill_") |
| 3126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill__Scalar, overload_name, "Scalar") |
| 3127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill__Scalar, schema_str, "fill_.Scalar(Tensor(a!) self, Scalar value) -> Tensor(a!)") |
| 3128 | |
| 3129 | // aten::fill_.Scalar(Tensor(a!) self, Scalar value) -> Tensor(a!) |
| 3130 | static C10_NOINLINE c10::TypedOperatorHandle<fill__Scalar::schema> create_fill__Scalar_typed_handle() { |
| 3131 | return c10::Dispatcher::singleton() |
| 3132 | .findSchemaOrThrow(fill__Scalar::name, fill__Scalar::overload_name) |
| 3133 | .typed<fill__Scalar::schema>(); |
| 3134 | } |
| 3135 | |
| 3136 | // aten::fill_.Scalar(Tensor(a!) self, Scalar value) -> Tensor(a!) |
| 3137 | at::Tensor & fill__Scalar::call(at::Tensor & self, const at::Scalar & value) { |
| 3138 | |
| 3139 | static auto op = create_fill__Scalar_typed_handle(); |
| 3140 | return op.call(self, value); |
| 3141 | } |
| 3142 | |
| 3143 | // aten::fill_.Scalar(Tensor(a!) self, Scalar value) -> Tensor(a!) |
| 3144 | at::Tensor & fill__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & value) { |
| 3145 | |
| 3146 | static auto op = create_fill__Scalar_typed_handle(); |
| 3147 | return op.redispatch(dispatchKeySet, self, value); |
| 3148 | } |
| 3149 | |
| 3150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill__Tensor, name, "aten::fill_") |
| 3151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill__Tensor, overload_name, "Tensor") |
| 3152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill__Tensor, schema_str, "fill_.Tensor(Tensor(a!) self, Tensor value) -> Tensor(a!)") |
| 3153 | |
| 3154 | // aten::fill_.Tensor(Tensor(a!) self, Tensor value) -> Tensor(a!) |
| 3155 | static C10_NOINLINE c10::TypedOperatorHandle<fill__Tensor::schema> create_fill__Tensor_typed_handle() { |
| 3156 | return c10::Dispatcher::singleton() |
| 3157 | .findSchemaOrThrow(fill__Tensor::name, fill__Tensor::overload_name) |
| 3158 | .typed<fill__Tensor::schema>(); |
| 3159 | } |
| 3160 | |
| 3161 | // aten::fill_.Tensor(Tensor(a!) self, Tensor value) -> Tensor(a!) |
| 3162 | at::Tensor & fill__Tensor::call(at::Tensor & self, const at::Tensor & value) { |
| 3163 | |
| 3164 | static auto op = create_fill__Tensor_typed_handle(); |
| 3165 | return op.call(self, value); |
| 3166 | } |
| 3167 | |
| 3168 | // aten::fill_.Tensor(Tensor(a!) self, Tensor value) -> Tensor(a!) |
| 3169 | at::Tensor & fill__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & value) { |
| 3170 | |
| 3171 | static auto op = create_fill__Tensor_typed_handle(); |
| 3172 | return op.redispatch(dispatchKeySet, self, value); |
| 3173 | } |
| 3174 | |
| 3175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm_out, name, "aten::lcm") |
| 3176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm_out, overload_name, "out") |
| 3177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm_out, schema_str, "lcm.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 3178 | |
| 3179 | // aten::lcm.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3180 | static C10_NOINLINE c10::TypedOperatorHandle<lcm_out::schema> create_lcm_out_typed_handle() { |
| 3181 | return c10::Dispatcher::singleton() |
| 3182 | .findSchemaOrThrow(lcm_out::name, lcm_out::overload_name) |
| 3183 | .typed<lcm_out::schema>(); |
| 3184 | } |
| 3185 | |
| 3186 | // aten::lcm.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3187 | at::Tensor & lcm_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3188 | |
| 3189 | static auto op = create_lcm_out_typed_handle(); |
| 3190 | return op.call(self, other, out); |
| 3191 | } |
| 3192 | |
| 3193 | // aten::lcm.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3194 | at::Tensor & lcm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3195 | |
| 3196 | static auto op = create_lcm_out_typed_handle(); |
| 3197 | return op.redispatch(dispatchKeySet, self, other, out); |
| 3198 | } |
| 3199 | |
| 3200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm, name, "aten::lcm") |
| 3201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm, overload_name, "") |
| 3202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm, schema_str, "lcm(Tensor self, Tensor other) -> Tensor") |
| 3203 | |
| 3204 | // aten::lcm(Tensor self, Tensor other) -> Tensor |
| 3205 | static C10_NOINLINE c10::TypedOperatorHandle<lcm::schema> create_lcm_typed_handle() { |
| 3206 | return c10::Dispatcher::singleton() |
| 3207 | .findSchemaOrThrow(lcm::name, lcm::overload_name) |
| 3208 | .typed<lcm::schema>(); |
| 3209 | } |
| 3210 | |
| 3211 | // aten::lcm(Tensor self, Tensor other) -> Tensor |
| 3212 | at::Tensor lcm::call(const at::Tensor & self, const at::Tensor & other) { |
| 3213 | |
| 3214 | static auto op = create_lcm_typed_handle(); |
| 3215 | return op.call(self, other); |
| 3216 | } |
| 3217 | |
| 3218 | // aten::lcm(Tensor self, Tensor other) -> Tensor |
| 3219 | at::Tensor lcm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 3220 | |
| 3221 | static auto op = create_lcm_typed_handle(); |
| 3222 | return op.redispatch(dispatchKeySet, self, other); |
| 3223 | } |
| 3224 | |
| 3225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm_, name, "aten::lcm_") |
| 3226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm_, overload_name, "") |
| 3227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lcm_, schema_str, "lcm_(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 3228 | |
| 3229 | // aten::lcm_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 3230 | static C10_NOINLINE c10::TypedOperatorHandle<lcm_::schema> create_lcm__typed_handle() { |
| 3231 | return c10::Dispatcher::singleton() |
| 3232 | .findSchemaOrThrow(lcm_::name, lcm_::overload_name) |
| 3233 | .typed<lcm_::schema>(); |
| 3234 | } |
| 3235 | |
| 3236 | // aten::lcm_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 3237 | at::Tensor & lcm_::call(at::Tensor & self, const at::Tensor & other) { |
| 3238 | |
| 3239 | static auto op = create_lcm__typed_handle(); |
| 3240 | return op.call(self, other); |
| 3241 | } |
| 3242 | |
| 3243 | // aten::lcm_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 3244 | at::Tensor & lcm_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 3245 | |
| 3246 | static auto op = create_lcm__typed_handle(); |
| 3247 | return op.redispatch(dispatchKeySet, self, other); |
| 3248 | } |
| 3249 | |
| 3250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_backward, name, "aten::grid_sampler_2d_backward") |
| 3251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_backward, overload_name, "") |
| 3252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_backward, schema_str, "grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor)") |
| 3253 | |
| 3254 | // aten::grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor) |
| 3255 | static C10_NOINLINE c10::TypedOperatorHandle<grid_sampler_2d_backward::schema> create_grid_sampler_2d_backward_typed_handle() { |
| 3256 | return c10::Dispatcher::singleton() |
| 3257 | .findSchemaOrThrow(grid_sampler_2d_backward::name, grid_sampler_2d_backward::overload_name) |
| 3258 | .typed<grid_sampler_2d_backward::schema>(); |
| 3259 | } |
| 3260 | |
| 3261 | // aten::grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor) |
| 3262 | ::std::tuple<at::Tensor,at::Tensor> grid_sampler_2d_backward::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask) { |
| 3263 | |
| 3264 | static auto op = create_grid_sampler_2d_backward_typed_handle(); |
| 3265 | return op.call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask); |
| 3266 | } |
| 3267 | |
| 3268 | // aten::grid_sampler_2d_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask) -> (Tensor, Tensor) |
| 3269 | ::std::tuple<at::Tensor,at::Tensor> grid_sampler_2d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask) { |
| 3270 | |
| 3271 | static auto op = create_grid_sampler_2d_backward_typed_handle(); |
| 3272 | return op.redispatch(dispatchKeySet, grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask); |
| 3273 | } |
| 3274 | |
| 3275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(group_norm, name, "aten::group_norm") |
| 3276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(group_norm, overload_name, "") |
| 3277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(group_norm, schema_str, "group_norm(Tensor input, int num_groups, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enabled=True) -> Tensor") |
| 3278 | |
| 3279 | // aten::group_norm(Tensor input, int num_groups, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enabled=True) -> Tensor |
| 3280 | static C10_NOINLINE c10::TypedOperatorHandle<group_norm::schema> create_group_norm_typed_handle() { |
| 3281 | return c10::Dispatcher::singleton() |
| 3282 | .findSchemaOrThrow(group_norm::name, group_norm::overload_name) |
| 3283 | .typed<group_norm::schema>(); |
| 3284 | } |
| 3285 | |
| 3286 | // aten::group_norm(Tensor input, int num_groups, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enabled=True) -> Tensor |
| 3287 | at::Tensor group_norm::call(const at::Tensor & input, int64_t num_groups, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, double eps, bool cudnn_enabled) { |
| 3288 | |
| 3289 | static auto op = create_group_norm_typed_handle(); |
| 3290 | return op.call(input, num_groups, weight, bias, eps, cudnn_enabled); |
| 3291 | } |
| 3292 | |
| 3293 | // aten::group_norm(Tensor input, int num_groups, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enabled=True) -> Tensor |
| 3294 | at::Tensor group_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, int64_t num_groups, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, double eps, bool cudnn_enabled) { |
| 3295 | |
| 3296 | static auto op = create_group_norm_typed_handle(); |
| 3297 | return op.redispatch(dispatchKeySet, input, num_groups, weight, bias, eps, cudnn_enabled); |
| 3298 | } |
| 3299 | |
| 3300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_out, name, "aten::index_copy") |
| 3301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_out, overload_name, "out") |
| 3302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_out, schema_str, "index_copy.out(Tensor self, int dim, Tensor index, Tensor source, *, Tensor(a!) out) -> Tensor(a!)") |
| 3303 | |
| 3304 | // aten::index_copy.out(Tensor self, int dim, Tensor index, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
| 3305 | static C10_NOINLINE c10::TypedOperatorHandle<index_copy_out::schema> create_index_copy_out_typed_handle() { |
| 3306 | return c10::Dispatcher::singleton() |
| 3307 | .findSchemaOrThrow(index_copy_out::name, index_copy_out::overload_name) |
| 3308 | .typed<index_copy_out::schema>(); |
| 3309 | } |
| 3310 | |
| 3311 | // aten::index_copy.out(Tensor self, int dim, Tensor index, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
| 3312 | at::Tensor & index_copy_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, at::Tensor & out) { |
| 3313 | |
| 3314 | static auto op = create_index_copy_out_typed_handle(); |
| 3315 | return op.call(self, dim, index, source, out); |
| 3316 | } |
| 3317 | |
| 3318 | // aten::index_copy.out(Tensor self, int dim, Tensor index, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
| 3319 | at::Tensor & index_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, at::Tensor & out) { |
| 3320 | |
| 3321 | static auto op = create_index_copy_out_typed_handle(); |
| 3322 | return op.redispatch(dispatchKeySet, self, dim, index, source, out); |
| 3323 | } |
| 3324 | |
| 3325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_, name, "aten::index_copy_") |
| 3326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_, overload_name, "") |
| 3327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_, schema_str, "index_copy_(Tensor(a!) self, int dim, Tensor index, Tensor source) -> Tensor(a!)") |
| 3328 | |
| 3329 | // aten::index_copy_(Tensor(a!) self, int dim, Tensor index, Tensor source) -> Tensor(a!) |
| 3330 | static C10_NOINLINE c10::TypedOperatorHandle<index_copy_::schema> create_index_copy__typed_handle() { |
| 3331 | return c10::Dispatcher::singleton() |
| 3332 | .findSchemaOrThrow(index_copy_::name, index_copy_::overload_name) |
| 3333 | .typed<index_copy_::schema>(); |
| 3334 | } |
| 3335 | |
| 3336 | // aten::index_copy_(Tensor(a!) self, int dim, Tensor index, Tensor source) -> Tensor(a!) |
| 3337 | at::Tensor & index_copy_::call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source) { |
| 3338 | |
| 3339 | static auto op = create_index_copy__typed_handle(); |
| 3340 | return op.call(self, dim, index, source); |
| 3341 | } |
| 3342 | |
| 3343 | // aten::index_copy_(Tensor(a!) self, int dim, Tensor index, Tensor source) -> Tensor(a!) |
| 3344 | at::Tensor & index_copy_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source) { |
| 3345 | |
| 3346 | static auto op = create_index_copy__typed_handle(); |
| 3347 | return op.redispatch(dispatchKeySet, self, dim, index, source); |
| 3348 | } |
| 3349 | |
| 3350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy, name, "aten::index_copy") |
| 3351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy, overload_name, "") |
| 3352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy, schema_str, "index_copy(Tensor self, int dim, Tensor index, Tensor source) -> Tensor") |
| 3353 | |
| 3354 | // aten::index_copy(Tensor self, int dim, Tensor index, Tensor source) -> Tensor |
| 3355 | static C10_NOINLINE c10::TypedOperatorHandle<index_copy::schema> create_index_copy_typed_handle() { |
| 3356 | return c10::Dispatcher::singleton() |
| 3357 | .findSchemaOrThrow(index_copy::name, index_copy::overload_name) |
| 3358 | .typed<index_copy::schema>(); |
| 3359 | } |
| 3360 | |
| 3361 | // aten::index_copy(Tensor self, int dim, Tensor index, Tensor source) -> Tensor |
| 3362 | at::Tensor index_copy::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source) { |
| 3363 | |
| 3364 | static auto op = create_index_copy_typed_handle(); |
| 3365 | return op.call(self, dim, index, source); |
| 3366 | } |
| 3367 | |
| 3368 | // aten::index_copy(Tensor self, int dim, Tensor index, Tensor source) -> Tensor |
| 3369 | at::Tensor index_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source) { |
| 3370 | |
| 3371 | static auto op = create_index_copy_typed_handle(); |
| 3372 | return op.redispatch(dispatchKeySet, self, dim, index, source); |
| 3373 | } |
| 3374 | |
| 3375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy__dimname, name, "aten::index_copy_") |
| 3376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy__dimname, overload_name, "dimname") |
| 3377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy__dimname, schema_str, "index_copy_.dimname(Tensor(a!) self, Dimname dim, Tensor index, Tensor source) -> Tensor(a!)") |
| 3378 | |
| 3379 | // aten::index_copy_.dimname(Tensor(a!) self, Dimname dim, Tensor index, Tensor source) -> Tensor(a!) |
| 3380 | static C10_NOINLINE c10::TypedOperatorHandle<index_copy__dimname::schema> create_index_copy__dimname_typed_handle() { |
| 3381 | return c10::Dispatcher::singleton() |
| 3382 | .findSchemaOrThrow(index_copy__dimname::name, index_copy__dimname::overload_name) |
| 3383 | .typed<index_copy__dimname::schema>(); |
| 3384 | } |
| 3385 | |
| 3386 | // aten::index_copy_.dimname(Tensor(a!) self, Dimname dim, Tensor index, Tensor source) -> Tensor(a!) |
| 3387 | at::Tensor & index_copy__dimname::call(at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source) { |
| 3388 | |
| 3389 | static auto op = create_index_copy__dimname_typed_handle(); |
| 3390 | return op.call(self, dim, index, source); |
| 3391 | } |
| 3392 | |
| 3393 | // aten::index_copy_.dimname(Tensor(a!) self, Dimname dim, Tensor index, Tensor source) -> Tensor(a!) |
| 3394 | at::Tensor & index_copy__dimname::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source) { |
| 3395 | |
| 3396 | static auto op = create_index_copy__dimname_typed_handle(); |
| 3397 | return op.redispatch(dispatchKeySet, self, dim, index, source); |
| 3398 | } |
| 3399 | |
| 3400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_dimname, name, "aten::index_copy") |
| 3401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_dimname, overload_name, "dimname") |
| 3402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_copy_dimname, schema_str, "index_copy.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor") |
| 3403 | |
| 3404 | // aten::index_copy.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor |
| 3405 | static C10_NOINLINE c10::TypedOperatorHandle<index_copy_dimname::schema> create_index_copy_dimname_typed_handle() { |
| 3406 | return c10::Dispatcher::singleton() |
| 3407 | .findSchemaOrThrow(index_copy_dimname::name, index_copy_dimname::overload_name) |
| 3408 | .typed<index_copy_dimname::schema>(); |
| 3409 | } |
| 3410 | |
| 3411 | // aten::index_copy.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor |
| 3412 | at::Tensor index_copy_dimname::call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source) { |
| 3413 | |
| 3414 | static auto op = create_index_copy_dimname_typed_handle(); |
| 3415 | return op.call(self, dim, index, source); |
| 3416 | } |
| 3417 | |
| 3418 | // aten::index_copy.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor |
| 3419 | at::Tensor index_copy_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source) { |
| 3420 | |
| 3421 | static auto op = create_index_copy_dimname_typed_handle(); |
| 3422 | return op.redispatch(dispatchKeySet, self, dim, index, source); |
| 3423 | } |
| 3424 | |
| 3425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl_, name, "aten::_index_put_impl_") |
| 3426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl_, overload_name, "") |
| 3427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl_, schema_str, "_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!)") |
| 3428 | |
| 3429 | // aten::_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!) |
| 3430 | static C10_NOINLINE c10::TypedOperatorHandle<_index_put_impl_::schema> create__index_put_impl__typed_handle() { |
| 3431 | return c10::Dispatcher::singleton() |
| 3432 | .findSchemaOrThrow(_index_put_impl_::name, _index_put_impl_::overload_name) |
| 3433 | .typed<_index_put_impl_::schema>(); |
| 3434 | } |
| 3435 | |
| 3436 | // aten::_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!) |
| 3437 | at::Tensor & _index_put_impl_::call(at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, bool unsafe) { |
| 3438 | |
| 3439 | static auto op = create__index_put_impl__typed_handle(); |
| 3440 | return op.call(self, indices, values, accumulate, unsafe); |
| 3441 | } |
| 3442 | |
| 3443 | // aten::_index_put_impl_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor(a!) |
| 3444 | at::Tensor & _index_put_impl_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, bool unsafe) { |
| 3445 | |
| 3446 | static auto op = create__index_put_impl__typed_handle(); |
| 3447 | return op.redispatch(dispatchKeySet, self, indices, values, accumulate, unsafe); |
| 3448 | } |
| 3449 | |
| 3450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_distributed, name, "aten::is_distributed") |
| 3451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_distributed, overload_name, "") |
| 3452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_distributed, schema_str, "is_distributed(Tensor self) -> bool") |
| 3453 | |
| 3454 | // aten::is_distributed(Tensor self) -> bool |
| 3455 | static C10_NOINLINE c10::TypedOperatorHandle<is_distributed::schema> create_is_distributed_typed_handle() { |
| 3456 | return c10::Dispatcher::singleton() |
| 3457 | .findSchemaOrThrow(is_distributed::name, is_distributed::overload_name) |
| 3458 | .typed<is_distributed::schema>(); |
| 3459 | } |
| 3460 | |
| 3461 | // aten::is_distributed(Tensor self) -> bool |
| 3462 | bool is_distributed::call(const at::Tensor & self) { |
| 3463 | |
| 3464 | static auto op = create_is_distributed_typed_handle(); |
| 3465 | return op.call(self); |
| 3466 | } |
| 3467 | |
| 3468 | // aten::is_distributed(Tensor self) -> bool |
| 3469 | bool is_distributed::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3470 | |
| 3471 | static auto op = create_is_distributed_typed_handle(); |
| 3472 | return op.redispatch(dispatchKeySet, self); |
| 3473 | } |
| 3474 | |
| 3475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_inference, name, "aten::is_inference") |
| 3476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_inference, overload_name, "") |
| 3477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_inference, schema_str, "is_inference(Tensor self) -> bool") |
| 3478 | |
| 3479 | // aten::is_inference(Tensor self) -> bool |
| 3480 | static C10_NOINLINE c10::TypedOperatorHandle<is_inference::schema> create_is_inference_typed_handle() { |
| 3481 | return c10::Dispatcher::singleton() |
| 3482 | .findSchemaOrThrow(is_inference::name, is_inference::overload_name) |
| 3483 | .typed<is_inference::schema>(); |
| 3484 | } |
| 3485 | |
| 3486 | // aten::is_inference(Tensor self) -> bool |
| 3487 | bool is_inference::call(const at::Tensor & self) { |
| 3488 | |
| 3489 | static auto op = create_is_inference_typed_handle(); |
| 3490 | return op.call(self); |
| 3491 | } |
| 3492 | |
| 3493 | // aten::is_inference(Tensor self) -> bool |
| 3494 | bool is_inference::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3495 | |
| 3496 | static auto op = create_is_inference_typed_handle(); |
| 3497 | return op.redispatch(dispatchKeySet, self); |
| 3498 | } |
| 3499 | |
| 3500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kron, name, "aten::kron") |
| 3501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kron, overload_name, "") |
| 3502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kron, schema_str, "kron(Tensor self, Tensor other) -> Tensor") |
| 3503 | |
| 3504 | // aten::kron(Tensor self, Tensor other) -> Tensor |
| 3505 | static C10_NOINLINE c10::TypedOperatorHandle<kron::schema> create_kron_typed_handle() { |
| 3506 | return c10::Dispatcher::singleton() |
| 3507 | .findSchemaOrThrow(kron::name, kron::overload_name) |
| 3508 | .typed<kron::schema>(); |
| 3509 | } |
| 3510 | |
| 3511 | // aten::kron(Tensor self, Tensor other) -> Tensor |
| 3512 | at::Tensor kron::call(const at::Tensor & self, const at::Tensor & other) { |
| 3513 | |
| 3514 | static auto op = create_kron_typed_handle(); |
| 3515 | return op.call(self, other); |
| 3516 | } |
| 3517 | |
| 3518 | // aten::kron(Tensor self, Tensor other) -> Tensor |
| 3519 | at::Tensor kron::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 3520 | |
| 3521 | static auto op = create_kron_typed_handle(); |
| 3522 | return op.redispatch(dispatchKeySet, self, other); |
| 3523 | } |
| 3524 | |
| 3525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kron_out, name, "aten::kron") |
| 3526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kron_out, overload_name, "out") |
| 3527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kron_out, schema_str, "kron.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 3528 | |
| 3529 | // aten::kron.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3530 | static C10_NOINLINE c10::TypedOperatorHandle<kron_out::schema> create_kron_out_typed_handle() { |
| 3531 | return c10::Dispatcher::singleton() |
| 3532 | .findSchemaOrThrow(kron_out::name, kron_out::overload_name) |
| 3533 | .typed<kron_out::schema>(); |
| 3534 | } |
| 3535 | |
| 3536 | // aten::kron.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3537 | at::Tensor & kron_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3538 | |
| 3539 | static auto op = create_kron_out_typed_handle(); |
| 3540 | return op.call(self, other, out); |
| 3541 | } |
| 3542 | |
| 3543 | // aten::kron.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3544 | at::Tensor & kron_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3545 | |
| 3546 | static auto op = create_kron_out_typed_handle(); |
| 3547 | return op.redispatch(dispatchKeySet, self, other, out); |
| 3548 | } |
| 3549 | |
| 3550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linear, name, "aten::linear") |
| 3551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linear, overload_name, "") |
| 3552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linear, schema_str, "linear(Tensor input, Tensor weight, Tensor? bias=None) -> Tensor") |
| 3553 | |
| 3554 | // aten::linear(Tensor input, Tensor weight, Tensor? bias=None) -> Tensor |
| 3555 | static C10_NOINLINE c10::TypedOperatorHandle<linear::schema> create_linear_typed_handle() { |
| 3556 | return c10::Dispatcher::singleton() |
| 3557 | .findSchemaOrThrow(linear::name, linear::overload_name) |
| 3558 | .typed<linear::schema>(); |
| 3559 | } |
| 3560 | |
| 3561 | // aten::linear(Tensor input, Tensor weight, Tensor? bias=None) -> Tensor |
| 3562 | at::Tensor linear::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias) { |
| 3563 | |
| 3564 | static auto op = create_linear_typed_handle(); |
| 3565 | return op.call(input, weight, bias); |
| 3566 | } |
| 3567 | |
| 3568 | // aten::linear(Tensor input, Tensor weight, Tensor? bias=None) -> Tensor |
| 3569 | at::Tensor linear::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias) { |
| 3570 | |
| 3571 | static auto op = create_linear_typed_handle(); |
| 3572 | return op.redispatch(dispatchKeySet, input, weight, bias); |
| 3573 | } |
| 3574 | |
| 3575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linear_out, name, "aten::linear") |
| 3576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linear_out, overload_name, "out") |
| 3577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linear_out, schema_str, "linear.out(Tensor input, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 3578 | |
| 3579 | // aten::linear.out(Tensor input, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) |
| 3580 | static C10_NOINLINE c10::TypedOperatorHandle<linear_out::schema> create_linear_out_typed_handle() { |
| 3581 | return c10::Dispatcher::singleton() |
| 3582 | .findSchemaOrThrow(linear_out::name, linear_out::overload_name) |
| 3583 | .typed<linear_out::schema>(); |
| 3584 | } |
| 3585 | |
| 3586 | // aten::linear.out(Tensor input, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) |
| 3587 | at::Tensor & linear_out::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::Tensor & out) { |
| 3588 | |
| 3589 | static auto op = create_linear_out_typed_handle(); |
| 3590 | return op.call(input, weight, bias, out); |
| 3591 | } |
| 3592 | |
| 3593 | // aten::linear.out(Tensor input, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) |
| 3594 | at::Tensor & linear_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::Tensor & out) { |
| 3595 | |
| 3596 | static auto op = create_linear_out_typed_handle(); |
| 3597 | return op.redispatch(dispatchKeySet, input, weight, bias, out); |
| 3598 | } |
| 3599 | |
| 3600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear, name, "aten::mkldnn_linear") |
| 3601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear, overload_name, "") |
| 3602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear, schema_str, "mkldnn_linear(Tensor self, Tensor weight, Tensor? bias=None) -> Tensor") |
| 3603 | |
| 3604 | // aten::mkldnn_linear(Tensor self, Tensor weight, Tensor? bias=None) -> Tensor |
| 3605 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_linear::schema> create_mkldnn_linear_typed_handle() { |
| 3606 | return c10::Dispatcher::singleton() |
| 3607 | .findSchemaOrThrow(mkldnn_linear::name, mkldnn_linear::overload_name) |
| 3608 | .typed<mkldnn_linear::schema>(); |
| 3609 | } |
| 3610 | |
| 3611 | // aten::mkldnn_linear(Tensor self, Tensor weight, Tensor? bias=None) -> Tensor |
| 3612 | at::Tensor mkldnn_linear::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias) { |
| 3613 | |
| 3614 | static auto op = create_mkldnn_linear_typed_handle(); |
| 3615 | return op.call(self, weight, bias); |
| 3616 | } |
| 3617 | |
| 3618 | // aten::mkldnn_linear(Tensor self, Tensor weight, Tensor? bias=None) -> Tensor |
| 3619 | at::Tensor mkldnn_linear::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias) { |
| 3620 | |
| 3621 | static auto op = create_mkldnn_linear_typed_handle(); |
| 3622 | return op.redispatch(dispatchKeySet, self, weight, bias); |
| 3623 | } |
| 3624 | |
| 3625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_backward_weights, name, "aten::mkldnn_linear_backward_weights") |
| 3626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_backward_weights, overload_name, "") |
| 3627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_backward_weights, schema_str, "mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor)") |
| 3628 | |
| 3629 | // aten::mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor) |
| 3630 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_linear_backward_weights::schema> create_mkldnn_linear_backward_weights_typed_handle() { |
| 3631 | return c10::Dispatcher::singleton() |
| 3632 | .findSchemaOrThrow(mkldnn_linear_backward_weights::name, mkldnn_linear_backward_weights::overload_name) |
| 3633 | .typed<mkldnn_linear_backward_weights::schema>(); |
| 3634 | } |
| 3635 | |
| 3636 | // aten::mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor) |
| 3637 | ::std::tuple<at::Tensor,at::Tensor> mkldnn_linear_backward_weights::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined) { |
| 3638 | |
| 3639 | static auto op = create_mkldnn_linear_backward_weights_typed_handle(); |
| 3640 | return op.call(grad_output, input, weight, bias_defined); |
| 3641 | } |
| 3642 | |
| 3643 | // aten::mkldnn_linear_backward_weights(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined) -> (Tensor, Tensor) |
| 3644 | ::std::tuple<at::Tensor,at::Tensor> mkldnn_linear_backward_weights::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined) { |
| 3645 | |
| 3646 | static auto op = create_mkldnn_linear_backward_weights_typed_handle(); |
| 3647 | return op.redispatch(dispatchKeySet, grad_output, input, weight, bias_defined); |
| 3648 | } |
| 3649 | |
| 3650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_linear_quantize_weight, name, "aten::fbgemm_linear_quantize_weight") |
| 3651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_linear_quantize_weight, overload_name, "") |
| 3652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_linear_quantize_weight, schema_str, "fbgemm_linear_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int)") |
| 3653 | |
| 3654 | // aten::fbgemm_linear_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int) |
| 3655 | static C10_NOINLINE c10::TypedOperatorHandle<fbgemm_linear_quantize_weight::schema> create_fbgemm_linear_quantize_weight_typed_handle() { |
| 3656 | return c10::Dispatcher::singleton() |
| 3657 | .findSchemaOrThrow(fbgemm_linear_quantize_weight::name, fbgemm_linear_quantize_weight::overload_name) |
| 3658 | .typed<fbgemm_linear_quantize_weight::schema>(); |
| 3659 | } |
| 3660 | |
| 3661 | // aten::fbgemm_linear_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int) |
| 3662 | ::std::tuple<at::Tensor,at::Tensor,double,int64_t> fbgemm_linear_quantize_weight::call(const at::Tensor & input) { |
| 3663 | |
| 3664 | static auto op = create_fbgemm_linear_quantize_weight_typed_handle(); |
| 3665 | return op.call(input); |
| 3666 | } |
| 3667 | |
| 3668 | // aten::fbgemm_linear_quantize_weight(Tensor input) -> (Tensor, Tensor, float, int) |
| 3669 | ::std::tuple<at::Tensor,at::Tensor,double,int64_t> fbgemm_linear_quantize_weight::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input) { |
| 3670 | |
| 3671 | static auto op = create_fbgemm_linear_quantize_weight_typed_handle(); |
| 3672 | return op.redispatch(dispatchKeySet, input); |
| 3673 | } |
| 3674 | |
| 3675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linspace, name, "aten::linspace") |
| 3676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linspace, overload_name, "") |
| 3677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linspace, schema_str, "linspace(Scalar start, Scalar end, int steps, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 3678 | |
| 3679 | // aten::linspace(Scalar start, Scalar end, int steps, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3680 | static C10_NOINLINE c10::TypedOperatorHandle<linspace::schema> create_linspace_typed_handle() { |
| 3681 | return c10::Dispatcher::singleton() |
| 3682 | .findSchemaOrThrow(linspace::name, linspace::overload_name) |
| 3683 | .typed<linspace::schema>(); |
| 3684 | } |
| 3685 | |
| 3686 | // aten::linspace(Scalar start, Scalar end, int steps, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3687 | at::Tensor linspace::call(const at::Scalar & start, const at::Scalar & end, int64_t steps, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 3688 | |
| 3689 | static auto op = create_linspace_typed_handle(); |
| 3690 | return op.call(start, end, steps, dtype, layout, device, pin_memory); |
| 3691 | } |
| 3692 | |
| 3693 | // aten::linspace(Scalar start, Scalar end, int steps, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3694 | at::Tensor linspace::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, int64_t steps, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 3695 | |
| 3696 | static auto op = create_linspace_typed_handle(); |
| 3697 | return op.redispatch(dispatchKeySet, start, end, steps, dtype, layout, device, pin_memory); |
| 3698 | } |
| 3699 | |
| 3700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linspace_out, name, "aten::linspace") |
| 3701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linspace_out, overload_name, "out") |
| 3702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linspace_out, schema_str, "linspace.out(Scalar start, Scalar end, int steps, *, Tensor(a!) out) -> Tensor(a!)") |
| 3703 | |
| 3704 | // aten::linspace.out(Scalar start, Scalar end, int steps, *, Tensor(a!) out) -> Tensor(a!) |
| 3705 | static C10_NOINLINE c10::TypedOperatorHandle<linspace_out::schema> create_linspace_out_typed_handle() { |
| 3706 | return c10::Dispatcher::singleton() |
| 3707 | .findSchemaOrThrow(linspace_out::name, linspace_out::overload_name) |
| 3708 | .typed<linspace_out::schema>(); |
| 3709 | } |
| 3710 | |
| 3711 | // aten::linspace.out(Scalar start, Scalar end, int steps, *, Tensor(a!) out) -> Tensor(a!) |
| 3712 | at::Tensor & linspace_out::call(const at::Scalar & start, const at::Scalar & end, int64_t steps, at::Tensor & out) { |
| 3713 | |
| 3714 | static auto op = create_linspace_out_typed_handle(); |
| 3715 | return op.call(start, end, steps, out); |
| 3716 | } |
| 3717 | |
| 3718 | // aten::linspace.out(Scalar start, Scalar end, int steps, *, Tensor(a!) out) -> Tensor(a!) |
| 3719 | at::Tensor & linspace_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, int64_t steps, at::Tensor & out) { |
| 3720 | |
| 3721 | static auto op = create_linspace_out_typed_handle(); |
| 3722 | return op.redispatch(dispatchKeySet, start, end, steps, out); |
| 3723 | } |
| 3724 | |
| 3725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10, name, "aten::log10") |
| 3726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10, overload_name, "") |
| 3727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10, schema_str, "log10(Tensor self) -> Tensor") |
| 3728 | |
| 3729 | // aten::log10(Tensor self) -> Tensor |
| 3730 | static C10_NOINLINE c10::TypedOperatorHandle<log10::schema> create_log10_typed_handle() { |
| 3731 | return c10::Dispatcher::singleton() |
| 3732 | .findSchemaOrThrow(log10::name, log10::overload_name) |
| 3733 | .typed<log10::schema>(); |
| 3734 | } |
| 3735 | |
| 3736 | // aten::log10(Tensor self) -> Tensor |
| 3737 | at::Tensor log10::call(const at::Tensor & self) { |
| 3738 | |
| 3739 | static auto op = create_log10_typed_handle(); |
| 3740 | return op.call(self); |
| 3741 | } |
| 3742 | |
| 3743 | // aten::log10(Tensor self) -> Tensor |
| 3744 | at::Tensor log10::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3745 | |
| 3746 | static auto op = create_log10_typed_handle(); |
| 3747 | return op.redispatch(dispatchKeySet, self); |
| 3748 | } |
| 3749 | |
| 3750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10_, name, "aten::log10_") |
| 3751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10_, overload_name, "") |
| 3752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10_, schema_str, "log10_(Tensor(a!) self) -> Tensor(a!)") |
| 3753 | |
| 3754 | // aten::log10_(Tensor(a!) self) -> Tensor(a!) |
| 3755 | static C10_NOINLINE c10::TypedOperatorHandle<log10_::schema> create_log10__typed_handle() { |
| 3756 | return c10::Dispatcher::singleton() |
| 3757 | .findSchemaOrThrow(log10_::name, log10_::overload_name) |
| 3758 | .typed<log10_::schema>(); |
| 3759 | } |
| 3760 | |
| 3761 | // aten::log10_(Tensor(a!) self) -> Tensor(a!) |
| 3762 | at::Tensor & log10_::call(at::Tensor & self) { |
| 3763 | |
| 3764 | static auto op = create_log10__typed_handle(); |
| 3765 | return op.call(self); |
| 3766 | } |
| 3767 | |
| 3768 | // aten::log10_(Tensor(a!) self) -> Tensor(a!) |
| 3769 | at::Tensor & log10_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 3770 | |
| 3771 | static auto op = create_log10__typed_handle(); |
| 3772 | return op.redispatch(dispatchKeySet, self); |
| 3773 | } |
| 3774 | |
| 3775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10_out, name, "aten::log10") |
| 3776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10_out, overload_name, "out") |
| 3777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log10_out, schema_str, "log10.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 3778 | |
| 3779 | // aten::log10.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3780 | static C10_NOINLINE c10::TypedOperatorHandle<log10_out::schema> create_log10_out_typed_handle() { |
| 3781 | return c10::Dispatcher::singleton() |
| 3782 | .findSchemaOrThrow(log10_out::name, log10_out::overload_name) |
| 3783 | .typed<log10_out::schema>(); |
| 3784 | } |
| 3785 | |
| 3786 | // aten::log10.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3787 | at::Tensor & log10_out::call(const at::Tensor & self, at::Tensor & out) { |
| 3788 | |
| 3789 | static auto op = create_log10_out_typed_handle(); |
| 3790 | return op.call(self, out); |
| 3791 | } |
| 3792 | |
| 3793 | // aten::log10.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3794 | at::Tensor & log10_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 3795 | |
| 3796 | static auto op = create_log10_out_typed_handle(); |
| 3797 | return op.redispatch(dispatchKeySet, self, out); |
| 3798 | } |
| 3799 | |
| 3800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p, name, "aten::log1p") |
| 3801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p, overload_name, "") |
| 3802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p, schema_str, "log1p(Tensor self) -> Tensor") |
| 3803 | |
| 3804 | // aten::log1p(Tensor self) -> Tensor |
| 3805 | static C10_NOINLINE c10::TypedOperatorHandle<log1p::schema> create_log1p_typed_handle() { |
| 3806 | return c10::Dispatcher::singleton() |
| 3807 | .findSchemaOrThrow(log1p::name, log1p::overload_name) |
| 3808 | .typed<log1p::schema>(); |
| 3809 | } |
| 3810 | |
| 3811 | // aten::log1p(Tensor self) -> Tensor |
| 3812 | at::Tensor log1p::call(const at::Tensor & self) { |
| 3813 | |
| 3814 | static auto op = create_log1p_typed_handle(); |
| 3815 | return op.call(self); |
| 3816 | } |
| 3817 | |
| 3818 | // aten::log1p(Tensor self) -> Tensor |
| 3819 | at::Tensor log1p::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3820 | |
| 3821 | static auto op = create_log1p_typed_handle(); |
| 3822 | return op.redispatch(dispatchKeySet, self); |
| 3823 | } |
| 3824 | |
| 3825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p_, name, "aten::log1p_") |
| 3826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p_, overload_name, "") |
| 3827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p_, schema_str, "log1p_(Tensor(a!) self) -> Tensor(a!)") |
| 3828 | |
| 3829 | // aten::log1p_(Tensor(a!) self) -> Tensor(a!) |
| 3830 | static C10_NOINLINE c10::TypedOperatorHandle<log1p_::schema> create_log1p__typed_handle() { |
| 3831 | return c10::Dispatcher::singleton() |
| 3832 | .findSchemaOrThrow(log1p_::name, log1p_::overload_name) |
| 3833 | .typed<log1p_::schema>(); |
| 3834 | } |
| 3835 | |
| 3836 | // aten::log1p_(Tensor(a!) self) -> Tensor(a!) |
| 3837 | at::Tensor & log1p_::call(at::Tensor & self) { |
| 3838 | |
| 3839 | static auto op = create_log1p__typed_handle(); |
| 3840 | return op.call(self); |
| 3841 | } |
| 3842 | |
| 3843 | // aten::log1p_(Tensor(a!) self) -> Tensor(a!) |
| 3844 | at::Tensor & log1p_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 3845 | |
| 3846 | static auto op = create_log1p__typed_handle(); |
| 3847 | return op.redispatch(dispatchKeySet, self); |
| 3848 | } |
| 3849 | |
| 3850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p_out, name, "aten::log1p") |
| 3851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p_out, overload_name, "out") |
| 3852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log1p_out, schema_str, "log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 3853 | |
| 3854 | // aten::log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3855 | static C10_NOINLINE c10::TypedOperatorHandle<log1p_out::schema> create_log1p_out_typed_handle() { |
| 3856 | return c10::Dispatcher::singleton() |
| 3857 | .findSchemaOrThrow(log1p_out::name, log1p_out::overload_name) |
| 3858 | .typed<log1p_out::schema>(); |
| 3859 | } |
| 3860 | |
| 3861 | // aten::log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3862 | at::Tensor & log1p_out::call(const at::Tensor & self, at::Tensor & out) { |
| 3863 | |
| 3864 | static auto op = create_log1p_out_typed_handle(); |
| 3865 | return op.call(self, out); |
| 3866 | } |
| 3867 | |
| 3868 | // aten::log1p.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3869 | at::Tensor & log1p_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 3870 | |
| 3871 | static auto op = create_log1p_out_typed_handle(); |
| 3872 | return op.redispatch(dispatchKeySet, self, out); |
| 3873 | } |
| 3874 | |
| 3875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp2_out, name, "aten::logaddexp2") |
| 3876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp2_out, overload_name, "out") |
| 3877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp2_out, schema_str, "logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 3878 | |
| 3879 | // aten::logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3880 | static C10_NOINLINE c10::TypedOperatorHandle<logaddexp2_out::schema> create_logaddexp2_out_typed_handle() { |
| 3881 | return c10::Dispatcher::singleton() |
| 3882 | .findSchemaOrThrow(logaddexp2_out::name, logaddexp2_out::overload_name) |
| 3883 | .typed<logaddexp2_out::schema>(); |
| 3884 | } |
| 3885 | |
| 3886 | // aten::logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3887 | at::Tensor & logaddexp2_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3888 | |
| 3889 | static auto op = create_logaddexp2_out_typed_handle(); |
| 3890 | return op.call(self, other, out); |
| 3891 | } |
| 3892 | |
| 3893 | // aten::logaddexp2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3894 | at::Tensor & logaddexp2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3895 | |
| 3896 | static auto op = create_logaddexp2_out_typed_handle(); |
| 3897 | return op.redispatch(dispatchKeySet, self, other, out); |
| 3898 | } |
| 3899 | |
| 3900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp2, name, "aten::logaddexp2") |
| 3901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp2, overload_name, "") |
| 3902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp2, schema_str, "logaddexp2(Tensor self, Tensor other) -> Tensor") |
| 3903 | |
| 3904 | // aten::logaddexp2(Tensor self, Tensor other) -> Tensor |
| 3905 | static C10_NOINLINE c10::TypedOperatorHandle<logaddexp2::schema> create_logaddexp2_typed_handle() { |
| 3906 | return c10::Dispatcher::singleton() |
| 3907 | .findSchemaOrThrow(logaddexp2::name, logaddexp2::overload_name) |
| 3908 | .typed<logaddexp2::schema>(); |
| 3909 | } |
| 3910 | |
| 3911 | // aten::logaddexp2(Tensor self, Tensor other) -> Tensor |
| 3912 | at::Tensor logaddexp2::call(const at::Tensor & self, const at::Tensor & other) { |
| 3913 | |
| 3914 | static auto op = create_logaddexp2_typed_handle(); |
| 3915 | return op.call(self, other); |
| 3916 | } |
| 3917 | |
| 3918 | // aten::logaddexp2(Tensor self, Tensor other) -> Tensor |
| 3919 | at::Tensor logaddexp2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 3920 | |
| 3921 | static auto op = create_logaddexp2_typed_handle(); |
| 3922 | return op.redispatch(dispatchKeySet, self, other); |
| 3923 | } |
| 3924 | |
| 3925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_log_softmax, name, "aten::_log_softmax") |
| 3926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_log_softmax, overload_name, "") |
| 3927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_log_softmax, schema_str, "_log_softmax(Tensor self, int dim, bool half_to_float) -> Tensor") |
| 3928 | |
| 3929 | // aten::_log_softmax(Tensor self, int dim, bool half_to_float) -> Tensor |
| 3930 | static C10_NOINLINE c10::TypedOperatorHandle<_log_softmax::schema> create__log_softmax_typed_handle() { |
| 3931 | return c10::Dispatcher::singleton() |
| 3932 | .findSchemaOrThrow(_log_softmax::name, _log_softmax::overload_name) |
| 3933 | .typed<_log_softmax::schema>(); |
| 3934 | } |
| 3935 | |
| 3936 | // aten::_log_softmax(Tensor self, int dim, bool half_to_float) -> Tensor |
| 3937 | at::Tensor _log_softmax::call(const at::Tensor & self, int64_t dim, bool half_to_float) { |
| 3938 | |
| 3939 | static auto op = create__log_softmax_typed_handle(); |
| 3940 | return op.call(self, dim, half_to_float); |
| 3941 | } |
| 3942 | |
| 3943 | // aten::_log_softmax(Tensor self, int dim, bool half_to_float) -> Tensor |
| 3944 | at::Tensor _log_softmax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float) { |
| 3945 | |
| 3946 | static auto op = create__log_softmax_typed_handle(); |
| 3947 | return op.redispatch(dispatchKeySet, self, dim, half_to_float); |
| 3948 | } |
| 3949 | |
| 3950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_log_softmax_out, name, "aten::_log_softmax") |
| 3951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_log_softmax_out, overload_name, "out") |
| 3952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_log_softmax_out, schema_str, "_log_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)") |
| 3953 | |
| 3954 | // aten::_log_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!) |
| 3955 | static C10_NOINLINE c10::TypedOperatorHandle<_log_softmax_out::schema> create__log_softmax_out_typed_handle() { |
| 3956 | return c10::Dispatcher::singleton() |
| 3957 | .findSchemaOrThrow(_log_softmax_out::name, _log_softmax_out::overload_name) |
| 3958 | .typed<_log_softmax_out::schema>(); |
| 3959 | } |
| 3960 | |
| 3961 | // aten::_log_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!) |
| 3962 | at::Tensor & _log_softmax_out::call(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out) { |
| 3963 | |
| 3964 | static auto op = create__log_softmax_out_typed_handle(); |
| 3965 | return op.call(self, dim, half_to_float, out); |
| 3966 | } |
| 3967 | |
| 3968 | // aten::_log_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!) |
| 3969 | at::Tensor & _log_softmax_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out) { |
| 3970 | |
| 3971 | static auto op = create__log_softmax_out_typed_handle(); |
| 3972 | return op.redispatch(dispatchKeySet, self, dim, half_to_float, out); |
| 3973 | } |
| 3974 | |
| 3975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp, name, "aten::logsumexp") |
| 3976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp, overload_name, "") |
| 3977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp, schema_str, "logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor") |
| 3978 | |
| 3979 | // aten::logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor |
| 3980 | static C10_NOINLINE c10::TypedOperatorHandle<logsumexp::schema> create_logsumexp_typed_handle() { |
| 3981 | return c10::Dispatcher::singleton() |
| 3982 | .findSchemaOrThrow(logsumexp::name, logsumexp::overload_name) |
| 3983 | .typed<logsumexp::schema>(); |
| 3984 | } |
| 3985 | |
| 3986 | // aten::logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor |
| 3987 | at::Tensor logsumexp::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim) { |
| 3988 | |
| 3989 | static auto op = create_logsumexp_typed_handle(); |
| 3990 | return op.call(self, dim, keepdim); |
| 3991 | } |
| 3992 | |
| 3993 | // aten::logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor |
| 3994 | at::Tensor logsumexp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim) { |
| 3995 | |
| 3996 | static auto op = create_logsumexp_typed_handle(); |
| 3997 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 3998 | } |
| 3999 | |
| 4000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_out, name, "aten::logsumexp") |
| 4001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_out, overload_name, "out") |
| 4002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_out, schema_str, "logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 4003 | |
| 4004 | // aten::logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 4005 | static C10_NOINLINE c10::TypedOperatorHandle<logsumexp_out::schema> create_logsumexp_out_typed_handle() { |
| 4006 | return c10::Dispatcher::singleton() |
| 4007 | .findSchemaOrThrow(logsumexp_out::name, logsumexp_out::overload_name) |
| 4008 | .typed<logsumexp_out::schema>(); |
| 4009 | } |
| 4010 | |
| 4011 | // aten::logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 4012 | at::Tensor & logsumexp_out::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
| 4013 | |
| 4014 | static auto op = create_logsumexp_out_typed_handle(); |
| 4015 | return op.call(self, dim, keepdim, out); |
| 4016 | } |
| 4017 | |
| 4018 | // aten::logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 4019 | at::Tensor & logsumexp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
| 4020 | |
| 4021 | static auto op = create_logsumexp_out_typed_handle(); |
| 4022 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
| 4023 | } |
| 4024 | |
| 4025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_names, name, "aten::logsumexp") |
| 4026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_names, overload_name, "names") |
| 4027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_names, schema_str, "logsumexp.names(Tensor self, Dimname[1] dim, bool keepdim=False) -> Tensor") |
| 4028 | |
| 4029 | // aten::logsumexp.names(Tensor self, Dimname[1] dim, bool keepdim=False) -> Tensor |
| 4030 | static C10_NOINLINE c10::TypedOperatorHandle<logsumexp_names::schema> create_logsumexp_names_typed_handle() { |
| 4031 | return c10::Dispatcher::singleton() |
| 4032 | .findSchemaOrThrow(logsumexp_names::name, logsumexp_names::overload_name) |
| 4033 | .typed<logsumexp_names::schema>(); |
| 4034 | } |
| 4035 | |
| 4036 | // aten::logsumexp.names(Tensor self, Dimname[1] dim, bool keepdim=False) -> Tensor |
| 4037 | at::Tensor logsumexp_names::call(const at::Tensor & self, at::DimnameList dim, bool keepdim) { |
| 4038 | |
| 4039 | static auto op = create_logsumexp_names_typed_handle(); |
| 4040 | return op.call(self, dim, keepdim); |
| 4041 | } |
| 4042 | |
| 4043 | // aten::logsumexp.names(Tensor self, Dimname[1] dim, bool keepdim=False) -> Tensor |
| 4044 | at::Tensor logsumexp_names::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim) { |
| 4045 | |
| 4046 | static auto op = create_logsumexp_names_typed_handle(); |
| 4047 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 4048 | } |
| 4049 | |
| 4050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_names_out, name, "aten::logsumexp") |
| 4051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_names_out, overload_name, "names_out") |
| 4052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logsumexp_names_out, schema_str, "logsumexp.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 4053 | |
| 4054 | // aten::logsumexp.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 4055 | static C10_NOINLINE c10::TypedOperatorHandle<logsumexp_names_out::schema> create_logsumexp_names_out_typed_handle() { |
| 4056 | return c10::Dispatcher::singleton() |
| 4057 | .findSchemaOrThrow(logsumexp_names_out::name, logsumexp_names_out::overload_name) |
| 4058 | .typed<logsumexp_names_out::schema>(); |
| 4059 | } |
| 4060 | |
| 4061 | // aten::logsumexp.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 4062 | at::Tensor & logsumexp_names_out::call(const at::Tensor & self, at::DimnameList dim, bool keepdim, at::Tensor & out) { |
| 4063 | |
| 4064 | static auto op = create_logsumexp_names_out_typed_handle(); |
| 4065 | return op.call(self, dim, keepdim, out); |
| 4066 | } |
| 4067 | |
| 4068 | // aten::logsumexp.names_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 4069 | at::Tensor & logsumexp_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim, at::Tensor & out) { |
| 4070 | |
| 4071 | static auto op = create_logsumexp_names_out_typed_handle(); |
| 4072 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
| 4073 | } |
| 4074 | |
| 4075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax, name, "aten::_aminmax") |
| 4076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax, overload_name, "") |
| 4077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax, schema_str, "_aminmax(Tensor self) -> (Tensor, Tensor)") |
| 4078 | |
| 4079 | // aten::_aminmax(Tensor self) -> (Tensor, Tensor) |
| 4080 | static C10_NOINLINE c10::TypedOperatorHandle<_aminmax::schema> create__aminmax_typed_handle() { |
| 4081 | return c10::Dispatcher::singleton() |
| 4082 | .findSchemaOrThrow(_aminmax::name, _aminmax::overload_name) |
| 4083 | .typed<_aminmax::schema>(); |
| 4084 | } |
| 4085 | |
| 4086 | // aten::_aminmax(Tensor self) -> (Tensor, Tensor) |
| 4087 | ::std::tuple<at::Tensor,at::Tensor> _aminmax::call(const at::Tensor & self) { |
| 4088 | |
| 4089 | static auto op = create__aminmax_typed_handle(); |
| 4090 | return op.call(self); |
| 4091 | } |
| 4092 | |
| 4093 | // aten::_aminmax(Tensor self) -> (Tensor, Tensor) |
| 4094 | ::std::tuple<at::Tensor,at::Tensor> _aminmax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 4095 | |
| 4096 | static auto op = create__aminmax_typed_handle(); |
| 4097 | return op.redispatch(dispatchKeySet, self); |
| 4098 | } |
| 4099 | |
| 4100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_dim, name, "aten::_aminmax") |
| 4101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_dim, overload_name, "dim") |
| 4102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_dim, schema_str, "_aminmax.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor, Tensor)") |
| 4103 | |
| 4104 | // aten::_aminmax.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor, Tensor) |
| 4105 | static C10_NOINLINE c10::TypedOperatorHandle<_aminmax_dim::schema> create__aminmax_dim_typed_handle() { |
| 4106 | return c10::Dispatcher::singleton() |
| 4107 | .findSchemaOrThrow(_aminmax_dim::name, _aminmax_dim::overload_name) |
| 4108 | .typed<_aminmax_dim::schema>(); |
| 4109 | } |
| 4110 | |
| 4111 | // aten::_aminmax.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor, Tensor) |
| 4112 | ::std::tuple<at::Tensor,at::Tensor> _aminmax_dim::call(const at::Tensor & self, int64_t dim, bool keepdim) { |
| 4113 | |
| 4114 | static auto op = create__aminmax_dim_typed_handle(); |
| 4115 | return op.call(self, dim, keepdim); |
| 4116 | } |
| 4117 | |
| 4118 | // aten::_aminmax.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor, Tensor) |
| 4119 | ::std::tuple<at::Tensor,at::Tensor> _aminmax_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim) { |
| 4120 | |
| 4121 | static auto op = create__aminmax_dim_typed_handle(); |
| 4122 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 4123 | } |
| 4124 | |
| 4125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(aminmax, name, "aten::aminmax") |
| 4126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(aminmax, overload_name, "") |
| 4127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(aminmax, schema_str, "aminmax(Tensor self, *, int? dim=None, bool keepdim=False) -> (Tensor min, Tensor max)") |
| 4128 | |
| 4129 | // aten::aminmax(Tensor self, *, int? dim=None, bool keepdim=False) -> (Tensor min, Tensor max) |
| 4130 | static C10_NOINLINE c10::TypedOperatorHandle<aminmax::schema> create_aminmax_typed_handle() { |
| 4131 | return c10::Dispatcher::singleton() |
| 4132 | .findSchemaOrThrow(aminmax::name, aminmax::overload_name) |
| 4133 | .typed<aminmax::schema>(); |
| 4134 | } |
| 4135 | |
| 4136 | // aten::aminmax(Tensor self, *, int? dim=None, bool keepdim=False) -> (Tensor min, Tensor max) |
| 4137 | ::std::tuple<at::Tensor,at::Tensor> aminmax::call(const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim) { |
| 4138 | |
| 4139 | static auto op = create_aminmax_typed_handle(); |
| 4140 | return op.call(self, dim, keepdim); |
| 4141 | } |
| 4142 | |
| 4143 | // aten::aminmax(Tensor self, *, int? dim=None, bool keepdim=False) -> (Tensor min, Tensor max) |
| 4144 | ::std::tuple<at::Tensor,at::Tensor> aminmax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim) { |
| 4145 | |
| 4146 | static auto op = create_aminmax_typed_handle(); |
| 4147 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 4148 | } |
| 4149 | |
| 4150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(aminmax_out, name, "aten::aminmax") |
| 4151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(aminmax_out, overload_name, "out") |
| 4152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(aminmax_out, schema_str, "aminmax.out(Tensor self, *, int? dim=None, bool keepdim=False, Tensor(a!) min, Tensor(b!) max) -> (Tensor(a!) min, Tensor(b!) max)") |
| 4153 | |
| 4154 | // aten::aminmax.out(Tensor self, *, int? dim=None, bool keepdim=False, Tensor(a!) min, Tensor(b!) max) -> (Tensor(a!) min, Tensor(b!) max) |
| 4155 | static C10_NOINLINE c10::TypedOperatorHandle<aminmax_out::schema> create_aminmax_out_typed_handle() { |
| 4156 | return c10::Dispatcher::singleton() |
| 4157 | .findSchemaOrThrow(aminmax_out::name, aminmax_out::overload_name) |
| 4158 | .typed<aminmax_out::schema>(); |
| 4159 | } |
| 4160 | |
| 4161 | // aten::aminmax.out(Tensor self, *, int? dim=None, bool keepdim=False, Tensor(a!) min, Tensor(b!) max) -> (Tensor(a!) min, Tensor(b!) max) |
| 4162 | ::std::tuple<at::Tensor &,at::Tensor &> aminmax_out::call(const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim, at::Tensor & min, at::Tensor & max) { |
| 4163 | |
| 4164 | static auto op = create_aminmax_out_typed_handle(); |
| 4165 | return op.call(self, dim, keepdim, min, max); |
| 4166 | } |
| 4167 | |
| 4168 | // aten::aminmax.out(Tensor self, *, int? dim=None, bool keepdim=False, Tensor(a!) min, Tensor(b!) max) -> (Tensor(a!) min, Tensor(b!) max) |
| 4169 | ::std::tuple<at::Tensor &,at::Tensor &> aminmax_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dim, bool keepdim, at::Tensor & min, at::Tensor & max) { |
| 4170 | |
| 4171 | static auto op = create_aminmax_out_typed_handle(); |
| 4172 | return op.redispatch(dispatchKeySet, self, dim, keepdim, min, max); |
| 4173 | } |
| 4174 | |
| 4175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_dim, name, "aten::max") |
| 4176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_dim, overload_name, "dim") |
| 4177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_dim, schema_str, "max.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 4178 | |
| 4179 | // aten::max.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4180 | static C10_NOINLINE c10::TypedOperatorHandle<max_dim::schema> create_max_dim_typed_handle() { |
| 4181 | return c10::Dispatcher::singleton() |
| 4182 | .findSchemaOrThrow(max_dim::name, max_dim::overload_name) |
| 4183 | .typed<max_dim::schema>(); |
| 4184 | } |
| 4185 | |
| 4186 | // aten::max.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4187 | ::std::tuple<at::Tensor,at::Tensor> max_dim::call(const at::Tensor & self, int64_t dim, bool keepdim) { |
| 4188 | |
| 4189 | static auto op = create_max_dim_typed_handle(); |
| 4190 | return op.call(self, dim, keepdim); |
| 4191 | } |
| 4192 | |
| 4193 | // aten::max.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4194 | ::std::tuple<at::Tensor,at::Tensor> max_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim) { |
| 4195 | |
| 4196 | static auto op = create_max_dim_typed_handle(); |
| 4197 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 4198 | } |
| 4199 | |
| 4200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_dim_max, name, "aten::max") |
| 4201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_dim_max, overload_name, "dim_max") |
| 4202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_dim_max, schema_str, "max.dim_max(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 4203 | |
| 4204 | // aten::max.dim_max(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4205 | static C10_NOINLINE c10::TypedOperatorHandle<max_dim_max::schema> create_max_dim_max_typed_handle() { |
| 4206 | return c10::Dispatcher::singleton() |
| 4207 | .findSchemaOrThrow(max_dim_max::name, max_dim_max::overload_name) |
| 4208 | .typed<max_dim_max::schema>(); |
| 4209 | } |
| 4210 | |
| 4211 | // aten::max.dim_max(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4212 | ::std::tuple<at::Tensor &,at::Tensor &> max_dim_max::call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & max, at::Tensor & max_values) { |
| 4213 | |
| 4214 | static auto op = create_max_dim_max_typed_handle(); |
| 4215 | return op.call(self, dim, keepdim, max, max_values); |
| 4216 | } |
| 4217 | |
| 4218 | // aten::max.dim_max(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4219 | ::std::tuple<at::Tensor &,at::Tensor &> max_dim_max::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & max, at::Tensor & max_values) { |
| 4220 | |
| 4221 | static auto op = create_max_dim_max_typed_handle(); |
| 4222 | return op.redispatch(dispatchKeySet, self, dim, keepdim, max, max_values); |
| 4223 | } |
| 4224 | |
| 4225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_names_dim, name, "aten::max") |
| 4226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_names_dim, overload_name, "names_dim") |
| 4227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_names_dim, schema_str, "max.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 4228 | |
| 4229 | // aten::max.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4230 | static C10_NOINLINE c10::TypedOperatorHandle<max_names_dim::schema> create_max_names_dim_typed_handle() { |
| 4231 | return c10::Dispatcher::singleton() |
| 4232 | .findSchemaOrThrow(max_names_dim::name, max_names_dim::overload_name) |
| 4233 | .typed<max_names_dim::schema>(); |
| 4234 | } |
| 4235 | |
| 4236 | // aten::max.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4237 | ::std::tuple<at::Tensor,at::Tensor> max_names_dim::call(const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 4238 | |
| 4239 | static auto op = create_max_names_dim_typed_handle(); |
| 4240 | return op.call(self, dim, keepdim); |
| 4241 | } |
| 4242 | |
| 4243 | // aten::max.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4244 | ::std::tuple<at::Tensor,at::Tensor> max_names_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 4245 | |
| 4246 | static auto op = create_max_names_dim_typed_handle(); |
| 4247 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 4248 | } |
| 4249 | |
| 4250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_names_dim_max, name, "aten::max") |
| 4251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_names_dim_max, overload_name, "names_dim_max") |
| 4252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_names_dim_max, schema_str, "max.names_dim_max(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 4253 | |
| 4254 | // aten::max.names_dim_max(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4255 | static C10_NOINLINE c10::TypedOperatorHandle<max_names_dim_max::schema> create_max_names_dim_max_typed_handle() { |
| 4256 | return c10::Dispatcher::singleton() |
| 4257 | .findSchemaOrThrow(max_names_dim_max::name, max_names_dim_max::overload_name) |
| 4258 | .typed<max_names_dim_max::schema>(); |
| 4259 | } |
| 4260 | |
| 4261 | // aten::max.names_dim_max(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4262 | ::std::tuple<at::Tensor &,at::Tensor &> max_names_dim_max::call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & max, at::Tensor & max_values) { |
| 4263 | |
| 4264 | static auto op = create_max_names_dim_max_typed_handle(); |
| 4265 | return op.call(self, dim, keepdim, max, max_values); |
| 4266 | } |
| 4267 | |
| 4268 | // aten::max.names_dim_max(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) max, Tensor(b!) max_values) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4269 | ::std::tuple<at::Tensor &,at::Tensor &> max_names_dim_max::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & max, at::Tensor & max_values) { |
| 4270 | |
| 4271 | static auto op = create_max_names_dim_max_typed_handle(); |
| 4272 | return op.redispatch(dispatchKeySet, self, dim, keepdim, max, max_values); |
| 4273 | } |
| 4274 | |
| 4275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool1d_with_indices, name, "aten::max_pool1d_with_indices") |
| 4276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool1d_with_indices, overload_name, "") |
| 4277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool1d_with_indices, schema_str, "max_pool1d_with_indices(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor)") |
| 4278 | |
| 4279 | // aten::max_pool1d_with_indices(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 4280 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool1d_with_indices::schema> create_max_pool1d_with_indices_typed_handle() { |
| 4281 | return c10::Dispatcher::singleton() |
| 4282 | .findSchemaOrThrow(max_pool1d_with_indices::name, max_pool1d_with_indices::overload_name) |
| 4283 | .typed<max_pool1d_with_indices::schema>(); |
| 4284 | } |
| 4285 | |
| 4286 | // aten::max_pool1d_with_indices(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 4287 | ::std::tuple<at::Tensor,at::Tensor> max_pool1d_with_indices::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 4288 | |
| 4289 | static auto op = create_max_pool1d_with_indices_typed_handle(); |
| 4290 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode); |
| 4291 | } |
| 4292 | |
| 4293 | // aten::max_pool1d_with_indices(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 4294 | ::std::tuple<at::Tensor,at::Tensor> max_pool1d_with_indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 4295 | |
| 4296 | static auto op = create_max_pool1d_with_indices_typed_handle(); |
| 4297 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode); |
| 4298 | } |
| 4299 | |
| 4300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_backward, name, "aten::mkldnn_max_pool3d_backward") |
| 4301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_backward, overload_name, "") |
| 4302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_backward, schema_str, "mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor") |
| 4303 | |
| 4304 | // aten::mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
| 4305 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_max_pool3d_backward::schema> create_mkldnn_max_pool3d_backward_typed_handle() { |
| 4306 | return c10::Dispatcher::singleton() |
| 4307 | .findSchemaOrThrow(mkldnn_max_pool3d_backward::name, mkldnn_max_pool3d_backward::overload_name) |
| 4308 | .typed<mkldnn_max_pool3d_backward::schema>(); |
| 4309 | } |
| 4310 | |
| 4311 | // aten::mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
| 4312 | at::Tensor mkldnn_max_pool3d_backward::call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 4313 | |
| 4314 | static auto op = create_mkldnn_max_pool3d_backward_typed_handle(); |
| 4315 | return op.call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode); |
| 4316 | } |
| 4317 | |
| 4318 | // aten::mkldnn_max_pool3d_backward(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
| 4319 | at::Tensor mkldnn_max_pool3d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 4320 | |
| 4321 | static auto op = create_mkldnn_max_pool3d_backward_typed_handle(); |
| 4322 | return op.redispatch(dispatchKeySet, grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode); |
| 4323 | } |
| 4324 | |
| 4325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_max_pool1d, name, "aten::quantized_max_pool1d") |
| 4326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_max_pool1d, overload_name, "") |
| 4327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_max_pool1d, schema_str, "quantized_max_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> Tensor") |
| 4328 | |
| 4329 | // aten::quantized_max_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> Tensor |
| 4330 | static C10_NOINLINE c10::TypedOperatorHandle<quantized_max_pool1d::schema> create_quantized_max_pool1d_typed_handle() { |
| 4331 | return c10::Dispatcher::singleton() |
| 4332 | .findSchemaOrThrow(quantized_max_pool1d::name, quantized_max_pool1d::overload_name) |
| 4333 | .typed<quantized_max_pool1d::schema>(); |
| 4334 | } |
| 4335 | |
| 4336 | // aten::quantized_max_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> Tensor |
| 4337 | at::Tensor quantized_max_pool1d::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 4338 | |
| 4339 | static auto op = create_quantized_max_pool1d_typed_handle(); |
| 4340 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode); |
| 4341 | } |
| 4342 | |
| 4343 | // aten::quantized_max_pool1d(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False) -> Tensor |
| 4344 | at::Tensor quantized_max_pool1d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 4345 | |
| 4346 | static auto op = create_quantized_max_pool1d_typed_handle(); |
| 4347 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode); |
| 4348 | } |
| 4349 | |
| 4350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_convolution, name, "aten::mkldnn_convolution") |
| 4351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_convolution, overload_name, "") |
| 4352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_convolution, schema_str, "mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor") |
| 4353 | |
| 4354 | // aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor |
| 4355 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_convolution::schema> create_mkldnn_convolution_typed_handle() { |
| 4356 | return c10::Dispatcher::singleton() |
| 4357 | .findSchemaOrThrow(mkldnn_convolution::name, mkldnn_convolution::overload_name) |
| 4358 | .typed<mkldnn_convolution::schema>(); |
| 4359 | } |
| 4360 | |
| 4361 | // aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor |
| 4362 | at::Tensor mkldnn_convolution::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { |
| 4363 | |
| 4364 | static auto op = create_mkldnn_convolution_typed_handle(); |
| 4365 | return op.call(self, weight, bias, padding, stride, dilation, groups); |
| 4366 | } |
| 4367 | |
| 4368 | // aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor |
| 4369 | at::Tensor mkldnn_convolution::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { |
| 4370 | |
| 4371 | static auto op = create_mkldnn_convolution_typed_handle(); |
| 4372 | return op.redispatch(dispatchKeySet, self, weight, bias, padding, stride, dilation, groups); |
| 4373 | } |
| 4374 | |
| 4375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_backward, name, "aten::miopen_batch_norm_backward") |
| 4376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_backward, overload_name, "") |
| 4377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_backward, schema_str, "miopen_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon) -> (Tensor, Tensor, Tensor)") |
| 4378 | |
| 4379 | // aten::miopen_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon) -> (Tensor, Tensor, Tensor) |
| 4380 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_batch_norm_backward::schema> create_miopen_batch_norm_backward_typed_handle() { |
| 4381 | return c10::Dispatcher::singleton() |
| 4382 | .findSchemaOrThrow(miopen_batch_norm_backward::name, miopen_batch_norm_backward::overload_name) |
| 4383 | .typed<miopen_batch_norm_backward::schema>(); |
| 4384 | } |
| 4385 | |
| 4386 | // aten::miopen_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon) -> (Tensor, Tensor, Tensor) |
| 4387 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> miopen_batch_norm_backward::call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon) { |
| 4388 | |
| 4389 | static auto op = create_miopen_batch_norm_backward_typed_handle(); |
| 4390 | return op.call(input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon); |
| 4391 | } |
| 4392 | |
| 4393 | // aten::miopen_batch_norm_backward(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon) -> (Tensor, Tensor, Tensor) |
| 4394 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> miopen_batch_norm_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon) { |
| 4395 | |
| 4396 | static auto op = create_miopen_batch_norm_backward_typed_handle(); |
| 4397 | return op.redispatch(dispatchKeySet, input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon); |
| 4398 | } |
| 4399 | |
| 4400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_relu, name, "aten::miopen_convolution_relu") |
| 4401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_relu, overload_name, "") |
| 4402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_relu, schema_str, "miopen_convolution_relu(Tensor self, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor") |
| 4403 | |
| 4404 | // aten::miopen_convolution_relu(Tensor self, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
| 4405 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_convolution_relu::schema> create_miopen_convolution_relu_typed_handle() { |
| 4406 | return c10::Dispatcher::singleton() |
| 4407 | .findSchemaOrThrow(miopen_convolution_relu::name, miopen_convolution_relu::overload_name) |
| 4408 | .typed<miopen_convolution_relu::schema>(); |
| 4409 | } |
| 4410 | |
| 4411 | // aten::miopen_convolution_relu(Tensor self, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
| 4412 | at::Tensor miopen_convolution_relu::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { |
| 4413 | |
| 4414 | static auto op = create_miopen_convolution_relu_typed_handle(); |
| 4415 | return op.call(self, weight, bias, stride, padding, dilation, groups); |
| 4416 | } |
| 4417 | |
| 4418 | // aten::miopen_convolution_relu(Tensor self, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
| 4419 | at::Tensor miopen_convolution_relu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { |
| 4420 | |
| 4421 | static auto op = create_miopen_convolution_relu_typed_handle(); |
| 4422 | return op.redispatch(dispatchKeySet, self, weight, bias, stride, padding, dilation, groups); |
| 4423 | } |
| 4424 | |
| 4425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode, name, "aten::mode") |
| 4426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode, overload_name, "") |
| 4427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode, schema_str, "mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 4428 | |
| 4429 | // aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4430 | static C10_NOINLINE c10::TypedOperatorHandle<mode::schema> create_mode_typed_handle() { |
| 4431 | return c10::Dispatcher::singleton() |
| 4432 | .findSchemaOrThrow(mode::name, mode::overload_name) |
| 4433 | .typed<mode::schema>(); |
| 4434 | } |
| 4435 | |
| 4436 | // aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4437 | ::std::tuple<at::Tensor,at::Tensor> mode::call(const at::Tensor & self, int64_t dim, bool keepdim) { |
| 4438 | |
| 4439 | static auto op = create_mode_typed_handle(); |
| 4440 | return op.call(self, dim, keepdim); |
| 4441 | } |
| 4442 | |
| 4443 | // aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4444 | ::std::tuple<at::Tensor,at::Tensor> mode::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim) { |
| 4445 | |
| 4446 | static auto op = create_mode_typed_handle(); |
| 4447 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 4448 | } |
| 4449 | |
| 4450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_values, name, "aten::mode") |
| 4451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_values, overload_name, "values") |
| 4452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_values, schema_str, "mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 4453 | |
| 4454 | // aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4455 | static C10_NOINLINE c10::TypedOperatorHandle<mode_values::schema> create_mode_values_typed_handle() { |
| 4456 | return c10::Dispatcher::singleton() |
| 4457 | .findSchemaOrThrow(mode_values::name, mode_values::overload_name) |
| 4458 | .typed<mode_values::schema>(); |
| 4459 | } |
| 4460 | |
| 4461 | // aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4462 | ::std::tuple<at::Tensor &,at::Tensor &> mode_values::call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 4463 | |
| 4464 | static auto op = create_mode_values_typed_handle(); |
| 4465 | return op.call(self, dim, keepdim, values, indices); |
| 4466 | } |
| 4467 | |
| 4468 | // aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4469 | ::std::tuple<at::Tensor &,at::Tensor &> mode_values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 4470 | |
| 4471 | static auto op = create_mode_values_typed_handle(); |
| 4472 | return op.redispatch(dispatchKeySet, self, dim, keepdim, values, indices); |
| 4473 | } |
| 4474 | |
| 4475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_dimname, name, "aten::mode") |
| 4476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_dimname, overload_name, "dimname") |
| 4477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_dimname, schema_str, "mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 4478 | |
| 4479 | // aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4480 | static C10_NOINLINE c10::TypedOperatorHandle<mode_dimname::schema> create_mode_dimname_typed_handle() { |
| 4481 | return c10::Dispatcher::singleton() |
| 4482 | .findSchemaOrThrow(mode_dimname::name, mode_dimname::overload_name) |
| 4483 | .typed<mode_dimname::schema>(); |
| 4484 | } |
| 4485 | |
| 4486 | // aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4487 | ::std::tuple<at::Tensor,at::Tensor> mode_dimname::call(const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 4488 | |
| 4489 | static auto op = create_mode_dimname_typed_handle(); |
| 4490 | return op.call(self, dim, keepdim); |
| 4491 | } |
| 4492 | |
| 4493 | // aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 4494 | ::std::tuple<at::Tensor,at::Tensor> mode_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 4495 | |
| 4496 | static auto op = create_mode_dimname_typed_handle(); |
| 4497 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 4498 | } |
| 4499 | |
| 4500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_dimname_out, name, "aten::mode") |
| 4501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_dimname_out, overload_name, "dimname_out") |
| 4502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mode_dimname_out, schema_str, "mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 4503 | |
| 4504 | // aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4505 | static C10_NOINLINE c10::TypedOperatorHandle<mode_dimname_out::schema> create_mode_dimname_out_typed_handle() { |
| 4506 | return c10::Dispatcher::singleton() |
| 4507 | .findSchemaOrThrow(mode_dimname_out::name, mode_dimname_out::overload_name) |
| 4508 | .typed<mode_dimname_out::schema>(); |
| 4509 | } |
| 4510 | |
| 4511 | // aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4512 | ::std::tuple<at::Tensor &,at::Tensor &> mode_dimname_out::call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 4513 | |
| 4514 | static auto op = create_mode_dimname_out_typed_handle(); |
| 4515 | return op.call(self, dim, keepdim, values, indices); |
| 4516 | } |
| 4517 | |
| 4518 | // aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 4519 | ::std::tuple<at::Tensor &,at::Tensor &> mode_dimname_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 4520 | |
| 4521 | static auto op = create_mode_dimname_out_typed_handle(); |
| 4522 | return op.redispatch(dispatchKeySet, self, dim, keepdim, values, indices); |
| 4523 | } |
| 4524 | |
| 4525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Tensor, name, "aten::mul") |
| 4526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Tensor, overload_name, "Tensor") |
| 4527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Tensor, schema_str, "mul.Tensor(Tensor self, Tensor other) -> Tensor") |
| 4528 | |
| 4529 | // aten::mul.Tensor(Tensor self, Tensor other) -> Tensor |
| 4530 | static C10_NOINLINE c10::TypedOperatorHandle<mul_Tensor::schema> create_mul_Tensor_typed_handle() { |
| 4531 | return c10::Dispatcher::singleton() |
| 4532 | .findSchemaOrThrow(mul_Tensor::name, mul_Tensor::overload_name) |
| 4533 | .typed<mul_Tensor::schema>(); |
| 4534 | } |
| 4535 | |
| 4536 | // aten::mul.Tensor(Tensor self, Tensor other) -> Tensor |
| 4537 | at::Tensor mul_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 4538 | |
| 4539 | static auto op = create_mul_Tensor_typed_handle(); |
| 4540 | return op.call(self, other); |
| 4541 | } |
| 4542 | |
| 4543 | // aten::mul.Tensor(Tensor self, Tensor other) -> Tensor |
| 4544 | at::Tensor mul_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 4545 | |
| 4546 | static auto op = create_mul_Tensor_typed_handle(); |
| 4547 | return op.redispatch(dispatchKeySet, self, other); |
| 4548 | } |
| 4549 | |
| 4550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul__Tensor, name, "aten::mul_") |
| 4551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul__Tensor, overload_name, "Tensor") |
| 4552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul__Tensor, schema_str, "mul_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 4553 | |
| 4554 | // aten::mul_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 4555 | static C10_NOINLINE c10::TypedOperatorHandle<mul__Tensor::schema> create_mul__Tensor_typed_handle() { |
| 4556 | return c10::Dispatcher::singleton() |
| 4557 | .findSchemaOrThrow(mul__Tensor::name, mul__Tensor::overload_name) |
| 4558 | .typed<mul__Tensor::schema>(); |
| 4559 | } |
| 4560 | |
| 4561 | // aten::mul_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 4562 | at::Tensor & mul__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 4563 | |
| 4564 | static auto op = create_mul__Tensor_typed_handle(); |
| 4565 | return op.call(self, other); |
| 4566 | } |
| 4567 | |
| 4568 | // aten::mul_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 4569 | at::Tensor & mul__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 4570 | |
| 4571 | static auto op = create_mul__Tensor_typed_handle(); |
| 4572 | return op.redispatch(dispatchKeySet, self, other); |
| 4573 | } |
| 4574 | |
| 4575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_out, name, "aten::mul") |
| 4576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_out, overload_name, "out") |
| 4577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_out, schema_str, "mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 4578 | |
| 4579 | // aten::mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 4580 | static C10_NOINLINE c10::TypedOperatorHandle<mul_out::schema> create_mul_out_typed_handle() { |
| 4581 | return c10::Dispatcher::singleton() |
| 4582 | .findSchemaOrThrow(mul_out::name, mul_out::overload_name) |
| 4583 | .typed<mul_out::schema>(); |
| 4584 | } |
| 4585 | |
| 4586 | // aten::mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 4587 | at::Tensor & mul_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 4588 | |
| 4589 | static auto op = create_mul_out_typed_handle(); |
| 4590 | return op.call(self, other, out); |
| 4591 | } |
| 4592 | |
| 4593 | // aten::mul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 4594 | at::Tensor & mul_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 4595 | |
| 4596 | static auto op = create_mul_out_typed_handle(); |
| 4597 | return op.redispatch(dispatchKeySet, self, other, out); |
| 4598 | } |
| 4599 | |
| 4600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Scalar, name, "aten::mul") |
| 4601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Scalar, overload_name, "Scalar") |
| 4602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Scalar, schema_str, "mul.Scalar(Tensor self, Scalar other) -> Tensor") |
| 4603 | |
| 4604 | // aten::mul.Scalar(Tensor self, Scalar other) -> Tensor |
| 4605 | static C10_NOINLINE c10::TypedOperatorHandle<mul_Scalar::schema> create_mul_Scalar_typed_handle() { |
| 4606 | return c10::Dispatcher::singleton() |
| 4607 | .findSchemaOrThrow(mul_Scalar::name, mul_Scalar::overload_name) |
| 4608 | .typed<mul_Scalar::schema>(); |
| 4609 | } |
| 4610 | |
| 4611 | // aten::mul.Scalar(Tensor self, Scalar other) -> Tensor |
| 4612 | at::Tensor mul_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 4613 | |
| 4614 | static auto op = create_mul_Scalar_typed_handle(); |
| 4615 | return op.call(self, other); |
| 4616 | } |
| 4617 | |
| 4618 | // aten::mul.Scalar(Tensor self, Scalar other) -> Tensor |
| 4619 | at::Tensor mul_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 4620 | |
| 4621 | static auto op = create_mul_Scalar_typed_handle(); |
| 4622 | return op.redispatch(dispatchKeySet, self, other); |
| 4623 | } |
| 4624 | |
| 4625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul__Scalar, name, "aten::mul_") |
| 4626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul__Scalar, overload_name, "Scalar") |
| 4627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul__Scalar, schema_str, "mul_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 4628 | |
| 4629 | // aten::mul_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 4630 | static C10_NOINLINE c10::TypedOperatorHandle<mul__Scalar::schema> create_mul__Scalar_typed_handle() { |
| 4631 | return c10::Dispatcher::singleton() |
| 4632 | .findSchemaOrThrow(mul__Scalar::name, mul__Scalar::overload_name) |
| 4633 | .typed<mul__Scalar::schema>(); |
| 4634 | } |
| 4635 | |
| 4636 | // aten::mul_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 4637 | at::Tensor & mul__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 4638 | |
| 4639 | static auto op = create_mul__Scalar_typed_handle(); |
| 4640 | return op.call(self, other); |
| 4641 | } |
| 4642 | |
| 4643 | // aten::mul_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 4644 | at::Tensor & mul__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 4645 | |
| 4646 | static auto op = create_mul__Scalar_typed_handle(); |
| 4647 | return op.redispatch(dispatchKeySet, self, other); |
| 4648 | } |
| 4649 | |
| 4650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma_out, name, "aten::mvlgamma") |
| 4651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma_out, overload_name, "out") |
| 4652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma_out, schema_str, "mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!)") |
| 4653 | |
| 4654 | // aten::mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) |
| 4655 | static C10_NOINLINE c10::TypedOperatorHandle<mvlgamma_out::schema> create_mvlgamma_out_typed_handle() { |
| 4656 | return c10::Dispatcher::singleton() |
| 4657 | .findSchemaOrThrow(mvlgamma_out::name, mvlgamma_out::overload_name) |
| 4658 | .typed<mvlgamma_out::schema>(); |
| 4659 | } |
| 4660 | |
| 4661 | // aten::mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) |
| 4662 | at::Tensor & mvlgamma_out::call(const at::Tensor & self, int64_t p, at::Tensor & out) { |
| 4663 | |
| 4664 | static auto op = create_mvlgamma_out_typed_handle(); |
| 4665 | return op.call(self, p, out); |
| 4666 | } |
| 4667 | |
| 4668 | // aten::mvlgamma.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) |
| 4669 | at::Tensor & mvlgamma_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p, at::Tensor & out) { |
| 4670 | |
| 4671 | static auto op = create_mvlgamma_out_typed_handle(); |
| 4672 | return op.redispatch(dispatchKeySet, self, p, out); |
| 4673 | } |
| 4674 | |
| 4675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma, name, "aten::mvlgamma") |
| 4676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma, overload_name, "") |
| 4677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma, schema_str, "mvlgamma(Tensor self, int p) -> Tensor") |
| 4678 | |
| 4679 | // aten::mvlgamma(Tensor self, int p) -> Tensor |
| 4680 | static C10_NOINLINE c10::TypedOperatorHandle<mvlgamma::schema> create_mvlgamma_typed_handle() { |
| 4681 | return c10::Dispatcher::singleton() |
| 4682 | .findSchemaOrThrow(mvlgamma::name, mvlgamma::overload_name) |
| 4683 | .typed<mvlgamma::schema>(); |
| 4684 | } |
| 4685 | |
| 4686 | // aten::mvlgamma(Tensor self, int p) -> Tensor |
| 4687 | at::Tensor mvlgamma::call(const at::Tensor & self, int64_t p) { |
| 4688 | |
| 4689 | static auto op = create_mvlgamma_typed_handle(); |
| 4690 | return op.call(self, p); |
| 4691 | } |
| 4692 | |
| 4693 | // aten::mvlgamma(Tensor self, int p) -> Tensor |
| 4694 | at::Tensor mvlgamma::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p) { |
| 4695 | |
| 4696 | static auto op = create_mvlgamma_typed_handle(); |
| 4697 | return op.redispatch(dispatchKeySet, self, p); |
| 4698 | } |
| 4699 | |
| 4700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma_, name, "aten::mvlgamma_") |
| 4701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma_, overload_name, "") |
| 4702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mvlgamma_, schema_str, "mvlgamma_(Tensor(a!) self, int p) -> Tensor(a!)") |
| 4703 | |
| 4704 | // aten::mvlgamma_(Tensor(a!) self, int p) -> Tensor(a!) |
| 4705 | static C10_NOINLINE c10::TypedOperatorHandle<mvlgamma_::schema> create_mvlgamma__typed_handle() { |
| 4706 | return c10::Dispatcher::singleton() |
| 4707 | .findSchemaOrThrow(mvlgamma_::name, mvlgamma_::overload_name) |
| 4708 | .typed<mvlgamma_::schema>(); |
| 4709 | } |
| 4710 | |
| 4711 | // aten::mvlgamma_(Tensor(a!) self, int p) -> Tensor(a!) |
| 4712 | at::Tensor & mvlgamma_::call(at::Tensor & self, int64_t p) { |
| 4713 | |
| 4714 | static auto op = create_mvlgamma__typed_handle(); |
| 4715 | return op.call(self, p); |
| 4716 | } |
| 4717 | |
| 4718 | // aten::mvlgamma_(Tensor(a!) self, int p) -> Tensor(a!) |
| 4719 | at::Tensor & mvlgamma_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t p) { |
| 4720 | |
| 4721 | static auto op = create_mvlgamma__typed_handle(); |
| 4722 | return op.redispatch(dispatchKeySet, self, p); |
| 4723 | } |
| 4724 | |
| 4725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(narrow, name, "aten::narrow") |
| 4726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(narrow, overload_name, "") |
| 4727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(narrow, schema_str, "narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a)") |
| 4728 | |
| 4729 | // aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) |
| 4730 | static C10_NOINLINE c10::TypedOperatorHandle<narrow::schema> create_narrow_typed_handle() { |
| 4731 | return c10::Dispatcher::singleton() |
| 4732 | .findSchemaOrThrow(narrow::name, narrow::overload_name) |
| 4733 | .typed<narrow::schema>(); |
| 4734 | } |
| 4735 | |
| 4736 | // aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) |
| 4737 | at::Tensor narrow::call(const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { |
| 4738 | |
| 4739 | static auto op = create_narrow_typed_handle(); |
| 4740 | return op.call(self, dim, start, length); |
| 4741 | } |
| 4742 | |
| 4743 | // aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) |
| 4744 | at::Tensor narrow::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymInt start, c10::SymInt length) { |
| 4745 | |
| 4746 | static auto op = create_narrow_typed_handle(); |
| 4747 | return op.redispatch(dispatchKeySet, self, dim, start, length); |
| 4748 | } |
| 4749 | |
| 4750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(narrow_Tensor, name, "aten::narrow") |
| 4751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(narrow_Tensor, overload_name, "Tensor") |
| 4752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(narrow_Tensor, schema_str, "narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a)") |
| 4753 | |
| 4754 | // aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) |
| 4755 | static C10_NOINLINE c10::TypedOperatorHandle<narrow_Tensor::schema> create_narrow_Tensor_typed_handle() { |
| 4756 | return c10::Dispatcher::singleton() |
| 4757 | .findSchemaOrThrow(narrow_Tensor::name, narrow_Tensor::overload_name) |
| 4758 | .typed<narrow_Tensor::schema>(); |
| 4759 | } |
| 4760 | |
| 4761 | // aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) |
| 4762 | at::Tensor narrow_Tensor::call(const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length) { |
| 4763 | |
| 4764 | static auto op = create_narrow_Tensor_typed_handle(); |
| 4765 | return op.call(self, dim, start, length); |
| 4766 | } |
| 4767 | |
| 4768 | // aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) |
| 4769 | at::Tensor narrow_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & start, c10::SymInt length) { |
| 4770 | |
| 4771 | static auto op = create_narrow_Tensor_typed_handle(); |
| 4772 | return op.redispatch(dispatchKeySet, self, dim, start, length); |
| 4773 | } |
| 4774 | |
| 4775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_backward_elemt, name, "aten::batch_norm_backward_elemt") |
| 4776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_backward_elemt, overload_name, "") |
| 4777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_backward_elemt, schema_str, "batch_norm_backward_elemt(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count) -> Tensor") |
| 4778 | |
| 4779 | // aten::batch_norm_backward_elemt(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count) -> Tensor |
| 4780 | static C10_NOINLINE c10::TypedOperatorHandle<batch_norm_backward_elemt::schema> create_batch_norm_backward_elemt_typed_handle() { |
| 4781 | return c10::Dispatcher::singleton() |
| 4782 | .findSchemaOrThrow(batch_norm_backward_elemt::name, batch_norm_backward_elemt::overload_name) |
| 4783 | .typed<batch_norm_backward_elemt::schema>(); |
| 4784 | } |
| 4785 | |
| 4786 | // aten::batch_norm_backward_elemt(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count) -> Tensor |
| 4787 | at::Tensor batch_norm_backward_elemt::call(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional<at::Tensor> & weight, const at::Tensor & mean_dy, const at::Tensor & mean_dy_xmu, const at::Tensor & count) { |
| 4788 | |
| 4789 | static auto op = create_batch_norm_backward_elemt_typed_handle(); |
| 4790 | return op.call(grad_out, input, mean, invstd, weight, mean_dy, mean_dy_xmu, count); |
| 4791 | } |
| 4792 | |
| 4793 | // aten::batch_norm_backward_elemt(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count) -> Tensor |
| 4794 | at::Tensor batch_norm_backward_elemt::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional<at::Tensor> & weight, const at::Tensor & mean_dy, const at::Tensor & mean_dy_xmu, const at::Tensor & count) { |
| 4795 | |
| 4796 | static auto op = create_batch_norm_backward_elemt_typed_handle(); |
| 4797 | return op.redispatch(dispatchKeySet, grad_out, input, mean, invstd, weight, mean_dy, mean_dy_xmu, count); |
| 4798 | } |
| 4799 | |
| 4800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pdist, name, "aten::pdist") |
| 4801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pdist, overload_name, "") |
| 4802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pdist, schema_str, "pdist(Tensor self, float p=2) -> Tensor") |
| 4803 | |
| 4804 | // aten::pdist(Tensor self, float p=2) -> Tensor |
| 4805 | static C10_NOINLINE c10::TypedOperatorHandle<pdist::schema> create_pdist_typed_handle() { |
| 4806 | return c10::Dispatcher::singleton() |
| 4807 | .findSchemaOrThrow(pdist::name, pdist::overload_name) |
| 4808 | .typed<pdist::schema>(); |
| 4809 | } |
| 4810 | |
| 4811 | // aten::pdist(Tensor self, float p=2) -> Tensor |
| 4812 | at::Tensor pdist::call(const at::Tensor & self, double p) { |
| 4813 | |
| 4814 | static auto op = create_pdist_typed_handle(); |
| 4815 | return op.call(self, p); |
| 4816 | } |
| 4817 | |
| 4818 | // aten::pdist(Tensor self, float p=2) -> Tensor |
| 4819 | at::Tensor pdist::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p) { |
| 4820 | |
| 4821 | static auto op = create_pdist_typed_handle(); |
| 4822 | return op.redispatch(dispatchKeySet, self, p); |
| 4823 | } |
| 4824 | |
| 4825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(moveaxis_intlist, name, "aten::moveaxis") |
| 4826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(moveaxis_intlist, overload_name, "intlist") |
| 4827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(moveaxis_intlist, schema_str, "moveaxis.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a)") |
| 4828 | |
| 4829 | // aten::moveaxis.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a) |
| 4830 | static C10_NOINLINE c10::TypedOperatorHandle<moveaxis_intlist::schema> create_moveaxis_intlist_typed_handle() { |
| 4831 | return c10::Dispatcher::singleton() |
| 4832 | .findSchemaOrThrow(moveaxis_intlist::name, moveaxis_intlist::overload_name) |
| 4833 | .typed<moveaxis_intlist::schema>(); |
| 4834 | } |
| 4835 | |
| 4836 | // aten::moveaxis.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a) |
| 4837 | at::Tensor moveaxis_intlist::call(const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination) { |
| 4838 | |
| 4839 | static auto op = create_moveaxis_intlist_typed_handle(); |
| 4840 | return op.call(self, source, destination); |
| 4841 | } |
| 4842 | |
| 4843 | // aten::moveaxis.intlist(Tensor(a) self, int[] source, int[] destination) -> Tensor(a) |
| 4844 | at::Tensor moveaxis_intlist::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef source, at::IntArrayRef destination) { |
| 4845 | |
| 4846 | static auto op = create_moveaxis_intlist_typed_handle(); |
| 4847 | return op.redispatch(dispatchKeySet, self, source, destination); |
| 4848 | } |
| 4849 | |
| 4850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(moveaxis_int, name, "aten::moveaxis") |
| 4851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(moveaxis_int, overload_name, "int") |
| 4852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(moveaxis_int, schema_str, "moveaxis.int(Tensor(a) self, int source, int destination) -> Tensor(a)") |
| 4853 | |
| 4854 | // aten::moveaxis.int(Tensor(a) self, int source, int destination) -> Tensor(a) |
| 4855 | static C10_NOINLINE c10::TypedOperatorHandle<moveaxis_int::schema> create_moveaxis_int_typed_handle() { |
| 4856 | return c10::Dispatcher::singleton() |
| 4857 | .findSchemaOrThrow(moveaxis_int::name, moveaxis_int::overload_name) |
| 4858 | .typed<moveaxis_int::schema>(); |
| 4859 | } |
| 4860 | |
| 4861 | // aten::moveaxis.int(Tensor(a) self, int source, int destination) -> Tensor(a) |
| 4862 | at::Tensor moveaxis_int::call(const at::Tensor & self, int64_t source, int64_t destination) { |
| 4863 | |
| 4864 | static auto op = create_moveaxis_int_typed_handle(); |
| 4865 | return op.call(self, source, destination); |
| 4866 | } |
| 4867 | |
| 4868 | // aten::moveaxis.int(Tensor(a) self, int source, int destination) -> Tensor(a) |
| 4869 | at::Tensor moveaxis_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t source, int64_t destination) { |
| 4870 | |
| 4871 | static auto op = create_moveaxis_int_typed_handle(); |
| 4872 | return op.redispatch(dispatchKeySet, self, source, destination); |
| 4873 | } |
| 4874 | |
| 4875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pixel_unshuffle, name, "aten::pixel_unshuffle") |
| 4876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pixel_unshuffle, overload_name, "") |
| 4877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pixel_unshuffle, schema_str, "pixel_unshuffle(Tensor self, int downscale_factor) -> Tensor") |
| 4878 | |
| 4879 | // aten::pixel_unshuffle(Tensor self, int downscale_factor) -> Tensor |
| 4880 | static C10_NOINLINE c10::TypedOperatorHandle<pixel_unshuffle::schema> create_pixel_unshuffle_typed_handle() { |
| 4881 | return c10::Dispatcher::singleton() |
| 4882 | .findSchemaOrThrow(pixel_unshuffle::name, pixel_unshuffle::overload_name) |
| 4883 | .typed<pixel_unshuffle::schema>(); |
| 4884 | } |
| 4885 | |
| 4886 | // aten::pixel_unshuffle(Tensor self, int downscale_factor) -> Tensor |
| 4887 | at::Tensor pixel_unshuffle::call(const at::Tensor & self, int64_t downscale_factor) { |
| 4888 | |
| 4889 | static auto op = create_pixel_unshuffle_typed_handle(); |
| 4890 | return op.call(self, downscale_factor); |
| 4891 | } |
| 4892 | |
| 4893 | // aten::pixel_unshuffle(Tensor self, int downscale_factor) -> Tensor |
| 4894 | at::Tensor pixel_unshuffle::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t downscale_factor) { |
| 4895 | |
| 4896 | static auto op = create_pixel_unshuffle_typed_handle(); |
| 4897 | return op.redispatch(dispatchKeySet, self, downscale_factor); |
| 4898 | } |
| 4899 | |
| 4900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_pinned, name, "aten::is_pinned") |
| 4901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_pinned, overload_name, "") |
| 4902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_pinned, schema_str, "is_pinned(Tensor self, Device? device=None) -> bool") |
| 4903 | |
| 4904 | // aten::is_pinned(Tensor self, Device? device=None) -> bool |
| 4905 | static C10_NOINLINE c10::TypedOperatorHandle<is_pinned::schema> create_is_pinned_typed_handle() { |
| 4906 | return c10::Dispatcher::singleton() |
| 4907 | .findSchemaOrThrow(is_pinned::name, is_pinned::overload_name) |
| 4908 | .typed<is_pinned::schema>(); |
| 4909 | } |
| 4910 | |
| 4911 | // aten::is_pinned(Tensor self, Device? device=None) -> bool |
| 4912 | bool is_pinned::call(const at::Tensor & self, c10::optional<at::Device> device) { |
| 4913 | |
| 4914 | static auto op = create_is_pinned_typed_handle(); |
| 4915 | return op.call(self, device); |
| 4916 | } |
| 4917 | |
| 4918 | // aten::is_pinned(Tensor self, Device? device=None) -> bool |
| 4919 | bool is_pinned::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Device> device) { |
| 4920 | |
| 4921 | static auto op = create_is_pinned_typed_handle(); |
| 4922 | return op.redispatch(dispatchKeySet, self, device); |
| 4923 | } |
| 4924 | |
| 4925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pin_memory, name, "aten::pin_memory") |
| 4926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pin_memory, overload_name, "") |
| 4927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pin_memory, schema_str, "pin_memory(Tensor(a) self, Device? device=None) -> Tensor(a)") |
| 4928 | |
| 4929 | // aten::pin_memory(Tensor(a) self, Device? device=None) -> Tensor(a) |
| 4930 | static C10_NOINLINE c10::TypedOperatorHandle<pin_memory::schema> create_pin_memory_typed_handle() { |
| 4931 | return c10::Dispatcher::singleton() |
| 4932 | .findSchemaOrThrow(pin_memory::name, pin_memory::overload_name) |
| 4933 | .typed<pin_memory::schema>(); |
| 4934 | } |
| 4935 | |
| 4936 | // aten::pin_memory(Tensor(a) self, Device? device=None) -> Tensor(a) |
| 4937 | at::Tensor pin_memory::call(const at::Tensor & self, c10::optional<at::Device> device) { |
| 4938 | |
| 4939 | static auto op = create_pin_memory_typed_handle(); |
| 4940 | return op.call(self, device); |
| 4941 | } |
| 4942 | |
| 4943 | // aten::pin_memory(Tensor(a) self, Device? device=None) -> Tensor(a) |
| 4944 | at::Tensor pin_memory::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Device> device) { |
| 4945 | |
| 4946 | static auto op = create_pin_memory_typed_handle(); |
| 4947 | return op.redispatch(dispatchKeySet, self, device); |
| 4948 | } |
| 4949 | |
| 4950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pin_memory, name, "aten::_pin_memory") |
| 4951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pin_memory, overload_name, "") |
| 4952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pin_memory, schema_str, "_pin_memory(Tensor self, Device? device=None) -> Tensor") |
| 4953 | |
| 4954 | // aten::_pin_memory(Tensor self, Device? device=None) -> Tensor |
| 4955 | static C10_NOINLINE c10::TypedOperatorHandle<_pin_memory::schema> create__pin_memory_typed_handle() { |
| 4956 | return c10::Dispatcher::singleton() |
| 4957 | .findSchemaOrThrow(_pin_memory::name, _pin_memory::overload_name) |
| 4958 | .typed<_pin_memory::schema>(); |
| 4959 | } |
| 4960 | |
| 4961 | // aten::_pin_memory(Tensor self, Device? device=None) -> Tensor |
| 4962 | at::Tensor _pin_memory::call(const at::Tensor & self, c10::optional<at::Device> device) { |
| 4963 | |
| 4964 | static auto op = create__pin_memory_typed_handle(); |
| 4965 | return op.call(self, device); |
| 4966 | } |
| 4967 | |
| 4968 | // aten::_pin_memory(Tensor self, Device? device=None) -> Tensor |
| 4969 | at::Tensor _pin_memory::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Device> device) { |
| 4970 | |
| 4971 | static auto op = create__pin_memory_typed_handle(); |
| 4972 | return op.redispatch(dispatchKeySet, self, device); |
| 4973 | } |
| 4974 | |
| 4975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn, name, "aten::randn") |
| 4976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn, overload_name, "") |
| 4977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn, schema_str, "randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 4978 | |
| 4979 | // aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 4980 | static C10_NOINLINE c10::TypedOperatorHandle<randn::schema> create_randn_typed_handle() { |
| 4981 | return c10::Dispatcher::singleton() |
| 4982 | .findSchemaOrThrow(randn::name, randn::overload_name) |
| 4983 | .typed<randn::schema>(); |
| 4984 | } |
| 4985 | |
| 4986 | // aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 4987 | at::Tensor randn::call(c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 4988 | |
| 4989 | static auto op = create_randn_typed_handle(); |
| 4990 | return op.call(size, dtype, layout, device, pin_memory); |
| 4991 | } |
| 4992 | |
| 4993 | // aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 4994 | at::Tensor randn::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 4995 | |
| 4996 | static auto op = create_randn_typed_handle(); |
| 4997 | return op.redispatch(dispatchKeySet, size, dtype, layout, device, pin_memory); |
| 4998 | } |
| 4999 | |
| 5000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator, name, "aten::randn") |
| 5001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator, overload_name, "generator") |
| 5002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator, schema_str, "randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 5003 | |
| 5004 | // aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5005 | static C10_NOINLINE c10::TypedOperatorHandle<randn_generator::schema> create_randn_generator_typed_handle() { |
| 5006 | return c10::Dispatcher::singleton() |
| 5007 | .findSchemaOrThrow(randn_generator::name, randn_generator::overload_name) |
| 5008 | .typed<randn_generator::schema>(); |
| 5009 | } |
| 5010 | |
| 5011 | // aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5012 | at::Tensor randn_generator::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5013 | |
| 5014 | static auto op = create_randn_generator_typed_handle(); |
| 5015 | return op.call(size, generator, dtype, layout, device, pin_memory); |
| 5016 | } |
| 5017 | |
| 5018 | // aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5019 | at::Tensor randn_generator::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5020 | |
| 5021 | static auto op = create_randn_generator_typed_handle(); |
| 5022 | return op.redispatch(dispatchKeySet, size, generator, dtype, layout, device, pin_memory); |
| 5023 | } |
| 5024 | |
| 5025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_names, name, "aten::randn") |
| 5026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_names, overload_name, "names") |
| 5027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_names, schema_str, "randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 5028 | |
| 5029 | // aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5030 | static C10_NOINLINE c10::TypedOperatorHandle<randn_names::schema> create_randn_names_typed_handle() { |
| 5031 | return c10::Dispatcher::singleton() |
| 5032 | .findSchemaOrThrow(randn_names::name, randn_names::overload_name) |
| 5033 | .typed<randn_names::schema>(); |
| 5034 | } |
| 5035 | |
| 5036 | // aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5037 | at::Tensor randn_names::call(c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5038 | |
| 5039 | static auto op = create_randn_names_typed_handle(); |
| 5040 | return op.call(size, names, dtype, layout, device, pin_memory); |
| 5041 | } |
| 5042 | |
| 5043 | // aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5044 | at::Tensor randn_names::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5045 | |
| 5046 | static auto op = create_randn_names_typed_handle(); |
| 5047 | return op.redispatch(dispatchKeySet, size, names, dtype, layout, device, pin_memory); |
| 5048 | } |
| 5049 | |
| 5050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_with_names, name, "aten::randn") |
| 5051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_with_names, overload_name, "generator_with_names") |
| 5052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_with_names, schema_str, "randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 5053 | |
| 5054 | // aten::randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5055 | static C10_NOINLINE c10::TypedOperatorHandle<randn_generator_with_names::schema> create_randn_generator_with_names_typed_handle() { |
| 5056 | return c10::Dispatcher::singleton() |
| 5057 | .findSchemaOrThrow(randn_generator_with_names::name, randn_generator_with_names::overload_name) |
| 5058 | .typed<randn_generator_with_names::schema>(); |
| 5059 | } |
| 5060 | |
| 5061 | // aten::randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5062 | at::Tensor randn_generator_with_names::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5063 | |
| 5064 | static auto op = create_randn_generator_with_names_typed_handle(); |
| 5065 | return op.call(size, generator, names, dtype, layout, device, pin_memory); |
| 5066 | } |
| 5067 | |
| 5068 | // aten::randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5069 | at::Tensor randn_generator_with_names::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5070 | |
| 5071 | static auto op = create_randn_generator_with_names_typed_handle(); |
| 5072 | return op.redispatch(dispatchKeySet, size, generator, names, dtype, layout, device, pin_memory); |
| 5073 | } |
| 5074 | |
| 5075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_out, name, "aten::randn") |
| 5076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_out, overload_name, "out") |
| 5077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_out, schema_str, "randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") |
| 5078 | |
| 5079 | // aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 5080 | static C10_NOINLINE c10::TypedOperatorHandle<randn_out::schema> create_randn_out_typed_handle() { |
| 5081 | return c10::Dispatcher::singleton() |
| 5082 | .findSchemaOrThrow(randn_out::name, randn_out::overload_name) |
| 5083 | .typed<randn_out::schema>(); |
| 5084 | } |
| 5085 | |
| 5086 | // aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 5087 | at::Tensor & randn_out::call(c10::SymIntArrayRef size, at::Tensor & out) { |
| 5088 | |
| 5089 | static auto op = create_randn_out_typed_handle(); |
| 5090 | return op.call(size, out); |
| 5091 | } |
| 5092 | |
| 5093 | // aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 5094 | at::Tensor & randn_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, at::Tensor & out) { |
| 5095 | |
| 5096 | static auto op = create_randn_out_typed_handle(); |
| 5097 | return op.redispatch(dispatchKeySet, size, out); |
| 5098 | } |
| 5099 | |
| 5100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_out, name, "aten::randn") |
| 5101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_out, overload_name, "generator_out") |
| 5102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_out, schema_str, "randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)") |
| 5103 | |
| 5104 | // aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
| 5105 | static C10_NOINLINE c10::TypedOperatorHandle<randn_generator_out::schema> create_randn_generator_out_typed_handle() { |
| 5106 | return c10::Dispatcher::singleton() |
| 5107 | .findSchemaOrThrow(randn_generator_out::name, randn_generator_out::overload_name) |
| 5108 | .typed<randn_generator_out::schema>(); |
| 5109 | } |
| 5110 | |
| 5111 | // aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
| 5112 | at::Tensor & randn_generator_out::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 5113 | |
| 5114 | static auto op = create_randn_generator_out_typed_handle(); |
| 5115 | return op.call(size, generator, out); |
| 5116 | } |
| 5117 | |
| 5118 | // aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
| 5119 | at::Tensor & randn_generator_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 5120 | |
| 5121 | static auto op = create_randn_generator_out_typed_handle(); |
| 5122 | return op.redispatch(dispatchKeySet, size, generator, out); |
| 5123 | } |
| 5124 | |
| 5125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_step, name, "aten::range") |
| 5126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_step, overload_name, "step") |
| 5127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_step, schema_str, "range.step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 5128 | |
| 5129 | // aten::range.step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5130 | static C10_NOINLINE c10::TypedOperatorHandle<range_step::schema> create_range_step_typed_handle() { |
| 5131 | return c10::Dispatcher::singleton() |
| 5132 | .findSchemaOrThrow(range_step::name, range_step::overload_name) |
| 5133 | .typed<range_step::schema>(); |
| 5134 | } |
| 5135 | |
| 5136 | // aten::range.step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5137 | at::Tensor range_step::call(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5138 | |
| 5139 | static auto op = create_range_step_typed_handle(); |
| 5140 | return op.call(start, end, step, dtype, layout, device, pin_memory); |
| 5141 | } |
| 5142 | |
| 5143 | // aten::range.step(Scalar start, Scalar end, Scalar step=1, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5144 | at::Tensor range_step::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5145 | |
| 5146 | static auto op = create_range_step_typed_handle(); |
| 5147 | return op.redispatch(dispatchKeySet, start, end, step, dtype, layout, device, pin_memory); |
| 5148 | } |
| 5149 | |
| 5150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range, name, "aten::range") |
| 5151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range, overload_name, "") |
| 5152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range, schema_str, "range(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 5153 | |
| 5154 | // aten::range(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5155 | static C10_NOINLINE c10::TypedOperatorHandle<range::schema> create_range_typed_handle() { |
| 5156 | return c10::Dispatcher::singleton() |
| 5157 | .findSchemaOrThrow(range::name, range::overload_name) |
| 5158 | .typed<range::schema>(); |
| 5159 | } |
| 5160 | |
| 5161 | // aten::range(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5162 | at::Tensor range::call(const at::Scalar & start, const at::Scalar & end, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5163 | |
| 5164 | static auto op = create_range_typed_handle(); |
| 5165 | return op.call(start, end, dtype, layout, device, pin_memory); |
| 5166 | } |
| 5167 | |
| 5168 | // aten::range(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5169 | at::Tensor range::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5170 | |
| 5171 | static auto op = create_range_typed_handle(); |
| 5172 | return op.redispatch(dispatchKeySet, start, end, dtype, layout, device, pin_memory); |
| 5173 | } |
| 5174 | |
| 5175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_out_, name, "aten::range") |
| 5176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_out_, overload_name, "out_") |
| 5177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_out_, schema_str, "range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!)") |
| 5178 | |
| 5179 | // aten::range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!) |
| 5180 | static C10_NOINLINE c10::TypedOperatorHandle<range_out_::schema> create_range_out__typed_handle() { |
| 5181 | return c10::Dispatcher::singleton() |
| 5182 | .findSchemaOrThrow(range_out_::name, range_out_::overload_name) |
| 5183 | .typed<range_out_::schema>(); |
| 5184 | } |
| 5185 | |
| 5186 | // aten::range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!) |
| 5187 | at::Tensor & range_out_::call(const at::Scalar & start, const at::Scalar & end, at::Tensor & out) { |
| 5188 | |
| 5189 | static auto op = create_range_out__typed_handle(); |
| 5190 | return op.call(start, end, out); |
| 5191 | } |
| 5192 | |
| 5193 | // aten::range.out_(Scalar start, Scalar end, *, Tensor(a!) out) -> Tensor(a!) |
| 5194 | at::Tensor & range_out_::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, at::Tensor & out) { |
| 5195 | |
| 5196 | static auto op = create_range_out__typed_handle(); |
| 5197 | return op.redispatch(dispatchKeySet, start, end, out); |
| 5198 | } |
| 5199 | |
| 5200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_out, name, "aten::range") |
| 5201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_out, overload_name, "out") |
| 5202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(range_out, schema_str, "range.out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 5203 | |
| 5204 | // aten::range.out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!) |
| 5205 | static C10_NOINLINE c10::TypedOperatorHandle<range_out::schema> create_range_out_typed_handle() { |
| 5206 | return c10::Dispatcher::singleton() |
| 5207 | .findSchemaOrThrow(range_out::name, range_out::overload_name) |
| 5208 | .typed<range_out::schema>(); |
| 5209 | } |
| 5210 | |
| 5211 | // aten::range.out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!) |
| 5212 | at::Tensor & range_out::call(const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out) { |
| 5213 | |
| 5214 | static auto op = create_range_out_typed_handle(); |
| 5215 | return op.call(start, end, step, out); |
| 5216 | } |
| 5217 | |
| 5218 | // aten::range.out(Scalar start, Scalar end, Scalar step=1, *, Tensor(a!) out) -> Tensor(a!) |
| 5219 | at::Tensor & range_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, const at::Scalar & step, at::Tensor & out) { |
| 5220 | |
| 5221 | static auto op = create_range_out_typed_handle(); |
| 5222 | return op.redispatch(dispatchKeySet, start, end, step, out); |
| 5223 | } |
| 5224 | |
| 5225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ravel, name, "aten::ravel") |
| 5226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ravel, overload_name, "") |
| 5227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ravel, schema_str, "ravel(Tensor(a) self) -> Tensor(a)") |
| 5228 | |
| 5229 | // aten::ravel(Tensor(a) self) -> Tensor(a) |
| 5230 | static C10_NOINLINE c10::TypedOperatorHandle<ravel::schema> create_ravel_typed_handle() { |
| 5231 | return c10::Dispatcher::singleton() |
| 5232 | .findSchemaOrThrow(ravel::name, ravel::overload_name) |
| 5233 | .typed<ravel::schema>(); |
| 5234 | } |
| 5235 | |
| 5236 | // aten::ravel(Tensor(a) self) -> Tensor(a) |
| 5237 | at::Tensor ravel::call(const at::Tensor & self) { |
| 5238 | |
| 5239 | static auto op = create_ravel_typed_handle(); |
| 5240 | return op.call(self); |
| 5241 | } |
| 5242 | |
| 5243 | // aten::ravel(Tensor(a) self) -> Tensor(a) |
| 5244 | at::Tensor ravel::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5245 | |
| 5246 | static auto op = create_ravel_typed_handle(); |
| 5247 | return op.redispatch(dispatchKeySet, self); |
| 5248 | } |
| 5249 | |
| 5250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal, name, "aten::reciprocal") |
| 5251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal, overload_name, "") |
| 5252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal, schema_str, "reciprocal(Tensor self) -> Tensor") |
| 5253 | |
| 5254 | // aten::reciprocal(Tensor self) -> Tensor |
| 5255 | static C10_NOINLINE c10::TypedOperatorHandle<reciprocal::schema> create_reciprocal_typed_handle() { |
| 5256 | return c10::Dispatcher::singleton() |
| 5257 | .findSchemaOrThrow(reciprocal::name, reciprocal::overload_name) |
| 5258 | .typed<reciprocal::schema>(); |
| 5259 | } |
| 5260 | |
| 5261 | // aten::reciprocal(Tensor self) -> Tensor |
| 5262 | at::Tensor reciprocal::call(const at::Tensor & self) { |
| 5263 | |
| 5264 | static auto op = create_reciprocal_typed_handle(); |
| 5265 | return op.call(self); |
| 5266 | } |
| 5267 | |
| 5268 | // aten::reciprocal(Tensor self) -> Tensor |
| 5269 | at::Tensor reciprocal::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5270 | |
| 5271 | static auto op = create_reciprocal_typed_handle(); |
| 5272 | return op.redispatch(dispatchKeySet, self); |
| 5273 | } |
| 5274 | |
| 5275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal_, name, "aten::reciprocal_") |
| 5276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal_, overload_name, "") |
| 5277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal_, schema_str, "reciprocal_(Tensor(a!) self) -> Tensor(a!)") |
| 5278 | |
| 5279 | // aten::reciprocal_(Tensor(a!) self) -> Tensor(a!) |
| 5280 | static C10_NOINLINE c10::TypedOperatorHandle<reciprocal_::schema> create_reciprocal__typed_handle() { |
| 5281 | return c10::Dispatcher::singleton() |
| 5282 | .findSchemaOrThrow(reciprocal_::name, reciprocal_::overload_name) |
| 5283 | .typed<reciprocal_::schema>(); |
| 5284 | } |
| 5285 | |
| 5286 | // aten::reciprocal_(Tensor(a!) self) -> Tensor(a!) |
| 5287 | at::Tensor & reciprocal_::call(at::Tensor & self) { |
| 5288 | |
| 5289 | static auto op = create_reciprocal__typed_handle(); |
| 5290 | return op.call(self); |
| 5291 | } |
| 5292 | |
| 5293 | // aten::reciprocal_(Tensor(a!) self) -> Tensor(a!) |
| 5294 | at::Tensor & reciprocal_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 5295 | |
| 5296 | static auto op = create_reciprocal__typed_handle(); |
| 5297 | return op.redispatch(dispatchKeySet, self); |
| 5298 | } |
| 5299 | |
| 5300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal_out, name, "aten::reciprocal") |
| 5301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal_out, overload_name, "out") |
| 5302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reciprocal_out, schema_str, "reciprocal.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 5303 | |
| 5304 | // aten::reciprocal.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5305 | static C10_NOINLINE c10::TypedOperatorHandle<reciprocal_out::schema> create_reciprocal_out_typed_handle() { |
| 5306 | return c10::Dispatcher::singleton() |
| 5307 | .findSchemaOrThrow(reciprocal_out::name, reciprocal_out::overload_name) |
| 5308 | .typed<reciprocal_out::schema>(); |
| 5309 | } |
| 5310 | |
| 5311 | // aten::reciprocal.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5312 | at::Tensor & reciprocal_out::call(const at::Tensor & self, at::Tensor & out) { |
| 5313 | |
| 5314 | static auto op = create_reciprocal_out_typed_handle(); |
| 5315 | return op.call(self, out); |
| 5316 | } |
| 5317 | |
| 5318 | // aten::reciprocal.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5319 | at::Tensor & reciprocal_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 5320 | |
| 5321 | static auto op = create_reciprocal_out_typed_handle(); |
| 5322 | return op.redispatch(dispatchKeySet, self, out); |
| 5323 | } |
| 5324 | |
| 5325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg, name, "aten::neg") |
| 5326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg, overload_name, "") |
| 5327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg, schema_str, "neg(Tensor self) -> Tensor") |
| 5328 | |
| 5329 | // aten::neg(Tensor self) -> Tensor |
| 5330 | static C10_NOINLINE c10::TypedOperatorHandle<neg::schema> create_neg_typed_handle() { |
| 5331 | return c10::Dispatcher::singleton() |
| 5332 | .findSchemaOrThrow(neg::name, neg::overload_name) |
| 5333 | .typed<neg::schema>(); |
| 5334 | } |
| 5335 | |
| 5336 | // aten::neg(Tensor self) -> Tensor |
| 5337 | at::Tensor neg::call(const at::Tensor & self) { |
| 5338 | |
| 5339 | static auto op = create_neg_typed_handle(); |
| 5340 | return op.call(self); |
| 5341 | } |
| 5342 | |
| 5343 | // aten::neg(Tensor self) -> Tensor |
| 5344 | at::Tensor neg::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5345 | |
| 5346 | static auto op = create_neg_typed_handle(); |
| 5347 | return op.redispatch(dispatchKeySet, self); |
| 5348 | } |
| 5349 | |
| 5350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg_, name, "aten::neg_") |
| 5351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg_, overload_name, "") |
| 5352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg_, schema_str, "neg_(Tensor(a!) self) -> Tensor(a!)") |
| 5353 | |
| 5354 | // aten::neg_(Tensor(a!) self) -> Tensor(a!) |
| 5355 | static C10_NOINLINE c10::TypedOperatorHandle<neg_::schema> create_neg__typed_handle() { |
| 5356 | return c10::Dispatcher::singleton() |
| 5357 | .findSchemaOrThrow(neg_::name, neg_::overload_name) |
| 5358 | .typed<neg_::schema>(); |
| 5359 | } |
| 5360 | |
| 5361 | // aten::neg_(Tensor(a!) self) -> Tensor(a!) |
| 5362 | at::Tensor & neg_::call(at::Tensor & self) { |
| 5363 | |
| 5364 | static auto op = create_neg__typed_handle(); |
| 5365 | return op.call(self); |
| 5366 | } |
| 5367 | |
| 5368 | // aten::neg_(Tensor(a!) self) -> Tensor(a!) |
| 5369 | at::Tensor & neg_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 5370 | |
| 5371 | static auto op = create_neg__typed_handle(); |
| 5372 | return op.redispatch(dispatchKeySet, self); |
| 5373 | } |
| 5374 | |
| 5375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg_out, name, "aten::neg") |
| 5376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg_out, overload_name, "out") |
| 5377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(neg_out, schema_str, "neg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 5378 | |
| 5379 | // aten::neg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5380 | static C10_NOINLINE c10::TypedOperatorHandle<neg_out::schema> create_neg_out_typed_handle() { |
| 5381 | return c10::Dispatcher::singleton() |
| 5382 | .findSchemaOrThrow(neg_out::name, neg_out::overload_name) |
| 5383 | .typed<neg_out::schema>(); |
| 5384 | } |
| 5385 | |
| 5386 | // aten::neg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5387 | at::Tensor & neg_out::call(const at::Tensor & self, at::Tensor & out) { |
| 5388 | |
| 5389 | static auto op = create_neg_out_typed_handle(); |
| 5390 | return op.call(self, out); |
| 5391 | } |
| 5392 | |
| 5393 | // aten::neg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5394 | at::Tensor & neg_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 5395 | |
| 5396 | static auto op = create_neg_out_typed_handle(); |
| 5397 | return op.redispatch(dispatchKeySet, self, out); |
| 5398 | } |
| 5399 | |
| 5400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reshape_as, name, "aten::reshape_as") |
| 5401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reshape_as, overload_name, "") |
| 5402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reshape_as, schema_str, "reshape_as(Tensor(a) self, Tensor other) -> Tensor(a)") |
| 5403 | |
| 5404 | // aten::reshape_as(Tensor(a) self, Tensor other) -> Tensor(a) |
| 5405 | static C10_NOINLINE c10::TypedOperatorHandle<reshape_as::schema> create_reshape_as_typed_handle() { |
| 5406 | return c10::Dispatcher::singleton() |
| 5407 | .findSchemaOrThrow(reshape_as::name, reshape_as::overload_name) |
| 5408 | .typed<reshape_as::schema>(); |
| 5409 | } |
| 5410 | |
| 5411 | // aten::reshape_as(Tensor(a) self, Tensor other) -> Tensor(a) |
| 5412 | at::Tensor reshape_as::call(const at::Tensor & self, const at::Tensor & other) { |
| 5413 | |
| 5414 | static auto op = create_reshape_as_typed_handle(); |
| 5415 | return op.call(self, other); |
| 5416 | } |
| 5417 | |
| 5418 | // aten::reshape_as(Tensor(a) self, Tensor other) -> Tensor(a) |
| 5419 | at::Tensor reshape_as::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 5420 | |
| 5421 | static auto op = create_reshape_as_typed_handle(); |
| 5422 | return op.redispatch(dispatchKeySet, self, other); |
| 5423 | } |
| 5424 | |
| 5425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu, name, "aten::rrelu") |
| 5426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu, overload_name, "") |
| 5427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu, schema_str, "rrelu(Tensor self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor") |
| 5428 | |
| 5429 | // aten::rrelu(Tensor self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor |
| 5430 | static C10_NOINLINE c10::TypedOperatorHandle<rrelu::schema> create_rrelu_typed_handle() { |
| 5431 | return c10::Dispatcher::singleton() |
| 5432 | .findSchemaOrThrow(rrelu::name, rrelu::overload_name) |
| 5433 | .typed<rrelu::schema>(); |
| 5434 | } |
| 5435 | |
| 5436 | // aten::rrelu(Tensor self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor |
| 5437 | at::Tensor rrelu::call(const at::Tensor & self, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
| 5438 | |
| 5439 | static auto op = create_rrelu_typed_handle(); |
| 5440 | return op.call(self, lower, upper, training, generator); |
| 5441 | } |
| 5442 | |
| 5443 | // aten::rrelu(Tensor self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor |
| 5444 | at::Tensor rrelu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
| 5445 | |
| 5446 | static auto op = create_rrelu_typed_handle(); |
| 5447 | return op.redispatch(dispatchKeySet, self, lower, upper, training, generator); |
| 5448 | } |
| 5449 | |
| 5450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_, name, "aten::rrelu_") |
| 5451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_, overload_name, "") |
| 5452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_, schema_str, "rrelu_(Tensor(a!) self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!)") |
| 5453 | |
| 5454 | // aten::rrelu_(Tensor(a!) self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) |
| 5455 | static C10_NOINLINE c10::TypedOperatorHandle<rrelu_::schema> create_rrelu__typed_handle() { |
| 5456 | return c10::Dispatcher::singleton() |
| 5457 | .findSchemaOrThrow(rrelu_::name, rrelu_::overload_name) |
| 5458 | .typed<rrelu_::schema>(); |
| 5459 | } |
| 5460 | |
| 5461 | // aten::rrelu_(Tensor(a!) self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) |
| 5462 | at::Tensor & rrelu_::call(at::Tensor & self, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
| 5463 | |
| 5464 | static auto op = create_rrelu__typed_handle(); |
| 5465 | return op.call(self, lower, upper, training, generator); |
| 5466 | } |
| 5467 | |
| 5468 | // aten::rrelu_(Tensor(a!) self, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) |
| 5469 | at::Tensor & rrelu_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
| 5470 | |
| 5471 | static auto op = create_rrelu__typed_handle(); |
| 5472 | return op.redispatch(dispatchKeySet, self, lower, upper, training, generator); |
| 5473 | } |
| 5474 | |
| 5475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu6, name, "aten::relu6") |
| 5476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu6, overload_name, "") |
| 5477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu6, schema_str, "relu6(Tensor self) -> Tensor") |
| 5478 | |
| 5479 | // aten::relu6(Tensor self) -> Tensor |
| 5480 | static C10_NOINLINE c10::TypedOperatorHandle<relu6::schema> create_relu6_typed_handle() { |
| 5481 | return c10::Dispatcher::singleton() |
| 5482 | .findSchemaOrThrow(relu6::name, relu6::overload_name) |
| 5483 | .typed<relu6::schema>(); |
| 5484 | } |
| 5485 | |
| 5486 | // aten::relu6(Tensor self) -> Tensor |
| 5487 | at::Tensor relu6::call(const at::Tensor & self) { |
| 5488 | |
| 5489 | static auto op = create_relu6_typed_handle(); |
| 5490 | return op.call(self); |
| 5491 | } |
| 5492 | |
| 5493 | // aten::relu6(Tensor self) -> Tensor |
| 5494 | at::Tensor relu6::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5495 | |
| 5496 | static auto op = create_relu6_typed_handle(); |
| 5497 | return op.redispatch(dispatchKeySet, self); |
| 5498 | } |
| 5499 | |
| 5500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu6_, name, "aten::relu6_") |
| 5501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu6_, overload_name, "") |
| 5502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu6_, schema_str, "relu6_(Tensor(a!) self) -> Tensor(a!)") |
| 5503 | |
| 5504 | // aten::relu6_(Tensor(a!) self) -> Tensor(a!) |
| 5505 | static C10_NOINLINE c10::TypedOperatorHandle<relu6_::schema> create_relu6__typed_handle() { |
| 5506 | return c10::Dispatcher::singleton() |
| 5507 | .findSchemaOrThrow(relu6_::name, relu6_::overload_name) |
| 5508 | .typed<relu6_::schema>(); |
| 5509 | } |
| 5510 | |
| 5511 | // aten::relu6_(Tensor(a!) self) -> Tensor(a!) |
| 5512 | at::Tensor & relu6_::call(at::Tensor & self) { |
| 5513 | |
| 5514 | static auto op = create_relu6__typed_handle(); |
| 5515 | return op.call(self); |
| 5516 | } |
| 5517 | |
| 5518 | // aten::relu6_(Tensor(a!) self) -> Tensor(a!) |
| 5519 | at::Tensor & relu6_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 5520 | |
| 5521 | static auto op = create_relu6__typed_handle(); |
| 5522 | return op.redispatch(dispatchKeySet, self); |
| 5523 | } |
| 5524 | |
| 5525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prelu, name, "aten::prelu") |
| 5526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prelu, overload_name, "") |
| 5527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prelu, schema_str, "prelu(Tensor self, Tensor weight) -> Tensor") |
| 5528 | |
| 5529 | // aten::prelu(Tensor self, Tensor weight) -> Tensor |
| 5530 | static C10_NOINLINE c10::TypedOperatorHandle<prelu::schema> create_prelu_typed_handle() { |
| 5531 | return c10::Dispatcher::singleton() |
| 5532 | .findSchemaOrThrow(prelu::name, prelu::overload_name) |
| 5533 | .typed<prelu::schema>(); |
| 5534 | } |
| 5535 | |
| 5536 | // aten::prelu(Tensor self, Tensor weight) -> Tensor |
| 5537 | at::Tensor prelu::call(const at::Tensor & self, const at::Tensor & weight) { |
| 5538 | |
| 5539 | static auto op = create_prelu_typed_handle(); |
| 5540 | return op.call(self, weight); |
| 5541 | } |
| 5542 | |
| 5543 | // aten::prelu(Tensor self, Tensor weight) -> Tensor |
| 5544 | at::Tensor prelu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight) { |
| 5545 | |
| 5546 | static auto op = create_prelu_typed_handle(); |
| 5547 | return op.redispatch(dispatchKeySet, self, weight); |
| 5548 | } |
| 5549 | |
| 5550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_prelu_kernel_backward, name, "aten::_prelu_kernel_backward") |
| 5551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_prelu_kernel_backward, overload_name, "") |
| 5552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_prelu_kernel_backward, schema_str, "_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor)") |
| 5553 | |
| 5554 | // aten::_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) |
| 5555 | static C10_NOINLINE c10::TypedOperatorHandle<_prelu_kernel_backward::schema> create__prelu_kernel_backward_typed_handle() { |
| 5556 | return c10::Dispatcher::singleton() |
| 5557 | .findSchemaOrThrow(_prelu_kernel_backward::name, _prelu_kernel_backward::overload_name) |
| 5558 | .typed<_prelu_kernel_backward::schema>(); |
| 5559 | } |
| 5560 | |
| 5561 | // aten::_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) |
| 5562 | ::std::tuple<at::Tensor,at::Tensor> _prelu_kernel_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight) { |
| 5563 | |
| 5564 | static auto op = create__prelu_kernel_backward_typed_handle(); |
| 5565 | return op.call(grad_output, self, weight); |
| 5566 | } |
| 5567 | |
| 5568 | // aten::_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) |
| 5569 | ::std::tuple<at::Tensor,at::Tensor> _prelu_kernel_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & weight) { |
| 5570 | |
| 5571 | static auto op = create__prelu_kernel_backward_typed_handle(); |
| 5572 | return op.redispatch(dispatchKeySet, grad_output, self, weight); |
| 5573 | } |
| 5574 | |
| 5575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gelu_backward_grad_input, name, "aten::gelu_backward") |
| 5576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gelu_backward_grad_input, overload_name, "grad_input") |
| 5577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gelu_backward_grad_input, schema_str, "gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!)") |
| 5578 | |
| 5579 | // aten::gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!) |
| 5580 | static C10_NOINLINE c10::TypedOperatorHandle<gelu_backward_grad_input::schema> create_gelu_backward_grad_input_typed_handle() { |
| 5581 | return c10::Dispatcher::singleton() |
| 5582 | .findSchemaOrThrow(gelu_backward_grad_input::name, gelu_backward_grad_input::overload_name) |
| 5583 | .typed<gelu_backward_grad_input::schema>(); |
| 5584 | } |
| 5585 | |
| 5586 | // aten::gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!) |
| 5587 | at::Tensor & gelu_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input) { |
| 5588 | |
| 5589 | static auto op = create_gelu_backward_grad_input_typed_handle(); |
| 5590 | return op.call(grad_output, self, approximate, grad_input); |
| 5591 | } |
| 5592 | |
| 5593 | // aten::gelu_backward.grad_input(Tensor grad_output, Tensor self, *, str approximate='none', Tensor(a!) grad_input) -> Tensor(a!) |
| 5594 | at::Tensor & gelu_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate, at::Tensor & grad_input) { |
| 5595 | |
| 5596 | static auto op = create_gelu_backward_grad_input_typed_handle(); |
| 5597 | return op.redispatch(dispatchKeySet, grad_output, self, approximate, grad_input); |
| 5598 | } |
| 5599 | |
| 5600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gelu_backward, name, "aten::gelu_backward") |
| 5601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gelu_backward, overload_name, "") |
| 5602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gelu_backward, schema_str, "gelu_backward(Tensor grad_output, Tensor self, *, str approximate='none') -> Tensor") |
| 5603 | |
| 5604 | // aten::gelu_backward(Tensor grad_output, Tensor self, *, str approximate='none') -> Tensor |
| 5605 | static C10_NOINLINE c10::TypedOperatorHandle<gelu_backward::schema> create_gelu_backward_typed_handle() { |
| 5606 | return c10::Dispatcher::singleton() |
| 5607 | .findSchemaOrThrow(gelu_backward::name, gelu_backward::overload_name) |
| 5608 | .typed<gelu_backward::schema>(); |
| 5609 | } |
| 5610 | |
| 5611 | // aten::gelu_backward(Tensor grad_output, Tensor self, *, str approximate='none') -> Tensor |
| 5612 | at::Tensor gelu_backward::call(const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate) { |
| 5613 | |
| 5614 | static auto op = create_gelu_backward_typed_handle(); |
| 5615 | return op.call(grad_output, self, approximate); |
| 5616 | } |
| 5617 | |
| 5618 | // aten::gelu_backward(Tensor grad_output, Tensor self, *, str approximate='none') -> Tensor |
| 5619 | at::Tensor gelu_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::string_view approximate) { |
| 5620 | |
| 5621 | static auto op = create_gelu_backward_typed_handle(); |
| 5622 | return op.redispatch(dispatchKeySet, grad_output, self, approximate); |
| 5623 | } |
| 5624 | |
| 5625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(selu, name, "aten::selu") |
| 5626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(selu, overload_name, "") |
| 5627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(selu, schema_str, "selu(Tensor self) -> Tensor") |
| 5628 | |
| 5629 | // aten::selu(Tensor self) -> Tensor |
| 5630 | static C10_NOINLINE c10::TypedOperatorHandle<selu::schema> create_selu_typed_handle() { |
| 5631 | return c10::Dispatcher::singleton() |
| 5632 | .findSchemaOrThrow(selu::name, selu::overload_name) |
| 5633 | .typed<selu::schema>(); |
| 5634 | } |
| 5635 | |
| 5636 | // aten::selu(Tensor self) -> Tensor |
| 5637 | at::Tensor selu::call(const at::Tensor & self) { |
| 5638 | |
| 5639 | static auto op = create_selu_typed_handle(); |
| 5640 | return op.call(self); |
| 5641 | } |
| 5642 | |
| 5643 | // aten::selu(Tensor self) -> Tensor |
| 5644 | at::Tensor selu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5645 | |
| 5646 | static auto op = create_selu_typed_handle(); |
| 5647 | return op.redispatch(dispatchKeySet, self); |
| 5648 | } |
| 5649 | |
| 5650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(selu_, name, "aten::selu_") |
| 5651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(selu_, overload_name, "") |
| 5652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(selu_, schema_str, "selu_(Tensor(a!) self) -> Tensor(a!)") |
| 5653 | |
| 5654 | // aten::selu_(Tensor(a!) self) -> Tensor(a!) |
| 5655 | static C10_NOINLINE c10::TypedOperatorHandle<selu_::schema> create_selu__typed_handle() { |
| 5656 | return c10::Dispatcher::singleton() |
| 5657 | .findSchemaOrThrow(selu_::name, selu_::overload_name) |
| 5658 | .typed<selu_::schema>(); |
| 5659 | } |
| 5660 | |
| 5661 | // aten::selu_(Tensor(a!) self) -> Tensor(a!) |
| 5662 | at::Tensor & selu_::call(at::Tensor & self) { |
| 5663 | |
| 5664 | static auto op = create_selu__typed_handle(); |
| 5665 | return op.call(self); |
| 5666 | } |
| 5667 | |
| 5668 | // aten::selu_(Tensor(a!) self) -> Tensor(a!) |
| 5669 | at::Tensor & selu_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 5670 | |
| 5671 | static auto op = create_selu__typed_handle(); |
| 5672 | return op.redispatch(dispatchKeySet, self); |
| 5673 | } |
| 5674 | |
| 5675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(silu_backward_grad_input, name, "aten::silu_backward") |
| 5676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(silu_backward_grad_input, overload_name, "grad_input") |
| 5677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(silu_backward_grad_input, schema_str, "silu_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 5678 | |
| 5679 | // aten::silu_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 5680 | static C10_NOINLINE c10::TypedOperatorHandle<silu_backward_grad_input::schema> create_silu_backward_grad_input_typed_handle() { |
| 5681 | return c10::Dispatcher::singleton() |
| 5682 | .findSchemaOrThrow(silu_backward_grad_input::name, silu_backward_grad_input::overload_name) |
| 5683 | .typed<silu_backward_grad_input::schema>(); |
| 5684 | } |
| 5685 | |
| 5686 | // aten::silu_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 5687 | at::Tensor & silu_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input) { |
| 5688 | |
| 5689 | static auto op = create_silu_backward_grad_input_typed_handle(); |
| 5690 | return op.call(grad_output, self, grad_input); |
| 5691 | } |
| 5692 | |
| 5693 | // aten::silu_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 5694 | at::Tensor & silu_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input) { |
| 5695 | |
| 5696 | static auto op = create_silu_backward_grad_input_typed_handle(); |
| 5697 | return op.redispatch(dispatchKeySet, grad_output, self, grad_input); |
| 5698 | } |
| 5699 | |
| 5700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(silu_backward, name, "aten::silu_backward") |
| 5701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(silu_backward, overload_name, "") |
| 5702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(silu_backward, schema_str, "silu_backward(Tensor grad_output, Tensor self) -> Tensor") |
| 5703 | |
| 5704 | // aten::silu_backward(Tensor grad_output, Tensor self) -> Tensor |
| 5705 | static C10_NOINLINE c10::TypedOperatorHandle<silu_backward::schema> create_silu_backward_typed_handle() { |
| 5706 | return c10::Dispatcher::singleton() |
| 5707 | .findSchemaOrThrow(silu_backward::name, silu_backward::overload_name) |
| 5708 | .typed<silu_backward::schema>(); |
| 5709 | } |
| 5710 | |
| 5711 | // aten::silu_backward(Tensor grad_output, Tensor self) -> Tensor |
| 5712 | at::Tensor silu_backward::call(const at::Tensor & grad_output, const at::Tensor & self) { |
| 5713 | |
| 5714 | static auto op = create_silu_backward_typed_handle(); |
| 5715 | return op.call(grad_output, self); |
| 5716 | } |
| 5717 | |
| 5718 | // aten::silu_backward(Tensor grad_output, Tensor self) -> Tensor |
| 5719 | at::Tensor silu_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self) { |
| 5720 | |
| 5721 | static auto op = create_silu_backward_typed_handle(); |
| 5722 | return op.redispatch(dispatchKeySet, grad_output, self); |
| 5723 | } |
| 5724 | |
| 5725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin, name, "aten::sin") |
| 5726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin, overload_name, "") |
| 5727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin, schema_str, "sin(Tensor self) -> Tensor") |
| 5728 | |
| 5729 | // aten::sin(Tensor self) -> Tensor |
| 5730 | static C10_NOINLINE c10::TypedOperatorHandle<sin::schema> create_sin_typed_handle() { |
| 5731 | return c10::Dispatcher::singleton() |
| 5732 | .findSchemaOrThrow(sin::name, sin::overload_name) |
| 5733 | .typed<sin::schema>(); |
| 5734 | } |
| 5735 | |
| 5736 | // aten::sin(Tensor self) -> Tensor |
| 5737 | at::Tensor sin::call(const at::Tensor & self) { |
| 5738 | |
| 5739 | static auto op = create_sin_typed_handle(); |
| 5740 | return op.call(self); |
| 5741 | } |
| 5742 | |
| 5743 | // aten::sin(Tensor self) -> Tensor |
| 5744 | at::Tensor sin::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5745 | |
| 5746 | static auto op = create_sin_typed_handle(); |
| 5747 | return op.redispatch(dispatchKeySet, self); |
| 5748 | } |
| 5749 | |
| 5750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin_, name, "aten::sin_") |
| 5751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin_, overload_name, "") |
| 5752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin_, schema_str, "sin_(Tensor(a!) self) -> Tensor(a!)") |
| 5753 | |
| 5754 | // aten::sin_(Tensor(a!) self) -> Tensor(a!) |
| 5755 | static C10_NOINLINE c10::TypedOperatorHandle<sin_::schema> create_sin__typed_handle() { |
| 5756 | return c10::Dispatcher::singleton() |
| 5757 | .findSchemaOrThrow(sin_::name, sin_::overload_name) |
| 5758 | .typed<sin_::schema>(); |
| 5759 | } |
| 5760 | |
| 5761 | // aten::sin_(Tensor(a!) self) -> Tensor(a!) |
| 5762 | at::Tensor & sin_::call(at::Tensor & self) { |
| 5763 | |
| 5764 | static auto op = create_sin__typed_handle(); |
| 5765 | return op.call(self); |
| 5766 | } |
| 5767 | |
| 5768 | // aten::sin_(Tensor(a!) self) -> Tensor(a!) |
| 5769 | at::Tensor & sin_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 5770 | |
| 5771 | static auto op = create_sin__typed_handle(); |
| 5772 | return op.redispatch(dispatchKeySet, self); |
| 5773 | } |
| 5774 | |
| 5775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin_out, name, "aten::sin") |
| 5776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin_out, overload_name, "out") |
| 5777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sin_out, schema_str, "sin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 5778 | |
| 5779 | // aten::sin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5780 | static C10_NOINLINE c10::TypedOperatorHandle<sin_out::schema> create_sin_out_typed_handle() { |
| 5781 | return c10::Dispatcher::singleton() |
| 5782 | .findSchemaOrThrow(sin_out::name, sin_out::overload_name) |
| 5783 | .typed<sin_out::schema>(); |
| 5784 | } |
| 5785 | |
| 5786 | // aten::sin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5787 | at::Tensor & sin_out::call(const at::Tensor & self, at::Tensor & out) { |
| 5788 | |
| 5789 | static auto op = create_sin_out_typed_handle(); |
| 5790 | return op.call(self, out); |
| 5791 | } |
| 5792 | |
| 5793 | // aten::sin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 5794 | at::Tensor & sin_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 5795 | |
| 5796 | static auto op = create_sin_out_typed_handle(); |
| 5797 | return op.redispatch(dispatchKeySet, self, out); |
| 5798 | } |
| 5799 | |
| 5800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_scatter, name, "aten::diagonal_scatter") |
| 5801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_scatter, overload_name, "") |
| 5802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_scatter, schema_str, "diagonal_scatter(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1) -> Tensor") |
| 5803 | |
| 5804 | // aten::diagonal_scatter(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1) -> Tensor |
| 5805 | static C10_NOINLINE c10::TypedOperatorHandle<diagonal_scatter::schema> create_diagonal_scatter_typed_handle() { |
| 5806 | return c10::Dispatcher::singleton() |
| 5807 | .findSchemaOrThrow(diagonal_scatter::name, diagonal_scatter::overload_name) |
| 5808 | .typed<diagonal_scatter::schema>(); |
| 5809 | } |
| 5810 | |
| 5811 | // aten::diagonal_scatter(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1) -> Tensor |
| 5812 | at::Tensor diagonal_scatter::call(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2) { |
| 5813 | |
| 5814 | static auto op = create_diagonal_scatter_typed_handle(); |
| 5815 | return op.call(self, src, offset, dim1, dim2); |
| 5816 | } |
| 5817 | |
| 5818 | // aten::diagonal_scatter(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1) -> Tensor |
| 5819 | at::Tensor diagonal_scatter::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2) { |
| 5820 | |
| 5821 | static auto op = create_diagonal_scatter_typed_handle(); |
| 5822 | return op.redispatch(dispatchKeySet, self, src, offset, dim1, dim2); |
| 5823 | } |
| 5824 | |
| 5825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_scatter, name, "aten::as_strided_scatter") |
| 5826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_scatter, overload_name, "") |
| 5827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_scatter, schema_str, "as_strided_scatter(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor") |
| 5828 | |
| 5829 | // aten::as_strided_scatter(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor |
| 5830 | static C10_NOINLINE c10::TypedOperatorHandle<as_strided_scatter::schema> create_as_strided_scatter_typed_handle() { |
| 5831 | return c10::Dispatcher::singleton() |
| 5832 | .findSchemaOrThrow(as_strided_scatter::name, as_strided_scatter::overload_name) |
| 5833 | .typed<as_strided_scatter::schema>(); |
| 5834 | } |
| 5835 | |
| 5836 | // aten::as_strided_scatter(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor |
| 5837 | at::Tensor as_strided_scatter::call(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset) { |
| 5838 | |
| 5839 | static auto op = create_as_strided_scatter_typed_handle(); |
| 5840 | return op.call(self, src, size, stride, storage_offset); |
| 5841 | } |
| 5842 | |
| 5843 | // aten::as_strided_scatter(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None) -> Tensor |
| 5844 | at::Tensor as_strided_scatter::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset) { |
| 5845 | |
| 5846 | static auto op = create_as_strided_scatter_typed_handle(); |
| 5847 | return op.redispatch(dispatchKeySet, self, src, size, stride, storage_offset); |
| 5848 | } |
| 5849 | |
| 5850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_Tensor, name, "aten::split") |
| 5851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_Tensor, overload_name, "Tensor") |
| 5852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_Tensor, schema_str, "split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[]") |
| 5853 | |
| 5854 | // aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] |
| 5855 | static C10_NOINLINE c10::TypedOperatorHandle<split_Tensor::schema> create_split_Tensor_typed_handle() { |
| 5856 | return c10::Dispatcher::singleton() |
| 5857 | .findSchemaOrThrow(split_Tensor::name, split_Tensor::overload_name) |
| 5858 | .typed<split_Tensor::schema>(); |
| 5859 | } |
| 5860 | |
| 5861 | // aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] |
| 5862 | ::std::vector<at::Tensor> split_Tensor::call(const at::Tensor & self, c10::SymInt split_size, int64_t dim) { |
| 5863 | |
| 5864 | static auto op = create_split_Tensor_typed_handle(); |
| 5865 | return op.call(self, split_size, dim); |
| 5866 | } |
| 5867 | |
| 5868 | // aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] |
| 5869 | ::std::vector<at::Tensor> split_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt split_size, int64_t dim) { |
| 5870 | |
| 5871 | static auto op = create_split_Tensor_typed_handle(); |
| 5872 | return op.redispatch(dispatchKeySet, self, split_size, dim); |
| 5873 | } |
| 5874 | |
| 5875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_sizes, name, "aten::split") |
| 5876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_sizes, overload_name, "sizes") |
| 5877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_sizes, schema_str, "split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[]") |
| 5878 | |
| 5879 | // aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] |
| 5880 | static C10_NOINLINE c10::TypedOperatorHandle<split_sizes::schema> create_split_sizes_typed_handle() { |
| 5881 | return c10::Dispatcher::singleton() |
| 5882 | .findSchemaOrThrow(split_sizes::name, split_sizes::overload_name) |
| 5883 | .typed<split_sizes::schema>(); |
| 5884 | } |
| 5885 | |
| 5886 | // aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] |
| 5887 | ::std::vector<at::Tensor> split_sizes::call(const at::Tensor & self, c10::SymIntArrayRef split_size, int64_t dim) { |
| 5888 | |
| 5889 | static auto op = create_split_sizes_typed_handle(); |
| 5890 | return op.call(self, split_size, dim); |
| 5891 | } |
| 5892 | |
| 5893 | // aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] |
| 5894 | ::std::vector<at::Tensor> split_sizes::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_size, int64_t dim) { |
| 5895 | |
| 5896 | static auto op = create_split_sizes_typed_handle(); |
| 5897 | return op.redispatch(dispatchKeySet, self, split_size, dim); |
| 5898 | } |
| 5899 | |
| 5900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze, name, "aten::squeeze") |
| 5901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze, overload_name, "") |
| 5902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze, schema_str, "squeeze(Tensor(a) self) -> Tensor(a)") |
| 5903 | |
| 5904 | // aten::squeeze(Tensor(a) self) -> Tensor(a) |
| 5905 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze::schema> create_squeeze_typed_handle() { |
| 5906 | return c10::Dispatcher::singleton() |
| 5907 | .findSchemaOrThrow(squeeze::name, squeeze::overload_name) |
| 5908 | .typed<squeeze::schema>(); |
| 5909 | } |
| 5910 | |
| 5911 | // aten::squeeze(Tensor(a) self) -> Tensor(a) |
| 5912 | at::Tensor squeeze::call(const at::Tensor & self) { |
| 5913 | |
| 5914 | static auto op = create_squeeze_typed_handle(); |
| 5915 | return op.call(self); |
| 5916 | } |
| 5917 | |
| 5918 | // aten::squeeze(Tensor(a) self) -> Tensor(a) |
| 5919 | at::Tensor squeeze::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5920 | |
| 5921 | static auto op = create_squeeze_typed_handle(); |
| 5922 | return op.redispatch(dispatchKeySet, self); |
| 5923 | } |
| 5924 | |
| 5925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dim, name, "aten::squeeze") |
| 5926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dim, overload_name, "dim") |
| 5927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dim, schema_str, "squeeze.dim(Tensor(a) self, int dim) -> Tensor(a)") |
| 5928 | |
| 5929 | // aten::squeeze.dim(Tensor(a) self, int dim) -> Tensor(a) |
| 5930 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze_dim::schema> create_squeeze_dim_typed_handle() { |
| 5931 | return c10::Dispatcher::singleton() |
| 5932 | .findSchemaOrThrow(squeeze_dim::name, squeeze_dim::overload_name) |
| 5933 | .typed<squeeze_dim::schema>(); |
| 5934 | } |
| 5935 | |
| 5936 | // aten::squeeze.dim(Tensor(a) self, int dim) -> Tensor(a) |
| 5937 | at::Tensor squeeze_dim::call(const at::Tensor & self, int64_t dim) { |
| 5938 | |
| 5939 | static auto op = create_squeeze_dim_typed_handle(); |
| 5940 | return op.call(self, dim); |
| 5941 | } |
| 5942 | |
| 5943 | // aten::squeeze.dim(Tensor(a) self, int dim) -> Tensor(a) |
| 5944 | at::Tensor squeeze_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim) { |
| 5945 | |
| 5946 | static auto op = create_squeeze_dim_typed_handle(); |
| 5947 | return op.redispatch(dispatchKeySet, self, dim); |
| 5948 | } |
| 5949 | |
| 5950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dimname, name, "aten::squeeze") |
| 5951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dimname, overload_name, "dimname") |
| 5952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dimname, schema_str, "squeeze.dimname(Tensor(a) self, Dimname dim) -> Tensor(a)") |
| 5953 | |
| 5954 | // aten::squeeze.dimname(Tensor(a) self, Dimname dim) -> Tensor(a) |
| 5955 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze_dimname::schema> create_squeeze_dimname_typed_handle() { |
| 5956 | return c10::Dispatcher::singleton() |
| 5957 | .findSchemaOrThrow(squeeze_dimname::name, squeeze_dimname::overload_name) |
| 5958 | .typed<squeeze_dimname::schema>(); |
| 5959 | } |
| 5960 | |
| 5961 | // aten::squeeze.dimname(Tensor(a) self, Dimname dim) -> Tensor(a) |
| 5962 | at::Tensor squeeze_dimname::call(const at::Tensor & self, at::Dimname dim) { |
| 5963 | |
| 5964 | static auto op = create_squeeze_dimname_typed_handle(); |
| 5965 | return op.call(self, dim); |
| 5966 | } |
| 5967 | |
| 5968 | // aten::squeeze.dimname(Tensor(a) self, Dimname dim) -> Tensor(a) |
| 5969 | at::Tensor squeeze_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim) { |
| 5970 | |
| 5971 | static auto op = create_squeeze_dimname_typed_handle(); |
| 5972 | return op.redispatch(dispatchKeySet, self, dim); |
| 5973 | } |
| 5974 | |
| 5975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dims, name, "aten::squeeze") |
| 5976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dims, overload_name, "dims") |
| 5977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_dims, schema_str, "squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a)") |
| 5978 | |
| 5979 | // aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a) |
| 5980 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze_dims::schema> create_squeeze_dims_typed_handle() { |
| 5981 | return c10::Dispatcher::singleton() |
| 5982 | .findSchemaOrThrow(squeeze_dims::name, squeeze_dims::overload_name) |
| 5983 | .typed<squeeze_dims::schema>(); |
| 5984 | } |
| 5985 | |
| 5986 | // aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a) |
| 5987 | at::Tensor squeeze_dims::call(const at::Tensor & self, at::IntArrayRef dim) { |
| 5988 | |
| 5989 | static auto op = create_squeeze_dims_typed_handle(); |
| 5990 | return op.call(self, dim); |
| 5991 | } |
| 5992 | |
| 5993 | // aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a) |
| 5994 | at::Tensor squeeze_dims::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim) { |
| 5995 | |
| 5996 | static auto op = create_squeeze_dims_typed_handle(); |
| 5997 | return op.redispatch(dispatchKeySet, self, dim); |
| 5998 | } |
| 5999 | |
| 6000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_, name, "aten::squeeze_") |
| 6001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_, overload_name, "") |
| 6002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze_, schema_str, "squeeze_(Tensor(a!) self) -> Tensor(a!)") |
| 6003 | |
| 6004 | // aten::squeeze_(Tensor(a!) self) -> Tensor(a!) |
| 6005 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze_::schema> create_squeeze__typed_handle() { |
| 6006 | return c10::Dispatcher::singleton() |
| 6007 | .findSchemaOrThrow(squeeze_::name, squeeze_::overload_name) |
| 6008 | .typed<squeeze_::schema>(); |
| 6009 | } |
| 6010 | |
| 6011 | // aten::squeeze_(Tensor(a!) self) -> Tensor(a!) |
| 6012 | at::Tensor & squeeze_::call(at::Tensor & self) { |
| 6013 | |
| 6014 | static auto op = create_squeeze__typed_handle(); |
| 6015 | return op.call(self); |
| 6016 | } |
| 6017 | |
| 6018 | // aten::squeeze_(Tensor(a!) self) -> Tensor(a!) |
| 6019 | at::Tensor & squeeze_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 6020 | |
| 6021 | static auto op = create_squeeze__typed_handle(); |
| 6022 | return op.redispatch(dispatchKeySet, self); |
| 6023 | } |
| 6024 | |
| 6025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dim, name, "aten::squeeze_") |
| 6026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dim, overload_name, "dim") |
| 6027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dim, schema_str, "squeeze_.dim(Tensor(a!) self, int dim) -> Tensor(a!)") |
| 6028 | |
| 6029 | // aten::squeeze_.dim(Tensor(a!) self, int dim) -> Tensor(a!) |
| 6030 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze__dim::schema> create_squeeze__dim_typed_handle() { |
| 6031 | return c10::Dispatcher::singleton() |
| 6032 | .findSchemaOrThrow(squeeze__dim::name, squeeze__dim::overload_name) |
| 6033 | .typed<squeeze__dim::schema>(); |
| 6034 | } |
| 6035 | |
| 6036 | // aten::squeeze_.dim(Tensor(a!) self, int dim) -> Tensor(a!) |
| 6037 | at::Tensor & squeeze__dim::call(at::Tensor & self, int64_t dim) { |
| 6038 | |
| 6039 | static auto op = create_squeeze__dim_typed_handle(); |
| 6040 | return op.call(self, dim); |
| 6041 | } |
| 6042 | |
| 6043 | // aten::squeeze_.dim(Tensor(a!) self, int dim) -> Tensor(a!) |
| 6044 | at::Tensor & squeeze__dim::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim) { |
| 6045 | |
| 6046 | static auto op = create_squeeze__dim_typed_handle(); |
| 6047 | return op.redispatch(dispatchKeySet, self, dim); |
| 6048 | } |
| 6049 | |
| 6050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dims, name, "aten::squeeze_") |
| 6051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dims, overload_name, "dims") |
| 6052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dims, schema_str, "squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!)") |
| 6053 | |
| 6054 | // aten::squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!) |
| 6055 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze__dims::schema> create_squeeze__dims_typed_handle() { |
| 6056 | return c10::Dispatcher::singleton() |
| 6057 | .findSchemaOrThrow(squeeze__dims::name, squeeze__dims::overload_name) |
| 6058 | .typed<squeeze__dims::schema>(); |
| 6059 | } |
| 6060 | |
| 6061 | // aten::squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!) |
| 6062 | at::Tensor & squeeze__dims::call(at::Tensor & self, at::IntArrayRef dim) { |
| 6063 | |
| 6064 | static auto op = create_squeeze__dims_typed_handle(); |
| 6065 | return op.call(self, dim); |
| 6066 | } |
| 6067 | |
| 6068 | // aten::squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!) |
| 6069 | at::Tensor & squeeze__dims::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::IntArrayRef dim) { |
| 6070 | |
| 6071 | static auto op = create_squeeze__dims_typed_handle(); |
| 6072 | return op.redispatch(dispatchKeySet, self, dim); |
| 6073 | } |
| 6074 | |
| 6075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dimname, name, "aten::squeeze_") |
| 6076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dimname, overload_name, "dimname") |
| 6077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(squeeze__dimname, schema_str, "squeeze_.dimname(Tensor(a!) self, Dimname dim) -> Tensor(a!)") |
| 6078 | |
| 6079 | // aten::squeeze_.dimname(Tensor(a!) self, Dimname dim) -> Tensor(a!) |
| 6080 | static C10_NOINLINE c10::TypedOperatorHandle<squeeze__dimname::schema> create_squeeze__dimname_typed_handle() { |
| 6081 | return c10::Dispatcher::singleton() |
| 6082 | .findSchemaOrThrow(squeeze__dimname::name, squeeze__dimname::overload_name) |
| 6083 | .typed<squeeze__dimname::schema>(); |
| 6084 | } |
| 6085 | |
| 6086 | // aten::squeeze_.dimname(Tensor(a!) self, Dimname dim) -> Tensor(a!) |
| 6087 | at::Tensor & squeeze__dimname::call(at::Tensor & self, at::Dimname dim) { |
| 6088 | |
| 6089 | static auto op = create_squeeze__dimname_typed_handle(); |
| 6090 | return op.call(self, dim); |
| 6091 | } |
| 6092 | |
| 6093 | // aten::squeeze_.dimname(Tensor(a!) self, Dimname dim) -> Tensor(a!) |
| 6094 | at::Tensor & squeeze__dimname::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Dimname dim) { |
| 6095 | |
| 6096 | static auto op = create_squeeze__dimname_typed_handle(); |
| 6097 | return op.redispatch(dispatchKeySet, self, dim); |
| 6098 | } |
| 6099 | |
| 6100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sspaddmm, name, "aten::sspaddmm") |
| 6101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sspaddmm, overload_name, "") |
| 6102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sspaddmm, schema_str, "sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor") |
| 6103 | |
| 6104 | // aten::sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6105 | static C10_NOINLINE c10::TypedOperatorHandle<sspaddmm::schema> create_sspaddmm_typed_handle() { |
| 6106 | return c10::Dispatcher::singleton() |
| 6107 | .findSchemaOrThrow(sspaddmm::name, sspaddmm::overload_name) |
| 6108 | .typed<sspaddmm::schema>(); |
| 6109 | } |
| 6110 | |
| 6111 | // aten::sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6112 | at::Tensor sspaddmm::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6113 | |
| 6114 | static auto op = create_sspaddmm_typed_handle(); |
| 6115 | return op.call(self, mat1, mat2, beta, alpha); |
| 6116 | } |
| 6117 | |
| 6118 | // aten::sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6119 | at::Tensor sspaddmm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6120 | |
| 6121 | static auto op = create_sspaddmm_typed_handle(); |
| 6122 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha); |
| 6123 | } |
| 6124 | |
| 6125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sspaddmm_out, name, "aten::sspaddmm") |
| 6126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sspaddmm_out, overload_name, "out") |
| 6127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sspaddmm_out, schema_str, "sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") |
| 6128 | |
| 6129 | // aten::sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6130 | static C10_NOINLINE c10::TypedOperatorHandle<sspaddmm_out::schema> create_sspaddmm_out_typed_handle() { |
| 6131 | return c10::Dispatcher::singleton() |
| 6132 | .findSchemaOrThrow(sspaddmm_out::name, sspaddmm_out::overload_name) |
| 6133 | .typed<sspaddmm_out::schema>(); |
| 6134 | } |
| 6135 | |
| 6136 | // aten::sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6137 | at::Tensor & sspaddmm_out::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
| 6138 | |
| 6139 | static auto op = create_sspaddmm_out_typed_handle(); |
| 6140 | return op.call(self, mat1, mat2, beta, alpha, out); |
| 6141 | } |
| 6142 | |
| 6143 | // aten::sspaddmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6144 | at::Tensor & sspaddmm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
| 6145 | |
| 6146 | static auto op = create_sspaddmm_out_typed_handle(); |
| 6147 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha, out); |
| 6148 | } |
| 6149 | |
| 6150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(stride_int, name, "aten::stride") |
| 6151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(stride_int, overload_name, "int") |
| 6152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(stride_int, schema_str, "stride.int(Tensor self, int dim) -> int") |
| 6153 | |
| 6154 | // aten::stride.int(Tensor self, int dim) -> int |
| 6155 | static C10_NOINLINE c10::TypedOperatorHandle<stride_int::schema> create_stride_int_typed_handle() { |
| 6156 | return c10::Dispatcher::singleton() |
| 6157 | .findSchemaOrThrow(stride_int::name, stride_int::overload_name) |
| 6158 | .typed<stride_int::schema>(); |
| 6159 | } |
| 6160 | |
| 6161 | // aten::stride.int(Tensor self, int dim) -> int |
| 6162 | int64_t stride_int::call(const at::Tensor & self, int64_t dim) { |
| 6163 | |
| 6164 | static auto op = create_stride_int_typed_handle(); |
| 6165 | return op.call(self, dim); |
| 6166 | } |
| 6167 | |
| 6168 | // aten::stride.int(Tensor self, int dim) -> int |
| 6169 | int64_t stride_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim) { |
| 6170 | |
| 6171 | static auto op = create_stride_int_typed_handle(); |
| 6172 | return op.redispatch(dispatchKeySet, self, dim); |
| 6173 | } |
| 6174 | |
| 6175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(stride_Dimname, name, "aten::stride") |
| 6176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(stride_Dimname, overload_name, "Dimname") |
| 6177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(stride_Dimname, schema_str, "stride.Dimname(Tensor self, Dimname dim) -> int") |
| 6178 | |
| 6179 | // aten::stride.Dimname(Tensor self, Dimname dim) -> int |
| 6180 | static C10_NOINLINE c10::TypedOperatorHandle<stride_Dimname::schema> create_stride_Dimname_typed_handle() { |
| 6181 | return c10::Dispatcher::singleton() |
| 6182 | .findSchemaOrThrow(stride_Dimname::name, stride_Dimname::overload_name) |
| 6183 | .typed<stride_Dimname::schema>(); |
| 6184 | } |
| 6185 | |
| 6186 | // aten::stride.Dimname(Tensor self, Dimname dim) -> int |
| 6187 | int64_t stride_Dimname::call(const at::Tensor & self, at::Dimname dim) { |
| 6188 | |
| 6189 | static auto op = create_stride_Dimname_typed_handle(); |
| 6190 | return op.call(self, dim); |
| 6191 | } |
| 6192 | |
| 6193 | // aten::stride.Dimname(Tensor self, Dimname dim) -> int |
| 6194 | int64_t stride_Dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim) { |
| 6195 | |
| 6196 | static auto op = create_stride_Dimname_typed_handle(); |
| 6197 | return op.redispatch(dispatchKeySet, self, dim); |
| 6198 | } |
| 6199 | |
| 6200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(threshold_backward_grad_input, name, "aten::threshold_backward") |
| 6201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(threshold_backward_grad_input, overload_name, "grad_input") |
| 6202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(threshold_backward_grad_input, schema_str, "threshold_backward.grad_input(Tensor grad_output, Tensor self, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 6203 | |
| 6204 | // aten::threshold_backward.grad_input(Tensor grad_output, Tensor self, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 6205 | static C10_NOINLINE c10::TypedOperatorHandle<threshold_backward_grad_input::schema> create_threshold_backward_grad_input_typed_handle() { |
| 6206 | return c10::Dispatcher::singleton() |
| 6207 | .findSchemaOrThrow(threshold_backward_grad_input::name, threshold_backward_grad_input::overload_name) |
| 6208 | .typed<threshold_backward_grad_input::schema>(); |
| 6209 | } |
| 6210 | |
| 6211 | // aten::threshold_backward.grad_input(Tensor grad_output, Tensor self, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 6212 | at::Tensor & threshold_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold, at::Tensor & grad_input) { |
| 6213 | |
| 6214 | static auto op = create_threshold_backward_grad_input_typed_handle(); |
| 6215 | return op.call(grad_output, self, threshold, grad_input); |
| 6216 | } |
| 6217 | |
| 6218 | // aten::threshold_backward.grad_input(Tensor grad_output, Tensor self, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 6219 | at::Tensor & threshold_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold, at::Tensor & grad_input) { |
| 6220 | |
| 6221 | static auto op = create_threshold_backward_grad_input_typed_handle(); |
| 6222 | return op.redispatch(dispatchKeySet, grad_output, self, threshold, grad_input); |
| 6223 | } |
| 6224 | |
| 6225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(threshold_backward, name, "aten::threshold_backward") |
| 6226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(threshold_backward, overload_name, "") |
| 6227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(threshold_backward, schema_str, "threshold_backward(Tensor grad_output, Tensor self, Scalar threshold) -> Tensor") |
| 6228 | |
| 6229 | // aten::threshold_backward(Tensor grad_output, Tensor self, Scalar threshold) -> Tensor |
| 6230 | static C10_NOINLINE c10::TypedOperatorHandle<threshold_backward::schema> create_threshold_backward_typed_handle() { |
| 6231 | return c10::Dispatcher::singleton() |
| 6232 | .findSchemaOrThrow(threshold_backward::name, threshold_backward::overload_name) |
| 6233 | .typed<threshold_backward::schema>(); |
| 6234 | } |
| 6235 | |
| 6236 | // aten::threshold_backward(Tensor grad_output, Tensor self, Scalar threshold) -> Tensor |
| 6237 | at::Tensor threshold_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold) { |
| 6238 | |
| 6239 | static auto op = create_threshold_backward_typed_handle(); |
| 6240 | return op.call(grad_output, self, threshold); |
| 6241 | } |
| 6242 | |
| 6243 | // aten::threshold_backward(Tensor grad_output, Tensor self, Scalar threshold) -> Tensor |
| 6244 | at::Tensor threshold_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & threshold) { |
| 6245 | |
| 6246 | static auto op = create_threshold_backward_typed_handle(); |
| 6247 | return op.redispatch(dispatchKeySet, grad_output, self, threshold); |
| 6248 | } |
| 6249 | |
| 6250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(one_hot, name, "aten::one_hot") |
| 6251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(one_hot, overload_name, "") |
| 6252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(one_hot, schema_str, "one_hot(Tensor self, int num_classes=-1) -> Tensor") |
| 6253 | |
| 6254 | // aten::one_hot(Tensor self, int num_classes=-1) -> Tensor |
| 6255 | static C10_NOINLINE c10::TypedOperatorHandle<one_hot::schema> create_one_hot_typed_handle() { |
| 6256 | return c10::Dispatcher::singleton() |
| 6257 | .findSchemaOrThrow(one_hot::name, one_hot::overload_name) |
| 6258 | .typed<one_hot::schema>(); |
| 6259 | } |
| 6260 | |
| 6261 | // aten::one_hot(Tensor self, int num_classes=-1) -> Tensor |
| 6262 | at::Tensor one_hot::call(const at::Tensor & self, int64_t num_classes) { |
| 6263 | |
| 6264 | static auto op = create_one_hot_typed_handle(); |
| 6265 | return op.call(self, num_classes); |
| 6266 | } |
| 6267 | |
| 6268 | // aten::one_hot(Tensor self, int num_classes=-1) -> Tensor |
| 6269 | at::Tensor one_hot::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t num_classes) { |
| 6270 | |
| 6271 | static auto op = create_one_hot_typed_handle(); |
| 6272 | return op.redispatch(dispatchKeySet, self, num_classes); |
| 6273 | } |
| 6274 | |
| 6275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_transform_bias_rescale_qkv, name, "aten::_transform_bias_rescale_qkv") |
| 6276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_transform_bias_rescale_qkv, overload_name, "") |
| 6277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_transform_bias_rescale_qkv, schema_str, "_transform_bias_rescale_qkv(Tensor qkv, Tensor qkv_bias, int num_heads) -> (Tensor, Tensor, Tensor)") |
| 6278 | |
| 6279 | // aten::_transform_bias_rescale_qkv(Tensor qkv, Tensor qkv_bias, int num_heads) -> (Tensor, Tensor, Tensor) |
| 6280 | static C10_NOINLINE c10::TypedOperatorHandle<_transform_bias_rescale_qkv::schema> create__transform_bias_rescale_qkv_typed_handle() { |
| 6281 | return c10::Dispatcher::singleton() |
| 6282 | .findSchemaOrThrow(_transform_bias_rescale_qkv::name, _transform_bias_rescale_qkv::overload_name) |
| 6283 | .typed<_transform_bias_rescale_qkv::schema>(); |
| 6284 | } |
| 6285 | |
| 6286 | // aten::_transform_bias_rescale_qkv(Tensor qkv, Tensor qkv_bias, int num_heads) -> (Tensor, Tensor, Tensor) |
| 6287 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _transform_bias_rescale_qkv::call(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads) { |
| 6288 | |
| 6289 | static auto op = create__transform_bias_rescale_qkv_typed_handle(); |
| 6290 | return op.call(qkv, qkv_bias, num_heads); |
| 6291 | } |
| 6292 | |
| 6293 | // aten::_transform_bias_rescale_qkv(Tensor qkv, Tensor qkv_bias, int num_heads) -> (Tensor, Tensor, Tensor) |
| 6294 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _transform_bias_rescale_qkv::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads) { |
| 6295 | |
| 6296 | static auto op = create__transform_bias_rescale_qkv_typed_handle(); |
| 6297 | return op.redispatch(dispatchKeySet, qkv, qkv_bias, num_heads); |
| 6298 | } |
| 6299 | |
| 6300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unique, name, "aten::_unique") |
| 6301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unique, overload_name, "") |
| 6302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unique, schema_str, "_unique(Tensor self, bool sorted=True, bool return_inverse=False) -> (Tensor, Tensor)") |
| 6303 | |
| 6304 | // aten::_unique(Tensor self, bool sorted=True, bool return_inverse=False) -> (Tensor, Tensor) |
| 6305 | static C10_NOINLINE c10::TypedOperatorHandle<_unique::schema> create__unique_typed_handle() { |
| 6306 | return c10::Dispatcher::singleton() |
| 6307 | .findSchemaOrThrow(_unique::name, _unique::overload_name) |
| 6308 | .typed<_unique::schema>(); |
| 6309 | } |
| 6310 | |
| 6311 | // aten::_unique(Tensor self, bool sorted=True, bool return_inverse=False) -> (Tensor, Tensor) |
| 6312 | ::std::tuple<at::Tensor,at::Tensor> _unique::call(const at::Tensor & self, bool sorted, bool return_inverse) { |
| 6313 | |
| 6314 | static auto op = create__unique_typed_handle(); |
| 6315 | return op.call(self, sorted, return_inverse); |
| 6316 | } |
| 6317 | |
| 6318 | // aten::_unique(Tensor self, bool sorted=True, bool return_inverse=False) -> (Tensor, Tensor) |
| 6319 | ::std::tuple<at::Tensor,at::Tensor> _unique::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool sorted, bool return_inverse) { |
| 6320 | |
| 6321 | static auto op = create__unique_typed_handle(); |
| 6322 | return op.redispatch(dispatchKeySet, self, sorted, return_inverse); |
| 6323 | } |
| 6324 | |
| 6325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_self, name, "aten::where") |
| 6326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_self, overload_name, "self") |
| 6327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_self, schema_str, "where.self(Tensor condition, Tensor self, Tensor other) -> Tensor") |
| 6328 | |
| 6329 | // aten::where.self(Tensor condition, Tensor self, Tensor other) -> Tensor |
| 6330 | static C10_NOINLINE c10::TypedOperatorHandle<where_self::schema> create_where_self_typed_handle() { |
| 6331 | return c10::Dispatcher::singleton() |
| 6332 | .findSchemaOrThrow(where_self::name, where_self::overload_name) |
| 6333 | .typed<where_self::schema>(); |
| 6334 | } |
| 6335 | |
| 6336 | // aten::where.self(Tensor condition, Tensor self, Tensor other) -> Tensor |
| 6337 | at::Tensor where_self::call(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other) { |
| 6338 | |
| 6339 | static auto op = create_where_self_typed_handle(); |
| 6340 | return op.call(condition, self, other); |
| 6341 | } |
| 6342 | |
| 6343 | // aten::where.self(Tensor condition, Tensor self, Tensor other) -> Tensor |
| 6344 | at::Tensor where_self::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other) { |
| 6345 | |
| 6346 | static auto op = create_where_self_typed_handle(); |
| 6347 | return op.redispatch(dispatchKeySet, condition, self, other); |
| 6348 | } |
| 6349 | |
| 6350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_self_out, name, "aten::where") |
| 6351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_self_out, overload_name, "self_out") |
| 6352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_self_out, schema_str, "where.self_out(Tensor condition, Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 6353 | |
| 6354 | // aten::where.self_out(Tensor condition, Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6355 | static C10_NOINLINE c10::TypedOperatorHandle<where_self_out::schema> create_where_self_out_typed_handle() { |
| 6356 | return c10::Dispatcher::singleton() |
| 6357 | .findSchemaOrThrow(where_self_out::name, where_self_out::overload_name) |
| 6358 | .typed<where_self_out::schema>(); |
| 6359 | } |
| 6360 | |
| 6361 | // aten::where.self_out(Tensor condition, Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6362 | at::Tensor & where_self_out::call(const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 6363 | |
| 6364 | static auto op = create_where_self_out_typed_handle(); |
| 6365 | return op.call(condition, self, other, out); |
| 6366 | } |
| 6367 | |
| 6368 | // aten::where.self_out(Tensor condition, Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6369 | at::Tensor & where_self_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 6370 | |
| 6371 | static auto op = create_where_self_out_typed_handle(); |
| 6372 | return op.redispatch(dispatchKeySet, condition, self, other, out); |
| 6373 | } |
| 6374 | |
| 6375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_ScalarSelf, name, "aten::where") |
| 6376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_ScalarSelf, overload_name, "ScalarSelf") |
| 6377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_ScalarSelf, schema_str, "where.ScalarSelf(Tensor condition, Scalar self, Tensor other) -> Tensor") |
| 6378 | |
| 6379 | // aten::where.ScalarSelf(Tensor condition, Scalar self, Tensor other) -> Tensor |
| 6380 | static C10_NOINLINE c10::TypedOperatorHandle<where_ScalarSelf::schema> create_where_ScalarSelf_typed_handle() { |
| 6381 | return c10::Dispatcher::singleton() |
| 6382 | .findSchemaOrThrow(where_ScalarSelf::name, where_ScalarSelf::overload_name) |
| 6383 | .typed<where_ScalarSelf::schema>(); |
| 6384 | } |
| 6385 | |
| 6386 | // aten::where.ScalarSelf(Tensor condition, Scalar self, Tensor other) -> Tensor |
| 6387 | at::Tensor where_ScalarSelf::call(const at::Tensor & condition, const at::Scalar & self, const at::Tensor & other) { |
| 6388 | |
| 6389 | static auto op = create_where_ScalarSelf_typed_handle(); |
| 6390 | return op.call(condition, self, other); |
| 6391 | } |
| 6392 | |
| 6393 | // aten::where.ScalarSelf(Tensor condition, Scalar self, Tensor other) -> Tensor |
| 6394 | at::Tensor where_ScalarSelf::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Scalar & self, const at::Tensor & other) { |
| 6395 | |
| 6396 | static auto op = create_where_ScalarSelf_typed_handle(); |
| 6397 | return op.redispatch(dispatchKeySet, condition, self, other); |
| 6398 | } |
| 6399 | |
| 6400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_ScalarOther, name, "aten::where") |
| 6401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_ScalarOther, overload_name, "ScalarOther") |
| 6402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_ScalarOther, schema_str, "where.ScalarOther(Tensor condition, Tensor self, Scalar other) -> Tensor") |
| 6403 | |
| 6404 | // aten::where.ScalarOther(Tensor condition, Tensor self, Scalar other) -> Tensor |
| 6405 | static C10_NOINLINE c10::TypedOperatorHandle<where_ScalarOther::schema> create_where_ScalarOther_typed_handle() { |
| 6406 | return c10::Dispatcher::singleton() |
| 6407 | .findSchemaOrThrow(where_ScalarOther::name, where_ScalarOther::overload_name) |
| 6408 | .typed<where_ScalarOther::schema>(); |
| 6409 | } |
| 6410 | |
| 6411 | // aten::where.ScalarOther(Tensor condition, Tensor self, Scalar other) -> Tensor |
| 6412 | at::Tensor where_ScalarOther::call(const at::Tensor & condition, const at::Tensor & self, const at::Scalar & other) { |
| 6413 | |
| 6414 | static auto op = create_where_ScalarOther_typed_handle(); |
| 6415 | return op.call(condition, self, other); |
| 6416 | } |
| 6417 | |
| 6418 | // aten::where.ScalarOther(Tensor condition, Tensor self, Scalar other) -> Tensor |
| 6419 | at::Tensor where_ScalarOther::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Tensor & self, const at::Scalar & other) { |
| 6420 | |
| 6421 | static auto op = create_where_ScalarOther_typed_handle(); |
| 6422 | return op.redispatch(dispatchKeySet, condition, self, other); |
| 6423 | } |
| 6424 | |
| 6425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_Scalar, name, "aten::where") |
| 6426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_Scalar, overload_name, "Scalar") |
| 6427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where_Scalar, schema_str, "where.Scalar(Tensor condition, Scalar self, Scalar other) -> Tensor") |
| 6428 | |
| 6429 | // aten::where.Scalar(Tensor condition, Scalar self, Scalar other) -> Tensor |
| 6430 | static C10_NOINLINE c10::TypedOperatorHandle<where_Scalar::schema> create_where_Scalar_typed_handle() { |
| 6431 | return c10::Dispatcher::singleton() |
| 6432 | .findSchemaOrThrow(where_Scalar::name, where_Scalar::overload_name) |
| 6433 | .typed<where_Scalar::schema>(); |
| 6434 | } |
| 6435 | |
| 6436 | // aten::where.Scalar(Tensor condition, Scalar self, Scalar other) -> Tensor |
| 6437 | at::Tensor where_Scalar::call(const at::Tensor & condition, const at::Scalar & self, const at::Scalar & other) { |
| 6438 | |
| 6439 | static auto op = create_where_Scalar_typed_handle(); |
| 6440 | return op.call(condition, self, other); |
| 6441 | } |
| 6442 | |
| 6443 | // aten::where.Scalar(Tensor condition, Scalar self, Scalar other) -> Tensor |
| 6444 | at::Tensor where_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition, const at::Scalar & self, const at::Scalar & other) { |
| 6445 | |
| 6446 | static auto op = create_where_Scalar_typed_handle(); |
| 6447 | return op.redispatch(dispatchKeySet, condition, self, other); |
| 6448 | } |
| 6449 | |
| 6450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where, name, "aten::where") |
| 6451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where, overload_name, "") |
| 6452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(where, schema_str, "where(Tensor condition) -> Tensor[]") |
| 6453 | |
| 6454 | // aten::where(Tensor condition) -> Tensor[] |
| 6455 | static C10_NOINLINE c10::TypedOperatorHandle<where::schema> create_where_typed_handle() { |
| 6456 | return c10::Dispatcher::singleton() |
| 6457 | .findSchemaOrThrow(where::name, where::overload_name) |
| 6458 | .typed<where::schema>(); |
| 6459 | } |
| 6460 | |
| 6461 | // aten::where(Tensor condition) -> Tensor[] |
| 6462 | ::std::vector<at::Tensor> where::call(const at::Tensor & condition) { |
| 6463 | |
| 6464 | static auto op = create_where_typed_handle(); |
| 6465 | return op.call(condition); |
| 6466 | } |
| 6467 | |
| 6468 | // aten::where(Tensor condition) -> Tensor[] |
| 6469 | ::std::vector<at::Tensor> where::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & condition) { |
| 6470 | |
| 6471 | static auto op = create_where_typed_handle(); |
| 6472 | return op.redispatch(dispatchKeySet, condition); |
| 6473 | } |
| 6474 | |
| 6475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm, name, "aten::_weight_norm") |
| 6476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm, overload_name, "") |
| 6477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm, schema_str, "_weight_norm(Tensor v, Tensor g, int dim=0) -> Tensor") |
| 6478 | |
| 6479 | // aten::_weight_norm(Tensor v, Tensor g, int dim=0) -> Tensor |
| 6480 | static C10_NOINLINE c10::TypedOperatorHandle<_weight_norm::schema> create__weight_norm_typed_handle() { |
| 6481 | return c10::Dispatcher::singleton() |
| 6482 | .findSchemaOrThrow(_weight_norm::name, _weight_norm::overload_name) |
| 6483 | .typed<_weight_norm::schema>(); |
| 6484 | } |
| 6485 | |
| 6486 | // aten::_weight_norm(Tensor v, Tensor g, int dim=0) -> Tensor |
| 6487 | at::Tensor _weight_norm::call(const at::Tensor & v, const at::Tensor & g, int64_t dim) { |
| 6488 | |
| 6489 | static auto op = create__weight_norm_typed_handle(); |
| 6490 | return op.call(v, g, dim); |
| 6491 | } |
| 6492 | |
| 6493 | // aten::_weight_norm(Tensor v, Tensor g, int dim=0) -> Tensor |
| 6494 | at::Tensor _weight_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & v, const at::Tensor & g, int64_t dim) { |
| 6495 | |
| 6496 | static auto op = create__weight_norm_typed_handle(); |
| 6497 | return op.redispatch(dispatchKeySet, v, g, dim); |
| 6498 | } |
| 6499 | |
| 6500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_interface, name, "aten::_weight_norm_interface") |
| 6501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_interface, overload_name, "") |
| 6502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_interface, schema_str, "_weight_norm_interface(Tensor v, Tensor g, int dim=0) -> (Tensor, Tensor)") |
| 6503 | |
| 6504 | // aten::_weight_norm_interface(Tensor v, Tensor g, int dim=0) -> (Tensor, Tensor) |
| 6505 | static C10_NOINLINE c10::TypedOperatorHandle<_weight_norm_interface::schema> create__weight_norm_interface_typed_handle() { |
| 6506 | return c10::Dispatcher::singleton() |
| 6507 | .findSchemaOrThrow(_weight_norm_interface::name, _weight_norm_interface::overload_name) |
| 6508 | .typed<_weight_norm_interface::schema>(); |
| 6509 | } |
| 6510 | |
| 6511 | // aten::_weight_norm_interface(Tensor v, Tensor g, int dim=0) -> (Tensor, Tensor) |
| 6512 | ::std::tuple<at::Tensor,at::Tensor> _weight_norm_interface::call(const at::Tensor & v, const at::Tensor & g, int64_t dim) { |
| 6513 | |
| 6514 | static auto op = create__weight_norm_interface_typed_handle(); |
| 6515 | return op.call(v, g, dim); |
| 6516 | } |
| 6517 | |
| 6518 | // aten::_weight_norm_interface(Tensor v, Tensor g, int dim=0) -> (Tensor, Tensor) |
| 6519 | ::std::tuple<at::Tensor,at::Tensor> _weight_norm_interface::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & v, const at::Tensor & g, int64_t dim) { |
| 6520 | |
| 6521 | static auto op = create__weight_norm_interface_typed_handle(); |
| 6522 | return op.redispatch(dispatchKeySet, v, g, dim); |
| 6523 | } |
| 6524 | |
| 6525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_differentiable_backward, name, "aten::_weight_norm_differentiable_backward") |
| 6526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_differentiable_backward, overload_name, "") |
| 6527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_differentiable_backward, schema_str, "_weight_norm_differentiable_backward(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim) -> (Tensor, Tensor)") |
| 6528 | |
| 6529 | // aten::_weight_norm_differentiable_backward(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim) -> (Tensor, Tensor) |
| 6530 | static C10_NOINLINE c10::TypedOperatorHandle<_weight_norm_differentiable_backward::schema> create__weight_norm_differentiable_backward_typed_handle() { |
| 6531 | return c10::Dispatcher::singleton() |
| 6532 | .findSchemaOrThrow(_weight_norm_differentiable_backward::name, _weight_norm_differentiable_backward::overload_name) |
| 6533 | .typed<_weight_norm_differentiable_backward::schema>(); |
| 6534 | } |
| 6535 | |
| 6536 | // aten::_weight_norm_differentiable_backward(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim) -> (Tensor, Tensor) |
| 6537 | ::std::tuple<at::Tensor,at::Tensor> _weight_norm_differentiable_backward::call(const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim) { |
| 6538 | |
| 6539 | static auto op = create__weight_norm_differentiable_backward_typed_handle(); |
| 6540 | return op.call(grad_w, saved_v, saved_g, saved_norms, dim); |
| 6541 | } |
| 6542 | |
| 6543 | // aten::_weight_norm_differentiable_backward(Tensor grad_w, Tensor saved_v, Tensor saved_g, Tensor saved_norms, int dim) -> (Tensor, Tensor) |
| 6544 | ::std::tuple<at::Tensor,at::Tensor> _weight_norm_differentiable_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_w, const at::Tensor & saved_v, const at::Tensor & saved_g, const at::Tensor & saved_norms, int64_t dim) { |
| 6545 | |
| 6546 | static auto op = create__weight_norm_differentiable_backward_typed_handle(); |
| 6547 | return op.redispatch(dispatchKeySet, grad_w, saved_v, saved_g, saved_norms, dim); |
| 6548 | } |
| 6549 | |
| 6550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_names, name, "aten::zeros") |
| 6551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_names, overload_name, "names") |
| 6552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_names, schema_str, "zeros.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 6553 | |
| 6554 | // aten::zeros.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6555 | static C10_NOINLINE c10::TypedOperatorHandle<zeros_names::schema> create_zeros_names_typed_handle() { |
| 6556 | return c10::Dispatcher::singleton() |
| 6557 | .findSchemaOrThrow(zeros_names::name, zeros_names::overload_name) |
| 6558 | .typed<zeros_names::schema>(); |
| 6559 | } |
| 6560 | |
| 6561 | // aten::zeros.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6562 | at::Tensor zeros_names::call(at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6563 | |
| 6564 | static auto op = create_zeros_names_typed_handle(); |
| 6565 | return op.call(size, names, dtype, layout, device, pin_memory); |
| 6566 | } |
| 6567 | |
| 6568 | // aten::zeros.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6569 | at::Tensor zeros_names::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6570 | |
| 6571 | static auto op = create_zeros_names_typed_handle(); |
| 6572 | return op.redispatch(dispatchKeySet, size, names, dtype, layout, device, pin_memory); |
| 6573 | } |
| 6574 | |
| 6575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros, name, "aten::zeros") |
| 6576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros, overload_name, "") |
| 6577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros, schema_str, "zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 6578 | |
| 6579 | // aten::zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6580 | static C10_NOINLINE c10::TypedOperatorHandle<zeros::schema> create_zeros_typed_handle() { |
| 6581 | return c10::Dispatcher::singleton() |
| 6582 | .findSchemaOrThrow(zeros::name, zeros::overload_name) |
| 6583 | .typed<zeros::schema>(); |
| 6584 | } |
| 6585 | |
| 6586 | // aten::zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6587 | at::Tensor zeros::call(c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6588 | |
| 6589 | static auto op = create_zeros_typed_handle(); |
| 6590 | return op.call(size, dtype, layout, device, pin_memory); |
| 6591 | } |
| 6592 | |
| 6593 | // aten::zeros(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6594 | at::Tensor zeros::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6595 | |
| 6596 | static auto op = create_zeros_typed_handle(); |
| 6597 | return op.redispatch(dispatchKeySet, size, dtype, layout, device, pin_memory); |
| 6598 | } |
| 6599 | |
| 6600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_out, name, "aten::zeros") |
| 6601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_out, overload_name, "out") |
| 6602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_out, schema_str, "zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") |
| 6603 | |
| 6604 | // aten::zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 6605 | static C10_NOINLINE c10::TypedOperatorHandle<zeros_out::schema> create_zeros_out_typed_handle() { |
| 6606 | return c10::Dispatcher::singleton() |
| 6607 | .findSchemaOrThrow(zeros_out::name, zeros_out::overload_name) |
| 6608 | .typed<zeros_out::schema>(); |
| 6609 | } |
| 6610 | |
| 6611 | // aten::zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 6612 | at::Tensor & zeros_out::call(c10::SymIntArrayRef size, at::Tensor & out) { |
| 6613 | |
| 6614 | static auto op = create_zeros_out_typed_handle(); |
| 6615 | return op.call(size, out); |
| 6616 | } |
| 6617 | |
| 6618 | // aten::zeros.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 6619 | at::Tensor & zeros_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, at::Tensor & out) { |
| 6620 | |
| 6621 | static auto op = create_zeros_out_typed_handle(); |
| 6622 | return op.redispatch(dispatchKeySet, size, out); |
| 6623 | } |
| 6624 | |
| 6625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma, name, "aten::_standard_gamma") |
| 6626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma, overload_name, "") |
| 6627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma, schema_str, "_standard_gamma(Tensor self, Generator? generator=None) -> Tensor") |
| 6628 | |
| 6629 | // aten::_standard_gamma(Tensor self, Generator? generator=None) -> Tensor |
| 6630 | static C10_NOINLINE c10::TypedOperatorHandle<_standard_gamma::schema> create__standard_gamma_typed_handle() { |
| 6631 | return c10::Dispatcher::singleton() |
| 6632 | .findSchemaOrThrow(_standard_gamma::name, _standard_gamma::overload_name) |
| 6633 | .typed<_standard_gamma::schema>(); |
| 6634 | } |
| 6635 | |
| 6636 | // aten::_standard_gamma(Tensor self, Generator? generator=None) -> Tensor |
| 6637 | at::Tensor _standard_gamma::call(const at::Tensor & self, c10::optional<at::Generator> generator) { |
| 6638 | |
| 6639 | static auto op = create__standard_gamma_typed_handle(); |
| 6640 | return op.call(self, generator); |
| 6641 | } |
| 6642 | |
| 6643 | // aten::_standard_gamma(Tensor self, Generator? generator=None) -> Tensor |
| 6644 | at::Tensor _standard_gamma::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator) { |
| 6645 | |
| 6646 | static auto op = create__standard_gamma_typed_handle(); |
| 6647 | return op.redispatch(dispatchKeySet, self, generator); |
| 6648 | } |
| 6649 | |
| 6650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sample_dirichlet, name, "aten::_sample_dirichlet") |
| 6651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sample_dirichlet, overload_name, "") |
| 6652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sample_dirichlet, schema_str, "_sample_dirichlet(Tensor self, Generator? generator=None) -> Tensor") |
| 6653 | |
| 6654 | // aten::_sample_dirichlet(Tensor self, Generator? generator=None) -> Tensor |
| 6655 | static C10_NOINLINE c10::TypedOperatorHandle<_sample_dirichlet::schema> create__sample_dirichlet_typed_handle() { |
| 6656 | return c10::Dispatcher::singleton() |
| 6657 | .findSchemaOrThrow(_sample_dirichlet::name, _sample_dirichlet::overload_name) |
| 6658 | .typed<_sample_dirichlet::schema>(); |
| 6659 | } |
| 6660 | |
| 6661 | // aten::_sample_dirichlet(Tensor self, Generator? generator=None) -> Tensor |
| 6662 | at::Tensor _sample_dirichlet::call(const at::Tensor & self, c10::optional<at::Generator> generator) { |
| 6663 | |
| 6664 | static auto op = create__sample_dirichlet_typed_handle(); |
| 6665 | return op.call(self, generator); |
| 6666 | } |
| 6667 | |
| 6668 | // aten::_sample_dirichlet(Tensor self, Generator? generator=None) -> Tensor |
| 6669 | at::Tensor _sample_dirichlet::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator) { |
| 6670 | |
| 6671 | static auto op = create__sample_dirichlet_typed_handle(); |
| 6672 | return op.redispatch(dispatchKeySet, self, generator); |
| 6673 | } |
| 6674 | |
| 6675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binomial, name, "aten::binomial") |
| 6676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binomial, overload_name, "") |
| 6677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binomial, schema_str, "binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor") |
| 6678 | |
| 6679 | // aten::binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor |
| 6680 | static C10_NOINLINE c10::TypedOperatorHandle<binomial::schema> create_binomial_typed_handle() { |
| 6681 | return c10::Dispatcher::singleton() |
| 6682 | .findSchemaOrThrow(binomial::name, binomial::overload_name) |
| 6683 | .typed<binomial::schema>(); |
| 6684 | } |
| 6685 | |
| 6686 | // aten::binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor |
| 6687 | at::Tensor binomial::call(const at::Tensor & count, const at::Tensor & prob, c10::optional<at::Generator> generator) { |
| 6688 | |
| 6689 | static auto op = create_binomial_typed_handle(); |
| 6690 | return op.call(count, prob, generator); |
| 6691 | } |
| 6692 | |
| 6693 | // aten::binomial(Tensor count, Tensor prob, Generator? generator=None) -> Tensor |
| 6694 | at::Tensor binomial::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & count, const at::Tensor & prob, c10::optional<at::Generator> generator) { |
| 6695 | |
| 6696 | static auto op = create_binomial_typed_handle(); |
| 6697 | return op.redispatch(dispatchKeySet, count, prob, generator); |
| 6698 | } |
| 6699 | |
| 6700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum, name, "aten::_sparse_sum") |
| 6701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum, overload_name, "") |
| 6702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum, schema_str, "_sparse_sum(Tensor self) -> Tensor") |
| 6703 | |
| 6704 | // aten::_sparse_sum(Tensor self) -> Tensor |
| 6705 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sum::schema> create__sparse_sum_typed_handle() { |
| 6706 | return c10::Dispatcher::singleton() |
| 6707 | .findSchemaOrThrow(_sparse_sum::name, _sparse_sum::overload_name) |
| 6708 | .typed<_sparse_sum::schema>(); |
| 6709 | } |
| 6710 | |
| 6711 | // aten::_sparse_sum(Tensor self) -> Tensor |
| 6712 | at::Tensor _sparse_sum::call(const at::Tensor & self) { |
| 6713 | |
| 6714 | static auto op = create__sparse_sum_typed_handle(); |
| 6715 | return op.call(self); |
| 6716 | } |
| 6717 | |
| 6718 | // aten::_sparse_sum(Tensor self) -> Tensor |
| 6719 | at::Tensor _sparse_sum::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 6720 | |
| 6721 | static auto op = create__sparse_sum_typed_handle(); |
| 6722 | return op.redispatch(dispatchKeySet, self); |
| 6723 | } |
| 6724 | |
| 6725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dtype, name, "aten::_sparse_sum") |
| 6726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dtype, overload_name, "dtype") |
| 6727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dtype, schema_str, "_sparse_sum.dtype(Tensor self, *, ScalarType dtype) -> Tensor") |
| 6728 | |
| 6729 | // aten::_sparse_sum.dtype(Tensor self, *, ScalarType dtype) -> Tensor |
| 6730 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sum_dtype::schema> create__sparse_sum_dtype_typed_handle() { |
| 6731 | return c10::Dispatcher::singleton() |
| 6732 | .findSchemaOrThrow(_sparse_sum_dtype::name, _sparse_sum_dtype::overload_name) |
| 6733 | .typed<_sparse_sum_dtype::schema>(); |
| 6734 | } |
| 6735 | |
| 6736 | // aten::_sparse_sum.dtype(Tensor self, *, ScalarType dtype) -> Tensor |
| 6737 | at::Tensor _sparse_sum_dtype::call(const at::Tensor & self, at::ScalarType dtype) { |
| 6738 | |
| 6739 | static auto op = create__sparse_sum_dtype_typed_handle(); |
| 6740 | return op.call(self, dtype); |
| 6741 | } |
| 6742 | |
| 6743 | // aten::_sparse_sum.dtype(Tensor self, *, ScalarType dtype) -> Tensor |
| 6744 | at::Tensor _sparse_sum_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype) { |
| 6745 | |
| 6746 | static auto op = create__sparse_sum_dtype_typed_handle(); |
| 6747 | return op.redispatch(dispatchKeySet, self, dtype); |
| 6748 | } |
| 6749 | |
| 6750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim, name, "aten::_sparse_sum") |
| 6751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim, overload_name, "dim") |
| 6752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim, schema_str, "_sparse_sum.dim(Tensor self, int[1] dim) -> Tensor") |
| 6753 | |
| 6754 | // aten::_sparse_sum.dim(Tensor self, int[1] dim) -> Tensor |
| 6755 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sum_dim::schema> create__sparse_sum_dim_typed_handle() { |
| 6756 | return c10::Dispatcher::singleton() |
| 6757 | .findSchemaOrThrow(_sparse_sum_dim::name, _sparse_sum_dim::overload_name) |
| 6758 | .typed<_sparse_sum_dim::schema>(); |
| 6759 | } |
| 6760 | |
| 6761 | // aten::_sparse_sum.dim(Tensor self, int[1] dim) -> Tensor |
| 6762 | at::Tensor _sparse_sum_dim::call(const at::Tensor & self, at::IntArrayRef dim) { |
| 6763 | |
| 6764 | static auto op = create__sparse_sum_dim_typed_handle(); |
| 6765 | return op.call(self, dim); |
| 6766 | } |
| 6767 | |
| 6768 | // aten::_sparse_sum.dim(Tensor self, int[1] dim) -> Tensor |
| 6769 | at::Tensor _sparse_sum_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim) { |
| 6770 | |
| 6771 | static auto op = create__sparse_sum_dim_typed_handle(); |
| 6772 | return op.redispatch(dispatchKeySet, self, dim); |
| 6773 | } |
| 6774 | |
| 6775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim_dtype, name, "aten::_sparse_sum") |
| 6776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim_dtype, overload_name, "dim_dtype") |
| 6777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim_dtype, schema_str, "_sparse_sum.dim_dtype(Tensor self, int[1] dim, *, ScalarType dtype) -> Tensor") |
| 6778 | |
| 6779 | // aten::_sparse_sum.dim_dtype(Tensor self, int[1] dim, *, ScalarType dtype) -> Tensor |
| 6780 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sum_dim_dtype::schema> create__sparse_sum_dim_dtype_typed_handle() { |
| 6781 | return c10::Dispatcher::singleton() |
| 6782 | .findSchemaOrThrow(_sparse_sum_dim_dtype::name, _sparse_sum_dim_dtype::overload_name) |
| 6783 | .typed<_sparse_sum_dim_dtype::schema>(); |
| 6784 | } |
| 6785 | |
| 6786 | // aten::_sparse_sum.dim_dtype(Tensor self, int[1] dim, *, ScalarType dtype) -> Tensor |
| 6787 | at::Tensor _sparse_sum_dim_dtype::call(const at::Tensor & self, at::IntArrayRef dim, at::ScalarType dtype) { |
| 6788 | |
| 6789 | static auto op = create__sparse_sum_dim_dtype_typed_handle(); |
| 6790 | return op.call(self, dim, dtype); |
| 6791 | } |
| 6792 | |
| 6793 | // aten::_sparse_sum.dim_dtype(Tensor self, int[1] dim, *, ScalarType dtype) -> Tensor |
| 6794 | at::Tensor _sparse_sum_dim_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::ScalarType dtype) { |
| 6795 | |
| 6796 | static auto op = create__sparse_sum_dim_dtype_typed_handle(); |
| 6797 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
| 6798 | } |
| 6799 | |
| 6800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_addmm, name, "aten::_sparse_addmm") |
| 6801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_addmm, overload_name, "") |
| 6802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_addmm, schema_str, "_sparse_addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor") |
| 6803 | |
| 6804 | // aten::_sparse_addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6805 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_addmm::schema> create__sparse_addmm_typed_handle() { |
| 6806 | return c10::Dispatcher::singleton() |
| 6807 | .findSchemaOrThrow(_sparse_addmm::name, _sparse_addmm::overload_name) |
| 6808 | .typed<_sparse_addmm::schema>(); |
| 6809 | } |
| 6810 | |
| 6811 | // aten::_sparse_addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6812 | at::Tensor _sparse_addmm::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6813 | |
| 6814 | static auto op = create__sparse_addmm_typed_handle(); |
| 6815 | return op.call(self, mat1, mat2, beta, alpha); |
| 6816 | } |
| 6817 | |
| 6818 | // aten::_sparse_addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6819 | at::Tensor _sparse_addmm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6820 | |
| 6821 | static auto op = create__sparse_addmm_typed_handle(); |
| 6822 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha); |
| 6823 | } |
| 6824 | |
| 6825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm_reduce_impl_backward, name, "aten::_sparse_mm_reduce_impl_backward") |
| 6826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm_reduce_impl_backward, overload_name, "") |
| 6827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm_reduce_impl_backward, schema_str, "_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor)") |
| 6828 | |
| 6829 | // aten::_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor) |
| 6830 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_mm_reduce_impl_backward::schema> create__sparse_mm_reduce_impl_backward_typed_handle() { |
| 6831 | return c10::Dispatcher::singleton() |
| 6832 | .findSchemaOrThrow(_sparse_mm_reduce_impl_backward::name, _sparse_mm_reduce_impl_backward::overload_name) |
| 6833 | .typed<_sparse_mm_reduce_impl_backward::schema>(); |
| 6834 | } |
| 6835 | |
| 6836 | // aten::_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor) |
| 6837 | ::std::tuple<at::Tensor,at::Tensor> _sparse_mm_reduce_impl_backward::call(const at::Tensor & self, const at::Tensor & grad_out, const at::Tensor & weight, c10::string_view reduce, const at::Tensor & arg_out, ::std::array<bool,2> output_mask) { |
| 6838 | |
| 6839 | static auto op = create__sparse_mm_reduce_impl_backward_typed_handle(); |
| 6840 | return op.call(self, grad_out, weight, reduce, arg_out, output_mask); |
| 6841 | } |
| 6842 | |
| 6843 | // aten::_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor) |
| 6844 | ::std::tuple<at::Tensor,at::Tensor> _sparse_mm_reduce_impl_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_out, const at::Tensor & weight, c10::string_view reduce, const at::Tensor & arg_out, ::std::array<bool,2> output_mask) { |
| 6845 | |
| 6846 | static auto op = create__sparse_mm_reduce_impl_backward_typed_handle(); |
| 6847 | return op.redispatch(dispatchKeySet, self, grad_out, weight, reduce, arg_out, output_mask); |
| 6848 | } |
| 6849 | |
| 6850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm_out, name, "aten::addmm") |
| 6851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm_out, overload_name, "out") |
| 6852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm_out, schema_str, "addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") |
| 6853 | |
| 6854 | // aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6855 | static C10_NOINLINE c10::TypedOperatorHandle<addmm_out::schema> create_addmm_out_typed_handle() { |
| 6856 | return c10::Dispatcher::singleton() |
| 6857 | .findSchemaOrThrow(addmm_out::name, addmm_out::overload_name) |
| 6858 | .typed<addmm_out::schema>(); |
| 6859 | } |
| 6860 | |
| 6861 | // aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6862 | at::Tensor & addmm_out::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
| 6863 | |
| 6864 | static auto op = create_addmm_out_typed_handle(); |
| 6865 | return op.call(self, mat1, mat2, beta, alpha, out); |
| 6866 | } |
| 6867 | |
| 6868 | // aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6869 | at::Tensor & addmm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
| 6870 | |
| 6871 | static auto op = create_addmm_out_typed_handle(); |
| 6872 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha, out); |
| 6873 | } |
| 6874 | |
| 6875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm, name, "aten::addmm") |
| 6876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm, overload_name, "") |
| 6877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm, schema_str, "addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor") |
| 6878 | |
| 6879 | // aten::addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6880 | static C10_NOINLINE c10::TypedOperatorHandle<addmm::schema> create_addmm_typed_handle() { |
| 6881 | return c10::Dispatcher::singleton() |
| 6882 | .findSchemaOrThrow(addmm::name, addmm::overload_name) |
| 6883 | .typed<addmm::schema>(); |
| 6884 | } |
| 6885 | |
| 6886 | // aten::addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6887 | at::Tensor addmm::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6888 | |
| 6889 | static auto op = create_addmm_typed_handle(); |
| 6890 | return op.call(self, mat1, mat2, beta, alpha); |
| 6891 | } |
| 6892 | |
| 6893 | // aten::addmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
| 6894 | at::Tensor addmm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6895 | |
| 6896 | static auto op = create_addmm_typed_handle(); |
| 6897 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha); |
| 6898 | } |
| 6899 | |
| 6900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm_, name, "aten::addmm_") |
| 6901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm_, overload_name, "") |
| 6902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addmm_, schema_str, "addmm_(Tensor(a!) self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)") |
| 6903 | |
| 6904 | // aten::addmm_(Tensor(a!) self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!) |
| 6905 | static C10_NOINLINE c10::TypedOperatorHandle<addmm_::schema> create_addmm__typed_handle() { |
| 6906 | return c10::Dispatcher::singleton() |
| 6907 | .findSchemaOrThrow(addmm_::name, addmm_::overload_name) |
| 6908 | .typed<addmm_::schema>(); |
| 6909 | } |
| 6910 | |
| 6911 | // aten::addmm_(Tensor(a!) self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!) |
| 6912 | at::Tensor & addmm_::call(at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6913 | |
| 6914 | static auto op = create_addmm__typed_handle(); |
| 6915 | return op.call(self, mat1, mat2, beta, alpha); |
| 6916 | } |
| 6917 | |
| 6918 | // aten::addmm_(Tensor(a!) self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!) |
| 6919 | at::Tensor & addmm_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha) { |
| 6920 | |
| 6921 | static auto op = create_addmm__typed_handle(); |
| 6922 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha); |
| 6923 | } |
| 6924 | |
| 6925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_csc_tensor_ccol_row_value_size, name, "aten::sparse_csc_tensor") |
| 6926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_csc_tensor_ccol_row_value_size, overload_name, "ccol_row_value_size") |
| 6927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_csc_tensor_ccol_row_value_size, schema_str, "sparse_csc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 6928 | |
| 6929 | // aten::sparse_csc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6930 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_csc_tensor_ccol_row_value_size::schema> create_sparse_csc_tensor_ccol_row_value_size_typed_handle() { |
| 6931 | return c10::Dispatcher::singleton() |
| 6932 | .findSchemaOrThrow(sparse_csc_tensor_ccol_row_value_size::name, sparse_csc_tensor_ccol_row_value_size::overload_name) |
| 6933 | .typed<sparse_csc_tensor_ccol_row_value_size::schema>(); |
| 6934 | } |
| 6935 | |
| 6936 | // aten::sparse_csc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6937 | at::Tensor sparse_csc_tensor_ccol_row_value_size::call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6938 | |
| 6939 | static auto op = create_sparse_csc_tensor_ccol_row_value_size_typed_handle(); |
| 6940 | return op.call(ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); |
| 6941 | } |
| 6942 | |
| 6943 | // aten::sparse_csc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6944 | at::Tensor sparse_csc_tensor_ccol_row_value_size::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6945 | |
| 6946 | static auto op = create_sparse_csc_tensor_ccol_row_value_size_typed_handle(); |
| 6947 | return op.redispatch(dispatchKeySet, ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); |
| 6948 | } |
| 6949 | |
| 6950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsc_tensor_ccol_row_value_size, name, "aten::sparse_bsc_tensor") |
| 6951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsc_tensor_ccol_row_value_size, overload_name, "ccol_row_value_size") |
| 6952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsc_tensor_ccol_row_value_size, schema_str, "sparse_bsc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 6953 | |
| 6954 | // aten::sparse_bsc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6955 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_bsc_tensor_ccol_row_value_size::schema> create_sparse_bsc_tensor_ccol_row_value_size_typed_handle() { |
| 6956 | return c10::Dispatcher::singleton() |
| 6957 | .findSchemaOrThrow(sparse_bsc_tensor_ccol_row_value_size::name, sparse_bsc_tensor_ccol_row_value_size::overload_name) |
| 6958 | .typed<sparse_bsc_tensor_ccol_row_value_size::schema>(); |
| 6959 | } |
| 6960 | |
| 6961 | // aten::sparse_bsc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6962 | at::Tensor sparse_bsc_tensor_ccol_row_value_size::call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6963 | |
| 6964 | static auto op = create_sparse_bsc_tensor_ccol_row_value_size_typed_handle(); |
| 6965 | return op.call(ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); |
| 6966 | } |
| 6967 | |
| 6968 | // aten::sparse_bsc_tensor.ccol_row_value_size(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6969 | at::Tensor sparse_bsc_tensor_ccol_row_value_size::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6970 | |
| 6971 | static auto op = create_sparse_bsc_tensor_ccol_row_value_size_typed_handle(); |
| 6972 | return op.redispatch(dispatchKeySet, ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); |
| 6973 | } |
| 6974 | |
| 6975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_csc_tensor_ccol_row_value, name, "aten::sparse_csc_tensor") |
| 6976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_csc_tensor_ccol_row_value, overload_name, "ccol_row_value") |
| 6977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_csc_tensor_ccol_row_value, schema_str, "sparse_csc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 6978 | |
| 6979 | // aten::sparse_csc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6980 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_csc_tensor_ccol_row_value::schema> create_sparse_csc_tensor_ccol_row_value_typed_handle() { |
| 6981 | return c10::Dispatcher::singleton() |
| 6982 | .findSchemaOrThrow(sparse_csc_tensor_ccol_row_value::name, sparse_csc_tensor_ccol_row_value::overload_name) |
| 6983 | .typed<sparse_csc_tensor_ccol_row_value::schema>(); |
| 6984 | } |
| 6985 | |
| 6986 | // aten::sparse_csc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6987 | at::Tensor sparse_csc_tensor_ccol_row_value::call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6988 | |
| 6989 | static auto op = create_sparse_csc_tensor_ccol_row_value_typed_handle(); |
| 6990 | return op.call(ccol_indices, row_indices, values, dtype, layout, device, pin_memory); |
| 6991 | } |
| 6992 | |
| 6993 | // aten::sparse_csc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 6994 | at::Tensor sparse_csc_tensor_ccol_row_value::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6995 | |
| 6996 | static auto op = create_sparse_csc_tensor_ccol_row_value_typed_handle(); |
| 6997 | return op.redispatch(dispatchKeySet, ccol_indices, row_indices, values, dtype, layout, device, pin_memory); |
| 6998 | } |
| 6999 | |
| 7000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsc_tensor_ccol_row_value, name, "aten::sparse_bsc_tensor") |
| 7001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsc_tensor_ccol_row_value, overload_name, "ccol_row_value") |
| 7002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsc_tensor_ccol_row_value, schema_str, "sparse_bsc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 7003 | |
| 7004 | // aten::sparse_bsc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 7005 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_bsc_tensor_ccol_row_value::schema> create_sparse_bsc_tensor_ccol_row_value_typed_handle() { |
| 7006 | return c10::Dispatcher::singleton() |
| 7007 | .findSchemaOrThrow(sparse_bsc_tensor_ccol_row_value::name, sparse_bsc_tensor_ccol_row_value::overload_name) |
| 7008 | .typed<sparse_bsc_tensor_ccol_row_value::schema>(); |
| 7009 | } |
| 7010 | |
| 7011 | // aten::sparse_bsc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 7012 | at::Tensor sparse_bsc_tensor_ccol_row_value::call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7013 | |
| 7014 | static auto op = create_sparse_bsc_tensor_ccol_row_value_typed_handle(); |
| 7015 | return op.call(ccol_indices, row_indices, values, dtype, layout, device, pin_memory); |
| 7016 | } |
| 7017 | |
| 7018 | // aten::sparse_bsc_tensor.ccol_row_value(Tensor ccol_indices, Tensor row_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 7019 | at::Tensor sparse_bsc_tensor_ccol_row_value::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7020 | |
| 7021 | static auto op = create_sparse_bsc_tensor_ccol_row_value_typed_handle(); |
| 7022 | return op.redispatch(dispatchKeySet, ccol_indices, row_indices, values, dtype, layout, device, pin_memory); |
| 7023 | } |
| 7024 | |
| 7025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_compressed_tensor_unsafe, name, "aten::_sparse_compressed_tensor_unsafe") |
| 7026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_compressed_tensor_unsafe, overload_name, "") |
| 7027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_compressed_tensor_unsafe, schema_str, "_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 7028 | |
| 7029 | // aten::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7030 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_compressed_tensor_unsafe::schema> create__sparse_compressed_tensor_unsafe_typed_handle() { |
| 7031 | return c10::Dispatcher::singleton() |
| 7032 | .findSchemaOrThrow(_sparse_compressed_tensor_unsafe::name, _sparse_compressed_tensor_unsafe::overload_name) |
| 7033 | .typed<_sparse_compressed_tensor_unsafe::schema>(); |
| 7034 | } |
| 7035 | |
| 7036 | // aten::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7037 | at::Tensor _sparse_compressed_tensor_unsafe::call(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7038 | |
| 7039 | static auto op = create__sparse_compressed_tensor_unsafe_typed_handle(); |
| 7040 | return op.call(compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); |
| 7041 | } |
| 7042 | |
| 7043 | // aten::_sparse_compressed_tensor_unsafe(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7044 | at::Tensor _sparse_compressed_tensor_unsafe::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7045 | |
| 7046 | static auto op = create__sparse_compressed_tensor_unsafe_typed_handle(); |
| 7047 | return op.redispatch(dispatchKeySet, compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); |
| 7048 | } |
| 7049 | |
| 7050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_tensor_unsafe, name, "aten::_sparse_csr_tensor_unsafe") |
| 7051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_tensor_unsafe, overload_name, "") |
| 7052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_tensor_unsafe, schema_str, "_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 7053 | |
| 7054 | // aten::_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7055 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_csr_tensor_unsafe::schema> create__sparse_csr_tensor_unsafe_typed_handle() { |
| 7056 | return c10::Dispatcher::singleton() |
| 7057 | .findSchemaOrThrow(_sparse_csr_tensor_unsafe::name, _sparse_csr_tensor_unsafe::overload_name) |
| 7058 | .typed<_sparse_csr_tensor_unsafe::schema>(); |
| 7059 | } |
| 7060 | |
| 7061 | // aten::_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7062 | at::Tensor _sparse_csr_tensor_unsafe::call(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7063 | |
| 7064 | static auto op = create__sparse_csr_tensor_unsafe_typed_handle(); |
| 7065 | return op.call(crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); |
| 7066 | } |
| 7067 | |
| 7068 | // aten::_sparse_csr_tensor_unsafe(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7069 | at::Tensor _sparse_csr_tensor_unsafe::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7070 | |
| 7071 | static auto op = create__sparse_csr_tensor_unsafe_typed_handle(); |
| 7072 | return op.redispatch(dispatchKeySet, crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); |
| 7073 | } |
| 7074 | |
| 7075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_unsafe, name, "aten::_sparse_coo_tensor_unsafe") |
| 7076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_unsafe, overload_name, "") |
| 7077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_unsafe, schema_str, "_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 7078 | |
| 7079 | // aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7080 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_coo_tensor_unsafe::schema> create__sparse_coo_tensor_unsafe_typed_handle() { |
| 7081 | return c10::Dispatcher::singleton() |
| 7082 | .findSchemaOrThrow(_sparse_coo_tensor_unsafe::name, _sparse_coo_tensor_unsafe::overload_name) |
| 7083 | .typed<_sparse_coo_tensor_unsafe::schema>(); |
| 7084 | } |
| 7085 | |
| 7086 | // aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7087 | at::Tensor _sparse_coo_tensor_unsafe::call(const at::Tensor & indices, const at::Tensor & values, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7088 | |
| 7089 | static auto op = create__sparse_coo_tensor_unsafe_typed_handle(); |
| 7090 | return op.call(indices, values, size, dtype, layout, device, pin_memory); |
| 7091 | } |
| 7092 | |
| 7093 | // aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 7094 | at::Tensor _sparse_coo_tensor_unsafe::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & indices, const at::Tensor & values, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 7095 | |
| 7096 | static auto op = create__sparse_coo_tensor_unsafe_typed_handle(); |
| 7097 | return op.redispatch(dispatchKeySet, indices, values, size, dtype, layout, device, pin_memory); |
| 7098 | } |
| 7099 | |
| 7100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_csr_tensor_args, name, "aten::_validate_sparse_csr_tensor_args") |
| 7101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_csr_tensor_args, overload_name, "") |
| 7102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_csr_tensor_args, schema_str, "_validate_sparse_csr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> ()") |
| 7103 | |
| 7104 | // aten::_validate_sparse_csr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> () |
| 7105 | static C10_NOINLINE c10::TypedOperatorHandle<_validate_sparse_csr_tensor_args::schema> create__validate_sparse_csr_tensor_args_typed_handle() { |
| 7106 | return c10::Dispatcher::singleton() |
| 7107 | .findSchemaOrThrow(_validate_sparse_csr_tensor_args::name, _validate_sparse_csr_tensor_args::overload_name) |
| 7108 | .typed<_validate_sparse_csr_tensor_args::schema>(); |
| 7109 | } |
| 7110 | |
| 7111 | // aten::_validate_sparse_csr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> () |
| 7112 | void _validate_sparse_csr_tensor_args::call(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size) { |
| 7113 | |
| 7114 | static auto op = create__validate_sparse_csr_tensor_args_typed_handle(); |
| 7115 | return op.call(crow_indices, col_indices, values, size); |
| 7116 | } |
| 7117 | |
| 7118 | // aten::_validate_sparse_csr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> () |
| 7119 | void _validate_sparse_csr_tensor_args::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size) { |
| 7120 | |
| 7121 | static auto op = create__validate_sparse_csr_tensor_args_typed_handle(); |
| 7122 | return op.redispatch(dispatchKeySet, crow_indices, col_indices, values, size); |
| 7123 | } |
| 7124 | |
| 7125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_bsr_tensor_args, name, "aten::_validate_sparse_bsr_tensor_args") |
| 7126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_bsr_tensor_args, overload_name, "") |
| 7127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_bsr_tensor_args, schema_str, "_validate_sparse_bsr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> ()") |
| 7128 | |
| 7129 | // aten::_validate_sparse_bsr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> () |
| 7130 | static C10_NOINLINE c10::TypedOperatorHandle<_validate_sparse_bsr_tensor_args::schema> create__validate_sparse_bsr_tensor_args_typed_handle() { |
| 7131 | return c10::Dispatcher::singleton() |
| 7132 | .findSchemaOrThrow(_validate_sparse_bsr_tensor_args::name, _validate_sparse_bsr_tensor_args::overload_name) |
| 7133 | .typed<_validate_sparse_bsr_tensor_args::schema>(); |
| 7134 | } |
| 7135 | |
| 7136 | // aten::_validate_sparse_bsr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> () |
| 7137 | void _validate_sparse_bsr_tensor_args::call(const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size) { |
| 7138 | |
| 7139 | static auto op = create__validate_sparse_bsr_tensor_args_typed_handle(); |
| 7140 | return op.call(crow_indices, col_indices, values, size); |
| 7141 | } |
| 7142 | |
| 7143 | // aten::_validate_sparse_bsr_tensor_args(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size) -> () |
| 7144 | void _validate_sparse_bsr_tensor_args::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & crow_indices, const at::Tensor & col_indices, const at::Tensor & values, at::IntArrayRef size) { |
| 7145 | |
| 7146 | static auto op = create__validate_sparse_bsr_tensor_args_typed_handle(); |
| 7147 | return op.redispatch(dispatchKeySet, crow_indices, col_indices, values, size); |
| 7148 | } |
| 7149 | |
| 7150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_bsc_tensor_args, name, "aten::_validate_sparse_bsc_tensor_args") |
| 7151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_bsc_tensor_args, overload_name, "") |
| 7152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_bsc_tensor_args, schema_str, "_validate_sparse_bsc_tensor_args(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size) -> ()") |
| 7153 | |
| 7154 | // aten::_validate_sparse_bsc_tensor_args(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size) -> () |
| 7155 | static C10_NOINLINE c10::TypedOperatorHandle<_validate_sparse_bsc_tensor_args::schema> create__validate_sparse_bsc_tensor_args_typed_handle() { |
| 7156 | return c10::Dispatcher::singleton() |
| 7157 | .findSchemaOrThrow(_validate_sparse_bsc_tensor_args::name, _validate_sparse_bsc_tensor_args::overload_name) |
| 7158 | .typed<_validate_sparse_bsc_tensor_args::schema>(); |
| 7159 | } |
| 7160 | |
| 7161 | // aten::_validate_sparse_bsc_tensor_args(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size) -> () |
| 7162 | void _validate_sparse_bsc_tensor_args::call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size) { |
| 7163 | |
| 7164 | static auto op = create__validate_sparse_bsc_tensor_args_typed_handle(); |
| 7165 | return op.call(ccol_indices, row_indices, values, size); |
| 7166 | } |
| 7167 | |
| 7168 | // aten::_validate_sparse_bsc_tensor_args(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size) -> () |
| 7169 | void _validate_sparse_bsc_tensor_args::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size) { |
| 7170 | |
| 7171 | static auto op = create__validate_sparse_bsc_tensor_args_typed_handle(); |
| 7172 | return op.redispatch(dispatchKeySet, ccol_indices, row_indices, values, size); |
| 7173 | } |
| 7174 | |
| 7175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_, name, "aten::sparse_resize_") |
| 7176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_, overload_name, "") |
| 7177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_, schema_str, "sparse_resize_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!)") |
| 7178 | |
| 7179 | // aten::sparse_resize_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!) |
| 7180 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_resize_::schema> create_sparse_resize__typed_handle() { |
| 7181 | return c10::Dispatcher::singleton() |
| 7182 | .findSchemaOrThrow(sparse_resize_::name, sparse_resize_::overload_name) |
| 7183 | .typed<sparse_resize_::schema>(); |
| 7184 | } |
| 7185 | |
| 7186 | // aten::sparse_resize_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!) |
| 7187 | const at::Tensor & sparse_resize_::call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 7188 | |
| 7189 | static auto op = create_sparse_resize__typed_handle(); |
| 7190 | return op.call(self, size, sparse_dim, dense_dim); |
| 7191 | } |
| 7192 | |
| 7193 | // aten::sparse_resize_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!) |
| 7194 | const at::Tensor & sparse_resize_::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 7195 | |
| 7196 | static auto op = create_sparse_resize__typed_handle(); |
| 7197 | return op.redispatch(dispatchKeySet, self, size, sparse_dim, dense_dim); |
| 7198 | } |
| 7199 | |
| 7200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_mask, name, "aten::sparse_mask") |
| 7201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_mask, overload_name, "") |
| 7202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_mask, schema_str, "sparse_mask(Tensor self, Tensor mask) -> Tensor") |
| 7203 | |
| 7204 | // aten::sparse_mask(Tensor self, Tensor mask) -> Tensor |
| 7205 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_mask::schema> create_sparse_mask_typed_handle() { |
| 7206 | return c10::Dispatcher::singleton() |
| 7207 | .findSchemaOrThrow(sparse_mask::name, sparse_mask::overload_name) |
| 7208 | .typed<sparse_mask::schema>(); |
| 7209 | } |
| 7210 | |
| 7211 | // aten::sparse_mask(Tensor self, Tensor mask) -> Tensor |
| 7212 | at::Tensor sparse_mask::call(const at::Tensor & self, const at::Tensor & mask) { |
| 7213 | |
| 7214 | static auto op = create_sparse_mask_typed_handle(); |
| 7215 | return op.call(self, mask); |
| 7216 | } |
| 7217 | |
| 7218 | // aten::sparse_mask(Tensor self, Tensor mask) -> Tensor |
| 7219 | at::Tensor sparse_mask::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask) { |
| 7220 | |
| 7221 | static auto op = create_sparse_mask_typed_handle(); |
| 7222 | return op.redispatch(dispatchKeySet, self, mask); |
| 7223 | } |
| 7224 | |
| 7225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_cpu, name, "aten::_to_cpu") |
| 7226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_cpu, overload_name, "") |
| 7227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_cpu, schema_str, "_to_cpu(Tensor[] tensors) -> Tensor[]") |
| 7228 | |
| 7229 | // aten::_to_cpu(Tensor[] tensors) -> Tensor[] |
| 7230 | static C10_NOINLINE c10::TypedOperatorHandle<_to_cpu::schema> create__to_cpu_typed_handle() { |
| 7231 | return c10::Dispatcher::singleton() |
| 7232 | .findSchemaOrThrow(_to_cpu::name, _to_cpu::overload_name) |
| 7233 | .typed<_to_cpu::schema>(); |
| 7234 | } |
| 7235 | |
| 7236 | // aten::_to_cpu(Tensor[] tensors) -> Tensor[] |
| 7237 | ::std::vector<at::Tensor> _to_cpu::call(at::TensorList tensors) { |
| 7238 | |
| 7239 | static auto op = create__to_cpu_typed_handle(); |
| 7240 | return op.call(tensors); |
| 7241 | } |
| 7242 | |
| 7243 | // aten::_to_cpu(Tensor[] tensors) -> Tensor[] |
| 7244 | ::std::vector<at::Tensor> _to_cpu::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 7245 | |
| 7246 | static auto op = create__to_cpu_typed_handle(); |
| 7247 | return op.redispatch(dispatchKeySet, tensors); |
| 7248 | } |
| 7249 | |
| 7250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values, name, "aten::values") |
| 7251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values, overload_name, "") |
| 7252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values, schema_str, "values(Tensor(a) self) -> Tensor(a)") |
| 7253 | |
| 7254 | // aten::values(Tensor(a) self) -> Tensor(a) |
| 7255 | static C10_NOINLINE c10::TypedOperatorHandle<values::schema> create_values_typed_handle() { |
| 7256 | return c10::Dispatcher::singleton() |
| 7257 | .findSchemaOrThrow(values::name, values::overload_name) |
| 7258 | .typed<values::schema>(); |
| 7259 | } |
| 7260 | |
| 7261 | // aten::values(Tensor(a) self) -> Tensor(a) |
| 7262 | at::Tensor values::call(const at::Tensor & self) { |
| 7263 | |
| 7264 | static auto op = create_values_typed_handle(); |
| 7265 | return op.call(self); |
| 7266 | } |
| 7267 | |
| 7268 | // aten::values(Tensor(a) self) -> Tensor(a) |
| 7269 | at::Tensor values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7270 | |
| 7271 | static auto op = create_values_typed_handle(); |
| 7272 | return op.redispatch(dispatchKeySet, self); |
| 7273 | } |
| 7274 | |
| 7275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_indices, name, "aten::row_indices") |
| 7276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_indices, overload_name, "") |
| 7277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_indices, schema_str, "row_indices(Tensor(a) self) -> Tensor(a)") |
| 7278 | |
| 7279 | // aten::row_indices(Tensor(a) self) -> Tensor(a) |
| 7280 | static C10_NOINLINE c10::TypedOperatorHandle<row_indices::schema> create_row_indices_typed_handle() { |
| 7281 | return c10::Dispatcher::singleton() |
| 7282 | .findSchemaOrThrow(row_indices::name, row_indices::overload_name) |
| 7283 | .typed<row_indices::schema>(); |
| 7284 | } |
| 7285 | |
| 7286 | // aten::row_indices(Tensor(a) self) -> Tensor(a) |
| 7287 | at::Tensor row_indices::call(const at::Tensor & self) { |
| 7288 | |
| 7289 | static auto op = create_row_indices_typed_handle(); |
| 7290 | return op.call(self); |
| 7291 | } |
| 7292 | |
| 7293 | // aten::row_indices(Tensor(a) self) -> Tensor(a) |
| 7294 | at::Tensor row_indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7295 | |
| 7296 | static auto op = create_row_indices_typed_handle(); |
| 7297 | return op.redispatch(dispatchKeySet, self); |
| 7298 | } |
| 7299 | |
| 7300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse_, name, "aten::copy_sparse_to_sparse_") |
| 7301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse_, overload_name, "") |
| 7302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse_, schema_str, "copy_sparse_to_sparse_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!)") |
| 7303 | |
| 7304 | // aten::copy_sparse_to_sparse_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!) |
| 7305 | static C10_NOINLINE c10::TypedOperatorHandle<copy_sparse_to_sparse_::schema> create_copy_sparse_to_sparse__typed_handle() { |
| 7306 | return c10::Dispatcher::singleton() |
| 7307 | .findSchemaOrThrow(copy_sparse_to_sparse_::name, copy_sparse_to_sparse_::overload_name) |
| 7308 | .typed<copy_sparse_to_sparse_::schema>(); |
| 7309 | } |
| 7310 | |
| 7311 | // aten::copy_sparse_to_sparse_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!) |
| 7312 | at::Tensor & copy_sparse_to_sparse_::call(at::Tensor & self, const at::Tensor & src, bool non_blocking) { |
| 7313 | |
| 7314 | static auto op = create_copy_sparse_to_sparse__typed_handle(); |
| 7315 | return op.call(self, src, non_blocking); |
| 7316 | } |
| 7317 | |
| 7318 | // aten::copy_sparse_to_sparse_(Tensor(a!) self, Tensor src, bool non_blocking=False) -> Tensor(a!) |
| 7319 | at::Tensor & copy_sparse_to_sparse_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & src, bool non_blocking) { |
| 7320 | |
| 7321 | static auto op = create_copy_sparse_to_sparse__typed_handle(); |
| 7322 | return op.redispatch(dispatchKeySet, self, src, non_blocking); |
| 7323 | } |
| 7324 | |
| 7325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_int, name, "aten::unbind") |
| 7326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_int, overload_name, "int") |
| 7327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_int, schema_str, "unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[]") |
| 7328 | |
| 7329 | // aten::unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[] |
| 7330 | static C10_NOINLINE c10::TypedOperatorHandle<unbind_int::schema> create_unbind_int_typed_handle() { |
| 7331 | return c10::Dispatcher::singleton() |
| 7332 | .findSchemaOrThrow(unbind_int::name, unbind_int::overload_name) |
| 7333 | .typed<unbind_int::schema>(); |
| 7334 | } |
| 7335 | |
| 7336 | // aten::unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[] |
| 7337 | ::std::vector<at::Tensor> unbind_int::call(const at::Tensor & self, int64_t dim) { |
| 7338 | |
| 7339 | static auto op = create_unbind_int_typed_handle(); |
| 7340 | return op.call(self, dim); |
| 7341 | } |
| 7342 | |
| 7343 | // aten::unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[] |
| 7344 | ::std::vector<at::Tensor> unbind_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim) { |
| 7345 | |
| 7346 | static auto op = create_unbind_int_typed_handle(); |
| 7347 | return op.redispatch(dispatchKeySet, self, dim); |
| 7348 | } |
| 7349 | |
| 7350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_Dimname, name, "aten::unbind") |
| 7351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_Dimname, overload_name, "Dimname") |
| 7352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_Dimname, schema_str, "unbind.Dimname(Tensor(a -> *) self, Dimname dim) -> Tensor(a)[]") |
| 7353 | |
| 7354 | // aten::unbind.Dimname(Tensor(a -> *) self, Dimname dim) -> Tensor(a)[] |
| 7355 | static C10_NOINLINE c10::TypedOperatorHandle<unbind_Dimname::schema> create_unbind_Dimname_typed_handle() { |
| 7356 | return c10::Dispatcher::singleton() |
| 7357 | .findSchemaOrThrow(unbind_Dimname::name, unbind_Dimname::overload_name) |
| 7358 | .typed<unbind_Dimname::schema>(); |
| 7359 | } |
| 7360 | |
| 7361 | // aten::unbind.Dimname(Tensor(a -> *) self, Dimname dim) -> Tensor(a)[] |
| 7362 | ::std::vector<at::Tensor> unbind_Dimname::call(const at::Tensor & self, at::Dimname dim) { |
| 7363 | |
| 7364 | static auto op = create_unbind_Dimname_typed_handle(); |
| 7365 | return op.call(self, dim); |
| 7366 | } |
| 7367 | |
| 7368 | // aten::unbind.Dimname(Tensor(a -> *) self, Dimname dim) -> Tensor(a)[] |
| 7369 | ::std::vector<at::Tensor> unbind_Dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim) { |
| 7370 | |
| 7371 | static auto op = create_unbind_Dimname_typed_handle(); |
| 7372 | return op.redispatch(dispatchKeySet, self, dim); |
| 7373 | } |
| 7374 | |
| 7375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_sparse_dim, name, "aten::to_sparse") |
| 7376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_sparse_dim, overload_name, "sparse_dim") |
| 7377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_sparse_dim, schema_str, "to_sparse.sparse_dim(Tensor self, int sparse_dim) -> Tensor") |
| 7378 | |
| 7379 | // aten::to_sparse.sparse_dim(Tensor self, int sparse_dim) -> Tensor |
| 7380 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_sparse_dim::schema> create_to_sparse_sparse_dim_typed_handle() { |
| 7381 | return c10::Dispatcher::singleton() |
| 7382 | .findSchemaOrThrow(to_sparse_sparse_dim::name, to_sparse_sparse_dim::overload_name) |
| 7383 | .typed<to_sparse_sparse_dim::schema>(); |
| 7384 | } |
| 7385 | |
| 7386 | // aten::to_sparse.sparse_dim(Tensor self, int sparse_dim) -> Tensor |
| 7387 | at::Tensor to_sparse_sparse_dim::call(const at::Tensor & self, int64_t sparse_dim) { |
| 7388 | |
| 7389 | static auto op = create_to_sparse_sparse_dim_typed_handle(); |
| 7390 | return op.call(self, sparse_dim); |
| 7391 | } |
| 7392 | |
| 7393 | // aten::to_sparse.sparse_dim(Tensor self, int sparse_dim) -> Tensor |
| 7394 | at::Tensor to_sparse_sparse_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t sparse_dim) { |
| 7395 | |
| 7396 | static auto op = create_to_sparse_sparse_dim_typed_handle(); |
| 7397 | return op.redispatch(dispatchKeySet, self, sparse_dim); |
| 7398 | } |
| 7399 | |
| 7400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse, name, "aten::to_sparse") |
| 7401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse, overload_name, "") |
| 7402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse, schema_str, "to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor") |
| 7403 | |
| 7404 | // aten::to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor |
| 7405 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse::schema> create_to_sparse_typed_handle() { |
| 7406 | return c10::Dispatcher::singleton() |
| 7407 | .findSchemaOrThrow(to_sparse::name, to_sparse::overload_name) |
| 7408 | .typed<to_sparse::schema>(); |
| 7409 | } |
| 7410 | |
| 7411 | // aten::to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor |
| 7412 | at::Tensor to_sparse::call(const at::Tensor & self, c10::optional<at::Layout> layout, at::OptionalIntArrayRef blocksize, c10::optional<int64_t> dense_dim) { |
| 7413 | |
| 7414 | static auto op = create_to_sparse_typed_handle(); |
| 7415 | return op.call(self, layout, blocksize, dense_dim); |
| 7416 | } |
| 7417 | |
| 7418 | // aten::to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor |
| 7419 | at::Tensor to_sparse::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Layout> layout, at::OptionalIntArrayRef blocksize, c10::optional<int64_t> dense_dim) { |
| 7420 | |
| 7421 | static auto op = create_to_sparse_typed_handle(); |
| 7422 | return op.redispatch(dispatchKeySet, self, layout, blocksize, dense_dim); |
| 7423 | } |
| 7424 | |
| 7425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn, name, "aten::to_mkldnn") |
| 7426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn, overload_name, "") |
| 7427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn, schema_str, "to_mkldnn(Tensor self, ScalarType? dtype=None) -> Tensor") |
| 7428 | |
| 7429 | // aten::to_mkldnn(Tensor self, ScalarType? dtype=None) -> Tensor |
| 7430 | static C10_NOINLINE c10::TypedOperatorHandle<to_mkldnn::schema> create_to_mkldnn_typed_handle() { |
| 7431 | return c10::Dispatcher::singleton() |
| 7432 | .findSchemaOrThrow(to_mkldnn::name, to_mkldnn::overload_name) |
| 7433 | .typed<to_mkldnn::schema>(); |
| 7434 | } |
| 7435 | |
| 7436 | // aten::to_mkldnn(Tensor self, ScalarType? dtype=None) -> Tensor |
| 7437 | at::Tensor to_mkldnn::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
| 7438 | |
| 7439 | static auto op = create_to_mkldnn_typed_handle(); |
| 7440 | return op.call(self, dtype); |
| 7441 | } |
| 7442 | |
| 7443 | // aten::to_mkldnn(Tensor self, ScalarType? dtype=None) -> Tensor |
| 7444 | at::Tensor to_mkldnn::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
| 7445 | |
| 7446 | static auto op = create_to_mkldnn_typed_handle(); |
| 7447 | return op.redispatch(dispatchKeySet, self, dtype); |
| 7448 | } |
| 7449 | |
| 7450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn_backward, name, "aten::to_mkldnn_backward") |
| 7451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn_backward, overload_name, "") |
| 7452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn_backward, schema_str, "to_mkldnn_backward(Tensor grad, Tensor input) -> Tensor") |
| 7453 | |
| 7454 | // aten::to_mkldnn_backward(Tensor grad, Tensor input) -> Tensor |
| 7455 | static C10_NOINLINE c10::TypedOperatorHandle<to_mkldnn_backward::schema> create_to_mkldnn_backward_typed_handle() { |
| 7456 | return c10::Dispatcher::singleton() |
| 7457 | .findSchemaOrThrow(to_mkldnn_backward::name, to_mkldnn_backward::overload_name) |
| 7458 | .typed<to_mkldnn_backward::schema>(); |
| 7459 | } |
| 7460 | |
| 7461 | // aten::to_mkldnn_backward(Tensor grad, Tensor input) -> Tensor |
| 7462 | at::Tensor to_mkldnn_backward::call(const at::Tensor & grad, const at::Tensor & input) { |
| 7463 | |
| 7464 | static auto op = create_to_mkldnn_backward_typed_handle(); |
| 7465 | return op.call(grad, input); |
| 7466 | } |
| 7467 | |
| 7468 | // aten::to_mkldnn_backward(Tensor grad, Tensor input) -> Tensor |
| 7469 | at::Tensor to_mkldnn_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & input) { |
| 7470 | |
| 7471 | static auto op = create_to_mkldnn_backward_typed_handle(); |
| 7472 | return op.redispatch(dispatchKeySet, grad, input); |
| 7473 | } |
| 7474 | |
| 7475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(int_repr, name, "aten::int_repr") |
| 7476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(int_repr, overload_name, "") |
| 7477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(int_repr, schema_str, "int_repr(Tensor self) -> Tensor") |
| 7478 | |
| 7479 | // aten::int_repr(Tensor self) -> Tensor |
| 7480 | static C10_NOINLINE c10::TypedOperatorHandle<int_repr::schema> create_int_repr_typed_handle() { |
| 7481 | return c10::Dispatcher::singleton() |
| 7482 | .findSchemaOrThrow(int_repr::name, int_repr::overload_name) |
| 7483 | .typed<int_repr::schema>(); |
| 7484 | } |
| 7485 | |
| 7486 | // aten::int_repr(Tensor self) -> Tensor |
| 7487 | at::Tensor int_repr::call(const at::Tensor & self) { |
| 7488 | |
| 7489 | static auto op = create_int_repr_typed_handle(); |
| 7490 | return op.call(self); |
| 7491 | } |
| 7492 | |
| 7493 | // aten::int_repr(Tensor self) -> Tensor |
| 7494 | at::Tensor int_repr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7495 | |
| 7496 | static auto op = create_int_repr_typed_handle(); |
| 7497 | return op.redispatch(dispatchKeySet, self); |
| 7498 | } |
| 7499 | |
| 7500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(qscheme, name, "aten::qscheme") |
| 7501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(qscheme, overload_name, "") |
| 7502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(qscheme, schema_str, "qscheme(Tensor self) -> QScheme") |
| 7503 | |
| 7504 | // aten::qscheme(Tensor self) -> QScheme |
| 7505 | static C10_NOINLINE c10::TypedOperatorHandle<qscheme::schema> create_qscheme_typed_handle() { |
| 7506 | return c10::Dispatcher::singleton() |
| 7507 | .findSchemaOrThrow(qscheme::name, qscheme::overload_name) |
| 7508 | .typed<qscheme::schema>(); |
| 7509 | } |
| 7510 | |
| 7511 | // aten::qscheme(Tensor self) -> QScheme |
| 7512 | at::QScheme qscheme::call(const at::Tensor & self) { |
| 7513 | |
| 7514 | static auto op = create_qscheme_typed_handle(); |
| 7515 | return op.call(self); |
| 7516 | } |
| 7517 | |
| 7518 | // aten::qscheme(Tensor self) -> QScheme |
| 7519 | at::QScheme qscheme::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7520 | |
| 7521 | static auto op = create_qscheme_typed_handle(); |
| 7522 | return op.redispatch(dispatchKeySet, self); |
| 7523 | } |
| 7524 | |
| 7525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine, name, "aten::fake_quantize_per_channel_affine") |
| 7526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine, overload_name, "") |
| 7527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine, schema_str, "fake_quantize_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> Tensor") |
| 7528 | |
| 7529 | // aten::fake_quantize_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> Tensor |
| 7530 | static C10_NOINLINE c10::TypedOperatorHandle<fake_quantize_per_channel_affine::schema> create_fake_quantize_per_channel_affine_typed_handle() { |
| 7531 | return c10::Dispatcher::singleton() |
| 7532 | .findSchemaOrThrow(fake_quantize_per_channel_affine::name, fake_quantize_per_channel_affine::overload_name) |
| 7533 | .typed<fake_quantize_per_channel_affine::schema>(); |
| 7534 | } |
| 7535 | |
| 7536 | // aten::fake_quantize_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> Tensor |
| 7537 | at::Tensor fake_quantize_per_channel_affine::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max) { |
| 7538 | |
| 7539 | static auto op = create_fake_quantize_per_channel_affine_typed_handle(); |
| 7540 | return op.call(self, scale, zero_point, axis, quant_min, quant_max); |
| 7541 | } |
| 7542 | |
| 7543 | // aten::fake_quantize_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> Tensor |
| 7544 | at::Tensor fake_quantize_per_channel_affine::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max) { |
| 7545 | |
| 7546 | static auto op = create_fake_quantize_per_channel_affine_typed_handle(); |
| 7547 | return op.redispatch(dispatchKeySet, self, scale, zero_point, axis, quant_min, quant_max); |
| 7548 | } |
| 7549 | |
| 7550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask, name, "aten::fake_quantize_per_channel_affine_cachemask") |
| 7551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask, overload_name, "") |
| 7552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask, schema_str, "fake_quantize_per_channel_affine_cachemask(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> (Tensor output, Tensor mask)") |
| 7553 | |
| 7554 | // aten::fake_quantize_per_channel_affine_cachemask(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
| 7555 | static C10_NOINLINE c10::TypedOperatorHandle<fake_quantize_per_channel_affine_cachemask::schema> create_fake_quantize_per_channel_affine_cachemask_typed_handle() { |
| 7556 | return c10::Dispatcher::singleton() |
| 7557 | .findSchemaOrThrow(fake_quantize_per_channel_affine_cachemask::name, fake_quantize_per_channel_affine_cachemask::overload_name) |
| 7558 | .typed<fake_quantize_per_channel_affine_cachemask::schema>(); |
| 7559 | } |
| 7560 | |
| 7561 | // aten::fake_quantize_per_channel_affine_cachemask(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
| 7562 | ::std::tuple<at::Tensor,at::Tensor> fake_quantize_per_channel_affine_cachemask::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max) { |
| 7563 | |
| 7564 | static auto op = create_fake_quantize_per_channel_affine_cachemask_typed_handle(); |
| 7565 | return op.call(self, scale, zero_point, axis, quant_min, quant_max); |
| 7566 | } |
| 7567 | |
| 7568 | // aten::fake_quantize_per_channel_affine_cachemask(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
| 7569 | ::std::tuple<at::Tensor,at::Tensor> fake_quantize_per_channel_affine_cachemask::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max) { |
| 7570 | |
| 7571 | static auto op = create_fake_quantize_per_channel_affine_cachemask_typed_handle(); |
| 7572 | return op.redispatch(dispatchKeySet, self, scale, zero_point, axis, quant_min, quant_max); |
| 7573 | } |
| 7574 | |
| 7575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper, name, "aten::_fused_moving_avg_obs_fq_helper") |
| 7576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper, overload_name, "") |
| 7577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper, schema_str, "_fused_moving_avg_obs_fq_helper(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask)") |
| 7578 | |
| 7579 | // aten::_fused_moving_avg_obs_fq_helper(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask) |
| 7580 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_moving_avg_obs_fq_helper::schema> create__fused_moving_avg_obs_fq_helper_typed_handle() { |
| 7581 | return c10::Dispatcher::singleton() |
| 7582 | .findSchemaOrThrow(_fused_moving_avg_obs_fq_helper::name, _fused_moving_avg_obs_fq_helper::overload_name) |
| 7583 | .typed<_fused_moving_avg_obs_fq_helper::schema>(); |
| 7584 | } |
| 7585 | |
| 7586 | // aten::_fused_moving_avg_obs_fq_helper(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask) |
| 7587 | ::std::tuple<at::Tensor,at::Tensor> _fused_moving_avg_obs_fq_helper::call(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant) { |
| 7588 | |
| 7589 | static auto op = create__fused_moving_avg_obs_fq_helper_typed_handle(); |
| 7590 | return op.call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); |
| 7591 | } |
| 7592 | |
| 7593 | // aten::_fused_moving_avg_obs_fq_helper(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask) |
| 7594 | ::std::tuple<at::Tensor,at::Tensor> _fused_moving_avg_obs_fq_helper::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant) { |
| 7595 | |
| 7596 | static auto op = create__fused_moving_avg_obs_fq_helper_typed_handle(); |
| 7597 | return op.redispatch(dispatchKeySet, self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); |
| 7598 | } |
| 7599 | |
| 7600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_copy, name, "aten::_to_copy") |
| 7601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_copy, overload_name, "") |
| 7602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_copy, schema_str, "_to_copy(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, bool non_blocking=False, MemoryFormat? memory_format=None) -> Tensor") |
| 7603 | |
| 7604 | // aten::_to_copy(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, bool non_blocking=False, MemoryFormat? memory_format=None) -> Tensor |
| 7605 | static C10_NOINLINE c10::TypedOperatorHandle<_to_copy::schema> create__to_copy_typed_handle() { |
| 7606 | return c10::Dispatcher::singleton() |
| 7607 | .findSchemaOrThrow(_to_copy::name, _to_copy::overload_name) |
| 7608 | .typed<_to_copy::schema>(); |
| 7609 | } |
| 7610 | |
| 7611 | // aten::_to_copy(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, bool non_blocking=False, MemoryFormat? memory_format=None) -> Tensor |
| 7612 | at::Tensor _to_copy::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, bool non_blocking, c10::optional<at::MemoryFormat> memory_format) { |
| 7613 | |
| 7614 | static auto op = create__to_copy_typed_handle(); |
| 7615 | return op.call(self, dtype, layout, device, pin_memory, non_blocking, memory_format); |
| 7616 | } |
| 7617 | |
| 7618 | // aten::_to_copy(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, bool non_blocking=False, MemoryFormat? memory_format=None) -> Tensor |
| 7619 | at::Tensor _to_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, bool non_blocking, c10::optional<at::MemoryFormat> memory_format) { |
| 7620 | |
| 7621 | static auto op = create__to_copy_typed_handle(); |
| 7622 | return op.redispatch(dispatchKeySet, self, dtype, layout, device, pin_memory, non_blocking, memory_format); |
| 7623 | } |
| 7624 | |
| 7625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_differentiable_lstm_cell_backward, name, "aten::_thnn_differentiable_lstm_cell_backward") |
| 7626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_differentiable_lstm_cell_backward, overload_name, "") |
| 7627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_differentiable_lstm_cell_backward, schema_str, "_thnn_differentiable_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor input_gates, Tensor hidden_gates, Tensor? input_bias, Tensor? hidden_bias, Tensor cx, Tensor cy) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") |
| 7628 | |
| 7629 | // aten::_thnn_differentiable_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor input_gates, Tensor hidden_gates, Tensor? input_bias, Tensor? hidden_bias, Tensor cx, Tensor cy) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 7630 | static C10_NOINLINE c10::TypedOperatorHandle<_thnn_differentiable_lstm_cell_backward::schema> create__thnn_differentiable_lstm_cell_backward_typed_handle() { |
| 7631 | return c10::Dispatcher::singleton() |
| 7632 | .findSchemaOrThrow(_thnn_differentiable_lstm_cell_backward::name, _thnn_differentiable_lstm_cell_backward::overload_name) |
| 7633 | .typed<_thnn_differentiable_lstm_cell_backward::schema>(); |
| 7634 | } |
| 7635 | |
| 7636 | // aten::_thnn_differentiable_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor input_gates, Tensor hidden_gates, Tensor? input_bias, Tensor? hidden_bias, Tensor cx, Tensor cy) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 7637 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_differentiable_lstm_cell_backward::call(const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const c10::optional<at::Tensor> & input_bias, const c10::optional<at::Tensor> & hidden_bias, const at::Tensor & cx, const at::Tensor & cy) { |
| 7638 | |
| 7639 | static auto op = create__thnn_differentiable_lstm_cell_backward_typed_handle(); |
| 7640 | return op.call(grad_hy, grad_cy, input_gates, hidden_gates, input_bias, hidden_bias, cx, cy); |
| 7641 | } |
| 7642 | |
| 7643 | // aten::_thnn_differentiable_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor input_gates, Tensor hidden_gates, Tensor? input_bias, Tensor? hidden_bias, Tensor cx, Tensor cy) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 7644 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_differentiable_lstm_cell_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const c10::optional<at::Tensor> & input_bias, const c10::optional<at::Tensor> & hidden_bias, const at::Tensor & cx, const at::Tensor & cy) { |
| 7645 | |
| 7646 | static auto op = create__thnn_differentiable_lstm_cell_backward_typed_handle(); |
| 7647 | return op.redispatch(dispatchKeySet, grad_hy, grad_cy, input_gates, hidden_gates, input_bias, hidden_bias, cx, cy); |
| 7648 | } |
| 7649 | |
| 7650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_differentiable_gru_cell_backward, name, "aten::_thnn_differentiable_gru_cell_backward") |
| 7651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_differentiable_gru_cell_backward, overload_name, "") |
| 7652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_differentiable_gru_cell_backward, schema_str, "_thnn_differentiable_gru_cell_backward(Tensor grad_hy, Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias, Tensor? hidden_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") |
| 7653 | |
| 7654 | // aten::_thnn_differentiable_gru_cell_backward(Tensor grad_hy, Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias, Tensor? hidden_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 7655 | static C10_NOINLINE c10::TypedOperatorHandle<_thnn_differentiable_gru_cell_backward::schema> create__thnn_differentiable_gru_cell_backward_typed_handle() { |
| 7656 | return c10::Dispatcher::singleton() |
| 7657 | .findSchemaOrThrow(_thnn_differentiable_gru_cell_backward::name, _thnn_differentiable_gru_cell_backward::overload_name) |
| 7658 | .typed<_thnn_differentiable_gru_cell_backward::schema>(); |
| 7659 | } |
| 7660 | |
| 7661 | // aten::_thnn_differentiable_gru_cell_backward(Tensor grad_hy, Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias, Tensor? hidden_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 7662 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_differentiable_gru_cell_backward::call(const at::Tensor & grad_hy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const c10::optional<at::Tensor> & input_bias, const c10::optional<at::Tensor> & hidden_bias) { |
| 7663 | |
| 7664 | static auto op = create__thnn_differentiable_gru_cell_backward_typed_handle(); |
| 7665 | return op.call(grad_hy, input_gates, hidden_gates, hx, input_bias, hidden_bias); |
| 7666 | } |
| 7667 | |
| 7668 | // aten::_thnn_differentiable_gru_cell_backward(Tensor grad_hy, Tensor input_gates, Tensor hidden_gates, Tensor hx, Tensor? input_bias, Tensor? hidden_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 7669 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_differentiable_gru_cell_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_hy, const at::Tensor & input_gates, const at::Tensor & hidden_gates, const at::Tensor & hx, const c10::optional<at::Tensor> & input_bias, const c10::optional<at::Tensor> & hidden_bias) { |
| 7670 | |
| 7671 | static auto op = create__thnn_differentiable_gru_cell_backward_typed_handle(); |
| 7672 | return op.redispatch(dispatchKeySet, grad_hy, input_gates, hidden_gates, hx, input_bias, hidden_bias); |
| 7673 | } |
| 7674 | |
| 7675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_tanh_cell, name, "aten::rnn_tanh_cell") |
| 7676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_tanh_cell, overload_name, "") |
| 7677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_tanh_cell, schema_str, "rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor") |
| 7678 | |
| 7679 | // aten::rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor |
| 7680 | static C10_NOINLINE c10::TypedOperatorHandle<rnn_tanh_cell::schema> create_rnn_tanh_cell_typed_handle() { |
| 7681 | return c10::Dispatcher::singleton() |
| 7682 | .findSchemaOrThrow(rnn_tanh_cell::name, rnn_tanh_cell::overload_name) |
| 7683 | .typed<rnn_tanh_cell::schema>(); |
| 7684 | } |
| 7685 | |
| 7686 | // aten::rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor |
| 7687 | at::Tensor rnn_tanh_cell::call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const c10::optional<at::Tensor> & b_ih, const c10::optional<at::Tensor> & b_hh) { |
| 7688 | |
| 7689 | static auto op = create_rnn_tanh_cell_typed_handle(); |
| 7690 | return op.call(input, hx, w_ih, w_hh, b_ih, b_hh); |
| 7691 | } |
| 7692 | |
| 7693 | // aten::rnn_tanh_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor |
| 7694 | at::Tensor rnn_tanh_cell::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const c10::optional<at::Tensor> & b_ih, const c10::optional<at::Tensor> & b_hh) { |
| 7695 | |
| 7696 | static auto op = create_rnn_tanh_cell_typed_handle(); |
| 7697 | return op.redispatch(dispatchKeySet, input, hx, w_ih, w_hh, b_ih, b_hh); |
| 7698 | } |
| 7699 | |
| 7700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_gru_cell, name, "aten::quantized_gru_cell") |
| 7701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_gru_cell, overload_name, "") |
| 7702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_gru_cell, schema_str, "quantized_gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor") |
| 7703 | |
| 7704 | // aten::quantized_gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor |
| 7705 | static C10_NOINLINE c10::TypedOperatorHandle<quantized_gru_cell::schema> create_quantized_gru_cell_typed_handle() { |
| 7706 | return c10::Dispatcher::singleton() |
| 7707 | .findSchemaOrThrow(quantized_gru_cell::name, quantized_gru_cell::overload_name) |
| 7708 | .typed<quantized_gru_cell::schema>(); |
| 7709 | } |
| 7710 | |
| 7711 | // aten::quantized_gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor |
| 7712 | at::Tensor quantized_gru_cell::call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh) { |
| 7713 | |
| 7714 | static auto op = create_quantized_gru_cell_typed_handle(); |
| 7715 | return op.call(input, hx, w_ih, w_hh, b_ih, b_hh, packed_ih, packed_hh, col_offsets_ih, col_offsets_hh, scale_ih, scale_hh, zero_point_ih, zero_point_hh); |
| 7716 | } |
| 7717 | |
| 7718 | // aten::quantized_gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor b_ih, Tensor b_hh, Tensor packed_ih, Tensor packed_hh, Tensor col_offsets_ih, Tensor col_offsets_hh, Scalar scale_ih, Scalar scale_hh, Scalar zero_point_ih, Scalar zero_point_hh) -> Tensor |
| 7719 | at::Tensor quantized_gru_cell::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const at::Tensor & b_ih, const at::Tensor & b_hh, const at::Tensor & packed_ih, const at::Tensor & packed_hh, const at::Tensor & col_offsets_ih, const at::Tensor & col_offsets_hh, const at::Scalar & scale_ih, const at::Scalar & scale_hh, const at::Scalar & zero_point_ih, const at::Scalar & zero_point_hh) { |
| 7720 | |
| 7721 | static auto op = create_quantized_gru_cell_typed_handle(); |
| 7722 | return op.redispatch(dispatchKeySet, input, hx, w_ih, w_hh, b_ih, b_hh, packed_ih, packed_hh, col_offsets_ih, col_offsets_hh, scale_ih, scale_hh, zero_point_ih, zero_point_hh); |
| 7723 | } |
| 7724 | |
| 7725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pack_padded_sequence_backward, name, "aten::_pack_padded_sequence_backward") |
| 7726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pack_padded_sequence_backward, overload_name, "") |
| 7727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pack_padded_sequence_backward, schema_str, "_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor") |
| 7728 | |
| 7729 | // aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor |
| 7730 | static C10_NOINLINE c10::TypedOperatorHandle<_pack_padded_sequence_backward::schema> create__pack_padded_sequence_backward_typed_handle() { |
| 7731 | return c10::Dispatcher::singleton() |
| 7732 | .findSchemaOrThrow(_pack_padded_sequence_backward::name, _pack_padded_sequence_backward::overload_name) |
| 7733 | .typed<_pack_padded_sequence_backward::schema>(); |
| 7734 | } |
| 7735 | |
| 7736 | // aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor |
| 7737 | at::Tensor _pack_padded_sequence_backward::call(const at::Tensor & grad, c10::SymIntArrayRef input_size, const at::Tensor & batch_sizes, bool batch_first) { |
| 7738 | |
| 7739 | static auto op = create__pack_padded_sequence_backward_typed_handle(); |
| 7740 | return op.call(grad, input_size, batch_sizes, batch_first); |
| 7741 | } |
| 7742 | |
| 7743 | // aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor |
| 7744 | at::Tensor _pack_padded_sequence_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, c10::SymIntArrayRef input_size, const at::Tensor & batch_sizes, bool batch_first) { |
| 7745 | |
| 7746 | static auto op = create__pack_padded_sequence_backward_typed_handle(); |
| 7747 | return op.redispatch(dispatchKeySet, grad, input_size, batch_sizes, batch_first); |
| 7748 | } |
| 7749 | |
| 7750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift, name, "aten::lift") |
| 7751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift, overload_name, "") |
| 7752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift, schema_str, "lift(Tensor self) -> Tensor") |
| 7753 | |
| 7754 | // aten::lift(Tensor self) -> Tensor |
| 7755 | static C10_NOINLINE c10::TypedOperatorHandle<lift::schema> create_lift_typed_handle() { |
| 7756 | return c10::Dispatcher::singleton() |
| 7757 | .findSchemaOrThrow(lift::name, lift::overload_name) |
| 7758 | .typed<lift::schema>(); |
| 7759 | } |
| 7760 | |
| 7761 | // aten::lift(Tensor self) -> Tensor |
| 7762 | at::Tensor lift::call(const at::Tensor & self) { |
| 7763 | |
| 7764 | static auto op = create_lift_typed_handle(); |
| 7765 | return op.call(self); |
| 7766 | } |
| 7767 | |
| 7768 | // aten::lift(Tensor self) -> Tensor |
| 7769 | at::Tensor lift::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7770 | |
| 7771 | static auto op = create_lift_typed_handle(); |
| 7772 | return op.redispatch(dispatchKeySet, self); |
| 7773 | } |
| 7774 | |
| 7775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift_fresh, name, "aten::lift_fresh") |
| 7776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift_fresh, overload_name, "") |
| 7777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift_fresh, schema_str, "lift_fresh(Tensor(a) self) -> Tensor(a)") |
| 7778 | |
| 7779 | // aten::lift_fresh(Tensor(a) self) -> Tensor(a) |
| 7780 | static C10_NOINLINE c10::TypedOperatorHandle<lift_fresh::schema> create_lift_fresh_typed_handle() { |
| 7781 | return c10::Dispatcher::singleton() |
| 7782 | .findSchemaOrThrow(lift_fresh::name, lift_fresh::overload_name) |
| 7783 | .typed<lift_fresh::schema>(); |
| 7784 | } |
| 7785 | |
| 7786 | // aten::lift_fresh(Tensor(a) self) -> Tensor(a) |
| 7787 | at::Tensor lift_fresh::call(const at::Tensor & self) { |
| 7788 | |
| 7789 | static auto op = create_lift_fresh_typed_handle(); |
| 7790 | return op.call(self); |
| 7791 | } |
| 7792 | |
| 7793 | // aten::lift_fresh(Tensor(a) self) -> Tensor(a) |
| 7794 | at::Tensor lift_fresh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7795 | |
| 7796 | static auto op = create_lift_fresh_typed_handle(); |
| 7797 | return op.redispatch(dispatchKeySet, self); |
| 7798 | } |
| 7799 | |
| 7800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq__Scalar, name, "aten::eq_") |
| 7801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq__Scalar, overload_name, "Scalar") |
| 7802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq__Scalar, schema_str, "eq_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 7803 | |
| 7804 | // aten::eq_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7805 | static C10_NOINLINE c10::TypedOperatorHandle<eq__Scalar::schema> create_eq__Scalar_typed_handle() { |
| 7806 | return c10::Dispatcher::singleton() |
| 7807 | .findSchemaOrThrow(eq__Scalar::name, eq__Scalar::overload_name) |
| 7808 | .typed<eq__Scalar::schema>(); |
| 7809 | } |
| 7810 | |
| 7811 | // aten::eq_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7812 | at::Tensor & eq__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 7813 | |
| 7814 | static auto op = create_eq__Scalar_typed_handle(); |
| 7815 | return op.call(self, other); |
| 7816 | } |
| 7817 | |
| 7818 | // aten::eq_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7819 | at::Tensor & eq__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 7820 | |
| 7821 | static auto op = create_eq__Scalar_typed_handle(); |
| 7822 | return op.redispatch(dispatchKeySet, self, other); |
| 7823 | } |
| 7824 | |
| 7825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq__Tensor, name, "aten::eq_") |
| 7826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq__Tensor, overload_name, "Tensor") |
| 7827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq__Tensor, schema_str, "eq_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 7828 | |
| 7829 | // aten::eq_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7830 | static C10_NOINLINE c10::TypedOperatorHandle<eq__Tensor::schema> create_eq__Tensor_typed_handle() { |
| 7831 | return c10::Dispatcher::singleton() |
| 7832 | .findSchemaOrThrow(eq__Tensor::name, eq__Tensor::overload_name) |
| 7833 | .typed<eq__Tensor::schema>(); |
| 7834 | } |
| 7835 | |
| 7836 | // aten::eq_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7837 | at::Tensor & eq__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 7838 | |
| 7839 | static auto op = create_eq__Tensor_typed_handle(); |
| 7840 | return op.call(self, other); |
| 7841 | } |
| 7842 | |
| 7843 | // aten::eq_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7844 | at::Tensor & eq__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 7845 | |
| 7846 | static auto op = create_eq__Tensor_typed_handle(); |
| 7847 | return op.redispatch(dispatchKeySet, self, other); |
| 7848 | } |
| 7849 | |
| 7850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Tensor_out, name, "aten::bitwise_and") |
| 7851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Tensor_out, overload_name, "Tensor_out") |
| 7852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Tensor_out, schema_str, "bitwise_and.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 7853 | |
| 7854 | // aten::bitwise_and.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7855 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and_Tensor_out::schema> create_bitwise_and_Tensor_out_typed_handle() { |
| 7856 | return c10::Dispatcher::singleton() |
| 7857 | .findSchemaOrThrow(bitwise_and_Tensor_out::name, bitwise_and_Tensor_out::overload_name) |
| 7858 | .typed<bitwise_and_Tensor_out::schema>(); |
| 7859 | } |
| 7860 | |
| 7861 | // aten::bitwise_and.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7862 | at::Tensor & bitwise_and_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 7863 | |
| 7864 | static auto op = create_bitwise_and_Tensor_out_typed_handle(); |
| 7865 | return op.call(self, other, out); |
| 7866 | } |
| 7867 | |
| 7868 | // aten::bitwise_and.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7869 | at::Tensor & bitwise_and_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 7870 | |
| 7871 | static auto op = create_bitwise_and_Tensor_out_typed_handle(); |
| 7872 | return op.redispatch(dispatchKeySet, self, other, out); |
| 7873 | } |
| 7874 | |
| 7875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_out, name, "aten::bitwise_and") |
| 7876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_out, overload_name, "Scalar_out") |
| 7877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_out, schema_str, "bitwise_and.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 7878 | |
| 7879 | // aten::bitwise_and.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7880 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and_Scalar_out::schema> create_bitwise_and_Scalar_out_typed_handle() { |
| 7881 | return c10::Dispatcher::singleton() |
| 7882 | .findSchemaOrThrow(bitwise_and_Scalar_out::name, bitwise_and_Scalar_out::overload_name) |
| 7883 | .typed<bitwise_and_Scalar_out::schema>(); |
| 7884 | } |
| 7885 | |
| 7886 | // aten::bitwise_and.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7887 | at::Tensor & bitwise_and_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 7888 | |
| 7889 | static auto op = create_bitwise_and_Scalar_out_typed_handle(); |
| 7890 | return op.call(self, other, out); |
| 7891 | } |
| 7892 | |
| 7893 | // aten::bitwise_and.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7894 | at::Tensor & bitwise_and_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 7895 | |
| 7896 | static auto op = create_bitwise_and_Scalar_out_typed_handle(); |
| 7897 | return op.redispatch(dispatchKeySet, self, other, out); |
| 7898 | } |
| 7899 | |
| 7900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar, name, "aten::bitwise_and") |
| 7901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar, overload_name, "Scalar") |
| 7902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar, schema_str, "bitwise_and.Scalar(Tensor self, Scalar other) -> Tensor") |
| 7903 | |
| 7904 | // aten::bitwise_and.Scalar(Tensor self, Scalar other) -> Tensor |
| 7905 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and_Scalar::schema> create_bitwise_and_Scalar_typed_handle() { |
| 7906 | return c10::Dispatcher::singleton() |
| 7907 | .findSchemaOrThrow(bitwise_and_Scalar::name, bitwise_and_Scalar::overload_name) |
| 7908 | .typed<bitwise_and_Scalar::schema>(); |
| 7909 | } |
| 7910 | |
| 7911 | // aten::bitwise_and.Scalar(Tensor self, Scalar other) -> Tensor |
| 7912 | at::Tensor bitwise_and_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 7913 | |
| 7914 | static auto op = create_bitwise_and_Scalar_typed_handle(); |
| 7915 | return op.call(self, other); |
| 7916 | } |
| 7917 | |
| 7918 | // aten::bitwise_and.Scalar(Tensor self, Scalar other) -> Tensor |
| 7919 | at::Tensor bitwise_and_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 7920 | |
| 7921 | static auto op = create_bitwise_and_Scalar_typed_handle(); |
| 7922 | return op.redispatch(dispatchKeySet, self, other); |
| 7923 | } |
| 7924 | |
| 7925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_Tensor, name, "aten::bitwise_and") |
| 7926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_Tensor, overload_name, "Scalar_Tensor") |
| 7927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_Tensor, schema_str, "bitwise_and.Scalar_Tensor(Scalar self, Tensor other) -> Tensor") |
| 7928 | |
| 7929 | // aten::bitwise_and.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 7930 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and_Scalar_Tensor::schema> create_bitwise_and_Scalar_Tensor_typed_handle() { |
| 7931 | return c10::Dispatcher::singleton() |
| 7932 | .findSchemaOrThrow(bitwise_and_Scalar_Tensor::name, bitwise_and_Scalar_Tensor::overload_name) |
| 7933 | .typed<bitwise_and_Scalar_Tensor::schema>(); |
| 7934 | } |
| 7935 | |
| 7936 | // aten::bitwise_and.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 7937 | at::Tensor bitwise_and_Scalar_Tensor::call(const at::Scalar & self, const at::Tensor & other) { |
| 7938 | |
| 7939 | static auto op = create_bitwise_and_Scalar_Tensor_typed_handle(); |
| 7940 | return op.call(self, other); |
| 7941 | } |
| 7942 | |
| 7943 | // aten::bitwise_and.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 7944 | at::Tensor bitwise_and_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other) { |
| 7945 | |
| 7946 | static auto op = create_bitwise_and_Scalar_Tensor_typed_handle(); |
| 7947 | return op.redispatch(dispatchKeySet, self, other); |
| 7948 | } |
| 7949 | |
| 7950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Tensor, name, "aten::bitwise_and") |
| 7951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Tensor, overload_name, "Tensor") |
| 7952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Tensor, schema_str, "bitwise_and.Tensor(Tensor self, Tensor other) -> Tensor") |
| 7953 | |
| 7954 | // aten::bitwise_and.Tensor(Tensor self, Tensor other) -> Tensor |
| 7955 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and_Tensor::schema> create_bitwise_and_Tensor_typed_handle() { |
| 7956 | return c10::Dispatcher::singleton() |
| 7957 | .findSchemaOrThrow(bitwise_and_Tensor::name, bitwise_and_Tensor::overload_name) |
| 7958 | .typed<bitwise_and_Tensor::schema>(); |
| 7959 | } |
| 7960 | |
| 7961 | // aten::bitwise_and.Tensor(Tensor self, Tensor other) -> Tensor |
| 7962 | at::Tensor bitwise_and_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 7963 | |
| 7964 | static auto op = create_bitwise_and_Tensor_typed_handle(); |
| 7965 | return op.call(self, other); |
| 7966 | } |
| 7967 | |
| 7968 | // aten::bitwise_and.Tensor(Tensor self, Tensor other) -> Tensor |
| 7969 | at::Tensor bitwise_and_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 7970 | |
| 7971 | static auto op = create_bitwise_and_Tensor_typed_handle(); |
| 7972 | return op.redispatch(dispatchKeySet, self, other); |
| 7973 | } |
| 7974 | |
| 7975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and__Scalar, name, "aten::bitwise_and_") |
| 7976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and__Scalar, overload_name, "Scalar") |
| 7977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and__Scalar, schema_str, "bitwise_and_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 7978 | |
| 7979 | // aten::bitwise_and_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7980 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and__Scalar::schema> create_bitwise_and__Scalar_typed_handle() { |
| 7981 | return c10::Dispatcher::singleton() |
| 7982 | .findSchemaOrThrow(bitwise_and__Scalar::name, bitwise_and__Scalar::overload_name) |
| 7983 | .typed<bitwise_and__Scalar::schema>(); |
| 7984 | } |
| 7985 | |
| 7986 | // aten::bitwise_and_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7987 | at::Tensor & bitwise_and__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 7988 | |
| 7989 | static auto op = create_bitwise_and__Scalar_typed_handle(); |
| 7990 | return op.call(self, other); |
| 7991 | } |
| 7992 | |
| 7993 | // aten::bitwise_and_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7994 | at::Tensor & bitwise_and__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 7995 | |
| 7996 | static auto op = create_bitwise_and__Scalar_typed_handle(); |
| 7997 | return op.redispatch(dispatchKeySet, self, other); |
| 7998 | } |
| 7999 | |
| 8000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and__Tensor, name, "aten::bitwise_and_") |
| 8001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and__Tensor, overload_name, "Tensor") |
| 8002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and__Tensor, schema_str, "bitwise_and_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 8003 | |
| 8004 | // aten::bitwise_and_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8005 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and__Tensor::schema> create_bitwise_and__Tensor_typed_handle() { |
| 8006 | return c10::Dispatcher::singleton() |
| 8007 | .findSchemaOrThrow(bitwise_and__Tensor::name, bitwise_and__Tensor::overload_name) |
| 8008 | .typed<bitwise_and__Tensor::schema>(); |
| 8009 | } |
| 8010 | |
| 8011 | // aten::bitwise_and_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8012 | at::Tensor & bitwise_and__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 8013 | |
| 8014 | static auto op = create_bitwise_and__Tensor_typed_handle(); |
| 8015 | return op.call(self, other); |
| 8016 | } |
| 8017 | |
| 8018 | // aten::bitwise_and_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8019 | at::Tensor & bitwise_and__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 8020 | |
| 8021 | static auto op = create_bitwise_and__Tensor_typed_handle(); |
| 8022 | return op.redispatch(dispatchKeySet, self, other); |
| 8023 | } |
| 8024 | |
| 8025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__or___Scalar, name, "aten::__or__") |
| 8026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__or___Scalar, overload_name, "Scalar") |
| 8027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__or___Scalar, schema_str, "__or__.Scalar(Tensor self, Scalar other) -> Tensor") |
| 8028 | |
| 8029 | // aten::__or__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8030 | static C10_NOINLINE c10::TypedOperatorHandle<__or___Scalar::schema> create___or___Scalar_typed_handle() { |
| 8031 | return c10::Dispatcher::singleton() |
| 8032 | .findSchemaOrThrow(__or___Scalar::name, __or___Scalar::overload_name) |
| 8033 | .typed<__or___Scalar::schema>(); |
| 8034 | } |
| 8035 | |
| 8036 | // aten::__or__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8037 | at::Tensor __or___Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 8038 | |
| 8039 | static auto op = create___or___Scalar_typed_handle(); |
| 8040 | return op.call(self, other); |
| 8041 | } |
| 8042 | |
| 8043 | // aten::__or__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8044 | at::Tensor __or___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 8045 | |
| 8046 | static auto op = create___or___Scalar_typed_handle(); |
| 8047 | return op.redispatch(dispatchKeySet, self, other); |
| 8048 | } |
| 8049 | |
| 8050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__or___Tensor, name, "aten::__or__") |
| 8051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__or___Tensor, overload_name, "Tensor") |
| 8052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__or___Tensor, schema_str, "__or__.Tensor(Tensor self, Tensor other) -> Tensor") |
| 8053 | |
| 8054 | // aten::__or__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8055 | static C10_NOINLINE c10::TypedOperatorHandle<__or___Tensor::schema> create___or___Tensor_typed_handle() { |
| 8056 | return c10::Dispatcher::singleton() |
| 8057 | .findSchemaOrThrow(__or___Tensor::name, __or___Tensor::overload_name) |
| 8058 | .typed<__or___Tensor::schema>(); |
| 8059 | } |
| 8060 | |
| 8061 | // aten::__or__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8062 | at::Tensor __or___Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 8063 | |
| 8064 | static auto op = create___or___Tensor_typed_handle(); |
| 8065 | return op.call(self, other); |
| 8066 | } |
| 8067 | |
| 8068 | // aten::__or__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8069 | at::Tensor __or___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 8070 | |
| 8071 | static auto op = create___or___Tensor_typed_handle(); |
| 8072 | return op.redispatch(dispatchKeySet, self, other); |
| 8073 | } |
| 8074 | |
| 8075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ior___Scalar, name, "aten::__ior__") |
| 8076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ior___Scalar, overload_name, "Scalar") |
| 8077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ior___Scalar, schema_str, "__ior__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 8078 | |
| 8079 | // aten::__ior__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8080 | static C10_NOINLINE c10::TypedOperatorHandle<__ior___Scalar::schema> create___ior___Scalar_typed_handle() { |
| 8081 | return c10::Dispatcher::singleton() |
| 8082 | .findSchemaOrThrow(__ior___Scalar::name, __ior___Scalar::overload_name) |
| 8083 | .typed<__ior___Scalar::schema>(); |
| 8084 | } |
| 8085 | |
| 8086 | // aten::__ior__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8087 | at::Tensor & __ior___Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 8088 | |
| 8089 | static auto op = create___ior___Scalar_typed_handle(); |
| 8090 | return op.call(self, other); |
| 8091 | } |
| 8092 | |
| 8093 | // aten::__ior__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8094 | at::Tensor & __ior___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 8095 | |
| 8096 | static auto op = create___ior___Scalar_typed_handle(); |
| 8097 | return op.redispatch(dispatchKeySet, self, other); |
| 8098 | } |
| 8099 | |
| 8100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ior___Tensor, name, "aten::__ior__") |
| 8101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ior___Tensor, overload_name, "Tensor") |
| 8102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ior___Tensor, schema_str, "__ior__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 8103 | |
| 8104 | // aten::__ior__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8105 | static C10_NOINLINE c10::TypedOperatorHandle<__ior___Tensor::schema> create___ior___Tensor_typed_handle() { |
| 8106 | return c10::Dispatcher::singleton() |
| 8107 | .findSchemaOrThrow(__ior___Tensor::name, __ior___Tensor::overload_name) |
| 8108 | .typed<__ior___Tensor::schema>(); |
| 8109 | } |
| 8110 | |
| 8111 | // aten::__ior__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8112 | at::Tensor & __ior___Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 8113 | |
| 8114 | static auto op = create___ior___Tensor_typed_handle(); |
| 8115 | return op.call(self, other); |
| 8116 | } |
| 8117 | |
| 8118 | // aten::__ior__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8119 | at::Tensor & __ior___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 8120 | |
| 8121 | static auto op = create___ior___Tensor_typed_handle(); |
| 8122 | return op.redispatch(dispatchKeySet, self, other); |
| 8123 | } |
| 8124 | |
| 8125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Tensor_out, name, "aten::bitwise_xor") |
| 8126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Tensor_out, overload_name, "Tensor_out") |
| 8127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Tensor_out, schema_str, "bitwise_xor.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8128 | |
| 8129 | // aten::bitwise_xor.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8130 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor_Tensor_out::schema> create_bitwise_xor_Tensor_out_typed_handle() { |
| 8131 | return c10::Dispatcher::singleton() |
| 8132 | .findSchemaOrThrow(bitwise_xor_Tensor_out::name, bitwise_xor_Tensor_out::overload_name) |
| 8133 | .typed<bitwise_xor_Tensor_out::schema>(); |
| 8134 | } |
| 8135 | |
| 8136 | // aten::bitwise_xor.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8137 | at::Tensor & bitwise_xor_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8138 | |
| 8139 | static auto op = create_bitwise_xor_Tensor_out_typed_handle(); |
| 8140 | return op.call(self, other, out); |
| 8141 | } |
| 8142 | |
| 8143 | // aten::bitwise_xor.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8144 | at::Tensor & bitwise_xor_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8145 | |
| 8146 | static auto op = create_bitwise_xor_Tensor_out_typed_handle(); |
| 8147 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8148 | } |
| 8149 | |
| 8150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_out, name, "aten::bitwise_xor") |
| 8151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_out, overload_name, "Scalar_out") |
| 8152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_out, schema_str, "bitwise_xor.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8153 | |
| 8154 | // aten::bitwise_xor.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8155 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor_Scalar_out::schema> create_bitwise_xor_Scalar_out_typed_handle() { |
| 8156 | return c10::Dispatcher::singleton() |
| 8157 | .findSchemaOrThrow(bitwise_xor_Scalar_out::name, bitwise_xor_Scalar_out::overload_name) |
| 8158 | .typed<bitwise_xor_Scalar_out::schema>(); |
| 8159 | } |
| 8160 | |
| 8161 | // aten::bitwise_xor.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8162 | at::Tensor & bitwise_xor_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8163 | |
| 8164 | static auto op = create_bitwise_xor_Scalar_out_typed_handle(); |
| 8165 | return op.call(self, other, out); |
| 8166 | } |
| 8167 | |
| 8168 | // aten::bitwise_xor.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8169 | at::Tensor & bitwise_xor_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8170 | |
| 8171 | static auto op = create_bitwise_xor_Scalar_out_typed_handle(); |
| 8172 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8173 | } |
| 8174 | |
| 8175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar, name, "aten::bitwise_xor") |
| 8176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar, overload_name, "Scalar") |
| 8177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar, schema_str, "bitwise_xor.Scalar(Tensor self, Scalar other) -> Tensor") |
| 8178 | |
| 8179 | // aten::bitwise_xor.Scalar(Tensor self, Scalar other) -> Tensor |
| 8180 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor_Scalar::schema> create_bitwise_xor_Scalar_typed_handle() { |
| 8181 | return c10::Dispatcher::singleton() |
| 8182 | .findSchemaOrThrow(bitwise_xor_Scalar::name, bitwise_xor_Scalar::overload_name) |
| 8183 | .typed<bitwise_xor_Scalar::schema>(); |
| 8184 | } |
| 8185 | |
| 8186 | // aten::bitwise_xor.Scalar(Tensor self, Scalar other) -> Tensor |
| 8187 | at::Tensor bitwise_xor_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 8188 | |
| 8189 | static auto op = create_bitwise_xor_Scalar_typed_handle(); |
| 8190 | return op.call(self, other); |
| 8191 | } |
| 8192 | |
| 8193 | // aten::bitwise_xor.Scalar(Tensor self, Scalar other) -> Tensor |
| 8194 | at::Tensor bitwise_xor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 8195 | |
| 8196 | static auto op = create_bitwise_xor_Scalar_typed_handle(); |
| 8197 | return op.redispatch(dispatchKeySet, self, other); |
| 8198 | } |
| 8199 | |
| 8200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_Tensor, name, "aten::bitwise_xor") |
| 8201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_Tensor, overload_name, "Scalar_Tensor") |
| 8202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_Tensor, schema_str, "bitwise_xor.Scalar_Tensor(Scalar self, Tensor other) -> Tensor") |
| 8203 | |
| 8204 | // aten::bitwise_xor.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8205 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor_Scalar_Tensor::schema> create_bitwise_xor_Scalar_Tensor_typed_handle() { |
| 8206 | return c10::Dispatcher::singleton() |
| 8207 | .findSchemaOrThrow(bitwise_xor_Scalar_Tensor::name, bitwise_xor_Scalar_Tensor::overload_name) |
| 8208 | .typed<bitwise_xor_Scalar_Tensor::schema>(); |
| 8209 | } |
| 8210 | |
| 8211 | // aten::bitwise_xor.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8212 | at::Tensor bitwise_xor_Scalar_Tensor::call(const at::Scalar & self, const at::Tensor & other) { |
| 8213 | |
| 8214 | static auto op = create_bitwise_xor_Scalar_Tensor_typed_handle(); |
| 8215 | return op.call(self, other); |
| 8216 | } |
| 8217 | |
| 8218 | // aten::bitwise_xor.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8219 | at::Tensor bitwise_xor_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other) { |
| 8220 | |
| 8221 | static auto op = create_bitwise_xor_Scalar_Tensor_typed_handle(); |
| 8222 | return op.redispatch(dispatchKeySet, self, other); |
| 8223 | } |
| 8224 | |
| 8225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Tensor, name, "aten::bitwise_xor") |
| 8226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Tensor, overload_name, "Tensor") |
| 8227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Tensor, schema_str, "bitwise_xor.Tensor(Tensor self, Tensor other) -> Tensor") |
| 8228 | |
| 8229 | // aten::bitwise_xor.Tensor(Tensor self, Tensor other) -> Tensor |
| 8230 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor_Tensor::schema> create_bitwise_xor_Tensor_typed_handle() { |
| 8231 | return c10::Dispatcher::singleton() |
| 8232 | .findSchemaOrThrow(bitwise_xor_Tensor::name, bitwise_xor_Tensor::overload_name) |
| 8233 | .typed<bitwise_xor_Tensor::schema>(); |
| 8234 | } |
| 8235 | |
| 8236 | // aten::bitwise_xor.Tensor(Tensor self, Tensor other) -> Tensor |
| 8237 | at::Tensor bitwise_xor_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 8238 | |
| 8239 | static auto op = create_bitwise_xor_Tensor_typed_handle(); |
| 8240 | return op.call(self, other); |
| 8241 | } |
| 8242 | |
| 8243 | // aten::bitwise_xor.Tensor(Tensor self, Tensor other) -> Tensor |
| 8244 | at::Tensor bitwise_xor_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 8245 | |
| 8246 | static auto op = create_bitwise_xor_Tensor_typed_handle(); |
| 8247 | return op.redispatch(dispatchKeySet, self, other); |
| 8248 | } |
| 8249 | |
| 8250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor__Scalar, name, "aten::bitwise_xor_") |
| 8251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor__Scalar, overload_name, "Scalar") |
| 8252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor__Scalar, schema_str, "bitwise_xor_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 8253 | |
| 8254 | // aten::bitwise_xor_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8255 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor__Scalar::schema> create_bitwise_xor__Scalar_typed_handle() { |
| 8256 | return c10::Dispatcher::singleton() |
| 8257 | .findSchemaOrThrow(bitwise_xor__Scalar::name, bitwise_xor__Scalar::overload_name) |
| 8258 | .typed<bitwise_xor__Scalar::schema>(); |
| 8259 | } |
| 8260 | |
| 8261 | // aten::bitwise_xor_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8262 | at::Tensor & bitwise_xor__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 8263 | |
| 8264 | static auto op = create_bitwise_xor__Scalar_typed_handle(); |
| 8265 | return op.call(self, other); |
| 8266 | } |
| 8267 | |
| 8268 | // aten::bitwise_xor_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8269 | at::Tensor & bitwise_xor__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 8270 | |
| 8271 | static auto op = create_bitwise_xor__Scalar_typed_handle(); |
| 8272 | return op.redispatch(dispatchKeySet, self, other); |
| 8273 | } |
| 8274 | |
| 8275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor__Tensor, name, "aten::bitwise_xor_") |
| 8276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor__Tensor, overload_name, "Tensor") |
| 8277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor__Tensor, schema_str, "bitwise_xor_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 8278 | |
| 8279 | // aten::bitwise_xor_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8280 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor__Tensor::schema> create_bitwise_xor__Tensor_typed_handle() { |
| 8281 | return c10::Dispatcher::singleton() |
| 8282 | .findSchemaOrThrow(bitwise_xor__Tensor::name, bitwise_xor__Tensor::overload_name) |
| 8283 | .typed<bitwise_xor__Tensor::schema>(); |
| 8284 | } |
| 8285 | |
| 8286 | // aten::bitwise_xor_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8287 | at::Tensor & bitwise_xor__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 8288 | |
| 8289 | static auto op = create_bitwise_xor__Tensor_typed_handle(); |
| 8290 | return op.call(self, other); |
| 8291 | } |
| 8292 | |
| 8293 | // aten::bitwise_xor_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8294 | at::Tensor & bitwise_xor__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 8295 | |
| 8296 | static auto op = create_bitwise_xor__Tensor_typed_handle(); |
| 8297 | return op.redispatch(dispatchKeySet, self, other); |
| 8298 | } |
| 8299 | |
| 8300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Scalar, name, "aten::__lshift__") |
| 8301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Scalar, overload_name, "Scalar") |
| 8302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Scalar, schema_str, "__lshift__.Scalar(Tensor self, Scalar other) -> Tensor") |
| 8303 | |
| 8304 | // aten::__lshift__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8305 | static C10_NOINLINE c10::TypedOperatorHandle<__lshift___Scalar::schema> create___lshift___Scalar_typed_handle() { |
| 8306 | return c10::Dispatcher::singleton() |
| 8307 | .findSchemaOrThrow(__lshift___Scalar::name, __lshift___Scalar::overload_name) |
| 8308 | .typed<__lshift___Scalar::schema>(); |
| 8309 | } |
| 8310 | |
| 8311 | // aten::__lshift__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8312 | at::Tensor __lshift___Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 8313 | |
| 8314 | static auto op = create___lshift___Scalar_typed_handle(); |
| 8315 | return op.call(self, other); |
| 8316 | } |
| 8317 | |
| 8318 | // aten::__lshift__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8319 | at::Tensor __lshift___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 8320 | |
| 8321 | static auto op = create___lshift___Scalar_typed_handle(); |
| 8322 | return op.redispatch(dispatchKeySet, self, other); |
| 8323 | } |
| 8324 | |
| 8325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Tensor, name, "aten::__lshift__") |
| 8326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Tensor, overload_name, "Tensor") |
| 8327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Tensor, schema_str, "__lshift__.Tensor(Tensor self, Tensor other) -> Tensor") |
| 8328 | |
| 8329 | // aten::__lshift__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8330 | static C10_NOINLINE c10::TypedOperatorHandle<__lshift___Tensor::schema> create___lshift___Tensor_typed_handle() { |
| 8331 | return c10::Dispatcher::singleton() |
| 8332 | .findSchemaOrThrow(__lshift___Tensor::name, __lshift___Tensor::overload_name) |
| 8333 | .typed<__lshift___Tensor::schema>(); |
| 8334 | } |
| 8335 | |
| 8336 | // aten::__lshift__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8337 | at::Tensor __lshift___Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 8338 | |
| 8339 | static auto op = create___lshift___Tensor_typed_handle(); |
| 8340 | return op.call(self, other); |
| 8341 | } |
| 8342 | |
| 8343 | // aten::__lshift__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8344 | at::Tensor __lshift___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 8345 | |
| 8346 | static auto op = create___lshift___Tensor_typed_handle(); |
| 8347 | return op.redispatch(dispatchKeySet, self, other); |
| 8348 | } |
| 8349 | |
| 8350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ilshift___Scalar, name, "aten::__ilshift__") |
| 8351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ilshift___Scalar, overload_name, "Scalar") |
| 8352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ilshift___Scalar, schema_str, "__ilshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 8353 | |
| 8354 | // aten::__ilshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8355 | static C10_NOINLINE c10::TypedOperatorHandle<__ilshift___Scalar::schema> create___ilshift___Scalar_typed_handle() { |
| 8356 | return c10::Dispatcher::singleton() |
| 8357 | .findSchemaOrThrow(__ilshift___Scalar::name, __ilshift___Scalar::overload_name) |
| 8358 | .typed<__ilshift___Scalar::schema>(); |
| 8359 | } |
| 8360 | |
| 8361 | // aten::__ilshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8362 | at::Tensor & __ilshift___Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 8363 | |
| 8364 | static auto op = create___ilshift___Scalar_typed_handle(); |
| 8365 | return op.call(self, other); |
| 8366 | } |
| 8367 | |
| 8368 | // aten::__ilshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8369 | at::Tensor & __ilshift___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 8370 | |
| 8371 | static auto op = create___ilshift___Scalar_typed_handle(); |
| 8372 | return op.redispatch(dispatchKeySet, self, other); |
| 8373 | } |
| 8374 | |
| 8375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ilshift___Tensor, name, "aten::__ilshift__") |
| 8376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ilshift___Tensor, overload_name, "Tensor") |
| 8377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__ilshift___Tensor, schema_str, "__ilshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 8378 | |
| 8379 | // aten::__ilshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8380 | static C10_NOINLINE c10::TypedOperatorHandle<__ilshift___Tensor::schema> create___ilshift___Tensor_typed_handle() { |
| 8381 | return c10::Dispatcher::singleton() |
| 8382 | .findSchemaOrThrow(__ilshift___Tensor::name, __ilshift___Tensor::overload_name) |
| 8383 | .typed<__ilshift___Tensor::schema>(); |
| 8384 | } |
| 8385 | |
| 8386 | // aten::__ilshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8387 | at::Tensor & __ilshift___Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 8388 | |
| 8389 | static auto op = create___ilshift___Tensor_typed_handle(); |
| 8390 | return op.call(self, other); |
| 8391 | } |
| 8392 | |
| 8393 | // aten::__ilshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8394 | at::Tensor & __ilshift___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 8395 | |
| 8396 | static auto op = create___ilshift___Tensor_typed_handle(); |
| 8397 | return op.redispatch(dispatchKeySet, self, other); |
| 8398 | } |
| 8399 | |
| 8400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor, name, "aten::bitwise_left_shift") |
| 8401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor, overload_name, "Tensor") |
| 8402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor, schema_str, "bitwise_left_shift.Tensor(Tensor self, Tensor other) -> Tensor") |
| 8403 | |
| 8404 | // aten::bitwise_left_shift.Tensor(Tensor self, Tensor other) -> Tensor |
| 8405 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift_Tensor::schema> create_bitwise_left_shift_Tensor_typed_handle() { |
| 8406 | return c10::Dispatcher::singleton() |
| 8407 | .findSchemaOrThrow(bitwise_left_shift_Tensor::name, bitwise_left_shift_Tensor::overload_name) |
| 8408 | .typed<bitwise_left_shift_Tensor::schema>(); |
| 8409 | } |
| 8410 | |
| 8411 | // aten::bitwise_left_shift.Tensor(Tensor self, Tensor other) -> Tensor |
| 8412 | at::Tensor bitwise_left_shift_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 8413 | |
| 8414 | static auto op = create_bitwise_left_shift_Tensor_typed_handle(); |
| 8415 | return op.call(self, other); |
| 8416 | } |
| 8417 | |
| 8418 | // aten::bitwise_left_shift.Tensor(Tensor self, Tensor other) -> Tensor |
| 8419 | at::Tensor bitwise_left_shift_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 8420 | |
| 8421 | static auto op = create_bitwise_left_shift_Tensor_typed_handle(); |
| 8422 | return op.redispatch(dispatchKeySet, self, other); |
| 8423 | } |
| 8424 | |
| 8425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift__Tensor, name, "aten::bitwise_left_shift_") |
| 8426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift__Tensor, overload_name, "Tensor") |
| 8427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift__Tensor, schema_str, "bitwise_left_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 8428 | |
| 8429 | // aten::bitwise_left_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8430 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift__Tensor::schema> create_bitwise_left_shift__Tensor_typed_handle() { |
| 8431 | return c10::Dispatcher::singleton() |
| 8432 | .findSchemaOrThrow(bitwise_left_shift__Tensor::name, bitwise_left_shift__Tensor::overload_name) |
| 8433 | .typed<bitwise_left_shift__Tensor::schema>(); |
| 8434 | } |
| 8435 | |
| 8436 | // aten::bitwise_left_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8437 | at::Tensor & bitwise_left_shift__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 8438 | |
| 8439 | static auto op = create_bitwise_left_shift__Tensor_typed_handle(); |
| 8440 | return op.call(self, other); |
| 8441 | } |
| 8442 | |
| 8443 | // aten::bitwise_left_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8444 | at::Tensor & bitwise_left_shift__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 8445 | |
| 8446 | static auto op = create_bitwise_left_shift__Tensor_typed_handle(); |
| 8447 | return op.redispatch(dispatchKeySet, self, other); |
| 8448 | } |
| 8449 | |
| 8450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_out, name, "aten::bitwise_left_shift") |
| 8451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_out, overload_name, "Tensor_out") |
| 8452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_out, schema_str, "bitwise_left_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8453 | |
| 8454 | // aten::bitwise_left_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8455 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift_Tensor_out::schema> create_bitwise_left_shift_Tensor_out_typed_handle() { |
| 8456 | return c10::Dispatcher::singleton() |
| 8457 | .findSchemaOrThrow(bitwise_left_shift_Tensor_out::name, bitwise_left_shift_Tensor_out::overload_name) |
| 8458 | .typed<bitwise_left_shift_Tensor_out::schema>(); |
| 8459 | } |
| 8460 | |
| 8461 | // aten::bitwise_left_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8462 | at::Tensor & bitwise_left_shift_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8463 | |
| 8464 | static auto op = create_bitwise_left_shift_Tensor_out_typed_handle(); |
| 8465 | return op.call(self, other, out); |
| 8466 | } |
| 8467 | |
| 8468 | // aten::bitwise_left_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8469 | at::Tensor & bitwise_left_shift_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8470 | |
| 8471 | static auto op = create_bitwise_left_shift_Tensor_out_typed_handle(); |
| 8472 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8473 | } |
| 8474 | |
| 8475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_Scalar, name, "aten::bitwise_left_shift") |
| 8476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_Scalar, overload_name, "Tensor_Scalar") |
| 8477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_Scalar, schema_str, "bitwise_left_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor") |
| 8478 | |
| 8479 | // aten::bitwise_left_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor |
| 8480 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift_Tensor_Scalar::schema> create_bitwise_left_shift_Tensor_Scalar_typed_handle() { |
| 8481 | return c10::Dispatcher::singleton() |
| 8482 | .findSchemaOrThrow(bitwise_left_shift_Tensor_Scalar::name, bitwise_left_shift_Tensor_Scalar::overload_name) |
| 8483 | .typed<bitwise_left_shift_Tensor_Scalar::schema>(); |
| 8484 | } |
| 8485 | |
| 8486 | // aten::bitwise_left_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor |
| 8487 | at::Tensor bitwise_left_shift_Tensor_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 8488 | |
| 8489 | static auto op = create_bitwise_left_shift_Tensor_Scalar_typed_handle(); |
| 8490 | return op.call(self, other); |
| 8491 | } |
| 8492 | |
| 8493 | // aten::bitwise_left_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor |
| 8494 | at::Tensor bitwise_left_shift_Tensor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 8495 | |
| 8496 | static auto op = create_bitwise_left_shift_Tensor_Scalar_typed_handle(); |
| 8497 | return op.redispatch(dispatchKeySet, self, other); |
| 8498 | } |
| 8499 | |
| 8500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift__Tensor_Scalar, name, "aten::bitwise_left_shift_") |
| 8501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift__Tensor_Scalar, overload_name, "Tensor_Scalar") |
| 8502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift__Tensor_Scalar, schema_str, "bitwise_left_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 8503 | |
| 8504 | // aten::bitwise_left_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8505 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift__Tensor_Scalar::schema> create_bitwise_left_shift__Tensor_Scalar_typed_handle() { |
| 8506 | return c10::Dispatcher::singleton() |
| 8507 | .findSchemaOrThrow(bitwise_left_shift__Tensor_Scalar::name, bitwise_left_shift__Tensor_Scalar::overload_name) |
| 8508 | .typed<bitwise_left_shift__Tensor_Scalar::schema>(); |
| 8509 | } |
| 8510 | |
| 8511 | // aten::bitwise_left_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8512 | at::Tensor & bitwise_left_shift__Tensor_Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 8513 | |
| 8514 | static auto op = create_bitwise_left_shift__Tensor_Scalar_typed_handle(); |
| 8515 | return op.call(self, other); |
| 8516 | } |
| 8517 | |
| 8518 | // aten::bitwise_left_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8519 | at::Tensor & bitwise_left_shift__Tensor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 8520 | |
| 8521 | static auto op = create_bitwise_left_shift__Tensor_Scalar_typed_handle(); |
| 8522 | return op.redispatch(dispatchKeySet, self, other); |
| 8523 | } |
| 8524 | |
| 8525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_Scalar_out, name, "aten::bitwise_left_shift") |
| 8526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_Scalar_out, overload_name, "Tensor_Scalar_out") |
| 8527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Tensor_Scalar_out, schema_str, "bitwise_left_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8528 | |
| 8529 | // aten::bitwise_left_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8530 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift_Tensor_Scalar_out::schema> create_bitwise_left_shift_Tensor_Scalar_out_typed_handle() { |
| 8531 | return c10::Dispatcher::singleton() |
| 8532 | .findSchemaOrThrow(bitwise_left_shift_Tensor_Scalar_out::name, bitwise_left_shift_Tensor_Scalar_out::overload_name) |
| 8533 | .typed<bitwise_left_shift_Tensor_Scalar_out::schema>(); |
| 8534 | } |
| 8535 | |
| 8536 | // aten::bitwise_left_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8537 | at::Tensor & bitwise_left_shift_Tensor_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8538 | |
| 8539 | static auto op = create_bitwise_left_shift_Tensor_Scalar_out_typed_handle(); |
| 8540 | return op.call(self, other, out); |
| 8541 | } |
| 8542 | |
| 8543 | // aten::bitwise_left_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8544 | at::Tensor & bitwise_left_shift_Tensor_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8545 | |
| 8546 | static auto op = create_bitwise_left_shift_Tensor_Scalar_out_typed_handle(); |
| 8547 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8548 | } |
| 8549 | |
| 8550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Scalar_Tensor, name, "aten::bitwise_left_shift") |
| 8551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Scalar_Tensor, overload_name, "Scalar_Tensor") |
| 8552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Scalar_Tensor, schema_str, "bitwise_left_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor") |
| 8553 | |
| 8554 | // aten::bitwise_left_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8555 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift_Scalar_Tensor::schema> create_bitwise_left_shift_Scalar_Tensor_typed_handle() { |
| 8556 | return c10::Dispatcher::singleton() |
| 8557 | .findSchemaOrThrow(bitwise_left_shift_Scalar_Tensor::name, bitwise_left_shift_Scalar_Tensor::overload_name) |
| 8558 | .typed<bitwise_left_shift_Scalar_Tensor::schema>(); |
| 8559 | } |
| 8560 | |
| 8561 | // aten::bitwise_left_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8562 | at::Tensor bitwise_left_shift_Scalar_Tensor::call(const at::Scalar & self, const at::Tensor & other) { |
| 8563 | |
| 8564 | static auto op = create_bitwise_left_shift_Scalar_Tensor_typed_handle(); |
| 8565 | return op.call(self, other); |
| 8566 | } |
| 8567 | |
| 8568 | // aten::bitwise_left_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8569 | at::Tensor bitwise_left_shift_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other) { |
| 8570 | |
| 8571 | static auto op = create_bitwise_left_shift_Scalar_Tensor_typed_handle(); |
| 8572 | return op.redispatch(dispatchKeySet, self, other); |
| 8573 | } |
| 8574 | |
| 8575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Scalar, name, "aten::__rshift__") |
| 8576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Scalar, overload_name, "Scalar") |
| 8577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Scalar, schema_str, "__rshift__.Scalar(Tensor self, Scalar other) -> Tensor") |
| 8578 | |
| 8579 | // aten::__rshift__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8580 | static C10_NOINLINE c10::TypedOperatorHandle<__rshift___Scalar::schema> create___rshift___Scalar_typed_handle() { |
| 8581 | return c10::Dispatcher::singleton() |
| 8582 | .findSchemaOrThrow(__rshift___Scalar::name, __rshift___Scalar::overload_name) |
| 8583 | .typed<__rshift___Scalar::schema>(); |
| 8584 | } |
| 8585 | |
| 8586 | // aten::__rshift__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8587 | at::Tensor __rshift___Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 8588 | |
| 8589 | static auto op = create___rshift___Scalar_typed_handle(); |
| 8590 | return op.call(self, other); |
| 8591 | } |
| 8592 | |
| 8593 | // aten::__rshift__.Scalar(Tensor self, Scalar other) -> Tensor |
| 8594 | at::Tensor __rshift___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 8595 | |
| 8596 | static auto op = create___rshift___Scalar_typed_handle(); |
| 8597 | return op.redispatch(dispatchKeySet, self, other); |
| 8598 | } |
| 8599 | |
| 8600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Tensor, name, "aten::__rshift__") |
| 8601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Tensor, overload_name, "Tensor") |
| 8602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Tensor, schema_str, "__rshift__.Tensor(Tensor self, Tensor other) -> Tensor") |
| 8603 | |
| 8604 | // aten::__rshift__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8605 | static C10_NOINLINE c10::TypedOperatorHandle<__rshift___Tensor::schema> create___rshift___Tensor_typed_handle() { |
| 8606 | return c10::Dispatcher::singleton() |
| 8607 | .findSchemaOrThrow(__rshift___Tensor::name, __rshift___Tensor::overload_name) |
| 8608 | .typed<__rshift___Tensor::schema>(); |
| 8609 | } |
| 8610 | |
| 8611 | // aten::__rshift__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8612 | at::Tensor __rshift___Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 8613 | |
| 8614 | static auto op = create___rshift___Tensor_typed_handle(); |
| 8615 | return op.call(self, other); |
| 8616 | } |
| 8617 | |
| 8618 | // aten::__rshift__.Tensor(Tensor self, Tensor other) -> Tensor |
| 8619 | at::Tensor __rshift___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 8620 | |
| 8621 | static auto op = create___rshift___Tensor_typed_handle(); |
| 8622 | return op.redispatch(dispatchKeySet, self, other); |
| 8623 | } |
| 8624 | |
| 8625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__irshift___Scalar, name, "aten::__irshift__") |
| 8626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__irshift___Scalar, overload_name, "Scalar") |
| 8627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__irshift___Scalar, schema_str, "__irshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 8628 | |
| 8629 | // aten::__irshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8630 | static C10_NOINLINE c10::TypedOperatorHandle<__irshift___Scalar::schema> create___irshift___Scalar_typed_handle() { |
| 8631 | return c10::Dispatcher::singleton() |
| 8632 | .findSchemaOrThrow(__irshift___Scalar::name, __irshift___Scalar::overload_name) |
| 8633 | .typed<__irshift___Scalar::schema>(); |
| 8634 | } |
| 8635 | |
| 8636 | // aten::__irshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8637 | at::Tensor & __irshift___Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 8638 | |
| 8639 | static auto op = create___irshift___Scalar_typed_handle(); |
| 8640 | return op.call(self, other); |
| 8641 | } |
| 8642 | |
| 8643 | // aten::__irshift__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8644 | at::Tensor & __irshift___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 8645 | |
| 8646 | static auto op = create___irshift___Scalar_typed_handle(); |
| 8647 | return op.redispatch(dispatchKeySet, self, other); |
| 8648 | } |
| 8649 | |
| 8650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__irshift___Tensor, name, "aten::__irshift__") |
| 8651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__irshift___Tensor, overload_name, "Tensor") |
| 8652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__irshift___Tensor, schema_str, "__irshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 8653 | |
| 8654 | // aten::__irshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8655 | static C10_NOINLINE c10::TypedOperatorHandle<__irshift___Tensor::schema> create___irshift___Tensor_typed_handle() { |
| 8656 | return c10::Dispatcher::singleton() |
| 8657 | .findSchemaOrThrow(__irshift___Tensor::name, __irshift___Tensor::overload_name) |
| 8658 | .typed<__irshift___Tensor::schema>(); |
| 8659 | } |
| 8660 | |
| 8661 | // aten::__irshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8662 | at::Tensor & __irshift___Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 8663 | |
| 8664 | static auto op = create___irshift___Tensor_typed_handle(); |
| 8665 | return op.call(self, other); |
| 8666 | } |
| 8667 | |
| 8668 | // aten::__irshift__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8669 | at::Tensor & __irshift___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 8670 | |
| 8671 | static auto op = create___irshift___Tensor_typed_handle(); |
| 8672 | return op.redispatch(dispatchKeySet, self, other); |
| 8673 | } |
| 8674 | |
| 8675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor, name, "aten::bitwise_right_shift") |
| 8676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor, overload_name, "Tensor") |
| 8677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor, schema_str, "bitwise_right_shift.Tensor(Tensor self, Tensor other) -> Tensor") |
| 8678 | |
| 8679 | // aten::bitwise_right_shift.Tensor(Tensor self, Tensor other) -> Tensor |
| 8680 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift_Tensor::schema> create_bitwise_right_shift_Tensor_typed_handle() { |
| 8681 | return c10::Dispatcher::singleton() |
| 8682 | .findSchemaOrThrow(bitwise_right_shift_Tensor::name, bitwise_right_shift_Tensor::overload_name) |
| 8683 | .typed<bitwise_right_shift_Tensor::schema>(); |
| 8684 | } |
| 8685 | |
| 8686 | // aten::bitwise_right_shift.Tensor(Tensor self, Tensor other) -> Tensor |
| 8687 | at::Tensor bitwise_right_shift_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 8688 | |
| 8689 | static auto op = create_bitwise_right_shift_Tensor_typed_handle(); |
| 8690 | return op.call(self, other); |
| 8691 | } |
| 8692 | |
| 8693 | // aten::bitwise_right_shift.Tensor(Tensor self, Tensor other) -> Tensor |
| 8694 | at::Tensor bitwise_right_shift_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 8695 | |
| 8696 | static auto op = create_bitwise_right_shift_Tensor_typed_handle(); |
| 8697 | return op.redispatch(dispatchKeySet, self, other); |
| 8698 | } |
| 8699 | |
| 8700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift__Tensor, name, "aten::bitwise_right_shift_") |
| 8701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift__Tensor, overload_name, "Tensor") |
| 8702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift__Tensor, schema_str, "bitwise_right_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 8703 | |
| 8704 | // aten::bitwise_right_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8705 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift__Tensor::schema> create_bitwise_right_shift__Tensor_typed_handle() { |
| 8706 | return c10::Dispatcher::singleton() |
| 8707 | .findSchemaOrThrow(bitwise_right_shift__Tensor::name, bitwise_right_shift__Tensor::overload_name) |
| 8708 | .typed<bitwise_right_shift__Tensor::schema>(); |
| 8709 | } |
| 8710 | |
| 8711 | // aten::bitwise_right_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8712 | at::Tensor & bitwise_right_shift__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 8713 | |
| 8714 | static auto op = create_bitwise_right_shift__Tensor_typed_handle(); |
| 8715 | return op.call(self, other); |
| 8716 | } |
| 8717 | |
| 8718 | // aten::bitwise_right_shift_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 8719 | at::Tensor & bitwise_right_shift__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 8720 | |
| 8721 | static auto op = create_bitwise_right_shift__Tensor_typed_handle(); |
| 8722 | return op.redispatch(dispatchKeySet, self, other); |
| 8723 | } |
| 8724 | |
| 8725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_out, name, "aten::bitwise_right_shift") |
| 8726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_out, overload_name, "Tensor_out") |
| 8727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_out, schema_str, "bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8728 | |
| 8729 | // aten::bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8730 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift_Tensor_out::schema> create_bitwise_right_shift_Tensor_out_typed_handle() { |
| 8731 | return c10::Dispatcher::singleton() |
| 8732 | .findSchemaOrThrow(bitwise_right_shift_Tensor_out::name, bitwise_right_shift_Tensor_out::overload_name) |
| 8733 | .typed<bitwise_right_shift_Tensor_out::schema>(); |
| 8734 | } |
| 8735 | |
| 8736 | // aten::bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8737 | at::Tensor & bitwise_right_shift_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8738 | |
| 8739 | static auto op = create_bitwise_right_shift_Tensor_out_typed_handle(); |
| 8740 | return op.call(self, other, out); |
| 8741 | } |
| 8742 | |
| 8743 | // aten::bitwise_right_shift.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8744 | at::Tensor & bitwise_right_shift_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8745 | |
| 8746 | static auto op = create_bitwise_right_shift_Tensor_out_typed_handle(); |
| 8747 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8748 | } |
| 8749 | |
| 8750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_Scalar, name, "aten::bitwise_right_shift") |
| 8751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_Scalar, overload_name, "Tensor_Scalar") |
| 8752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_Scalar, schema_str, "bitwise_right_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor") |
| 8753 | |
| 8754 | // aten::bitwise_right_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor |
| 8755 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift_Tensor_Scalar::schema> create_bitwise_right_shift_Tensor_Scalar_typed_handle() { |
| 8756 | return c10::Dispatcher::singleton() |
| 8757 | .findSchemaOrThrow(bitwise_right_shift_Tensor_Scalar::name, bitwise_right_shift_Tensor_Scalar::overload_name) |
| 8758 | .typed<bitwise_right_shift_Tensor_Scalar::schema>(); |
| 8759 | } |
| 8760 | |
| 8761 | // aten::bitwise_right_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor |
| 8762 | at::Tensor bitwise_right_shift_Tensor_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 8763 | |
| 8764 | static auto op = create_bitwise_right_shift_Tensor_Scalar_typed_handle(); |
| 8765 | return op.call(self, other); |
| 8766 | } |
| 8767 | |
| 8768 | // aten::bitwise_right_shift.Tensor_Scalar(Tensor self, Scalar other) -> Tensor |
| 8769 | at::Tensor bitwise_right_shift_Tensor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 8770 | |
| 8771 | static auto op = create_bitwise_right_shift_Tensor_Scalar_typed_handle(); |
| 8772 | return op.redispatch(dispatchKeySet, self, other); |
| 8773 | } |
| 8774 | |
| 8775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift__Tensor_Scalar, name, "aten::bitwise_right_shift_") |
| 8776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift__Tensor_Scalar, overload_name, "Tensor_Scalar") |
| 8777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift__Tensor_Scalar, schema_str, "bitwise_right_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 8778 | |
| 8779 | // aten::bitwise_right_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8780 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift__Tensor_Scalar::schema> create_bitwise_right_shift__Tensor_Scalar_typed_handle() { |
| 8781 | return c10::Dispatcher::singleton() |
| 8782 | .findSchemaOrThrow(bitwise_right_shift__Tensor_Scalar::name, bitwise_right_shift__Tensor_Scalar::overload_name) |
| 8783 | .typed<bitwise_right_shift__Tensor_Scalar::schema>(); |
| 8784 | } |
| 8785 | |
| 8786 | // aten::bitwise_right_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8787 | at::Tensor & bitwise_right_shift__Tensor_Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 8788 | |
| 8789 | static auto op = create_bitwise_right_shift__Tensor_Scalar_typed_handle(); |
| 8790 | return op.call(self, other); |
| 8791 | } |
| 8792 | |
| 8793 | // aten::bitwise_right_shift_.Tensor_Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 8794 | at::Tensor & bitwise_right_shift__Tensor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 8795 | |
| 8796 | static auto op = create_bitwise_right_shift__Tensor_Scalar_typed_handle(); |
| 8797 | return op.redispatch(dispatchKeySet, self, other); |
| 8798 | } |
| 8799 | |
| 8800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_Scalar_out, name, "aten::bitwise_right_shift") |
| 8801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_Scalar_out, overload_name, "Tensor_Scalar_out") |
| 8802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Tensor_Scalar_out, schema_str, "bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8803 | |
| 8804 | // aten::bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8805 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift_Tensor_Scalar_out::schema> create_bitwise_right_shift_Tensor_Scalar_out_typed_handle() { |
| 8806 | return c10::Dispatcher::singleton() |
| 8807 | .findSchemaOrThrow(bitwise_right_shift_Tensor_Scalar_out::name, bitwise_right_shift_Tensor_Scalar_out::overload_name) |
| 8808 | .typed<bitwise_right_shift_Tensor_Scalar_out::schema>(); |
| 8809 | } |
| 8810 | |
| 8811 | // aten::bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8812 | at::Tensor & bitwise_right_shift_Tensor_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8813 | |
| 8814 | static auto op = create_bitwise_right_shift_Tensor_Scalar_out_typed_handle(); |
| 8815 | return op.call(self, other, out); |
| 8816 | } |
| 8817 | |
| 8818 | // aten::bitwise_right_shift.Tensor_Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8819 | at::Tensor & bitwise_right_shift_Tensor_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8820 | |
| 8821 | static auto op = create_bitwise_right_shift_Tensor_Scalar_out_typed_handle(); |
| 8822 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8823 | } |
| 8824 | |
| 8825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Scalar_Tensor, name, "aten::bitwise_right_shift") |
| 8826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Scalar_Tensor, overload_name, "Scalar_Tensor") |
| 8827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Scalar_Tensor, schema_str, "bitwise_right_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor") |
| 8828 | |
| 8829 | // aten::bitwise_right_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8830 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift_Scalar_Tensor::schema> create_bitwise_right_shift_Scalar_Tensor_typed_handle() { |
| 8831 | return c10::Dispatcher::singleton() |
| 8832 | .findSchemaOrThrow(bitwise_right_shift_Scalar_Tensor::name, bitwise_right_shift_Scalar_Tensor::overload_name) |
| 8833 | .typed<bitwise_right_shift_Scalar_Tensor::schema>(); |
| 8834 | } |
| 8835 | |
| 8836 | // aten::bitwise_right_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8837 | at::Tensor bitwise_right_shift_Scalar_Tensor::call(const at::Scalar & self, const at::Tensor & other) { |
| 8838 | |
| 8839 | static auto op = create_bitwise_right_shift_Scalar_Tensor_typed_handle(); |
| 8840 | return op.call(self, other); |
| 8841 | } |
| 8842 | |
| 8843 | // aten::bitwise_right_shift.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 8844 | at::Tensor bitwise_right_shift_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other) { |
| 8845 | |
| 8846 | static auto op = create_bitwise_right_shift_Scalar_Tensor_typed_handle(); |
| 8847 | return op.redispatch(dispatchKeySet, self, other); |
| 8848 | } |
| 8849 | |
| 8850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential_, name, "aten::exponential_") |
| 8851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential_, overload_name, "") |
| 8852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential_, schema_str, "exponential_(Tensor(a!) self, float lambd=1, *, Generator? generator=None) -> Tensor(a!)") |
| 8853 | |
| 8854 | // aten::exponential_(Tensor(a!) self, float lambd=1, *, Generator? generator=None) -> Tensor(a!) |
| 8855 | static C10_NOINLINE c10::TypedOperatorHandle<exponential_::schema> create_exponential__typed_handle() { |
| 8856 | return c10::Dispatcher::singleton() |
| 8857 | .findSchemaOrThrow(exponential_::name, exponential_::overload_name) |
| 8858 | .typed<exponential_::schema>(); |
| 8859 | } |
| 8860 | |
| 8861 | // aten::exponential_(Tensor(a!) self, float lambd=1, *, Generator? generator=None) -> Tensor(a!) |
| 8862 | at::Tensor & exponential_::call(at::Tensor & self, double lambd, c10::optional<at::Generator> generator) { |
| 8863 | |
| 8864 | static auto op = create_exponential__typed_handle(); |
| 8865 | return op.call(self, lambd, generator); |
| 8866 | } |
| 8867 | |
| 8868 | // aten::exponential_(Tensor(a!) self, float lambd=1, *, Generator? generator=None) -> Tensor(a!) |
| 8869 | at::Tensor & exponential_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double lambd, c10::optional<at::Generator> generator) { |
| 8870 | |
| 8871 | static auto op = create_exponential__typed_handle(); |
| 8872 | return op.redispatch(dispatchKeySet, self, lambd, generator); |
| 8873 | } |
| 8874 | |
| 8875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric_, name, "aten::geometric_") |
| 8876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric_, overload_name, "") |
| 8877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric_, schema_str, "geometric_(Tensor(a!) self, float p, *, Generator? generator=None) -> Tensor(a!)") |
| 8878 | |
| 8879 | // aten::geometric_(Tensor(a!) self, float p, *, Generator? generator=None) -> Tensor(a!) |
| 8880 | static C10_NOINLINE c10::TypedOperatorHandle<geometric_::schema> create_geometric__typed_handle() { |
| 8881 | return c10::Dispatcher::singleton() |
| 8882 | .findSchemaOrThrow(geometric_::name, geometric_::overload_name) |
| 8883 | .typed<geometric_::schema>(); |
| 8884 | } |
| 8885 | |
| 8886 | // aten::geometric_(Tensor(a!) self, float p, *, Generator? generator=None) -> Tensor(a!) |
| 8887 | at::Tensor & geometric_::call(at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
| 8888 | |
| 8889 | static auto op = create_geometric__typed_handle(); |
| 8890 | return op.call(self, p, generator); |
| 8891 | } |
| 8892 | |
| 8893 | // aten::geometric_(Tensor(a!) self, float p, *, Generator? generator=None) -> Tensor(a!) |
| 8894 | at::Tensor & geometric_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
| 8895 | |
| 8896 | static auto op = create_geometric__typed_handle(); |
| 8897 | return op.redispatch(dispatchKeySet, self, p, generator); |
| 8898 | } |
| 8899 | |
| 8900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace_backward, name, "aten::trace_backward") |
| 8901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace_backward, overload_name, "") |
| 8902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace_backward, schema_str, "trace_backward(Tensor grad, SymInt[] sizes) -> Tensor") |
| 8903 | |
| 8904 | // aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor |
| 8905 | static C10_NOINLINE c10::TypedOperatorHandle<trace_backward::schema> create_trace_backward_typed_handle() { |
| 8906 | return c10::Dispatcher::singleton() |
| 8907 | .findSchemaOrThrow(trace_backward::name, trace_backward::overload_name) |
| 8908 | .typed<trace_backward::schema>(); |
| 8909 | } |
| 8910 | |
| 8911 | // aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor |
| 8912 | at::Tensor trace_backward::call(const at::Tensor & grad, c10::SymIntArrayRef sizes) { |
| 8913 | |
| 8914 | static auto op = create_trace_backward_typed_handle(); |
| 8915 | return op.call(grad, sizes); |
| 8916 | } |
| 8917 | |
| 8918 | // aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor |
| 8919 | at::Tensor trace_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, c10::SymIntArrayRef sizes) { |
| 8920 | |
| 8921 | static auto op = create_trace_backward_typed_handle(); |
| 8922 | return op.redispatch(dispatchKeySet, grad, sizes); |
| 8923 | } |
| 8924 | |
| 8925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Scalar_out, name, "aten::eq") |
| 8926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Scalar_out, overload_name, "Scalar_out") |
| 8927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Scalar_out, schema_str, "eq.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8928 | |
| 8929 | // aten::eq.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8930 | static C10_NOINLINE c10::TypedOperatorHandle<eq_Scalar_out::schema> create_eq_Scalar_out_typed_handle() { |
| 8931 | return c10::Dispatcher::singleton() |
| 8932 | .findSchemaOrThrow(eq_Scalar_out::name, eq_Scalar_out::overload_name) |
| 8933 | .typed<eq_Scalar_out::schema>(); |
| 8934 | } |
| 8935 | |
| 8936 | // aten::eq.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8937 | at::Tensor & eq_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8938 | |
| 8939 | static auto op = create_eq_Scalar_out_typed_handle(); |
| 8940 | return op.call(self, other, out); |
| 8941 | } |
| 8942 | |
| 8943 | // aten::eq.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 8944 | at::Tensor & eq_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 8945 | |
| 8946 | static auto op = create_eq_Scalar_out_typed_handle(); |
| 8947 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8948 | } |
| 8949 | |
| 8950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Scalar, name, "aten::eq") |
| 8951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Scalar, overload_name, "Scalar") |
| 8952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Scalar, schema_str, "eq.Scalar(Tensor self, Scalar other) -> Tensor") |
| 8953 | |
| 8954 | // aten::eq.Scalar(Tensor self, Scalar other) -> Tensor |
| 8955 | static C10_NOINLINE c10::TypedOperatorHandle<eq_Scalar::schema> create_eq_Scalar_typed_handle() { |
| 8956 | return c10::Dispatcher::singleton() |
| 8957 | .findSchemaOrThrow(eq_Scalar::name, eq_Scalar::overload_name) |
| 8958 | .typed<eq_Scalar::schema>(); |
| 8959 | } |
| 8960 | |
| 8961 | // aten::eq.Scalar(Tensor self, Scalar other) -> Tensor |
| 8962 | at::Tensor eq_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 8963 | |
| 8964 | static auto op = create_eq_Scalar_typed_handle(); |
| 8965 | return op.call(self, other); |
| 8966 | } |
| 8967 | |
| 8968 | // aten::eq.Scalar(Tensor self, Scalar other) -> Tensor |
| 8969 | at::Tensor eq_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 8970 | |
| 8971 | static auto op = create_eq_Scalar_typed_handle(); |
| 8972 | return op.redispatch(dispatchKeySet, self, other); |
| 8973 | } |
| 8974 | |
| 8975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Tensor_out, name, "aten::eq") |
| 8976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Tensor_out, overload_name, "Tensor_out") |
| 8977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Tensor_out, schema_str, "eq.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 8978 | |
| 8979 | // aten::eq.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8980 | static C10_NOINLINE c10::TypedOperatorHandle<eq_Tensor_out::schema> create_eq_Tensor_out_typed_handle() { |
| 8981 | return c10::Dispatcher::singleton() |
| 8982 | .findSchemaOrThrow(eq_Tensor_out::name, eq_Tensor_out::overload_name) |
| 8983 | .typed<eq_Tensor_out::schema>(); |
| 8984 | } |
| 8985 | |
| 8986 | // aten::eq.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8987 | at::Tensor & eq_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8988 | |
| 8989 | static auto op = create_eq_Tensor_out_typed_handle(); |
| 8990 | return op.call(self, other, out); |
| 8991 | } |
| 8992 | |
| 8993 | // aten::eq.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 8994 | at::Tensor & eq_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 8995 | |
| 8996 | static auto op = create_eq_Tensor_out_typed_handle(); |
| 8997 | return op.redispatch(dispatchKeySet, self, other, out); |
| 8998 | } |
| 8999 | |
| 9000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Tensor, name, "aten::eq") |
| 9001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Tensor, overload_name, "Tensor") |
| 9002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eq_Tensor, schema_str, "eq.Tensor(Tensor self, Tensor other) -> Tensor") |
| 9003 | |
| 9004 | // aten::eq.Tensor(Tensor self, Tensor other) -> Tensor |
| 9005 | static C10_NOINLINE c10::TypedOperatorHandle<eq_Tensor::schema> create_eq_Tensor_typed_handle() { |
| 9006 | return c10::Dispatcher::singleton() |
| 9007 | .findSchemaOrThrow(eq_Tensor::name, eq_Tensor::overload_name) |
| 9008 | .typed<eq_Tensor::schema>(); |
| 9009 | } |
| 9010 | |
| 9011 | // aten::eq.Tensor(Tensor self, Tensor other) -> Tensor |
| 9012 | at::Tensor eq_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 9013 | |
| 9014 | static auto op = create_eq_Tensor_typed_handle(); |
| 9015 | return op.call(self, other); |
| 9016 | } |
| 9017 | |
| 9018 | // aten::eq.Tensor(Tensor self, Tensor other) -> Tensor |
| 9019 | at::Tensor eq_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 9020 | |
| 9021 | static auto op = create_eq_Tensor_typed_handle(); |
| 9022 | return op.redispatch(dispatchKeySet, self, other); |
| 9023 | } |
| 9024 | |
| 9025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Scalar_out, name, "aten::le") |
| 9026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Scalar_out, overload_name, "Scalar_out") |
| 9027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Scalar_out, schema_str, "le.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 9028 | |
| 9029 | // aten::le.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 9030 | static C10_NOINLINE c10::TypedOperatorHandle<le_Scalar_out::schema> create_le_Scalar_out_typed_handle() { |
| 9031 | return c10::Dispatcher::singleton() |
| 9032 | .findSchemaOrThrow(le_Scalar_out::name, le_Scalar_out::overload_name) |
| 9033 | .typed<le_Scalar_out::schema>(); |
| 9034 | } |
| 9035 | |
| 9036 | // aten::le.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 9037 | at::Tensor & le_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 9038 | |
| 9039 | static auto op = create_le_Scalar_out_typed_handle(); |
| 9040 | return op.call(self, other, out); |
| 9041 | } |
| 9042 | |
| 9043 | // aten::le.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 9044 | at::Tensor & le_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 9045 | |
| 9046 | static auto op = create_le_Scalar_out_typed_handle(); |
| 9047 | return op.redispatch(dispatchKeySet, self, other, out); |
| 9048 | } |
| 9049 | |
| 9050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Scalar, name, "aten::le") |
| 9051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Scalar, overload_name, "Scalar") |
| 9052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Scalar, schema_str, "le.Scalar(Tensor self, Scalar other) -> Tensor") |
| 9053 | |
| 9054 | // aten::le.Scalar(Tensor self, Scalar other) -> Tensor |
| 9055 | static C10_NOINLINE c10::TypedOperatorHandle<le_Scalar::schema> create_le_Scalar_typed_handle() { |
| 9056 | return c10::Dispatcher::singleton() |
| 9057 | .findSchemaOrThrow(le_Scalar::name, le_Scalar::overload_name) |
| 9058 | .typed<le_Scalar::schema>(); |
| 9059 | } |
| 9060 | |
| 9061 | // aten::le.Scalar(Tensor self, Scalar other) -> Tensor |
| 9062 | at::Tensor le_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 9063 | |
| 9064 | static auto op = create_le_Scalar_typed_handle(); |
| 9065 | return op.call(self, other); |
| 9066 | } |
| 9067 | |
| 9068 | // aten::le.Scalar(Tensor self, Scalar other) -> Tensor |
| 9069 | at::Tensor le_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 9070 | |
| 9071 | static auto op = create_le_Scalar_typed_handle(); |
| 9072 | return op.redispatch(dispatchKeySet, self, other); |
| 9073 | } |
| 9074 | |
| 9075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Tensor_out, name, "aten::le") |
| 9076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Tensor_out, overload_name, "Tensor_out") |
| 9077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Tensor_out, schema_str, "le.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 9078 | |
| 9079 | // aten::le.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9080 | static C10_NOINLINE c10::TypedOperatorHandle<le_Tensor_out::schema> create_le_Tensor_out_typed_handle() { |
| 9081 | return c10::Dispatcher::singleton() |
| 9082 | .findSchemaOrThrow(le_Tensor_out::name, le_Tensor_out::overload_name) |
| 9083 | .typed<le_Tensor_out::schema>(); |
| 9084 | } |
| 9085 | |
| 9086 | // aten::le.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9087 | at::Tensor & le_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 9088 | |
| 9089 | static auto op = create_le_Tensor_out_typed_handle(); |
| 9090 | return op.call(self, other, out); |
| 9091 | } |
| 9092 | |
| 9093 | // aten::le.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9094 | at::Tensor & le_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 9095 | |
| 9096 | static auto op = create_le_Tensor_out_typed_handle(); |
| 9097 | return op.redispatch(dispatchKeySet, self, other, out); |
| 9098 | } |
| 9099 | |
| 9100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Tensor, name, "aten::le") |
| 9101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Tensor, overload_name, "Tensor") |
| 9102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le_Tensor, schema_str, "le.Tensor(Tensor self, Tensor other) -> Tensor") |
| 9103 | |
| 9104 | // aten::le.Tensor(Tensor self, Tensor other) -> Tensor |
| 9105 | static C10_NOINLINE c10::TypedOperatorHandle<le_Tensor::schema> create_le_Tensor_typed_handle() { |
| 9106 | return c10::Dispatcher::singleton() |
| 9107 | .findSchemaOrThrow(le_Tensor::name, le_Tensor::overload_name) |
| 9108 | .typed<le_Tensor::schema>(); |
| 9109 | } |
| 9110 | |
| 9111 | // aten::le.Tensor(Tensor self, Tensor other) -> Tensor |
| 9112 | at::Tensor le_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 9113 | |
| 9114 | static auto op = create_le_Tensor_typed_handle(); |
| 9115 | return op.call(self, other); |
| 9116 | } |
| 9117 | |
| 9118 | // aten::le.Tensor(Tensor self, Tensor other) -> Tensor |
| 9119 | at::Tensor le_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 9120 | |
| 9121 | static auto op = create_le_Tensor_typed_handle(); |
| 9122 | return op.redispatch(dispatchKeySet, self, other); |
| 9123 | } |
| 9124 | |
| 9125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le__Scalar, name, "aten::le_") |
| 9126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le__Scalar, overload_name, "Scalar") |
| 9127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le__Scalar, schema_str, "le_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 9128 | |
| 9129 | // aten::le_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 9130 | static C10_NOINLINE c10::TypedOperatorHandle<le__Scalar::schema> create_le__Scalar_typed_handle() { |
| 9131 | return c10::Dispatcher::singleton() |
| 9132 | .findSchemaOrThrow(le__Scalar::name, le__Scalar::overload_name) |
| 9133 | .typed<le__Scalar::schema>(); |
| 9134 | } |
| 9135 | |
| 9136 | // aten::le_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 9137 | at::Tensor & le__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 9138 | |
| 9139 | static auto op = create_le__Scalar_typed_handle(); |
| 9140 | return op.call(self, other); |
| 9141 | } |
| 9142 | |
| 9143 | // aten::le_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 9144 | at::Tensor & le__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 9145 | |
| 9146 | static auto op = create_le__Scalar_typed_handle(); |
| 9147 | return op.redispatch(dispatchKeySet, self, other); |
| 9148 | } |
| 9149 | |
| 9150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le__Tensor, name, "aten::le_") |
| 9151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le__Tensor, overload_name, "Tensor") |
| 9152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(le__Tensor, schema_str, "le_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 9153 | |
| 9154 | // aten::le_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 9155 | static C10_NOINLINE c10::TypedOperatorHandle<le__Tensor::schema> create_le__Tensor_typed_handle() { |
| 9156 | return c10::Dispatcher::singleton() |
| 9157 | .findSchemaOrThrow(le__Tensor::name, le__Tensor::overload_name) |
| 9158 | .typed<le__Tensor::schema>(); |
| 9159 | } |
| 9160 | |
| 9161 | // aten::le_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 9162 | at::Tensor & le__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 9163 | |
| 9164 | static auto op = create_le__Tensor_typed_handle(); |
| 9165 | return op.call(self, other); |
| 9166 | } |
| 9167 | |
| 9168 | // aten::le_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 9169 | at::Tensor & le__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 9170 | |
| 9171 | static auto op = create_le__Tensor_typed_handle(); |
| 9172 | return op.redispatch(dispatchKeySet, self, other); |
| 9173 | } |
| 9174 | |
| 9175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_along_dim_out, name, "aten::take_along_dim") |
| 9176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_along_dim_out, overload_name, "out") |
| 9177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_along_dim_out, schema_str, "take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 9178 | |
| 9179 | // aten::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9180 | static C10_NOINLINE c10::TypedOperatorHandle<take_along_dim_out::schema> create_take_along_dim_out_typed_handle() { |
| 9181 | return c10::Dispatcher::singleton() |
| 9182 | .findSchemaOrThrow(take_along_dim_out::name, take_along_dim_out::overload_name) |
| 9183 | .typed<take_along_dim_out::schema>(); |
| 9184 | } |
| 9185 | |
| 9186 | // aten::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9187 | at::Tensor & take_along_dim_out::call(const at::Tensor & self, const at::Tensor & indices, c10::optional<int64_t> dim, at::Tensor & out) { |
| 9188 | |
| 9189 | static auto op = create_take_along_dim_out_typed_handle(); |
| 9190 | return op.call(self, indices, dim, out); |
| 9191 | } |
| 9192 | |
| 9193 | // aten::take_along_dim.out(Tensor self, Tensor indices, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9194 | at::Tensor & take_along_dim_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, c10::optional<int64_t> dim, at::Tensor & out) { |
| 9195 | |
| 9196 | static auto op = create_take_along_dim_out_typed_handle(); |
| 9197 | return op.redispatch(dispatchKeySet, self, indices, dim, out); |
| 9198 | } |
| 9199 | |
| 9200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_along_dim, name, "aten::take_along_dim") |
| 9201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_along_dim, overload_name, "") |
| 9202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_along_dim, schema_str, "take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor") |
| 9203 | |
| 9204 | // aten::take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor |
| 9205 | static C10_NOINLINE c10::TypedOperatorHandle<take_along_dim::schema> create_take_along_dim_typed_handle() { |
| 9206 | return c10::Dispatcher::singleton() |
| 9207 | .findSchemaOrThrow(take_along_dim::name, take_along_dim::overload_name) |
| 9208 | .typed<take_along_dim::schema>(); |
| 9209 | } |
| 9210 | |
| 9211 | // aten::take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor |
| 9212 | at::Tensor take_along_dim::call(const at::Tensor & self, const at::Tensor & indices, c10::optional<int64_t> dim) { |
| 9213 | |
| 9214 | static auto op = create_take_along_dim_typed_handle(); |
| 9215 | return op.call(self, indices, dim); |
| 9216 | } |
| 9217 | |
| 9218 | // aten::take_along_dim(Tensor self, Tensor indices, int? dim=None) -> Tensor |
| 9219 | at::Tensor take_along_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, c10::optional<int64_t> dim) { |
| 9220 | |
| 9221 | static auto op = create_take_along_dim_typed_handle(); |
| 9222 | return op.redispatch(dispatchKeySet, self, indices, dim); |
| 9223 | } |
| 9224 | |
| 9225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_out, name, "aten::index_select") |
| 9226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_out, overload_name, "out") |
| 9227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_out, schema_str, "index_select.out(Tensor self, int dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!)") |
| 9228 | |
| 9229 | // aten::index_select.out(Tensor self, int dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 9230 | static C10_NOINLINE c10::TypedOperatorHandle<index_select_out::schema> create_index_select_out_typed_handle() { |
| 9231 | return c10::Dispatcher::singleton() |
| 9232 | .findSchemaOrThrow(index_select_out::name, index_select_out::overload_name) |
| 9233 | .typed<index_select_out::schema>(); |
| 9234 | } |
| 9235 | |
| 9236 | // aten::index_select.out(Tensor self, int dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 9237 | at::Tensor & index_select_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out) { |
| 9238 | |
| 9239 | static auto op = create_index_select_out_typed_handle(); |
| 9240 | return op.call(self, dim, index, out); |
| 9241 | } |
| 9242 | |
| 9243 | // aten::index_select.out(Tensor self, int dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 9244 | at::Tensor & index_select_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, at::Tensor & out) { |
| 9245 | |
| 9246 | static auto op = create_index_select_out_typed_handle(); |
| 9247 | return op.redispatch(dispatchKeySet, self, dim, index, out); |
| 9248 | } |
| 9249 | |
| 9250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select, name, "aten::index_select") |
| 9251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select, overload_name, "") |
| 9252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select, schema_str, "index_select(Tensor self, int dim, Tensor index) -> Tensor") |
| 9253 | |
| 9254 | // aten::index_select(Tensor self, int dim, Tensor index) -> Tensor |
| 9255 | static C10_NOINLINE c10::TypedOperatorHandle<index_select::schema> create_index_select_typed_handle() { |
| 9256 | return c10::Dispatcher::singleton() |
| 9257 | .findSchemaOrThrow(index_select::name, index_select::overload_name) |
| 9258 | .typed<index_select::schema>(); |
| 9259 | } |
| 9260 | |
| 9261 | // aten::index_select(Tensor self, int dim, Tensor index) -> Tensor |
| 9262 | at::Tensor index_select::call(const at::Tensor & self, int64_t dim, const at::Tensor & index) { |
| 9263 | |
| 9264 | static auto op = create_index_select_typed_handle(); |
| 9265 | return op.call(self, dim, index); |
| 9266 | } |
| 9267 | |
| 9268 | // aten::index_select(Tensor self, int dim, Tensor index) -> Tensor |
| 9269 | at::Tensor index_select::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index) { |
| 9270 | |
| 9271 | static auto op = create_index_select_typed_handle(); |
| 9272 | return op.redispatch(dispatchKeySet, self, dim, index); |
| 9273 | } |
| 9274 | |
| 9275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_dimname_out, name, "aten::index_select") |
| 9276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_dimname_out, overload_name, "dimname_out") |
| 9277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_dimname_out, schema_str, "index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!)") |
| 9278 | |
| 9279 | // aten::index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 9280 | static C10_NOINLINE c10::TypedOperatorHandle<index_select_dimname_out::schema> create_index_select_dimname_out_typed_handle() { |
| 9281 | return c10::Dispatcher::singleton() |
| 9282 | .findSchemaOrThrow(index_select_dimname_out::name, index_select_dimname_out::overload_name) |
| 9283 | .typed<index_select_dimname_out::schema>(); |
| 9284 | } |
| 9285 | |
| 9286 | // aten::index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 9287 | at::Tensor & index_select_dimname_out::call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, at::Tensor & out) { |
| 9288 | |
| 9289 | static auto op = create_index_select_dimname_out_typed_handle(); |
| 9290 | return op.call(self, dim, index, out); |
| 9291 | } |
| 9292 | |
| 9293 | // aten::index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 9294 | at::Tensor & index_select_dimname_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, at::Tensor & out) { |
| 9295 | |
| 9296 | static auto op = create_index_select_dimname_out_typed_handle(); |
| 9297 | return op.redispatch(dispatchKeySet, self, dim, index, out); |
| 9298 | } |
| 9299 | |
| 9300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_dimname, name, "aten::index_select") |
| 9301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_dimname, overload_name, "dimname") |
| 9302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_dimname, schema_str, "index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor") |
| 9303 | |
| 9304 | // aten::index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor |
| 9305 | static C10_NOINLINE c10::TypedOperatorHandle<index_select_dimname::schema> create_index_select_dimname_typed_handle() { |
| 9306 | return c10::Dispatcher::singleton() |
| 9307 | .findSchemaOrThrow(index_select_dimname::name, index_select_dimname::overload_name) |
| 9308 | .typed<index_select_dimname::schema>(); |
| 9309 | } |
| 9310 | |
| 9311 | // aten::index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor |
| 9312 | at::Tensor index_select_dimname::call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index) { |
| 9313 | |
| 9314 | static auto op = create_index_select_dimname_typed_handle(); |
| 9315 | return op.call(self, dim, index); |
| 9316 | } |
| 9317 | |
| 9318 | // aten::index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor |
| 9319 | at::Tensor index_select_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index) { |
| 9320 | |
| 9321 | static auto op = create_index_select_dimname_typed_handle(); |
| 9322 | return op.redispatch(dispatchKeySet, self, dim, index); |
| 9323 | } |
| 9324 | |
| 9325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select_backward, name, "aten::masked_select_backward") |
| 9326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select_backward, overload_name, "") |
| 9327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select_backward, schema_str, "masked_select_backward(Tensor grad, Tensor input, Tensor mask) -> Tensor") |
| 9328 | |
| 9329 | // aten::masked_select_backward(Tensor grad, Tensor input, Tensor mask) -> Tensor |
| 9330 | static C10_NOINLINE c10::TypedOperatorHandle<masked_select_backward::schema> create_masked_select_backward_typed_handle() { |
| 9331 | return c10::Dispatcher::singleton() |
| 9332 | .findSchemaOrThrow(masked_select_backward::name, masked_select_backward::overload_name) |
| 9333 | .typed<masked_select_backward::schema>(); |
| 9334 | } |
| 9335 | |
| 9336 | // aten::masked_select_backward(Tensor grad, Tensor input, Tensor mask) -> Tensor |
| 9337 | at::Tensor masked_select_backward::call(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & mask) { |
| 9338 | |
| 9339 | static auto op = create_masked_select_backward_typed_handle(); |
| 9340 | return op.call(grad, input, mask); |
| 9341 | } |
| 9342 | |
| 9343 | // aten::masked_select_backward(Tensor grad, Tensor input, Tensor mask) -> Tensor |
| 9344 | at::Tensor masked_select_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & input, const at::Tensor & mask) { |
| 9345 | |
| 9346 | static auto op = create_masked_select_backward_typed_handle(); |
| 9347 | return op.redispatch(dispatchKeySet, grad, input, mask); |
| 9348 | } |
| 9349 | |
| 9350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero_out, name, "aten::nonzero") |
| 9351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero_out, overload_name, "out") |
| 9352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero_out, schema_str, "nonzero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 9353 | |
| 9354 | // aten::nonzero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9355 | static C10_NOINLINE c10::TypedOperatorHandle<nonzero_out::schema> create_nonzero_out_typed_handle() { |
| 9356 | return c10::Dispatcher::singleton() |
| 9357 | .findSchemaOrThrow(nonzero_out::name, nonzero_out::overload_name) |
| 9358 | .typed<nonzero_out::schema>(); |
| 9359 | } |
| 9360 | |
| 9361 | // aten::nonzero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9362 | at::Tensor & nonzero_out::call(const at::Tensor & self, at::Tensor & out) { |
| 9363 | |
| 9364 | static auto op = create_nonzero_out_typed_handle(); |
| 9365 | return op.call(self, out); |
| 9366 | } |
| 9367 | |
| 9368 | // aten::nonzero.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9369 | at::Tensor & nonzero_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 9370 | |
| 9371 | static auto op = create_nonzero_out_typed_handle(); |
| 9372 | return op.redispatch(dispatchKeySet, self, out); |
| 9373 | } |
| 9374 | |
| 9375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero, name, "aten::nonzero") |
| 9376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero, overload_name, "") |
| 9377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero, schema_str, "nonzero(Tensor self) -> Tensor") |
| 9378 | |
| 9379 | // aten::nonzero(Tensor self) -> Tensor |
| 9380 | static C10_NOINLINE c10::TypedOperatorHandle<nonzero::schema> create_nonzero_typed_handle() { |
| 9381 | return c10::Dispatcher::singleton() |
| 9382 | .findSchemaOrThrow(nonzero::name, nonzero::overload_name) |
| 9383 | .typed<nonzero::schema>(); |
| 9384 | } |
| 9385 | |
| 9386 | // aten::nonzero(Tensor self) -> Tensor |
| 9387 | at::Tensor nonzero::call(const at::Tensor & self) { |
| 9388 | |
| 9389 | static auto op = create_nonzero_typed_handle(); |
| 9390 | return op.call(self); |
| 9391 | } |
| 9392 | |
| 9393 | // aten::nonzero(Tensor self) -> Tensor |
| 9394 | at::Tensor nonzero::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9395 | |
| 9396 | static auto op = create_nonzero_typed_handle(); |
| 9397 | return op.redispatch(dispatchKeySet, self); |
| 9398 | } |
| 9399 | |
| 9400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero_numpy, name, "aten::nonzero_numpy") |
| 9401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero_numpy, overload_name, "") |
| 9402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nonzero_numpy, schema_str, "nonzero_numpy(Tensor self) -> Tensor[]") |
| 9403 | |
| 9404 | // aten::nonzero_numpy(Tensor self) -> Tensor[] |
| 9405 | static C10_NOINLINE c10::TypedOperatorHandle<nonzero_numpy::schema> create_nonzero_numpy_typed_handle() { |
| 9406 | return c10::Dispatcher::singleton() |
| 9407 | .findSchemaOrThrow(nonzero_numpy::name, nonzero_numpy::overload_name) |
| 9408 | .typed<nonzero_numpy::schema>(); |
| 9409 | } |
| 9410 | |
| 9411 | // aten::nonzero_numpy(Tensor self) -> Tensor[] |
| 9412 | ::std::vector<at::Tensor> nonzero_numpy::call(const at::Tensor & self) { |
| 9413 | |
| 9414 | static auto op = create_nonzero_numpy_typed_handle(); |
| 9415 | return op.call(self); |
| 9416 | } |
| 9417 | |
| 9418 | // aten::nonzero_numpy(Tensor self) -> Tensor[] |
| 9419 | ::std::vector<at::Tensor> nonzero_numpy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9420 | |
| 9421 | static auto op = create_nonzero_numpy_typed_handle(); |
| 9422 | return op.redispatch(dispatchKeySet, self); |
| 9423 | } |
| 9424 | |
| 9425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul_out, name, "aten::addcmul") |
| 9426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul_out, overload_name, "out") |
| 9427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul_out, schema_str, "addcmul.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!)") |
| 9428 | |
| 9429 | // aten::addcmul.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) |
| 9430 | static C10_NOINLINE c10::TypedOperatorHandle<addcmul_out::schema> create_addcmul_out_typed_handle() { |
| 9431 | return c10::Dispatcher::singleton() |
| 9432 | .findSchemaOrThrow(addcmul_out::name, addcmul_out::overload_name) |
| 9433 | .typed<addcmul_out::schema>(); |
| 9434 | } |
| 9435 | |
| 9436 | // aten::addcmul.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) |
| 9437 | at::Tensor & addcmul_out::call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out) { |
| 9438 | |
| 9439 | static auto op = create_addcmul_out_typed_handle(); |
| 9440 | return op.call(self, tensor1, tensor2, value, out); |
| 9441 | } |
| 9442 | |
| 9443 | // aten::addcmul.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) |
| 9444 | at::Tensor & addcmul_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out) { |
| 9445 | |
| 9446 | static auto op = create_addcmul_out_typed_handle(); |
| 9447 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value, out); |
| 9448 | } |
| 9449 | |
| 9450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul, name, "aten::addcmul") |
| 9451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul, overload_name, "") |
| 9452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul, schema_str, "addcmul(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor") |
| 9453 | |
| 9454 | // aten::addcmul(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor |
| 9455 | static C10_NOINLINE c10::TypedOperatorHandle<addcmul::schema> create_addcmul_typed_handle() { |
| 9456 | return c10::Dispatcher::singleton() |
| 9457 | .findSchemaOrThrow(addcmul::name, addcmul::overload_name) |
| 9458 | .typed<addcmul::schema>(); |
| 9459 | } |
| 9460 | |
| 9461 | // aten::addcmul(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor |
| 9462 | at::Tensor addcmul::call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
| 9463 | |
| 9464 | static auto op = create_addcmul_typed_handle(); |
| 9465 | return op.call(self, tensor1, tensor2, value); |
| 9466 | } |
| 9467 | |
| 9468 | // aten::addcmul(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor |
| 9469 | at::Tensor addcmul::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
| 9470 | |
| 9471 | static auto op = create_addcmul_typed_handle(); |
| 9472 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value); |
| 9473 | } |
| 9474 | |
| 9475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul_, name, "aten::addcmul_") |
| 9476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul_, overload_name, "") |
| 9477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcmul_, schema_str, "addcmul_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!)") |
| 9478 | |
| 9479 | // aten::addcmul_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!) |
| 9480 | static C10_NOINLINE c10::TypedOperatorHandle<addcmul_::schema> create_addcmul__typed_handle() { |
| 9481 | return c10::Dispatcher::singleton() |
| 9482 | .findSchemaOrThrow(addcmul_::name, addcmul_::overload_name) |
| 9483 | .typed<addcmul_::schema>(); |
| 9484 | } |
| 9485 | |
| 9486 | // aten::addcmul_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!) |
| 9487 | at::Tensor & addcmul_::call(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
| 9488 | |
| 9489 | static auto op = create_addcmul__typed_handle(); |
| 9490 | return op.call(self, tensor1, tensor2, value); |
| 9491 | } |
| 9492 | |
| 9493 | // aten::addcmul_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!) |
| 9494 | at::Tensor & addcmul_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
| 9495 | |
| 9496 | static auto op = create_addcmul__typed_handle(); |
| 9497 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value); |
| 9498 | } |
| 9499 | |
| 9500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(swapdims, name, "aten::swapdims") |
| 9501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(swapdims, overload_name, "") |
| 9502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(swapdims, schema_str, "swapdims(Tensor(a) self, int dim0, int dim1) -> Tensor(a)") |
| 9503 | |
| 9504 | // aten::swapdims(Tensor(a) self, int dim0, int dim1) -> Tensor(a) |
| 9505 | static C10_NOINLINE c10::TypedOperatorHandle<swapdims::schema> create_swapdims_typed_handle() { |
| 9506 | return c10::Dispatcher::singleton() |
| 9507 | .findSchemaOrThrow(swapdims::name, swapdims::overload_name) |
| 9508 | .typed<swapdims::schema>(); |
| 9509 | } |
| 9510 | |
| 9511 | // aten::swapdims(Tensor(a) self, int dim0, int dim1) -> Tensor(a) |
| 9512 | at::Tensor swapdims::call(const at::Tensor & self, int64_t dim0, int64_t dim1) { |
| 9513 | |
| 9514 | static auto op = create_swapdims_typed_handle(); |
| 9515 | return op.call(self, dim0, dim1); |
| 9516 | } |
| 9517 | |
| 9518 | // aten::swapdims(Tensor(a) self, int dim0, int dim1) -> Tensor(a) |
| 9519 | at::Tensor swapdims::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1) { |
| 9520 | |
| 9521 | static auto op = create_swapdims_typed_handle(); |
| 9522 | return op.redispatch(dispatchKeySet, self, dim0, dim1); |
| 9523 | } |
| 9524 | |
| 9525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(swapdims_, name, "aten::swapdims_") |
| 9526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(swapdims_, overload_name, "") |
| 9527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(swapdims_, schema_str, "swapdims_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!)") |
| 9528 | |
| 9529 | // aten::swapdims_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!) |
| 9530 | static C10_NOINLINE c10::TypedOperatorHandle<swapdims_::schema> create_swapdims__typed_handle() { |
| 9531 | return c10::Dispatcher::singleton() |
| 9532 | .findSchemaOrThrow(swapdims_::name, swapdims_::overload_name) |
| 9533 | .typed<swapdims_::schema>(); |
| 9534 | } |
| 9535 | |
| 9536 | // aten::swapdims_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!) |
| 9537 | at::Tensor & swapdims_::call(at::Tensor & self, int64_t dim0, int64_t dim1) { |
| 9538 | |
| 9539 | static auto op = create_swapdims__typed_handle(); |
| 9540 | return op.call(self, dim0, dim1); |
| 9541 | } |
| 9542 | |
| 9543 | // aten::swapdims_(Tensor(a!) self, int dim0, int dim1) -> Tensor(a!) |
| 9544 | at::Tensor & swapdims_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim0, int64_t dim1) { |
| 9545 | |
| 9546 | static auto op = create_swapdims__typed_handle(); |
| 9547 | return op.redispatch(dispatchKeySet, self, dim0, dim1); |
| 9548 | } |
| 9549 | |
| 9550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_out, name, "aten::cholesky") |
| 9551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_out, overload_name, "out") |
| 9552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_out, schema_str, "cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 9553 | |
| 9554 | // aten::cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) |
| 9555 | static C10_NOINLINE c10::TypedOperatorHandle<cholesky_out::schema> create_cholesky_out_typed_handle() { |
| 9556 | return c10::Dispatcher::singleton() |
| 9557 | .findSchemaOrThrow(cholesky_out::name, cholesky_out::overload_name) |
| 9558 | .typed<cholesky_out::schema>(); |
| 9559 | } |
| 9560 | |
| 9561 | // aten::cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) |
| 9562 | at::Tensor & cholesky_out::call(const at::Tensor & self, bool upper, at::Tensor & out) { |
| 9563 | |
| 9564 | static auto op = create_cholesky_out_typed_handle(); |
| 9565 | return op.call(self, upper, out); |
| 9566 | } |
| 9567 | |
| 9568 | // aten::cholesky.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) |
| 9569 | at::Tensor & cholesky_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper, at::Tensor & out) { |
| 9570 | |
| 9571 | static auto op = create_cholesky_out_typed_handle(); |
| 9572 | return op.redispatch(dispatchKeySet, self, upper, out); |
| 9573 | } |
| 9574 | |
| 9575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky, name, "aten::cholesky") |
| 9576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky, overload_name, "") |
| 9577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky, schema_str, "cholesky(Tensor self, bool upper=False) -> Tensor") |
| 9578 | |
| 9579 | // aten::cholesky(Tensor self, bool upper=False) -> Tensor |
| 9580 | static C10_NOINLINE c10::TypedOperatorHandle<cholesky::schema> create_cholesky_typed_handle() { |
| 9581 | return c10::Dispatcher::singleton() |
| 9582 | .findSchemaOrThrow(cholesky::name, cholesky::overload_name) |
| 9583 | .typed<cholesky::schema>(); |
| 9584 | } |
| 9585 | |
| 9586 | // aten::cholesky(Tensor self, bool upper=False) -> Tensor |
| 9587 | at::Tensor cholesky::call(const at::Tensor & self, bool upper) { |
| 9588 | |
| 9589 | static auto op = create_cholesky_typed_handle(); |
| 9590 | return op.call(self, upper); |
| 9591 | } |
| 9592 | |
| 9593 | // aten::cholesky(Tensor self, bool upper=False) -> Tensor |
| 9594 | at::Tensor cholesky::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper) { |
| 9595 | |
| 9596 | static auto op = create_cholesky_typed_handle(); |
| 9597 | return op.redispatch(dispatchKeySet, self, upper); |
| 9598 | } |
| 9599 | |
| 9600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_solve_out, name, "aten::lu_solve") |
| 9601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_solve_out, overload_name, "out") |
| 9602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_solve_out, schema_str, "lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!)") |
| 9603 | |
| 9604 | // aten::lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!) |
| 9605 | static C10_NOINLINE c10::TypedOperatorHandle<lu_solve_out::schema> create_lu_solve_out_typed_handle() { |
| 9606 | return c10::Dispatcher::singleton() |
| 9607 | .findSchemaOrThrow(lu_solve_out::name, lu_solve_out::overload_name) |
| 9608 | .typed<lu_solve_out::schema>(); |
| 9609 | } |
| 9610 | |
| 9611 | // aten::lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!) |
| 9612 | at::Tensor & lu_solve_out::call(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots, at::Tensor & out) { |
| 9613 | |
| 9614 | static auto op = create_lu_solve_out_typed_handle(); |
| 9615 | return op.call(self, LU_data, LU_pivots, out); |
| 9616 | } |
| 9617 | |
| 9618 | // aten::lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!) |
| 9619 | at::Tensor & lu_solve_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots, at::Tensor & out) { |
| 9620 | |
| 9621 | static auto op = create_lu_solve_out_typed_handle(); |
| 9622 | return op.redispatch(dispatchKeySet, self, LU_data, LU_pivots, out); |
| 9623 | } |
| 9624 | |
| 9625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_solve, name, "aten::lu_solve") |
| 9626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_solve, overload_name, "") |
| 9627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_solve, schema_str, "lu_solve(Tensor self, Tensor LU_data, Tensor LU_pivots) -> Tensor") |
| 9628 | |
| 9629 | // aten::lu_solve(Tensor self, Tensor LU_data, Tensor LU_pivots) -> Tensor |
| 9630 | static C10_NOINLINE c10::TypedOperatorHandle<lu_solve::schema> create_lu_solve_typed_handle() { |
| 9631 | return c10::Dispatcher::singleton() |
| 9632 | .findSchemaOrThrow(lu_solve::name, lu_solve::overload_name) |
| 9633 | .typed<lu_solve::schema>(); |
| 9634 | } |
| 9635 | |
| 9636 | // aten::lu_solve(Tensor self, Tensor LU_data, Tensor LU_pivots) -> Tensor |
| 9637 | at::Tensor lu_solve::call(const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots) { |
| 9638 | |
| 9639 | static auto op = create_lu_solve_typed_handle(); |
| 9640 | return op.call(self, LU_data, LU_pivots); |
| 9641 | } |
| 9642 | |
| 9643 | // aten::lu_solve(Tensor self, Tensor LU_data, Tensor LU_pivots) -> Tensor |
| 9644 | at::Tensor lu_solve::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & LU_data, const at::Tensor & LU_pivots) { |
| 9645 | |
| 9646 | static auto op = create_lu_solve_typed_handle(); |
| 9647 | return op.redispatch(dispatchKeySet, self, LU_data, LU_pivots); |
| 9648 | } |
| 9649 | |
| 9650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_unpack, name, "aten::lu_unpack") |
| 9651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_unpack, overload_name, "") |
| 9652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_unpack, schema_str, "lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True) -> (Tensor P, Tensor L, Tensor U)") |
| 9653 | |
| 9654 | // aten::lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True) -> (Tensor P, Tensor L, Tensor U) |
| 9655 | static C10_NOINLINE c10::TypedOperatorHandle<lu_unpack::schema> create_lu_unpack_typed_handle() { |
| 9656 | return c10::Dispatcher::singleton() |
| 9657 | .findSchemaOrThrow(lu_unpack::name, lu_unpack::overload_name) |
| 9658 | .typed<lu_unpack::schema>(); |
| 9659 | } |
| 9660 | |
| 9661 | // aten::lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True) -> (Tensor P, Tensor L, Tensor U) |
| 9662 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> lu_unpack::call(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots) { |
| 9663 | |
| 9664 | static auto op = create_lu_unpack_typed_handle(); |
| 9665 | return op.call(LU_data, LU_pivots, unpack_data, unpack_pivots); |
| 9666 | } |
| 9667 | |
| 9668 | // aten::lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True) -> (Tensor P, Tensor L, Tensor U) |
| 9669 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> lu_unpack::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots) { |
| 9670 | |
| 9671 | static auto op = create_lu_unpack_typed_handle(); |
| 9672 | return op.redispatch(dispatchKeySet, LU_data, LU_pivots, unpack_data, unpack_pivots); |
| 9673 | } |
| 9674 | |
| 9675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_unpack_out, name, "aten::lu_unpack") |
| 9676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_unpack_out, overload_name, "out") |
| 9677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lu_unpack_out, schema_str, "lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U)") |
| 9678 | |
| 9679 | // aten::lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) |
| 9680 | static C10_NOINLINE c10::TypedOperatorHandle<lu_unpack_out::schema> create_lu_unpack_out_typed_handle() { |
| 9681 | return c10::Dispatcher::singleton() |
| 9682 | .findSchemaOrThrow(lu_unpack_out::name, lu_unpack_out::overload_name) |
| 9683 | .typed<lu_unpack_out::schema>(); |
| 9684 | } |
| 9685 | |
| 9686 | // aten::lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) |
| 9687 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> lu_unpack_out::call(const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U) { |
| 9688 | |
| 9689 | static auto op = create_lu_unpack_out_typed_handle(); |
| 9690 | return op.call(LU_data, LU_pivots, unpack_data, unpack_pivots, P, L, U); |
| 9691 | } |
| 9692 | |
| 9693 | // aten::lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True, *, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) |
| 9694 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> lu_unpack_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LU_data, const at::Tensor & LU_pivots, bool unpack_data, bool unpack_pivots, at::Tensor & P, at::Tensor & L, at::Tensor & U) { |
| 9695 | |
| 9696 | static auto op = create_lu_unpack_out_typed_handle(); |
| 9697 | return op.redispatch(dispatchKeySet, LU_data, LU_pivots, unpack_data, unpack_pivots, P, L, U); |
| 9698 | } |
| 9699 | |
| 9700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multinomial_out, name, "aten::multinomial") |
| 9701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multinomial_out, overload_name, "out") |
| 9702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multinomial_out, schema_str, "multinomial.out(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)") |
| 9703 | |
| 9704 | // aten::multinomial.out(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 9705 | static C10_NOINLINE c10::TypedOperatorHandle<multinomial_out::schema> create_multinomial_out_typed_handle() { |
| 9706 | return c10::Dispatcher::singleton() |
| 9707 | .findSchemaOrThrow(multinomial_out::name, multinomial_out::overload_name) |
| 9708 | .typed<multinomial_out::schema>(); |
| 9709 | } |
| 9710 | |
| 9711 | // aten::multinomial.out(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 9712 | at::Tensor & multinomial_out::call(const at::Tensor & self, int64_t num_samples, bool replacement, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 9713 | |
| 9714 | static auto op = create_multinomial_out_typed_handle(); |
| 9715 | return op.call(self, num_samples, replacement, generator, out); |
| 9716 | } |
| 9717 | |
| 9718 | // aten::multinomial.out(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 9719 | at::Tensor & multinomial_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t num_samples, bool replacement, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 9720 | |
| 9721 | static auto op = create_multinomial_out_typed_handle(); |
| 9722 | return op.redispatch(dispatchKeySet, self, num_samples, replacement, generator, out); |
| 9723 | } |
| 9724 | |
| 9725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multinomial, name, "aten::multinomial") |
| 9726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multinomial, overload_name, "") |
| 9727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multinomial, schema_str, "multinomial(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None) -> Tensor") |
| 9728 | |
| 9729 | // aten::multinomial(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None) -> Tensor |
| 9730 | static C10_NOINLINE c10::TypedOperatorHandle<multinomial::schema> create_multinomial_typed_handle() { |
| 9731 | return c10::Dispatcher::singleton() |
| 9732 | .findSchemaOrThrow(multinomial::name, multinomial::overload_name) |
| 9733 | .typed<multinomial::schema>(); |
| 9734 | } |
| 9735 | |
| 9736 | // aten::multinomial(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None) -> Tensor |
| 9737 | at::Tensor multinomial::call(const at::Tensor & self, int64_t num_samples, bool replacement, c10::optional<at::Generator> generator) { |
| 9738 | |
| 9739 | static auto op = create_multinomial_typed_handle(); |
| 9740 | return op.call(self, num_samples, replacement, generator); |
| 9741 | } |
| 9742 | |
| 9743 | // aten::multinomial(Tensor self, int num_samples, bool replacement=False, *, Generator? generator=None) -> Tensor |
| 9744 | at::Tensor multinomial::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t num_samples, bool replacement, c10::optional<at::Generator> generator) { |
| 9745 | |
| 9746 | static auto op = create_multinomial_typed_handle(); |
| 9747 | return op.redispatch(dispatchKeySet, self, num_samples, replacement, generator); |
| 9748 | } |
| 9749 | |
| 9750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma_out, name, "aten::lgamma") |
| 9751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma_out, overload_name, "out") |
| 9752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma_out, schema_str, "lgamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 9753 | |
| 9754 | // aten::lgamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9755 | static C10_NOINLINE c10::TypedOperatorHandle<lgamma_out::schema> create_lgamma_out_typed_handle() { |
| 9756 | return c10::Dispatcher::singleton() |
| 9757 | .findSchemaOrThrow(lgamma_out::name, lgamma_out::overload_name) |
| 9758 | .typed<lgamma_out::schema>(); |
| 9759 | } |
| 9760 | |
| 9761 | // aten::lgamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9762 | at::Tensor & lgamma_out::call(const at::Tensor & self, at::Tensor & out) { |
| 9763 | |
| 9764 | static auto op = create_lgamma_out_typed_handle(); |
| 9765 | return op.call(self, out); |
| 9766 | } |
| 9767 | |
| 9768 | // aten::lgamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9769 | at::Tensor & lgamma_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 9770 | |
| 9771 | static auto op = create_lgamma_out_typed_handle(); |
| 9772 | return op.redispatch(dispatchKeySet, self, out); |
| 9773 | } |
| 9774 | |
| 9775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma_, name, "aten::lgamma_") |
| 9776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma_, overload_name, "") |
| 9777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma_, schema_str, "lgamma_(Tensor(a!) self) -> Tensor(a!)") |
| 9778 | |
| 9779 | // aten::lgamma_(Tensor(a!) self) -> Tensor(a!) |
| 9780 | static C10_NOINLINE c10::TypedOperatorHandle<lgamma_::schema> create_lgamma__typed_handle() { |
| 9781 | return c10::Dispatcher::singleton() |
| 9782 | .findSchemaOrThrow(lgamma_::name, lgamma_::overload_name) |
| 9783 | .typed<lgamma_::schema>(); |
| 9784 | } |
| 9785 | |
| 9786 | // aten::lgamma_(Tensor(a!) self) -> Tensor(a!) |
| 9787 | at::Tensor & lgamma_::call(at::Tensor & self) { |
| 9788 | |
| 9789 | static auto op = create_lgamma__typed_handle(); |
| 9790 | return op.call(self); |
| 9791 | } |
| 9792 | |
| 9793 | // aten::lgamma_(Tensor(a!) self) -> Tensor(a!) |
| 9794 | at::Tensor & lgamma_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 9795 | |
| 9796 | static auto op = create_lgamma__typed_handle(); |
| 9797 | return op.redispatch(dispatchKeySet, self); |
| 9798 | } |
| 9799 | |
| 9800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma, name, "aten::lgamma") |
| 9801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma, overload_name, "") |
| 9802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lgamma, schema_str, "lgamma(Tensor self) -> Tensor") |
| 9803 | |
| 9804 | // aten::lgamma(Tensor self) -> Tensor |
| 9805 | static C10_NOINLINE c10::TypedOperatorHandle<lgamma::schema> create_lgamma_typed_handle() { |
| 9806 | return c10::Dispatcher::singleton() |
| 9807 | .findSchemaOrThrow(lgamma::name, lgamma::overload_name) |
| 9808 | .typed<lgamma::schema>(); |
| 9809 | } |
| 9810 | |
| 9811 | // aten::lgamma(Tensor self) -> Tensor |
| 9812 | at::Tensor lgamma::call(const at::Tensor & self) { |
| 9813 | |
| 9814 | static auto op = create_lgamma_typed_handle(); |
| 9815 | return op.call(self); |
| 9816 | } |
| 9817 | |
| 9818 | // aten::lgamma(Tensor self) -> Tensor |
| 9819 | at::Tensor lgamma::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9820 | |
| 9821 | static auto op = create_lgamma_typed_handle(); |
| 9822 | return op.redispatch(dispatchKeySet, self); |
| 9823 | } |
| 9824 | |
| 9825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2, name, "aten::arctan2") |
| 9826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2, overload_name, "") |
| 9827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2, schema_str, "arctan2(Tensor self, Tensor other) -> Tensor") |
| 9828 | |
| 9829 | // aten::arctan2(Tensor self, Tensor other) -> Tensor |
| 9830 | static C10_NOINLINE c10::TypedOperatorHandle<arctan2::schema> create_arctan2_typed_handle() { |
| 9831 | return c10::Dispatcher::singleton() |
| 9832 | .findSchemaOrThrow(arctan2::name, arctan2::overload_name) |
| 9833 | .typed<arctan2::schema>(); |
| 9834 | } |
| 9835 | |
| 9836 | // aten::arctan2(Tensor self, Tensor other) -> Tensor |
| 9837 | at::Tensor arctan2::call(const at::Tensor & self, const at::Tensor & other) { |
| 9838 | |
| 9839 | static auto op = create_arctan2_typed_handle(); |
| 9840 | return op.call(self, other); |
| 9841 | } |
| 9842 | |
| 9843 | // aten::arctan2(Tensor self, Tensor other) -> Tensor |
| 9844 | at::Tensor arctan2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 9845 | |
| 9846 | static auto op = create_arctan2_typed_handle(); |
| 9847 | return op.redispatch(dispatchKeySet, self, other); |
| 9848 | } |
| 9849 | |
| 9850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2_out, name, "aten::arctan2") |
| 9851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2_out, overload_name, "out") |
| 9852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2_out, schema_str, "arctan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 9853 | |
| 9854 | // aten::arctan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9855 | static C10_NOINLINE c10::TypedOperatorHandle<arctan2_out::schema> create_arctan2_out_typed_handle() { |
| 9856 | return c10::Dispatcher::singleton() |
| 9857 | .findSchemaOrThrow(arctan2_out::name, arctan2_out::overload_name) |
| 9858 | .typed<arctan2_out::schema>(); |
| 9859 | } |
| 9860 | |
| 9861 | // aten::arctan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9862 | at::Tensor & arctan2_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 9863 | |
| 9864 | static auto op = create_arctan2_out_typed_handle(); |
| 9865 | return op.call(self, other, out); |
| 9866 | } |
| 9867 | |
| 9868 | // aten::arctan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9869 | at::Tensor & arctan2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 9870 | |
| 9871 | static auto op = create_arctan2_out_typed_handle(); |
| 9872 | return op.redispatch(dispatchKeySet, self, other, out); |
| 9873 | } |
| 9874 | |
| 9875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2_, name, "aten::arctan2_") |
| 9876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2_, overload_name, "") |
| 9877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arctan2_, schema_str, "arctan2_(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 9878 | |
| 9879 | // aten::arctan2_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 9880 | static C10_NOINLINE c10::TypedOperatorHandle<arctan2_::schema> create_arctan2__typed_handle() { |
| 9881 | return c10::Dispatcher::singleton() |
| 9882 | .findSchemaOrThrow(arctan2_::name, arctan2_::overload_name) |
| 9883 | .typed<arctan2_::schema>(); |
| 9884 | } |
| 9885 | |
| 9886 | // aten::arctan2_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 9887 | at::Tensor & arctan2_::call(at::Tensor & self, const at::Tensor & other) { |
| 9888 | |
| 9889 | static auto op = create_arctan2__typed_handle(); |
| 9890 | return op.call(self, other); |
| 9891 | } |
| 9892 | |
| 9893 | // aten::arctan2_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 9894 | at::Tensor & arctan2_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 9895 | |
| 9896 | static auto op = create_arctan2__typed_handle(); |
| 9897 | return op.redispatch(dispatchKeySet, self, other); |
| 9898 | } |
| 9899 | |
| 9900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bins_tensor_out, name, "aten::histogram") |
| 9901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bins_tensor_out, overload_name, "bins_tensor_out") |
| 9902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bins_tensor_out, schema_str, "histogram.bins_tensor_out(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges)") |
| 9903 | |
| 9904 | // aten::histogram.bins_tensor_out(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges) |
| 9905 | static C10_NOINLINE c10::TypedOperatorHandle<histogram_bins_tensor_out::schema> create_histogram_bins_tensor_out_typed_handle() { |
| 9906 | return c10::Dispatcher::singleton() |
| 9907 | .findSchemaOrThrow(histogram_bins_tensor_out::name, histogram_bins_tensor_out::overload_name) |
| 9908 | .typed<histogram_bins_tensor_out::schema>(); |
| 9909 | } |
| 9910 | |
| 9911 | // aten::histogram.bins_tensor_out(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges) |
| 9912 | ::std::tuple<at::Tensor &,at::Tensor &> histogram_bins_tensor_out::call(const at::Tensor & self, const at::Tensor & bins, const c10::optional<at::Tensor> & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges) { |
| 9913 | |
| 9914 | static auto op = create_histogram_bins_tensor_out_typed_handle(); |
| 9915 | return op.call(self, bins, weight, density, hist, bin_edges); |
| 9916 | } |
| 9917 | |
| 9918 | // aten::histogram.bins_tensor_out(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges) |
| 9919 | ::std::tuple<at::Tensor &,at::Tensor &> histogram_bins_tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & bins, const c10::optional<at::Tensor> & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges) { |
| 9920 | |
| 9921 | static auto op = create_histogram_bins_tensor_out_typed_handle(); |
| 9922 | return op.redispatch(dispatchKeySet, self, bins, weight, density, hist, bin_edges); |
| 9923 | } |
| 9924 | |
| 9925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bins_tensor, name, "aten::histogram") |
| 9926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bins_tensor, overload_name, "bins_tensor") |
| 9927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bins_tensor, schema_str, "histogram.bins_tensor(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges)") |
| 9928 | |
| 9929 | // aten::histogram.bins_tensor(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges) |
| 9930 | static C10_NOINLINE c10::TypedOperatorHandle<histogram_bins_tensor::schema> create_histogram_bins_tensor_typed_handle() { |
| 9931 | return c10::Dispatcher::singleton() |
| 9932 | .findSchemaOrThrow(histogram_bins_tensor::name, histogram_bins_tensor::overload_name) |
| 9933 | .typed<histogram_bins_tensor::schema>(); |
| 9934 | } |
| 9935 | |
| 9936 | // aten::histogram.bins_tensor(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges) |
| 9937 | ::std::tuple<at::Tensor,at::Tensor> histogram_bins_tensor::call(const at::Tensor & self, const at::Tensor & bins, const c10::optional<at::Tensor> & weight, bool density) { |
| 9938 | |
| 9939 | static auto op = create_histogram_bins_tensor_typed_handle(); |
| 9940 | return op.call(self, bins, weight, density); |
| 9941 | } |
| 9942 | |
| 9943 | // aten::histogram.bins_tensor(Tensor self, Tensor bins, *, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges) |
| 9944 | ::std::tuple<at::Tensor,at::Tensor> histogram_bins_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & bins, const c10::optional<at::Tensor> & weight, bool density) { |
| 9945 | |
| 9946 | static auto op = create_histogram_bins_tensor_typed_handle(); |
| 9947 | return op.redispatch(dispatchKeySet, self, bins, weight, density); |
| 9948 | } |
| 9949 | |
| 9950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bin_ct_out, name, "aten::histogram") |
| 9951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bin_ct_out, overload_name, "bin_ct_out") |
| 9952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bin_ct_out, schema_str, "histogram.bin_ct_out(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges)") |
| 9953 | |
| 9954 | // aten::histogram.bin_ct_out(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges) |
| 9955 | static C10_NOINLINE c10::TypedOperatorHandle<histogram_bin_ct_out::schema> create_histogram_bin_ct_out_typed_handle() { |
| 9956 | return c10::Dispatcher::singleton() |
| 9957 | .findSchemaOrThrow(histogram_bin_ct_out::name, histogram_bin_ct_out::overload_name) |
| 9958 | .typed<histogram_bin_ct_out::schema>(); |
| 9959 | } |
| 9960 | |
| 9961 | // aten::histogram.bin_ct_out(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges) |
| 9962 | ::std::tuple<at::Tensor &,at::Tensor &> histogram_bin_ct_out::call(const at::Tensor & self, int64_t bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges) { |
| 9963 | |
| 9964 | static auto op = create_histogram_bin_ct_out_typed_handle(); |
| 9965 | return op.call(self, bins, range, weight, density, hist, bin_edges); |
| 9966 | } |
| 9967 | |
| 9968 | // aten::histogram.bin_ct_out(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) hist, Tensor(b!) bin_edges) -> (Tensor(a!) hist, Tensor(b!) bin_edges) |
| 9969 | ::std::tuple<at::Tensor &,at::Tensor &> histogram_bin_ct_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density, at::Tensor & hist, at::Tensor & bin_edges) { |
| 9970 | |
| 9971 | static auto op = create_histogram_bin_ct_out_typed_handle(); |
| 9972 | return op.redispatch(dispatchKeySet, self, bins, range, weight, density, hist, bin_edges); |
| 9973 | } |
| 9974 | |
| 9975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bin_ct, name, "aten::histogram") |
| 9976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bin_ct, overload_name, "bin_ct") |
| 9977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogram_bin_ct, schema_str, "histogram.bin_ct(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges)") |
| 9978 | |
| 9979 | // aten::histogram.bin_ct(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges) |
| 9980 | static C10_NOINLINE c10::TypedOperatorHandle<histogram_bin_ct::schema> create_histogram_bin_ct_typed_handle() { |
| 9981 | return c10::Dispatcher::singleton() |
| 9982 | .findSchemaOrThrow(histogram_bin_ct::name, histogram_bin_ct::overload_name) |
| 9983 | .typed<histogram_bin_ct::schema>(); |
| 9984 | } |
| 9985 | |
| 9986 | // aten::histogram.bin_ct(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges) |
| 9987 | ::std::tuple<at::Tensor,at::Tensor> histogram_bin_ct::call(const at::Tensor & self, int64_t bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
| 9988 | |
| 9989 | static auto op = create_histogram_bin_ct_typed_handle(); |
| 9990 | return op.call(self, bins, range, weight, density); |
| 9991 | } |
| 9992 | |
| 9993 | // aten::histogram.bin_ct(Tensor self, int bins=100, *, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor bin_edges) |
| 9994 | ::std::tuple<at::Tensor,at::Tensor> histogram_bin_ct::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
| 9995 | |
| 9996 | static auto op = create_histogram_bin_ct_typed_handle(); |
| 9997 | return op.redispatch(dispatchKeySet, self, bins, range, weight, density); |
| 9998 | } |
| 9999 | |
| 10000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma_out, name, "aten::igamma") |
| 10001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma_out, overload_name, "out") |
| 10002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma_out, schema_str, "igamma.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 10003 | |
| 10004 | // aten::igamma.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 10005 | static C10_NOINLINE c10::TypedOperatorHandle<igamma_out::schema> create_igamma_out_typed_handle() { |
| 10006 | return c10::Dispatcher::singleton() |
| 10007 | .findSchemaOrThrow(igamma_out::name, igamma_out::overload_name) |
| 10008 | .typed<igamma_out::schema>(); |
| 10009 | } |
| 10010 | |
| 10011 | // aten::igamma.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 10012 | at::Tensor & igamma_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 10013 | |
| 10014 | static auto op = create_igamma_out_typed_handle(); |
| 10015 | return op.call(self, other, out); |
| 10016 | } |
| 10017 | |
| 10018 | // aten::igamma.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 10019 | at::Tensor & igamma_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 10020 | |
| 10021 | static auto op = create_igamma_out_typed_handle(); |
| 10022 | return op.redispatch(dispatchKeySet, self, other, out); |
| 10023 | } |
| 10024 | |
| 10025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma, name, "aten::igamma") |
| 10026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma, overload_name, "") |
| 10027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma, schema_str, "igamma(Tensor self, Tensor other) -> Tensor") |
| 10028 | |
| 10029 | // aten::igamma(Tensor self, Tensor other) -> Tensor |
| 10030 | static C10_NOINLINE c10::TypedOperatorHandle<igamma::schema> create_igamma_typed_handle() { |
| 10031 | return c10::Dispatcher::singleton() |
| 10032 | .findSchemaOrThrow(igamma::name, igamma::overload_name) |
| 10033 | .typed<igamma::schema>(); |
| 10034 | } |
| 10035 | |
| 10036 | // aten::igamma(Tensor self, Tensor other) -> Tensor |
| 10037 | at::Tensor igamma::call(const at::Tensor & self, const at::Tensor & other) { |
| 10038 | |
| 10039 | static auto op = create_igamma_typed_handle(); |
| 10040 | return op.call(self, other); |
| 10041 | } |
| 10042 | |
| 10043 | // aten::igamma(Tensor self, Tensor other) -> Tensor |
| 10044 | at::Tensor igamma::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 10045 | |
| 10046 | static auto op = create_igamma_typed_handle(); |
| 10047 | return op.redispatch(dispatchKeySet, self, other); |
| 10048 | } |
| 10049 | |
| 10050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma_, name, "aten::igamma_") |
| 10051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma_, overload_name, "") |
| 10052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igamma_, schema_str, "igamma_(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 10053 | |
| 10054 | // aten::igamma_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 10055 | static C10_NOINLINE c10::TypedOperatorHandle<igamma_::schema> create_igamma__typed_handle() { |
| 10056 | return c10::Dispatcher::singleton() |
| 10057 | .findSchemaOrThrow(igamma_::name, igamma_::overload_name) |
| 10058 | .typed<igamma_::schema>(); |
| 10059 | } |
| 10060 | |
| 10061 | // aten::igamma_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 10062 | at::Tensor & igamma_::call(at::Tensor & self, const at::Tensor & other) { |
| 10063 | |
| 10064 | static auto op = create_igamma__typed_handle(); |
| 10065 | return op.call(self, other); |
| 10066 | } |
| 10067 | |
| 10068 | // aten::igamma_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 10069 | at::Tensor & igamma_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 10070 | |
| 10071 | static auto op = create_igamma__typed_handle(); |
| 10072 | return op.redispatch(dispatchKeySet, self, other); |
| 10073 | } |
| 10074 | |
| 10075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max, name, "aten::max") |
| 10076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max, overload_name, "") |
| 10077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max, schema_str, "max(Tensor self) -> Tensor") |
| 10078 | |
| 10079 | // aten::max(Tensor self) -> Tensor |
| 10080 | static C10_NOINLINE c10::TypedOperatorHandle<max::schema> create_max_typed_handle() { |
| 10081 | return c10::Dispatcher::singleton() |
| 10082 | .findSchemaOrThrow(max::name, max::overload_name) |
| 10083 | .typed<max::schema>(); |
| 10084 | } |
| 10085 | |
| 10086 | // aten::max(Tensor self) -> Tensor |
| 10087 | at::Tensor max::call(const at::Tensor & self) { |
| 10088 | |
| 10089 | static auto op = create_max_typed_handle(); |
| 10090 | return op.call(self); |
| 10091 | } |
| 10092 | |
| 10093 | // aten::max(Tensor self) -> Tensor |
| 10094 | at::Tensor max::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 10095 | |
| 10096 | static auto op = create_max_typed_handle(); |
| 10097 | return op.redispatch(dispatchKeySet, self); |
| 10098 | } |
| 10099 | |
| 10100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_other, name, "aten::max") |
| 10101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_other, overload_name, "other") |
| 10102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_other, schema_str, "max.other(Tensor self, Tensor other) -> Tensor") |
| 10103 | |
| 10104 | // aten::max.other(Tensor self, Tensor other) -> Tensor |
| 10105 | static C10_NOINLINE c10::TypedOperatorHandle<max_other::schema> create_max_other_typed_handle() { |
| 10106 | return c10::Dispatcher::singleton() |
| 10107 | .findSchemaOrThrow(max_other::name, max_other::overload_name) |
| 10108 | .typed<max_other::schema>(); |
| 10109 | } |
| 10110 | |
| 10111 | // aten::max.other(Tensor self, Tensor other) -> Tensor |
| 10112 | at::Tensor max_other::call(const at::Tensor & self, const at::Tensor & other) { |
| 10113 | |
| 10114 | static auto op = create_max_other_typed_handle(); |
| 10115 | return op.call(self, other); |
| 10116 | } |
| 10117 | |
| 10118 | // aten::max.other(Tensor self, Tensor other) -> Tensor |
| 10119 | at::Tensor max_other::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 10120 | |
| 10121 | static auto op = create_max_other_typed_handle(); |
| 10122 | return op.redispatch(dispatchKeySet, self, other); |
| 10123 | } |
| 10124 | |
| 10125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_out, name, "aten::max") |
| 10126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_out, overload_name, "out") |
| 10127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_out, schema_str, "max.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 10128 | |
| 10129 | // aten::max.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 10130 | static C10_NOINLINE c10::TypedOperatorHandle<max_out::schema> create_max_out_typed_handle() { |
| 10131 | return c10::Dispatcher::singleton() |
| 10132 | .findSchemaOrThrow(max_out::name, max_out::overload_name) |
| 10133 | .typed<max_out::schema>(); |
| 10134 | } |
| 10135 | |
| 10136 | // aten::max.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 10137 | at::Tensor & max_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 10138 | |
| 10139 | static auto op = create_max_out_typed_handle(); |
| 10140 | return op.call(self, other, out); |
| 10141 | } |
| 10142 | |
| 10143 | // aten::max.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 10144 | at::Tensor & max_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 10145 | |
| 10146 | static auto op = create_max_out_typed_handle(); |
| 10147 | return op.redispatch(dispatchKeySet, self, other, out); |
| 10148 | } |
| 10149 | |
| 10150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_unary_out, name, "aten::max") |
| 10151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_unary_out, overload_name, "unary_out") |
| 10152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_unary_out, schema_str, "max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 10153 | |
| 10154 | // aten::max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 10155 | static C10_NOINLINE c10::TypedOperatorHandle<max_unary_out::schema> create_max_unary_out_typed_handle() { |
| 10156 | return c10::Dispatcher::singleton() |
| 10157 | .findSchemaOrThrow(max_unary_out::name, max_unary_out::overload_name) |
| 10158 | .typed<max_unary_out::schema>(); |
| 10159 | } |
| 10160 | |
| 10161 | // aten::max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 10162 | at::Tensor & max_unary_out::call(const at::Tensor & self, at::Tensor & out) { |
| 10163 | |
| 10164 | static auto op = create_max_unary_out_typed_handle(); |
| 10165 | return op.call(self, out); |
| 10166 | } |
| 10167 | |
| 10168 | // aten::max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 10169 | at::Tensor & max_unary_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 10170 | |
| 10171 | static auto op = create_max_unary_out_typed_handle(); |
| 10172 | return op.redispatch(dispatchKeySet, self, out); |
| 10173 | } |
| 10174 | |
| 10175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Tensor_out, name, "aten::pow") |
| 10176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Tensor_out, overload_name, "Tensor_Tensor_out") |
| 10177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Tensor_out, schema_str, "pow.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)") |
| 10178 | |
| 10179 | // aten::pow.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10180 | static C10_NOINLINE c10::TypedOperatorHandle<pow_Tensor_Tensor_out::schema> create_pow_Tensor_Tensor_out_typed_handle() { |
| 10181 | return c10::Dispatcher::singleton() |
| 10182 | .findSchemaOrThrow(pow_Tensor_Tensor_out::name, pow_Tensor_Tensor_out::overload_name) |
| 10183 | .typed<pow_Tensor_Tensor_out::schema>(); |
| 10184 | } |
| 10185 | |
| 10186 | // aten::pow.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10187 | at::Tensor & pow_Tensor_Tensor_out::call(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out) { |
| 10188 | |
| 10189 | static auto op = create_pow_Tensor_Tensor_out_typed_handle(); |
| 10190 | return op.call(self, exponent, out); |
| 10191 | } |
| 10192 | |
| 10193 | // aten::pow.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10194 | at::Tensor & pow_Tensor_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out) { |
| 10195 | |
| 10196 | static auto op = create_pow_Tensor_Tensor_out_typed_handle(); |
| 10197 | return op.redispatch(dispatchKeySet, self, exponent, out); |
| 10198 | } |
| 10199 | |
| 10200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Tensor, name, "aten::pow") |
| 10201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Tensor, overload_name, "Tensor_Tensor") |
| 10202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Tensor, schema_str, "pow.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor") |
| 10203 | |
| 10204 | // aten::pow.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor |
| 10205 | static C10_NOINLINE c10::TypedOperatorHandle<pow_Tensor_Tensor::schema> create_pow_Tensor_Tensor_typed_handle() { |
| 10206 | return c10::Dispatcher::singleton() |
| 10207 | .findSchemaOrThrow(pow_Tensor_Tensor::name, pow_Tensor_Tensor::overload_name) |
| 10208 | .typed<pow_Tensor_Tensor::schema>(); |
| 10209 | } |
| 10210 | |
| 10211 | // aten::pow.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor |
| 10212 | at::Tensor pow_Tensor_Tensor::call(const at::Tensor & self, const at::Tensor & exponent) { |
| 10213 | |
| 10214 | static auto op = create_pow_Tensor_Tensor_typed_handle(); |
| 10215 | return op.call(self, exponent); |
| 10216 | } |
| 10217 | |
| 10218 | // aten::pow.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor |
| 10219 | at::Tensor pow_Tensor_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent) { |
| 10220 | |
| 10221 | static auto op = create_pow_Tensor_Tensor_typed_handle(); |
| 10222 | return op.redispatch(dispatchKeySet, self, exponent); |
| 10223 | } |
| 10224 | |
| 10225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Scalar_out, name, "aten::pow") |
| 10226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Scalar_out, overload_name, "Scalar_out") |
| 10227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Scalar_out, schema_str, "pow.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)") |
| 10228 | |
| 10229 | // aten::pow.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10230 | static C10_NOINLINE c10::TypedOperatorHandle<pow_Scalar_out::schema> create_pow_Scalar_out_typed_handle() { |
| 10231 | return c10::Dispatcher::singleton() |
| 10232 | .findSchemaOrThrow(pow_Scalar_out::name, pow_Scalar_out::overload_name) |
| 10233 | .typed<pow_Scalar_out::schema>(); |
| 10234 | } |
| 10235 | |
| 10236 | // aten::pow.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10237 | at::Tensor & pow_Scalar_out::call(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out) { |
| 10238 | |
| 10239 | static auto op = create_pow_Scalar_out_typed_handle(); |
| 10240 | return op.call(self, exponent, out); |
| 10241 | } |
| 10242 | |
| 10243 | // aten::pow.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10244 | at::Tensor & pow_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out) { |
| 10245 | |
| 10246 | static auto op = create_pow_Scalar_out_typed_handle(); |
| 10247 | return op.redispatch(dispatchKeySet, self, exponent, out); |
| 10248 | } |
| 10249 | |
| 10250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Scalar, name, "aten::pow") |
| 10251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Scalar, overload_name, "Scalar") |
| 10252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Scalar, schema_str, "pow.Scalar(Scalar self, Tensor exponent) -> Tensor") |
| 10253 | |
| 10254 | // aten::pow.Scalar(Scalar self, Tensor exponent) -> Tensor |
| 10255 | static C10_NOINLINE c10::TypedOperatorHandle<pow_Scalar::schema> create_pow_Scalar_typed_handle() { |
| 10256 | return c10::Dispatcher::singleton() |
| 10257 | .findSchemaOrThrow(pow_Scalar::name, pow_Scalar::overload_name) |
| 10258 | .typed<pow_Scalar::schema>(); |
| 10259 | } |
| 10260 | |
| 10261 | // aten::pow.Scalar(Scalar self, Tensor exponent) -> Tensor |
| 10262 | at::Tensor pow_Scalar::call(const at::Scalar & self, const at::Tensor & exponent) { |
| 10263 | |
| 10264 | static auto op = create_pow_Scalar_typed_handle(); |
| 10265 | return op.call(self, exponent); |
| 10266 | } |
| 10267 | |
| 10268 | // aten::pow.Scalar(Scalar self, Tensor exponent) -> Tensor |
| 10269 | at::Tensor pow_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent) { |
| 10270 | |
| 10271 | static auto op = create_pow_Scalar_typed_handle(); |
| 10272 | return op.redispatch(dispatchKeySet, self, exponent); |
| 10273 | } |
| 10274 | |
| 10275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Scalar_out, name, "aten::pow") |
| 10276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Scalar_out, overload_name, "Tensor_Scalar_out") |
| 10277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Scalar_out, schema_str, "pow.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!)") |
| 10278 | |
| 10279 | // aten::pow.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10280 | static C10_NOINLINE c10::TypedOperatorHandle<pow_Tensor_Scalar_out::schema> create_pow_Tensor_Scalar_out_typed_handle() { |
| 10281 | return c10::Dispatcher::singleton() |
| 10282 | .findSchemaOrThrow(pow_Tensor_Scalar_out::name, pow_Tensor_Scalar_out::overload_name) |
| 10283 | .typed<pow_Tensor_Scalar_out::schema>(); |
| 10284 | } |
| 10285 | |
| 10286 | // aten::pow.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10287 | at::Tensor & pow_Tensor_Scalar_out::call(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out) { |
| 10288 | |
| 10289 | static auto op = create_pow_Tensor_Scalar_out_typed_handle(); |
| 10290 | return op.call(self, exponent, out); |
| 10291 | } |
| 10292 | |
| 10293 | // aten::pow.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 10294 | at::Tensor & pow_Tensor_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out) { |
| 10295 | |
| 10296 | static auto op = create_pow_Tensor_Scalar_out_typed_handle(); |
| 10297 | return op.redispatch(dispatchKeySet, self, exponent, out); |
| 10298 | } |
| 10299 | |
| 10300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Scalar, name, "aten::pow") |
| 10301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Scalar, overload_name, "Tensor_Scalar") |
| 10302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow_Tensor_Scalar, schema_str, "pow.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor") |
| 10303 | |
| 10304 | // aten::pow.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor |
| 10305 | static C10_NOINLINE c10::TypedOperatorHandle<pow_Tensor_Scalar::schema> create_pow_Tensor_Scalar_typed_handle() { |
| 10306 | return c10::Dispatcher::singleton() |
| 10307 | .findSchemaOrThrow(pow_Tensor_Scalar::name, pow_Tensor_Scalar::overload_name) |
| 10308 | .typed<pow_Tensor_Scalar::schema>(); |
| 10309 | } |
| 10310 | |
| 10311 | // aten::pow.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor |
| 10312 | at::Tensor pow_Tensor_Scalar::call(const at::Tensor & self, const at::Scalar & exponent) { |
| 10313 | |
| 10314 | static auto op = create_pow_Tensor_Scalar_typed_handle(); |
| 10315 | return op.call(self, exponent); |
| 10316 | } |
| 10317 | |
| 10318 | // aten::pow.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor |
| 10319 | at::Tensor pow_Tensor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent) { |
| 10320 | |
| 10321 | static auto op = create_pow_Tensor_Scalar_typed_handle(); |
| 10322 | return op.redispatch(dispatchKeySet, self, exponent); |
| 10323 | } |
| 10324 | |
| 10325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow__Scalar, name, "aten::pow_") |
| 10326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow__Scalar, overload_name, "Scalar") |
| 10327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow__Scalar, schema_str, "pow_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!)") |
| 10328 | |
| 10329 | // aten::pow_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!) |
| 10330 | static C10_NOINLINE c10::TypedOperatorHandle<pow__Scalar::schema> create_pow__Scalar_typed_handle() { |
| 10331 | return c10::Dispatcher::singleton() |
| 10332 | .findSchemaOrThrow(pow__Scalar::name, pow__Scalar::overload_name) |
| 10333 | .typed<pow__Scalar::schema>(); |
| 10334 | } |
| 10335 | |
| 10336 | // aten::pow_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!) |
| 10337 | at::Tensor & pow__Scalar::call(at::Tensor & self, const at::Scalar & exponent) { |
| 10338 | |
| 10339 | static auto op = create_pow__Scalar_typed_handle(); |
| 10340 | return op.call(self, exponent); |
| 10341 | } |
| 10342 | |
| 10343 | // aten::pow_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!) |
| 10344 | at::Tensor & pow__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & exponent) { |
| 10345 | |
| 10346 | static auto op = create_pow__Scalar_typed_handle(); |
| 10347 | return op.redispatch(dispatchKeySet, self, exponent); |
| 10348 | } |
| 10349 | |
| 10350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow__Tensor, name, "aten::pow_") |
| 10351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow__Tensor, overload_name, "Tensor") |
| 10352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pow__Tensor, schema_str, "pow_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!)") |
| 10353 | |
| 10354 | // aten::pow_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!) |
| 10355 | static C10_NOINLINE c10::TypedOperatorHandle<pow__Tensor::schema> create_pow__Tensor_typed_handle() { |
| 10356 | return c10::Dispatcher::singleton() |
| 10357 | .findSchemaOrThrow(pow__Tensor::name, pow__Tensor::overload_name) |
| 10358 | .typed<pow__Tensor::schema>(); |
| 10359 | } |
| 10360 | |
| 10361 | // aten::pow_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!) |
| 10362 | at::Tensor & pow__Tensor::call(at::Tensor & self, const at::Tensor & exponent) { |
| 10363 | |
| 10364 | static auto op = create_pow__Tensor_typed_handle(); |
| 10365 | return op.call(self, exponent); |
| 10366 | } |
| 10367 | |
| 10368 | // aten::pow_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!) |
| 10369 | at::Tensor & pow__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & exponent) { |
| 10370 | |
| 10371 | static auto op = create_pow__Tensor_typed_handle(); |
| 10372 | return op.redispatch(dispatchKeySet, self, exponent); |
| 10373 | } |
| 10374 | |
| 10375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale_, name, "aten::_amp_foreach_non_finite_check_and_unscale_") |
| 10376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale_, overload_name, "") |
| 10377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale_, schema_str, "_amp_foreach_non_finite_check_and_unscale_(Tensor(a!)[] self, Tensor(b!) found_inf, Tensor inv_scale) -> ()") |
| 10378 | |
| 10379 | // aten::_amp_foreach_non_finite_check_and_unscale_(Tensor(a!)[] self, Tensor(b!) found_inf, Tensor inv_scale) -> () |
| 10380 | static C10_NOINLINE c10::TypedOperatorHandle<_amp_foreach_non_finite_check_and_unscale_::schema> create__amp_foreach_non_finite_check_and_unscale__typed_handle() { |
| 10381 | return c10::Dispatcher::singleton() |
| 10382 | .findSchemaOrThrow(_amp_foreach_non_finite_check_and_unscale_::name, _amp_foreach_non_finite_check_and_unscale_::overload_name) |
| 10383 | .typed<_amp_foreach_non_finite_check_and_unscale_::schema>(); |
| 10384 | } |
| 10385 | |
| 10386 | // aten::_amp_foreach_non_finite_check_and_unscale_(Tensor(a!)[] self, Tensor(b!) found_inf, Tensor inv_scale) -> () |
| 10387 | void _amp_foreach_non_finite_check_and_unscale_::call(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale) { |
| 10388 | |
| 10389 | static auto op = create__amp_foreach_non_finite_check_and_unscale__typed_handle(); |
| 10390 | return op.call(self, found_inf, inv_scale); |
| 10391 | } |
| 10392 | |
| 10393 | // aten::_amp_foreach_non_finite_check_and_unscale_(Tensor(a!)[] self, Tensor(b!) found_inf, Tensor inv_scale) -> () |
| 10394 | void _amp_foreach_non_finite_check_and_unscale_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale) { |
| 10395 | |
| 10396 | static auto op = create__amp_foreach_non_finite_check_and_unscale__typed_handle(); |
| 10397 | return op.redispatch(dispatchKeySet, self, found_inf, inv_scale); |
| 10398 | } |
| 10399 | |
| 10400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_Scalar, name, "aten::_foreach_add") |
| 10401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_Scalar, overload_name, "Scalar") |
| 10402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_Scalar, schema_str, "_foreach_add.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]") |
| 10403 | |
| 10404 | // aten::_foreach_add.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10405 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add_Scalar::schema> create__foreach_add_Scalar_typed_handle() { |
| 10406 | return c10::Dispatcher::singleton() |
| 10407 | .findSchemaOrThrow(_foreach_add_Scalar::name, _foreach_add_Scalar::overload_name) |
| 10408 | .typed<_foreach_add_Scalar::schema>(); |
| 10409 | } |
| 10410 | |
| 10411 | // aten::_foreach_add.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10412 | ::std::vector<at::Tensor> _foreach_add_Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 10413 | |
| 10414 | static auto op = create__foreach_add_Scalar_typed_handle(); |
| 10415 | return op.call(self, scalar); |
| 10416 | } |
| 10417 | |
| 10418 | // aten::_foreach_add.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10419 | ::std::vector<at::Tensor> _foreach_add_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 10420 | |
| 10421 | static auto op = create__foreach_add_Scalar_typed_handle(); |
| 10422 | return op.redispatch(dispatchKeySet, self, scalar); |
| 10423 | } |
| 10424 | |
| 10425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__Scalar, name, "aten::_foreach_add_") |
| 10426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__Scalar, overload_name, "Scalar") |
| 10427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__Scalar, schema_str, "_foreach_add_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()") |
| 10428 | |
| 10429 | // aten::_foreach_add_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10430 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add__Scalar::schema> create__foreach_add__Scalar_typed_handle() { |
| 10431 | return c10::Dispatcher::singleton() |
| 10432 | .findSchemaOrThrow(_foreach_add__Scalar::name, _foreach_add__Scalar::overload_name) |
| 10433 | .typed<_foreach_add__Scalar::schema>(); |
| 10434 | } |
| 10435 | |
| 10436 | // aten::_foreach_add_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10437 | void _foreach_add__Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 10438 | |
| 10439 | static auto op = create__foreach_add__Scalar_typed_handle(); |
| 10440 | return op.call(self, scalar); |
| 10441 | } |
| 10442 | |
| 10443 | // aten::_foreach_add_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10444 | void _foreach_add__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 10445 | |
| 10446 | static auto op = create__foreach_add__Scalar_typed_handle(); |
| 10447 | return op.redispatch(dispatchKeySet, self, scalar); |
| 10448 | } |
| 10449 | |
| 10450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_Scalar, name, "aten::_foreach_clamp_min") |
| 10451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_Scalar, overload_name, "Scalar") |
| 10452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_Scalar, schema_str, "_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]") |
| 10453 | |
| 10454 | // aten::_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10455 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min_Scalar::schema> create__foreach_clamp_min_Scalar_typed_handle() { |
| 10456 | return c10::Dispatcher::singleton() |
| 10457 | .findSchemaOrThrow(_foreach_clamp_min_Scalar::name, _foreach_clamp_min_Scalar::overload_name) |
| 10458 | .typed<_foreach_clamp_min_Scalar::schema>(); |
| 10459 | } |
| 10460 | |
| 10461 | // aten::_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10462 | ::std::vector<at::Tensor> _foreach_clamp_min_Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 10463 | |
| 10464 | static auto op = create__foreach_clamp_min_Scalar_typed_handle(); |
| 10465 | return op.call(self, scalar); |
| 10466 | } |
| 10467 | |
| 10468 | // aten::_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10469 | ::std::vector<at::Tensor> _foreach_clamp_min_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 10470 | |
| 10471 | static auto op = create__foreach_clamp_min_Scalar_typed_handle(); |
| 10472 | return op.redispatch(dispatchKeySet, self, scalar); |
| 10473 | } |
| 10474 | |
| 10475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__Scalar, name, "aten::_foreach_clamp_min_") |
| 10476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__Scalar, overload_name, "Scalar") |
| 10477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__Scalar, schema_str, "_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()") |
| 10478 | |
| 10479 | // aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10480 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min__Scalar::schema> create__foreach_clamp_min__Scalar_typed_handle() { |
| 10481 | return c10::Dispatcher::singleton() |
| 10482 | .findSchemaOrThrow(_foreach_clamp_min__Scalar::name, _foreach_clamp_min__Scalar::overload_name) |
| 10483 | .typed<_foreach_clamp_min__Scalar::schema>(); |
| 10484 | } |
| 10485 | |
| 10486 | // aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10487 | void _foreach_clamp_min__Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 10488 | |
| 10489 | static auto op = create__foreach_clamp_min__Scalar_typed_handle(); |
| 10490 | return op.call(self, scalar); |
| 10491 | } |
| 10492 | |
| 10493 | // aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10494 | void _foreach_clamp_min__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 10495 | |
| 10496 | static auto op = create__foreach_clamp_min__Scalar_typed_handle(); |
| 10497 | return op.redispatch(dispatchKeySet, self, scalar); |
| 10498 | } |
| 10499 | |
| 10500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_Scalar, name, "aten::_foreach_minimum") |
| 10501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_Scalar, overload_name, "Scalar") |
| 10502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_Scalar, schema_str, "_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]") |
| 10503 | |
| 10504 | // aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10505 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum_Scalar::schema> create__foreach_minimum_Scalar_typed_handle() { |
| 10506 | return c10::Dispatcher::singleton() |
| 10507 | .findSchemaOrThrow(_foreach_minimum_Scalar::name, _foreach_minimum_Scalar::overload_name) |
| 10508 | .typed<_foreach_minimum_Scalar::schema>(); |
| 10509 | } |
| 10510 | |
| 10511 | // aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10512 | ::std::vector<at::Tensor> _foreach_minimum_Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 10513 | |
| 10514 | static auto op = create__foreach_minimum_Scalar_typed_handle(); |
| 10515 | return op.call(self, scalar); |
| 10516 | } |
| 10517 | |
| 10518 | // aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 10519 | ::std::vector<at::Tensor> _foreach_minimum_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 10520 | |
| 10521 | static auto op = create__foreach_minimum_Scalar_typed_handle(); |
| 10522 | return op.redispatch(dispatchKeySet, self, scalar); |
| 10523 | } |
| 10524 | |
| 10525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__Scalar, name, "aten::_foreach_minimum_") |
| 10526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__Scalar, overload_name, "Scalar") |
| 10527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__Scalar, schema_str, "_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()") |
| 10528 | |
| 10529 | // aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10530 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum__Scalar::schema> create__foreach_minimum__Scalar_typed_handle() { |
| 10531 | return c10::Dispatcher::singleton() |
| 10532 | .findSchemaOrThrow(_foreach_minimum__Scalar::name, _foreach_minimum__Scalar::overload_name) |
| 10533 | .typed<_foreach_minimum__Scalar::schema>(); |
| 10534 | } |
| 10535 | |
| 10536 | // aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10537 | void _foreach_minimum__Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 10538 | |
| 10539 | static auto op = create__foreach_minimum__Scalar_typed_handle(); |
| 10540 | return op.call(self, scalar); |
| 10541 | } |
| 10542 | |
| 10543 | // aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 10544 | void _foreach_minimum__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 10545 | |
| 10546 | static auto op = create__foreach_minimum__Scalar_typed_handle(); |
| 10547 | return op.redispatch(dispatchKeySet, self, scalar); |
| 10548 | } |
| 10549 | |
| 10550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_List, name, "aten::_foreach_add") |
| 10551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_List, overload_name, "List") |
| 10552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_List, schema_str, "_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[]") |
| 10553 | |
| 10554 | // aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] |
| 10555 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add_List::schema> create__foreach_add_List_typed_handle() { |
| 10556 | return c10::Dispatcher::singleton() |
| 10557 | .findSchemaOrThrow(_foreach_add_List::name, _foreach_add_List::overload_name) |
| 10558 | .typed<_foreach_add_List::schema>(); |
| 10559 | } |
| 10560 | |
| 10561 | // aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] |
| 10562 | ::std::vector<at::Tensor> _foreach_add_List::call(at::TensorList self, at::TensorList other, const at::Scalar & alpha) { |
| 10563 | |
| 10564 | static auto op = create__foreach_add_List_typed_handle(); |
| 10565 | return op.call(self, other, alpha); |
| 10566 | } |
| 10567 | |
| 10568 | // aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] |
| 10569 | ::std::vector<at::Tensor> _foreach_add_List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha) { |
| 10570 | |
| 10571 | static auto op = create__foreach_add_List_typed_handle(); |
| 10572 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 10573 | } |
| 10574 | |
| 10575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__List, name, "aten::_foreach_add_") |
| 10576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__List, overload_name, "List") |
| 10577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__List, schema_str, "_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> ()") |
| 10578 | |
| 10579 | // aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () |
| 10580 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add__List::schema> create__foreach_add__List_typed_handle() { |
| 10581 | return c10::Dispatcher::singleton() |
| 10582 | .findSchemaOrThrow(_foreach_add__List::name, _foreach_add__List::overload_name) |
| 10583 | .typed<_foreach_add__List::schema>(); |
| 10584 | } |
| 10585 | |
| 10586 | // aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () |
| 10587 | void _foreach_add__List::call(at::TensorList self, at::TensorList other, const at::Scalar & alpha) { |
| 10588 | |
| 10589 | static auto op = create__foreach_add__List_typed_handle(); |
| 10590 | return op.call(self, other, alpha); |
| 10591 | } |
| 10592 | |
| 10593 | // aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () |
| 10594 | void _foreach_add__List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha) { |
| 10595 | |
| 10596 | static auto op = create__foreach_add__List_typed_handle(); |
| 10597 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 10598 | } |
| 10599 | |
| 10600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_List, name, "aten::_foreach_clamp_min") |
| 10601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_List, overload_name, "List") |
| 10602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_List, schema_str, "_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[]") |
| 10603 | |
| 10604 | // aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 10605 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min_List::schema> create__foreach_clamp_min_List_typed_handle() { |
| 10606 | return c10::Dispatcher::singleton() |
| 10607 | .findSchemaOrThrow(_foreach_clamp_min_List::name, _foreach_clamp_min_List::overload_name) |
| 10608 | .typed<_foreach_clamp_min_List::schema>(); |
| 10609 | } |
| 10610 | |
| 10611 | // aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 10612 | ::std::vector<at::Tensor> _foreach_clamp_min_List::call(at::TensorList self, at::TensorList other) { |
| 10613 | |
| 10614 | static auto op = create__foreach_clamp_min_List_typed_handle(); |
| 10615 | return op.call(self, other); |
| 10616 | } |
| 10617 | |
| 10618 | // aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 10619 | ::std::vector<at::Tensor> _foreach_clamp_min_List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other) { |
| 10620 | |
| 10621 | static auto op = create__foreach_clamp_min_List_typed_handle(); |
| 10622 | return op.redispatch(dispatchKeySet, self, other); |
| 10623 | } |
| 10624 | |
| 10625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__List, name, "aten::_foreach_clamp_min_") |
| 10626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__List, overload_name, "List") |
| 10627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__List, schema_str, "_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> ()") |
| 10628 | |
| 10629 | // aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 10630 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min__List::schema> create__foreach_clamp_min__List_typed_handle() { |
| 10631 | return c10::Dispatcher::singleton() |
| 10632 | .findSchemaOrThrow(_foreach_clamp_min__List::name, _foreach_clamp_min__List::overload_name) |
| 10633 | .typed<_foreach_clamp_min__List::schema>(); |
| 10634 | } |
| 10635 | |
| 10636 | // aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 10637 | void _foreach_clamp_min__List::call(at::TensorList self, at::TensorList other) { |
| 10638 | |
| 10639 | static auto op = create__foreach_clamp_min__List_typed_handle(); |
| 10640 | return op.call(self, other); |
| 10641 | } |
| 10642 | |
| 10643 | // aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 10644 | void _foreach_clamp_min__List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other) { |
| 10645 | |
| 10646 | static auto op = create__foreach_clamp_min__List_typed_handle(); |
| 10647 | return op.redispatch(dispatchKeySet, self, other); |
| 10648 | } |
| 10649 | |
| 10650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_List, name, "aten::_foreach_minimum") |
| 10651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_List, overload_name, "List") |
| 10652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_List, schema_str, "_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[]") |
| 10653 | |
| 10654 | // aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 10655 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum_List::schema> create__foreach_minimum_List_typed_handle() { |
| 10656 | return c10::Dispatcher::singleton() |
| 10657 | .findSchemaOrThrow(_foreach_minimum_List::name, _foreach_minimum_List::overload_name) |
| 10658 | .typed<_foreach_minimum_List::schema>(); |
| 10659 | } |
| 10660 | |
| 10661 | // aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 10662 | ::std::vector<at::Tensor> _foreach_minimum_List::call(at::TensorList self, at::TensorList other) { |
| 10663 | |
| 10664 | static auto op = create__foreach_minimum_List_typed_handle(); |
| 10665 | return op.call(self, other); |
| 10666 | } |
| 10667 | |
| 10668 | // aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 10669 | ::std::vector<at::Tensor> _foreach_minimum_List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other) { |
| 10670 | |
| 10671 | static auto op = create__foreach_minimum_List_typed_handle(); |
| 10672 | return op.redispatch(dispatchKeySet, self, other); |
| 10673 | } |
| 10674 | |
| 10675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__List, name, "aten::_foreach_minimum_") |
| 10676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__List, overload_name, "List") |
| 10677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__List, schema_str, "_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> ()") |
| 10678 | |
| 10679 | // aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 10680 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum__List::schema> create__foreach_minimum__List_typed_handle() { |
| 10681 | return c10::Dispatcher::singleton() |
| 10682 | .findSchemaOrThrow(_foreach_minimum__List::name, _foreach_minimum__List::overload_name) |
| 10683 | .typed<_foreach_minimum__List::schema>(); |
| 10684 | } |
| 10685 | |
| 10686 | // aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 10687 | void _foreach_minimum__List::call(at::TensorList self, at::TensorList other) { |
| 10688 | |
| 10689 | static auto op = create__foreach_minimum__List_typed_handle(); |
| 10690 | return op.call(self, other); |
| 10691 | } |
| 10692 | |
| 10693 | // aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 10694 | void _foreach_minimum__List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other) { |
| 10695 | |
| 10696 | static auto op = create__foreach_minimum__List_typed_handle(); |
| 10697 | return op.redispatch(dispatchKeySet, self, other); |
| 10698 | } |
| 10699 | |
| 10700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_ScalarList, name, "aten::_foreach_add") |
| 10701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_ScalarList, overload_name, "ScalarList") |
| 10702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_ScalarList, schema_str, "_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]") |
| 10703 | |
| 10704 | // aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10705 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add_ScalarList::schema> create__foreach_add_ScalarList_typed_handle() { |
| 10706 | return c10::Dispatcher::singleton() |
| 10707 | .findSchemaOrThrow(_foreach_add_ScalarList::name, _foreach_add_ScalarList::overload_name) |
| 10708 | .typed<_foreach_add_ScalarList::schema>(); |
| 10709 | } |
| 10710 | |
| 10711 | // aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10712 | ::std::vector<at::Tensor> _foreach_add_ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10713 | |
| 10714 | static auto op = create__foreach_add_ScalarList_typed_handle(); |
| 10715 | return op.call(self, scalars); |
| 10716 | } |
| 10717 | |
| 10718 | // aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10719 | ::std::vector<at::Tensor> _foreach_add_ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10720 | |
| 10721 | static auto op = create__foreach_add_ScalarList_typed_handle(); |
| 10722 | return op.redispatch(dispatchKeySet, self, scalars); |
| 10723 | } |
| 10724 | |
| 10725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__ScalarList, name, "aten::_foreach_add_") |
| 10726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__ScalarList, overload_name, "ScalarList") |
| 10727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add__ScalarList, schema_str, "_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()") |
| 10728 | |
| 10729 | // aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10730 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add__ScalarList::schema> create__foreach_add__ScalarList_typed_handle() { |
| 10731 | return c10::Dispatcher::singleton() |
| 10732 | .findSchemaOrThrow(_foreach_add__ScalarList::name, _foreach_add__ScalarList::overload_name) |
| 10733 | .typed<_foreach_add__ScalarList::schema>(); |
| 10734 | } |
| 10735 | |
| 10736 | // aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10737 | void _foreach_add__ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10738 | |
| 10739 | static auto op = create__foreach_add__ScalarList_typed_handle(); |
| 10740 | return op.call(self, scalars); |
| 10741 | } |
| 10742 | |
| 10743 | // aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10744 | void _foreach_add__ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10745 | |
| 10746 | static auto op = create__foreach_add__ScalarList_typed_handle(); |
| 10747 | return op.redispatch(dispatchKeySet, self, scalars); |
| 10748 | } |
| 10749 | |
| 10750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_ScalarList, name, "aten::_foreach_clamp_min") |
| 10751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_ScalarList, overload_name, "ScalarList") |
| 10752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_ScalarList, schema_str, "_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]") |
| 10753 | |
| 10754 | // aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10755 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min_ScalarList::schema> create__foreach_clamp_min_ScalarList_typed_handle() { |
| 10756 | return c10::Dispatcher::singleton() |
| 10757 | .findSchemaOrThrow(_foreach_clamp_min_ScalarList::name, _foreach_clamp_min_ScalarList::overload_name) |
| 10758 | .typed<_foreach_clamp_min_ScalarList::schema>(); |
| 10759 | } |
| 10760 | |
| 10761 | // aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10762 | ::std::vector<at::Tensor> _foreach_clamp_min_ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10763 | |
| 10764 | static auto op = create__foreach_clamp_min_ScalarList_typed_handle(); |
| 10765 | return op.call(self, scalars); |
| 10766 | } |
| 10767 | |
| 10768 | // aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10769 | ::std::vector<at::Tensor> _foreach_clamp_min_ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10770 | |
| 10771 | static auto op = create__foreach_clamp_min_ScalarList_typed_handle(); |
| 10772 | return op.redispatch(dispatchKeySet, self, scalars); |
| 10773 | } |
| 10774 | |
| 10775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__ScalarList, name, "aten::_foreach_clamp_min_") |
| 10776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__ScalarList, overload_name, "ScalarList") |
| 10777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min__ScalarList, schema_str, "_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()") |
| 10778 | |
| 10779 | // aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10780 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min__ScalarList::schema> create__foreach_clamp_min__ScalarList_typed_handle() { |
| 10781 | return c10::Dispatcher::singleton() |
| 10782 | .findSchemaOrThrow(_foreach_clamp_min__ScalarList::name, _foreach_clamp_min__ScalarList::overload_name) |
| 10783 | .typed<_foreach_clamp_min__ScalarList::schema>(); |
| 10784 | } |
| 10785 | |
| 10786 | // aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10787 | void _foreach_clamp_min__ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10788 | |
| 10789 | static auto op = create__foreach_clamp_min__ScalarList_typed_handle(); |
| 10790 | return op.call(self, scalars); |
| 10791 | } |
| 10792 | |
| 10793 | // aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10794 | void _foreach_clamp_min__ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10795 | |
| 10796 | static auto op = create__foreach_clamp_min__ScalarList_typed_handle(); |
| 10797 | return op.redispatch(dispatchKeySet, self, scalars); |
| 10798 | } |
| 10799 | |
| 10800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_ScalarList, name, "aten::_foreach_minimum") |
| 10801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_ScalarList, overload_name, "ScalarList") |
| 10802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_ScalarList, schema_str, "_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]") |
| 10803 | |
| 10804 | // aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10805 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum_ScalarList::schema> create__foreach_minimum_ScalarList_typed_handle() { |
| 10806 | return c10::Dispatcher::singleton() |
| 10807 | .findSchemaOrThrow(_foreach_minimum_ScalarList::name, _foreach_minimum_ScalarList::overload_name) |
| 10808 | .typed<_foreach_minimum_ScalarList::schema>(); |
| 10809 | } |
| 10810 | |
| 10811 | // aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10812 | ::std::vector<at::Tensor> _foreach_minimum_ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10813 | |
| 10814 | static auto op = create__foreach_minimum_ScalarList_typed_handle(); |
| 10815 | return op.call(self, scalars); |
| 10816 | } |
| 10817 | |
| 10818 | // aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 10819 | ::std::vector<at::Tensor> _foreach_minimum_ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10820 | |
| 10821 | static auto op = create__foreach_minimum_ScalarList_typed_handle(); |
| 10822 | return op.redispatch(dispatchKeySet, self, scalars); |
| 10823 | } |
| 10824 | |
| 10825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__ScalarList, name, "aten::_foreach_minimum_") |
| 10826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__ScalarList, overload_name, "ScalarList") |
| 10827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum__ScalarList, schema_str, "_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()") |
| 10828 | |
| 10829 | // aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10830 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum__ScalarList::schema> create__foreach_minimum__ScalarList_typed_handle() { |
| 10831 | return c10::Dispatcher::singleton() |
| 10832 | .findSchemaOrThrow(_foreach_minimum__ScalarList::name, _foreach_minimum__ScalarList::overload_name) |
| 10833 | .typed<_foreach_minimum__ScalarList::schema>(); |
| 10834 | } |
| 10835 | |
| 10836 | // aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10837 | void _foreach_minimum__ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10838 | |
| 10839 | static auto op = create__foreach_minimum__ScalarList_typed_handle(); |
| 10840 | return op.call(self, scalars); |
| 10841 | } |
| 10842 | |
| 10843 | // aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 10844 | void _foreach_minimum__ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 10845 | |
| 10846 | static auto op = create__foreach_minimum__ScalarList_typed_handle(); |
| 10847 | return op.redispatch(dispatchKeySet, self, scalars); |
| 10848 | } |
| 10849 | |
| 10850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh, name, "aten::_foreach_cosh") |
| 10851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh, overload_name, "") |
| 10852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh, schema_str, "_foreach_cosh(Tensor[] self) -> Tensor[]") |
| 10853 | |
| 10854 | // aten::_foreach_cosh(Tensor[] self) -> Tensor[] |
| 10855 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_cosh::schema> create__foreach_cosh_typed_handle() { |
| 10856 | return c10::Dispatcher::singleton() |
| 10857 | .findSchemaOrThrow(_foreach_cosh::name, _foreach_cosh::overload_name) |
| 10858 | .typed<_foreach_cosh::schema>(); |
| 10859 | } |
| 10860 | |
| 10861 | // aten::_foreach_cosh(Tensor[] self) -> Tensor[] |
| 10862 | ::std::vector<at::Tensor> _foreach_cosh::call(at::TensorList self) { |
| 10863 | |
| 10864 | static auto op = create__foreach_cosh_typed_handle(); |
| 10865 | return op.call(self); |
| 10866 | } |
| 10867 | |
| 10868 | // aten::_foreach_cosh(Tensor[] self) -> Tensor[] |
| 10869 | ::std::vector<at::Tensor> _foreach_cosh::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 10870 | |
| 10871 | static auto op = create__foreach_cosh_typed_handle(); |
| 10872 | return op.redispatch(dispatchKeySet, self); |
| 10873 | } |
| 10874 | |
| 10875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh_, name, "aten::_foreach_cosh_") |
| 10876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh_, overload_name, "") |
| 10877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh_, schema_str, "_foreach_cosh_(Tensor(a!)[] self) -> ()") |
| 10878 | |
| 10879 | // aten::_foreach_cosh_(Tensor(a!)[] self) -> () |
| 10880 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_cosh_::schema> create__foreach_cosh__typed_handle() { |
| 10881 | return c10::Dispatcher::singleton() |
| 10882 | .findSchemaOrThrow(_foreach_cosh_::name, _foreach_cosh_::overload_name) |
| 10883 | .typed<_foreach_cosh_::schema>(); |
| 10884 | } |
| 10885 | |
| 10886 | // aten::_foreach_cosh_(Tensor(a!)[] self) -> () |
| 10887 | void _foreach_cosh_::call(at::TensorList self) { |
| 10888 | |
| 10889 | static auto op = create__foreach_cosh__typed_handle(); |
| 10890 | return op.call(self); |
| 10891 | } |
| 10892 | |
| 10893 | // aten::_foreach_cosh_(Tensor(a!)[] self) -> () |
| 10894 | void _foreach_cosh_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 10895 | |
| 10896 | static auto op = create__foreach_cosh__typed_handle(); |
| 10897 | return op.redispatch(dispatchKeySet, self); |
| 10898 | } |
| 10899 | |
| 10900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc, name, "aten::_foreach_erfc") |
| 10901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc, overload_name, "") |
| 10902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc, schema_str, "_foreach_erfc(Tensor[] self) -> Tensor[]") |
| 10903 | |
| 10904 | // aten::_foreach_erfc(Tensor[] self) -> Tensor[] |
| 10905 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_erfc::schema> create__foreach_erfc_typed_handle() { |
| 10906 | return c10::Dispatcher::singleton() |
| 10907 | .findSchemaOrThrow(_foreach_erfc::name, _foreach_erfc::overload_name) |
| 10908 | .typed<_foreach_erfc::schema>(); |
| 10909 | } |
| 10910 | |
| 10911 | // aten::_foreach_erfc(Tensor[] self) -> Tensor[] |
| 10912 | ::std::vector<at::Tensor> _foreach_erfc::call(at::TensorList self) { |
| 10913 | |
| 10914 | static auto op = create__foreach_erfc_typed_handle(); |
| 10915 | return op.call(self); |
| 10916 | } |
| 10917 | |
| 10918 | // aten::_foreach_erfc(Tensor[] self) -> Tensor[] |
| 10919 | ::std::vector<at::Tensor> _foreach_erfc::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 10920 | |
| 10921 | static auto op = create__foreach_erfc_typed_handle(); |
| 10922 | return op.redispatch(dispatchKeySet, self); |
| 10923 | } |
| 10924 | |
| 10925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc_, name, "aten::_foreach_erfc_") |
| 10926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc_, overload_name, "") |
| 10927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc_, schema_str, "_foreach_erfc_(Tensor(a!)[] self) -> ()") |
| 10928 | |
| 10929 | // aten::_foreach_erfc_(Tensor(a!)[] self) -> () |
| 10930 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_erfc_::schema> create__foreach_erfc__typed_handle() { |
| 10931 | return c10::Dispatcher::singleton() |
| 10932 | .findSchemaOrThrow(_foreach_erfc_::name, _foreach_erfc_::overload_name) |
| 10933 | .typed<_foreach_erfc_::schema>(); |
| 10934 | } |
| 10935 | |
| 10936 | // aten::_foreach_erfc_(Tensor(a!)[] self) -> () |
| 10937 | void _foreach_erfc_::call(at::TensorList self) { |
| 10938 | |
| 10939 | static auto op = create__foreach_erfc__typed_handle(); |
| 10940 | return op.call(self); |
| 10941 | } |
| 10942 | |
| 10943 | // aten::_foreach_erfc_(Tensor(a!)[] self) -> () |
| 10944 | void _foreach_erfc_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 10945 | |
| 10946 | static auto op = create__foreach_erfc__typed_handle(); |
| 10947 | return op.redispatch(dispatchKeySet, self); |
| 10948 | } |
| 10949 | |
| 10950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round, name, "aten::_foreach_round") |
| 10951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round, overload_name, "") |
| 10952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round, schema_str, "_foreach_round(Tensor[] self) -> Tensor[]") |
| 10953 | |
| 10954 | // aten::_foreach_round(Tensor[] self) -> Tensor[] |
| 10955 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_round::schema> create__foreach_round_typed_handle() { |
| 10956 | return c10::Dispatcher::singleton() |
| 10957 | .findSchemaOrThrow(_foreach_round::name, _foreach_round::overload_name) |
| 10958 | .typed<_foreach_round::schema>(); |
| 10959 | } |
| 10960 | |
| 10961 | // aten::_foreach_round(Tensor[] self) -> Tensor[] |
| 10962 | ::std::vector<at::Tensor> _foreach_round::call(at::TensorList self) { |
| 10963 | |
| 10964 | static auto op = create__foreach_round_typed_handle(); |
| 10965 | return op.call(self); |
| 10966 | } |
| 10967 | |
| 10968 | // aten::_foreach_round(Tensor[] self) -> Tensor[] |
| 10969 | ::std::vector<at::Tensor> _foreach_round::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 10970 | |
| 10971 | static auto op = create__foreach_round_typed_handle(); |
| 10972 | return op.redispatch(dispatchKeySet, self); |
| 10973 | } |
| 10974 | |
| 10975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round_, name, "aten::_foreach_round_") |
| 10976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round_, overload_name, "") |
| 10977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round_, schema_str, "_foreach_round_(Tensor(a!)[] self) -> ()") |
| 10978 | |
| 10979 | // aten::_foreach_round_(Tensor(a!)[] self) -> () |
| 10980 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_round_::schema> create__foreach_round__typed_handle() { |
| 10981 | return c10::Dispatcher::singleton() |
| 10982 | .findSchemaOrThrow(_foreach_round_::name, _foreach_round_::overload_name) |
| 10983 | .typed<_foreach_round_::schema>(); |
| 10984 | } |
| 10985 | |
| 10986 | // aten::_foreach_round_(Tensor(a!)[] self) -> () |
| 10987 | void _foreach_round_::call(at::TensorList self) { |
| 10988 | |
| 10989 | static auto op = create__foreach_round__typed_handle(); |
| 10990 | return op.call(self); |
| 10991 | } |
| 10992 | |
| 10993 | // aten::_foreach_round_(Tensor(a!)[] self) -> () |
| 10994 | void _foreach_round_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 10995 | |
| 10996 | static auto op = create__foreach_round__typed_handle(); |
| 10997 | return op.redispatch(dispatchKeySet, self); |
| 10998 | } |
| 10999 | |
| 11000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma, name, "aten::_foreach_lgamma") |
| 11001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma, overload_name, "") |
| 11002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma, schema_str, "_foreach_lgamma(Tensor[] self) -> Tensor[]") |
| 11003 | |
| 11004 | // aten::_foreach_lgamma(Tensor[] self) -> Tensor[] |
| 11005 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lgamma::schema> create__foreach_lgamma_typed_handle() { |
| 11006 | return c10::Dispatcher::singleton() |
| 11007 | .findSchemaOrThrow(_foreach_lgamma::name, _foreach_lgamma::overload_name) |
| 11008 | .typed<_foreach_lgamma::schema>(); |
| 11009 | } |
| 11010 | |
| 11011 | // aten::_foreach_lgamma(Tensor[] self) -> Tensor[] |
| 11012 | ::std::vector<at::Tensor> _foreach_lgamma::call(at::TensorList self) { |
| 11013 | |
| 11014 | static auto op = create__foreach_lgamma_typed_handle(); |
| 11015 | return op.call(self); |
| 11016 | } |
| 11017 | |
| 11018 | // aten::_foreach_lgamma(Tensor[] self) -> Tensor[] |
| 11019 | ::std::vector<at::Tensor> _foreach_lgamma::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 11020 | |
| 11021 | static auto op = create__foreach_lgamma_typed_handle(); |
| 11022 | return op.redispatch(dispatchKeySet, self); |
| 11023 | } |
| 11024 | |
| 11025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma_, name, "aten::_foreach_lgamma_") |
| 11026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma_, overload_name, "") |
| 11027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma_, schema_str, "_foreach_lgamma_(Tensor(a!)[] self) -> ()") |
| 11028 | |
| 11029 | // aten::_foreach_lgamma_(Tensor(a!)[] self) -> () |
| 11030 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lgamma_::schema> create__foreach_lgamma__typed_handle() { |
| 11031 | return c10::Dispatcher::singleton() |
| 11032 | .findSchemaOrThrow(_foreach_lgamma_::name, _foreach_lgamma_::overload_name) |
| 11033 | .typed<_foreach_lgamma_::schema>(); |
| 11034 | } |
| 11035 | |
| 11036 | // aten::_foreach_lgamma_(Tensor(a!)[] self) -> () |
| 11037 | void _foreach_lgamma_::call(at::TensorList self) { |
| 11038 | |
| 11039 | static auto op = create__foreach_lgamma__typed_handle(); |
| 11040 | return op.call(self); |
| 11041 | } |
| 11042 | |
| 11043 | // aten::_foreach_lgamma_(Tensor(a!)[] self) -> () |
| 11044 | void _foreach_lgamma_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 11045 | |
| 11046 | static auto op = create__foreach_lgamma__typed_handle(); |
| 11047 | return op.redispatch(dispatchKeySet, self); |
| 11048 | } |
| 11049 | |
| 11050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac, name, "aten::_foreach_frac") |
| 11051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac, overload_name, "") |
| 11052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac, schema_str, "_foreach_frac(Tensor[] self) -> Tensor[]") |
| 11053 | |
| 11054 | // aten::_foreach_frac(Tensor[] self) -> Tensor[] |
| 11055 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_frac::schema> create__foreach_frac_typed_handle() { |
| 11056 | return c10::Dispatcher::singleton() |
| 11057 | .findSchemaOrThrow(_foreach_frac::name, _foreach_frac::overload_name) |
| 11058 | .typed<_foreach_frac::schema>(); |
| 11059 | } |
| 11060 | |
| 11061 | // aten::_foreach_frac(Tensor[] self) -> Tensor[] |
| 11062 | ::std::vector<at::Tensor> _foreach_frac::call(at::TensorList self) { |
| 11063 | |
| 11064 | static auto op = create__foreach_frac_typed_handle(); |
| 11065 | return op.call(self); |
| 11066 | } |
| 11067 | |
| 11068 | // aten::_foreach_frac(Tensor[] self) -> Tensor[] |
| 11069 | ::std::vector<at::Tensor> _foreach_frac::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 11070 | |
| 11071 | static auto op = create__foreach_frac_typed_handle(); |
| 11072 | return op.redispatch(dispatchKeySet, self); |
| 11073 | } |
| 11074 | |
| 11075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac_, name, "aten::_foreach_frac_") |
| 11076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac_, overload_name, "") |
| 11077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac_, schema_str, "_foreach_frac_(Tensor(a!)[] self) -> ()") |
| 11078 | |
| 11079 | // aten::_foreach_frac_(Tensor(a!)[] self) -> () |
| 11080 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_frac_::schema> create__foreach_frac__typed_handle() { |
| 11081 | return c10::Dispatcher::singleton() |
| 11082 | .findSchemaOrThrow(_foreach_frac_::name, _foreach_frac_::overload_name) |
| 11083 | .typed<_foreach_frac_::schema>(); |
| 11084 | } |
| 11085 | |
| 11086 | // aten::_foreach_frac_(Tensor(a!)[] self) -> () |
| 11087 | void _foreach_frac_::call(at::TensorList self) { |
| 11088 | |
| 11089 | static auto op = create__foreach_frac__typed_handle(); |
| 11090 | return op.call(self); |
| 11091 | } |
| 11092 | |
| 11093 | // aten::_foreach_frac_(Tensor(a!)[] self) -> () |
| 11094 | void _foreach_frac_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 11095 | |
| 11096 | static auto op = create__foreach_frac__typed_handle(); |
| 11097 | return op.redispatch(dispatchKeySet, self); |
| 11098 | } |
| 11099 | |
| 11100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc, name, "aten::_foreach_trunc") |
| 11101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc, overload_name, "") |
| 11102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc, schema_str, "_foreach_trunc(Tensor[] self) -> Tensor[]") |
| 11103 | |
| 11104 | // aten::_foreach_trunc(Tensor[] self) -> Tensor[] |
| 11105 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_trunc::schema> create__foreach_trunc_typed_handle() { |
| 11106 | return c10::Dispatcher::singleton() |
| 11107 | .findSchemaOrThrow(_foreach_trunc::name, _foreach_trunc::overload_name) |
| 11108 | .typed<_foreach_trunc::schema>(); |
| 11109 | } |
| 11110 | |
| 11111 | // aten::_foreach_trunc(Tensor[] self) -> Tensor[] |
| 11112 | ::std::vector<at::Tensor> _foreach_trunc::call(at::TensorList self) { |
| 11113 | |
| 11114 | static auto op = create__foreach_trunc_typed_handle(); |
| 11115 | return op.call(self); |
| 11116 | } |
| 11117 | |
| 11118 | // aten::_foreach_trunc(Tensor[] self) -> Tensor[] |
| 11119 | ::std::vector<at::Tensor> _foreach_trunc::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 11120 | |
| 11121 | static auto op = create__foreach_trunc_typed_handle(); |
| 11122 | return op.redispatch(dispatchKeySet, self); |
| 11123 | } |
| 11124 | |
| 11125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc_, name, "aten::_foreach_trunc_") |
| 11126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc_, overload_name, "") |
| 11127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc_, schema_str, "_foreach_trunc_(Tensor(a!)[] self) -> ()") |
| 11128 | |
| 11129 | // aten::_foreach_trunc_(Tensor(a!)[] self) -> () |
| 11130 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_trunc_::schema> create__foreach_trunc__typed_handle() { |
| 11131 | return c10::Dispatcher::singleton() |
| 11132 | .findSchemaOrThrow(_foreach_trunc_::name, _foreach_trunc_::overload_name) |
| 11133 | .typed<_foreach_trunc_::schema>(); |
| 11134 | } |
| 11135 | |
| 11136 | // aten::_foreach_trunc_(Tensor(a!)[] self) -> () |
| 11137 | void _foreach_trunc_::call(at::TensorList self) { |
| 11138 | |
| 11139 | static auto op = create__foreach_trunc__typed_handle(); |
| 11140 | return op.call(self); |
| 11141 | } |
| 11142 | |
| 11143 | // aten::_foreach_trunc_(Tensor(a!)[] self) -> () |
| 11144 | void _foreach_trunc_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 11145 | |
| 11146 | static auto op = create__foreach_trunc__typed_handle(); |
| 11147 | return op.redispatch(dispatchKeySet, self); |
| 11148 | } |
| 11149 | |
| 11150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_List, name, "aten::_foreach_lerp") |
| 11151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_List, overload_name, "List") |
| 11152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_List, schema_str, "_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[]") |
| 11153 | |
| 11154 | // aten::_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] |
| 11155 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lerp_List::schema> create__foreach_lerp_List_typed_handle() { |
| 11156 | return c10::Dispatcher::singleton() |
| 11157 | .findSchemaOrThrow(_foreach_lerp_List::name, _foreach_lerp_List::overload_name) |
| 11158 | .typed<_foreach_lerp_List::schema>(); |
| 11159 | } |
| 11160 | |
| 11161 | // aten::_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] |
| 11162 | ::std::vector<at::Tensor> _foreach_lerp_List::call(at::TensorList self, at::TensorList tensors1, at::TensorList weights) { |
| 11163 | |
| 11164 | static auto op = create__foreach_lerp_List_typed_handle(); |
| 11165 | return op.call(self, tensors1, weights); |
| 11166 | } |
| 11167 | |
| 11168 | // aten::_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] |
| 11169 | ::std::vector<at::Tensor> _foreach_lerp_List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights) { |
| 11170 | |
| 11171 | static auto op = create__foreach_lerp_List_typed_handle(); |
| 11172 | return op.redispatch(dispatchKeySet, self, tensors1, weights); |
| 11173 | } |
| 11174 | |
| 11175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp__List, name, "aten::_foreach_lerp_") |
| 11176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp__List, overload_name, "List") |
| 11177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp__List, schema_str, "_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> ()") |
| 11178 | |
| 11179 | // aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () |
| 11180 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lerp__List::schema> create__foreach_lerp__List_typed_handle() { |
| 11181 | return c10::Dispatcher::singleton() |
| 11182 | .findSchemaOrThrow(_foreach_lerp__List::name, _foreach_lerp__List::overload_name) |
| 11183 | .typed<_foreach_lerp__List::schema>(); |
| 11184 | } |
| 11185 | |
| 11186 | // aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () |
| 11187 | void _foreach_lerp__List::call(at::TensorList self, at::TensorList tensors1, at::TensorList weights) { |
| 11188 | |
| 11189 | static auto op = create__foreach_lerp__List_typed_handle(); |
| 11190 | return op.call(self, tensors1, weights); |
| 11191 | } |
| 11192 | |
| 11193 | // aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () |
| 11194 | void _foreach_lerp__List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights) { |
| 11195 | |
| 11196 | static auto op = create__foreach_lerp__List_typed_handle(); |
| 11197 | return op.redispatch(dispatchKeySet, self, tensors1, weights); |
| 11198 | } |
| 11199 | |
| 11200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_Scalar, name, "aten::_foreach_lerp") |
| 11201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_Scalar, overload_name, "Scalar") |
| 11202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_Scalar, schema_str, "_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[]") |
| 11203 | |
| 11204 | // aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] |
| 11205 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lerp_Scalar::schema> create__foreach_lerp_Scalar_typed_handle() { |
| 11206 | return c10::Dispatcher::singleton() |
| 11207 | .findSchemaOrThrow(_foreach_lerp_Scalar::name, _foreach_lerp_Scalar::overload_name) |
| 11208 | .typed<_foreach_lerp_Scalar::schema>(); |
| 11209 | } |
| 11210 | |
| 11211 | // aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] |
| 11212 | ::std::vector<at::Tensor> _foreach_lerp_Scalar::call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight) { |
| 11213 | |
| 11214 | static auto op = create__foreach_lerp_Scalar_typed_handle(); |
| 11215 | return op.call(self, tensors1, weight); |
| 11216 | } |
| 11217 | |
| 11218 | // aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] |
| 11219 | ::std::vector<at::Tensor> _foreach_lerp_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight) { |
| 11220 | |
| 11221 | static auto op = create__foreach_lerp_Scalar_typed_handle(); |
| 11222 | return op.redispatch(dispatchKeySet, self, tensors1, weight); |
| 11223 | } |
| 11224 | |
| 11225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp__Scalar, name, "aten::_foreach_lerp_") |
| 11226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp__Scalar, overload_name, "Scalar") |
| 11227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp__Scalar, schema_str, "_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> ()") |
| 11228 | |
| 11229 | // aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () |
| 11230 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lerp__Scalar::schema> create__foreach_lerp__Scalar_typed_handle() { |
| 11231 | return c10::Dispatcher::singleton() |
| 11232 | .findSchemaOrThrow(_foreach_lerp__Scalar::name, _foreach_lerp__Scalar::overload_name) |
| 11233 | .typed<_foreach_lerp__Scalar::schema>(); |
| 11234 | } |
| 11235 | |
| 11236 | // aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () |
| 11237 | void _foreach_lerp__Scalar::call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight) { |
| 11238 | |
| 11239 | static auto op = create__foreach_lerp__Scalar_typed_handle(); |
| 11240 | return op.call(self, tensors1, weight); |
| 11241 | } |
| 11242 | |
| 11243 | // aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () |
| 11244 | void _foreach_lerp__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight) { |
| 11245 | |
| 11246 | static auto op = create__foreach_lerp__Scalar_typed_handle(); |
| 11247 | return op.redispatch(dispatchKeySet, self, tensors1, weight); |
| 11248 | } |
| 11249 | |
| 11250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mse_loss_backward_grad_input, name, "aten::mse_loss_backward") |
| 11251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mse_loss_backward_grad_input, overload_name, "grad_input") |
| 11252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mse_loss_backward_grad_input, schema_str, "mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11253 | |
| 11254 | // aten::mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11255 | static C10_NOINLINE c10::TypedOperatorHandle<mse_loss_backward_grad_input::schema> create_mse_loss_backward_grad_input_typed_handle() { |
| 11256 | return c10::Dispatcher::singleton() |
| 11257 | .findSchemaOrThrow(mse_loss_backward_grad_input::name, mse_loss_backward_grad_input::overload_name) |
| 11258 | .typed<mse_loss_backward_grad_input::schema>(); |
| 11259 | } |
| 11260 | |
| 11261 | // aten::mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11262 | at::Tensor & mse_loss_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input) { |
| 11263 | |
| 11264 | static auto op = create_mse_loss_backward_grad_input_typed_handle(); |
| 11265 | return op.call(grad_output, self, target, reduction, grad_input); |
| 11266 | } |
| 11267 | |
| 11268 | // aten::mse_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11269 | at::Tensor & mse_loss_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input) { |
| 11270 | |
| 11271 | static auto op = create_mse_loss_backward_grad_input_typed_handle(); |
| 11272 | return op.redispatch(dispatchKeySet, grad_output, self, target, reduction, grad_input); |
| 11273 | } |
| 11274 | |
| 11275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mse_loss_backward, name, "aten::mse_loss_backward") |
| 11276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mse_loss_backward, overload_name, "") |
| 11277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mse_loss_backward, schema_str, "mse_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor") |
| 11278 | |
| 11279 | // aten::mse_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor |
| 11280 | static C10_NOINLINE c10::TypedOperatorHandle<mse_loss_backward::schema> create_mse_loss_backward_typed_handle() { |
| 11281 | return c10::Dispatcher::singleton() |
| 11282 | .findSchemaOrThrow(mse_loss_backward::name, mse_loss_backward::overload_name) |
| 11283 | .typed<mse_loss_backward::schema>(); |
| 11284 | } |
| 11285 | |
| 11286 | // aten::mse_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor |
| 11287 | at::Tensor mse_loss_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
| 11288 | |
| 11289 | static auto op = create_mse_loss_backward_typed_handle(); |
| 11290 | return op.call(grad_output, self, target, reduction); |
| 11291 | } |
| 11292 | |
| 11293 | // aten::mse_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor |
| 11294 | at::Tensor mse_loss_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
| 11295 | |
| 11296 | static auto op = create_mse_loss_backward_typed_handle(); |
| 11297 | return op.redispatch(dispatchKeySet, grad_output, self, target, reduction); |
| 11298 | } |
| 11299 | |
| 11300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_backward_grad_input, name, "aten::multi_margin_loss_backward") |
| 11301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_backward_grad_input, overload_name, "grad_input") |
| 11302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_backward_grad_input, schema_str, "multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11303 | |
| 11304 | // aten::multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11305 | static C10_NOINLINE c10::TypedOperatorHandle<multi_margin_loss_backward_grad_input::schema> create_multi_margin_loss_backward_grad_input_typed_handle() { |
| 11306 | return c10::Dispatcher::singleton() |
| 11307 | .findSchemaOrThrow(multi_margin_loss_backward_grad_input::name, multi_margin_loss_backward_grad_input::overload_name) |
| 11308 | .typed<multi_margin_loss_backward_grad_input::schema>(); |
| 11309 | } |
| 11310 | |
| 11311 | // aten::multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11312 | at::Tensor & multi_margin_loss_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & grad_input) { |
| 11313 | |
| 11314 | static auto op = create_multi_margin_loss_backward_grad_input_typed_handle(); |
| 11315 | return op.call(grad_output, self, target, p, margin, weight, reduction, grad_input); |
| 11316 | } |
| 11317 | |
| 11318 | // aten::multi_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11319 | at::Tensor & multi_margin_loss_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & grad_input) { |
| 11320 | |
| 11321 | static auto op = create_multi_margin_loss_backward_grad_input_typed_handle(); |
| 11322 | return op.redispatch(dispatchKeySet, grad_output, self, target, p, margin, weight, reduction, grad_input); |
| 11323 | } |
| 11324 | |
| 11325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_backward, name, "aten::multi_margin_loss_backward") |
| 11326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_backward, overload_name, "") |
| 11327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_backward, schema_str, "multi_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean) -> Tensor") |
| 11328 | |
| 11329 | // aten::multi_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean) -> Tensor |
| 11330 | static C10_NOINLINE c10::TypedOperatorHandle<multi_margin_loss_backward::schema> create_multi_margin_loss_backward_typed_handle() { |
| 11331 | return c10::Dispatcher::singleton() |
| 11332 | .findSchemaOrThrow(multi_margin_loss_backward::name, multi_margin_loss_backward::overload_name) |
| 11333 | .typed<multi_margin_loss_backward::schema>(); |
| 11334 | } |
| 11335 | |
| 11336 | // aten::multi_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean) -> Tensor |
| 11337 | at::Tensor multi_margin_loss_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction) { |
| 11338 | |
| 11339 | static auto op = create_multi_margin_loss_backward_typed_handle(); |
| 11340 | return op.call(grad_output, self, target, p, margin, weight, reduction); |
| 11341 | } |
| 11342 | |
| 11343 | // aten::multi_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, Scalar p, Scalar margin, Tensor? weight=None, int reduction=Mean) -> Tensor |
| 11344 | at::Tensor multi_margin_loss_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction) { |
| 11345 | |
| 11346 | static auto op = create_multi_margin_loss_backward_typed_handle(); |
| 11347 | return op.redispatch(dispatchKeySet, grad_output, self, target, p, margin, weight, reduction); |
| 11348 | } |
| 11349 | |
| 11350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_backward_grad_input, name, "aten::multilabel_margin_loss_backward") |
| 11351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_backward_grad_input, overload_name, "grad_input") |
| 11352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_backward_grad_input, schema_str, "multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11353 | |
| 11354 | // aten::multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11355 | static C10_NOINLINE c10::TypedOperatorHandle<multilabel_margin_loss_backward_grad_input::schema> create_multilabel_margin_loss_backward_grad_input_typed_handle() { |
| 11356 | return c10::Dispatcher::singleton() |
| 11357 | .findSchemaOrThrow(multilabel_margin_loss_backward_grad_input::name, multilabel_margin_loss_backward_grad_input::overload_name) |
| 11358 | .typed<multilabel_margin_loss_backward_grad_input::schema>(); |
| 11359 | } |
| 11360 | |
| 11361 | // aten::multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11362 | at::Tensor & multilabel_margin_loss_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input) { |
| 11363 | |
| 11364 | static auto op = create_multilabel_margin_loss_backward_grad_input_typed_handle(); |
| 11365 | return op.call(grad_output, self, target, reduction, is_target, grad_input); |
| 11366 | } |
| 11367 | |
| 11368 | // aten::multilabel_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11369 | at::Tensor & multilabel_margin_loss_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target, at::Tensor & grad_input) { |
| 11370 | |
| 11371 | static auto op = create_multilabel_margin_loss_backward_grad_input_typed_handle(); |
| 11372 | return op.redispatch(dispatchKeySet, grad_output, self, target, reduction, is_target, grad_input); |
| 11373 | } |
| 11374 | |
| 11375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_backward, name, "aten::multilabel_margin_loss_backward") |
| 11376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_backward, overload_name, "") |
| 11377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_backward, schema_str, "multilabel_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target) -> Tensor") |
| 11378 | |
| 11379 | // aten::multilabel_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target) -> Tensor |
| 11380 | static C10_NOINLINE c10::TypedOperatorHandle<multilabel_margin_loss_backward::schema> create_multilabel_margin_loss_backward_typed_handle() { |
| 11381 | return c10::Dispatcher::singleton() |
| 11382 | .findSchemaOrThrow(multilabel_margin_loss_backward::name, multilabel_margin_loss_backward::overload_name) |
| 11383 | .typed<multilabel_margin_loss_backward::schema>(); |
| 11384 | } |
| 11385 | |
| 11386 | // aten::multilabel_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target) -> Tensor |
| 11387 | at::Tensor multilabel_margin_loss_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target) { |
| 11388 | |
| 11389 | static auto op = create_multilabel_margin_loss_backward_typed_handle(); |
| 11390 | return op.call(grad_output, self, target, reduction, is_target); |
| 11391 | } |
| 11392 | |
| 11393 | // aten::multilabel_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction, Tensor is_target) -> Tensor |
| 11394 | at::Tensor multilabel_margin_loss_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, const at::Tensor & is_target) { |
| 11395 | |
| 11396 | static auto op = create_multilabel_margin_loss_backward_typed_handle(); |
| 11397 | return op.redispatch(dispatchKeySet, grad_output, self, target, reduction, is_target); |
| 11398 | } |
| 11399 | |
| 11400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_backward_grad_input, name, "aten::elu_backward") |
| 11401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_backward_grad_input, overload_name, "grad_input") |
| 11402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_backward_grad_input, schema_str, "elu_backward.grad_input(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11403 | |
| 11404 | // aten::elu_backward.grad_input(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11405 | static C10_NOINLINE c10::TypedOperatorHandle<elu_backward_grad_input::schema> create_elu_backward_grad_input_typed_handle() { |
| 11406 | return c10::Dispatcher::singleton() |
| 11407 | .findSchemaOrThrow(elu_backward_grad_input::name, elu_backward_grad_input::overload_name) |
| 11408 | .typed<elu_backward_grad_input::schema>(); |
| 11409 | } |
| 11410 | |
| 11411 | // aten::elu_backward.grad_input(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11412 | at::Tensor & elu_backward_grad_input::call(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result, at::Tensor & grad_input) { |
| 11413 | |
| 11414 | static auto op = create_elu_backward_grad_input_typed_handle(); |
| 11415 | return op.call(grad_output, alpha, scale, input_scale, is_result, self_or_result, grad_input); |
| 11416 | } |
| 11417 | |
| 11418 | // aten::elu_backward.grad_input(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11419 | at::Tensor & elu_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result, at::Tensor & grad_input) { |
| 11420 | |
| 11421 | static auto op = create_elu_backward_grad_input_typed_handle(); |
| 11422 | return op.redispatch(dispatchKeySet, grad_output, alpha, scale, input_scale, is_result, self_or_result, grad_input); |
| 11423 | } |
| 11424 | |
| 11425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_backward, name, "aten::elu_backward") |
| 11426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_backward, overload_name, "") |
| 11427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_backward, schema_str, "elu_backward(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result) -> Tensor") |
| 11428 | |
| 11429 | // aten::elu_backward(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result) -> Tensor |
| 11430 | static C10_NOINLINE c10::TypedOperatorHandle<elu_backward::schema> create_elu_backward_typed_handle() { |
| 11431 | return c10::Dispatcher::singleton() |
| 11432 | .findSchemaOrThrow(elu_backward::name, elu_backward::overload_name) |
| 11433 | .typed<elu_backward::schema>(); |
| 11434 | } |
| 11435 | |
| 11436 | // aten::elu_backward(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result) -> Tensor |
| 11437 | at::Tensor elu_backward::call(const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result) { |
| 11438 | |
| 11439 | static auto op = create_elu_backward_typed_handle(); |
| 11440 | return op.call(grad_output, alpha, scale, input_scale, is_result, self_or_result); |
| 11441 | } |
| 11442 | |
| 11443 | // aten::elu_backward(Tensor grad_output, Scalar alpha, Scalar scale, Scalar input_scale, bool is_result, Tensor self_or_result) -> Tensor |
| 11444 | at::Tensor elu_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, bool is_result, const at::Tensor & self_or_result) { |
| 11445 | |
| 11446 | static auto op = create_elu_backward_typed_handle(); |
| 11447 | return op.redispatch(dispatchKeySet, grad_output, alpha, scale, input_scale, is_result, self_or_result); |
| 11448 | } |
| 11449 | |
| 11450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardsigmoid_backward_grad_input, name, "aten::hardsigmoid_backward") |
| 11451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardsigmoid_backward_grad_input, overload_name, "grad_input") |
| 11452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardsigmoid_backward_grad_input, schema_str, "hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11453 | |
| 11454 | // aten::hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11455 | static C10_NOINLINE c10::TypedOperatorHandle<hardsigmoid_backward_grad_input::schema> create_hardsigmoid_backward_grad_input_typed_handle() { |
| 11456 | return c10::Dispatcher::singleton() |
| 11457 | .findSchemaOrThrow(hardsigmoid_backward_grad_input::name, hardsigmoid_backward_grad_input::overload_name) |
| 11458 | .typed<hardsigmoid_backward_grad_input::schema>(); |
| 11459 | } |
| 11460 | |
| 11461 | // aten::hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11462 | at::Tensor & hardsigmoid_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input) { |
| 11463 | |
| 11464 | static auto op = create_hardsigmoid_backward_grad_input_typed_handle(); |
| 11465 | return op.call(grad_output, self, grad_input); |
| 11466 | } |
| 11467 | |
| 11468 | // aten::hardsigmoid_backward.grad_input(Tensor grad_output, Tensor self, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11469 | at::Tensor & hardsigmoid_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & grad_input) { |
| 11470 | |
| 11471 | static auto op = create_hardsigmoid_backward_grad_input_typed_handle(); |
| 11472 | return op.redispatch(dispatchKeySet, grad_output, self, grad_input); |
| 11473 | } |
| 11474 | |
| 11475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardsigmoid_backward, name, "aten::hardsigmoid_backward") |
| 11476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardsigmoid_backward, overload_name, "") |
| 11477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardsigmoid_backward, schema_str, "hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor") |
| 11478 | |
| 11479 | // aten::hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor |
| 11480 | static C10_NOINLINE c10::TypedOperatorHandle<hardsigmoid_backward::schema> create_hardsigmoid_backward_typed_handle() { |
| 11481 | return c10::Dispatcher::singleton() |
| 11482 | .findSchemaOrThrow(hardsigmoid_backward::name, hardsigmoid_backward::overload_name) |
| 11483 | .typed<hardsigmoid_backward::schema>(); |
| 11484 | } |
| 11485 | |
| 11486 | // aten::hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor |
| 11487 | at::Tensor hardsigmoid_backward::call(const at::Tensor & grad_output, const at::Tensor & self) { |
| 11488 | |
| 11489 | static auto op = create_hardsigmoid_backward_typed_handle(); |
| 11490 | return op.call(grad_output, self); |
| 11491 | } |
| 11492 | |
| 11493 | // aten::hardsigmoid_backward(Tensor grad_output, Tensor self) -> Tensor |
| 11494 | at::Tensor hardsigmoid_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self) { |
| 11495 | |
| 11496 | static auto op = create_hardsigmoid_backward_typed_handle(); |
| 11497 | return op.redispatch(dispatchKeySet, grad_output, self); |
| 11498 | } |
| 11499 | |
| 11500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_backward, name, "aten::rrelu_with_noise_backward") |
| 11501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_backward, overload_name, "") |
| 11502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_backward, schema_str, "rrelu_with_noise_backward(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result) -> Tensor") |
| 11503 | |
| 11504 | // aten::rrelu_with_noise_backward(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result) -> Tensor |
| 11505 | static C10_NOINLINE c10::TypedOperatorHandle<rrelu_with_noise_backward::schema> create_rrelu_with_noise_backward_typed_handle() { |
| 11506 | return c10::Dispatcher::singleton() |
| 11507 | .findSchemaOrThrow(rrelu_with_noise_backward::name, rrelu_with_noise_backward::overload_name) |
| 11508 | .typed<rrelu_with_noise_backward::schema>(); |
| 11509 | } |
| 11510 | |
| 11511 | // aten::rrelu_with_noise_backward(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result) -> Tensor |
| 11512 | at::Tensor rrelu_with_noise_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result) { |
| 11513 | |
| 11514 | static auto op = create_rrelu_with_noise_backward_typed_handle(); |
| 11515 | return op.call(grad_output, self, noise, lower, upper, training, self_is_result); |
| 11516 | } |
| 11517 | |
| 11518 | // aten::rrelu_with_noise_backward(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result) -> Tensor |
| 11519 | at::Tensor rrelu_with_noise_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result) { |
| 11520 | |
| 11521 | static auto op = create_rrelu_with_noise_backward_typed_handle(); |
| 11522 | return op.redispatch(dispatchKeySet, grad_output, self, noise, lower, upper, training, self_is_result); |
| 11523 | } |
| 11524 | |
| 11525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_backward_grad_input, name, "aten::softplus_backward") |
| 11526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_backward_grad_input, overload_name, "grad_input") |
| 11527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_backward_grad_input, schema_str, "softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11528 | |
| 11529 | // aten::softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11530 | static C10_NOINLINE c10::TypedOperatorHandle<softplus_backward_grad_input::schema> create_softplus_backward_grad_input_typed_handle() { |
| 11531 | return c10::Dispatcher::singleton() |
| 11532 | .findSchemaOrThrow(softplus_backward_grad_input::name, softplus_backward_grad_input::overload_name) |
| 11533 | .typed<softplus_backward_grad_input::schema>(); |
| 11534 | } |
| 11535 | |
| 11536 | // aten::softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11537 | at::Tensor & softplus_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & grad_input) { |
| 11538 | |
| 11539 | static auto op = create_softplus_backward_grad_input_typed_handle(); |
| 11540 | return op.call(grad_output, self, beta, threshold, grad_input); |
| 11541 | } |
| 11542 | |
| 11543 | // aten::softplus_backward.grad_input(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11544 | at::Tensor & softplus_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & grad_input) { |
| 11545 | |
| 11546 | static auto op = create_softplus_backward_grad_input_typed_handle(); |
| 11547 | return op.redispatch(dispatchKeySet, grad_output, self, beta, threshold, grad_input); |
| 11548 | } |
| 11549 | |
| 11550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_backward, name, "aten::softplus_backward") |
| 11551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_backward, overload_name, "") |
| 11552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_backward, schema_str, "softplus_backward(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold) -> Tensor") |
| 11553 | |
| 11554 | // aten::softplus_backward(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold) -> Tensor |
| 11555 | static C10_NOINLINE c10::TypedOperatorHandle<softplus_backward::schema> create_softplus_backward_typed_handle() { |
| 11556 | return c10::Dispatcher::singleton() |
| 11557 | .findSchemaOrThrow(softplus_backward::name, softplus_backward::overload_name) |
| 11558 | .typed<softplus_backward::schema>(); |
| 11559 | } |
| 11560 | |
| 11561 | // aten::softplus_backward(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold) -> Tensor |
| 11562 | at::Tensor softplus_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { |
| 11563 | |
| 11564 | static auto op = create_softplus_backward_typed_handle(); |
| 11565 | return op.call(grad_output, self, beta, threshold); |
| 11566 | } |
| 11567 | |
| 11568 | // aten::softplus_backward(Tensor grad_output, Tensor self, Scalar beta, Scalar threshold) -> Tensor |
| 11569 | at::Tensor softplus_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { |
| 11570 | |
| 11571 | static auto op = create_softplus_backward_typed_handle(); |
| 11572 | return op.redispatch(dispatchKeySet, grad_output, self, beta, threshold); |
| 11573 | } |
| 11574 | |
| 11575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_backward, name, "aten::mkldnn_adaptive_avg_pool2d_backward") |
| 11576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_backward, overload_name, "") |
| 11577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_backward, schema_str, "mkldnn_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor") |
| 11578 | |
| 11579 | // aten::mkldnn_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor |
| 11580 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_adaptive_avg_pool2d_backward::schema> create_mkldnn_adaptive_avg_pool2d_backward_typed_handle() { |
| 11581 | return c10::Dispatcher::singleton() |
| 11582 | .findSchemaOrThrow(mkldnn_adaptive_avg_pool2d_backward::name, mkldnn_adaptive_avg_pool2d_backward::overload_name) |
| 11583 | .typed<mkldnn_adaptive_avg_pool2d_backward::schema>(); |
| 11584 | } |
| 11585 | |
| 11586 | // aten::mkldnn_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor |
| 11587 | at::Tensor mkldnn_adaptive_avg_pool2d_backward::call(const at::Tensor & grad_output, const at::Tensor & self) { |
| 11588 | |
| 11589 | static auto op = create_mkldnn_adaptive_avg_pool2d_backward_typed_handle(); |
| 11590 | return op.call(grad_output, self); |
| 11591 | } |
| 11592 | |
| 11593 | // aten::mkldnn_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor |
| 11594 | at::Tensor mkldnn_adaptive_avg_pool2d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self) { |
| 11595 | |
| 11596 | static auto op = create_mkldnn_adaptive_avg_pool2d_backward_typed_handle(); |
| 11597 | return op.redispatch(dispatchKeySet, grad_output, self); |
| 11598 | } |
| 11599 | |
| 11600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool3d_backward_grad_input, name, "aten::fractional_max_pool3d_backward") |
| 11601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool3d_backward_grad_input, overload_name, "grad_input") |
| 11602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool3d_backward_grad_input, schema_str, "fractional_max_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11603 | |
| 11604 | // aten::fractional_max_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11605 | static C10_NOINLINE c10::TypedOperatorHandle<fractional_max_pool3d_backward_grad_input::schema> create_fractional_max_pool3d_backward_grad_input_typed_handle() { |
| 11606 | return c10::Dispatcher::singleton() |
| 11607 | .findSchemaOrThrow(fractional_max_pool3d_backward_grad_input::name, fractional_max_pool3d_backward_grad_input::overload_name) |
| 11608 | .typed<fractional_max_pool3d_backward_grad_input::schema>(); |
| 11609 | } |
| 11610 | |
| 11611 | // aten::fractional_max_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11612 | at::Tensor & fractional_max_pool3d_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input) { |
| 11613 | |
| 11614 | static auto op = create_fractional_max_pool3d_backward_grad_input_typed_handle(); |
| 11615 | return op.call(grad_output, self, kernel_size, output_size, indices, grad_input); |
| 11616 | } |
| 11617 | |
| 11618 | // aten::fractional_max_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11619 | at::Tensor & fractional_max_pool3d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input) { |
| 11620 | |
| 11621 | static auto op = create_fractional_max_pool3d_backward_grad_input_typed_handle(); |
| 11622 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, output_size, indices, grad_input); |
| 11623 | } |
| 11624 | |
| 11625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool3d_backward, name, "aten::fractional_max_pool3d_backward") |
| 11626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool3d_backward, overload_name, "") |
| 11627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool3d_backward, schema_str, "fractional_max_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices) -> Tensor") |
| 11628 | |
| 11629 | // aten::fractional_max_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices) -> Tensor |
| 11630 | static C10_NOINLINE c10::TypedOperatorHandle<fractional_max_pool3d_backward::schema> create_fractional_max_pool3d_backward_typed_handle() { |
| 11631 | return c10::Dispatcher::singleton() |
| 11632 | .findSchemaOrThrow(fractional_max_pool3d_backward::name, fractional_max_pool3d_backward::overload_name) |
| 11633 | .typed<fractional_max_pool3d_backward::schema>(); |
| 11634 | } |
| 11635 | |
| 11636 | // aten::fractional_max_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices) -> Tensor |
| 11637 | at::Tensor fractional_max_pool3d_backward::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) { |
| 11638 | |
| 11639 | static auto op = create_fractional_max_pool3d_backward_typed_handle(); |
| 11640 | return op.call(grad_output, self, kernel_size, output_size, indices); |
| 11641 | } |
| 11642 | |
| 11643 | // aten::fractional_max_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] output_size, Tensor indices) -> Tensor |
| 11644 | at::Tensor fractional_max_pool3d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) { |
| 11645 | |
| 11646 | static auto op = create_fractional_max_pool3d_backward_typed_handle(); |
| 11647 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, output_size, indices); |
| 11648 | } |
| 11649 | |
| 11650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_out, name, "aten::max_pool2d_with_indices") |
| 11651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_out, overload_name, "out") |
| 11652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_out, schema_str, "max_pool2d_with_indices.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))") |
| 11653 | |
| 11654 | // aten::max_pool2d_with_indices.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) |
| 11655 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool2d_with_indices_out::schema> create_max_pool2d_with_indices_out_typed_handle() { |
| 11656 | return c10::Dispatcher::singleton() |
| 11657 | .findSchemaOrThrow(max_pool2d_with_indices_out::name, max_pool2d_with_indices_out::overload_name) |
| 11658 | .typed<max_pool2d_with_indices_out::schema>(); |
| 11659 | } |
| 11660 | |
| 11661 | // aten::max_pool2d_with_indices.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) |
| 11662 | ::std::tuple<at::Tensor &,at::Tensor &> max_pool2d_with_indices_out::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices) { |
| 11663 | |
| 11664 | static auto op = create_max_pool2d_with_indices_out_typed_handle(); |
| 11665 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); |
| 11666 | } |
| 11667 | |
| 11668 | // aten::max_pool2d_with_indices.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) |
| 11669 | ::std::tuple<at::Tensor &,at::Tensor &> max_pool2d_with_indices_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out, at::Tensor & indices) { |
| 11670 | |
| 11671 | static auto op = create_max_pool2d_with_indices_out_typed_handle(); |
| 11672 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); |
| 11673 | } |
| 11674 | |
| 11675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices, name, "aten::max_pool2d_with_indices") |
| 11676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices, overload_name, "") |
| 11677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices, schema_str, "max_pool2d_with_indices(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor)") |
| 11678 | |
| 11679 | // aten::max_pool2d_with_indices(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 11680 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool2d_with_indices::schema> create_max_pool2d_with_indices_typed_handle() { |
| 11681 | return c10::Dispatcher::singleton() |
| 11682 | .findSchemaOrThrow(max_pool2d_with_indices::name, max_pool2d_with_indices::overload_name) |
| 11683 | .typed<max_pool2d_with_indices::schema>(); |
| 11684 | } |
| 11685 | |
| 11686 | // aten::max_pool2d_with_indices(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 11687 | ::std::tuple<at::Tensor,at::Tensor> max_pool2d_with_indices::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 11688 | |
| 11689 | static auto op = create_max_pool2d_with_indices_typed_handle(); |
| 11690 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode); |
| 11691 | } |
| 11692 | |
| 11693 | // aten::max_pool2d_with_indices(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 11694 | ::std::tuple<at::Tensor,at::Tensor> max_pool2d_with_indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 11695 | |
| 11696 | static auto op = create_max_pool2d_with_indices_typed_handle(); |
| 11697 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode); |
| 11698 | } |
| 11699 | |
| 11700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_out, name, "aten::reflection_pad1d") |
| 11701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_out, overload_name, "out") |
| 11702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_out, schema_str, "reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!)") |
| 11703 | |
| 11704 | // aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) |
| 11705 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad1d_out::schema> create_reflection_pad1d_out_typed_handle() { |
| 11706 | return c10::Dispatcher::singleton() |
| 11707 | .findSchemaOrThrow(reflection_pad1d_out::name, reflection_pad1d_out::overload_name) |
| 11708 | .typed<reflection_pad1d_out::schema>(); |
| 11709 | } |
| 11710 | |
| 11711 | // aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) |
| 11712 | at::Tensor & reflection_pad1d_out::call(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { |
| 11713 | |
| 11714 | static auto op = create_reflection_pad1d_out_typed_handle(); |
| 11715 | return op.call(self, padding, out); |
| 11716 | } |
| 11717 | |
| 11718 | // aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) |
| 11719 | at::Tensor & reflection_pad1d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { |
| 11720 | |
| 11721 | static auto op = create_reflection_pad1d_out_typed_handle(); |
| 11722 | return op.redispatch(dispatchKeySet, self, padding, out); |
| 11723 | } |
| 11724 | |
| 11725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d, name, "aten::reflection_pad1d") |
| 11726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d, overload_name, "") |
| 11727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d, schema_str, "reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor") |
| 11728 | |
| 11729 | // aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor |
| 11730 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad1d::schema> create_reflection_pad1d_typed_handle() { |
| 11731 | return c10::Dispatcher::singleton() |
| 11732 | .findSchemaOrThrow(reflection_pad1d::name, reflection_pad1d::overload_name) |
| 11733 | .typed<reflection_pad1d::schema>(); |
| 11734 | } |
| 11735 | |
| 11736 | // aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor |
| 11737 | at::Tensor reflection_pad1d::call(const at::Tensor & self, c10::SymIntArrayRef padding) { |
| 11738 | |
| 11739 | static auto op = create_reflection_pad1d_typed_handle(); |
| 11740 | return op.call(self, padding); |
| 11741 | } |
| 11742 | |
| 11743 | // aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor |
| 11744 | at::Tensor reflection_pad1d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding) { |
| 11745 | |
| 11746 | static auto op = create_reflection_pad1d_typed_handle(); |
| 11747 | return op.redispatch(dispatchKeySet, self, padding); |
| 11748 | } |
| 11749 | |
| 11750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pad_enum, name, "aten::_pad_enum") |
| 11751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pad_enum, overload_name, "") |
| 11752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pad_enum, schema_str, "_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor") |
| 11753 | |
| 11754 | // aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor |
| 11755 | static C10_NOINLINE c10::TypedOperatorHandle<_pad_enum::schema> create__pad_enum_typed_handle() { |
| 11756 | return c10::Dispatcher::singleton() |
| 11757 | .findSchemaOrThrow(_pad_enum::name, _pad_enum::overload_name) |
| 11758 | .typed<_pad_enum::schema>(); |
| 11759 | } |
| 11760 | |
| 11761 | // aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor |
| 11762 | at::Tensor _pad_enum::call(const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, c10::optional<double> value) { |
| 11763 | |
| 11764 | static auto op = create__pad_enum_typed_handle(); |
| 11765 | return op.call(self, pad, mode, value); |
| 11766 | } |
| 11767 | |
| 11768 | // aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor |
| 11769 | at::Tensor _pad_enum::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad, int64_t mode, c10::optional<double> value) { |
| 11770 | |
| 11771 | static auto op = create__pad_enum_typed_handle(); |
| 11772 | return op.redispatch(dispatchKeySet, self, pad, mode, value); |
| 11773 | } |
| 11774 | |
| 11775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d_vec, name, "aten::upsample_trilinear3d") |
| 11776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d_vec, overload_name, "vec") |
| 11777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d_vec, schema_str, "upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor") |
| 11778 | |
| 11779 | // aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 11780 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_trilinear3d_vec::schema> create_upsample_trilinear3d_vec_typed_handle() { |
| 11781 | return c10::Dispatcher::singleton() |
| 11782 | .findSchemaOrThrow(upsample_trilinear3d_vec::name, upsample_trilinear3d_vec::overload_name) |
| 11783 | .typed<upsample_trilinear3d_vec::schema>(); |
| 11784 | } |
| 11785 | |
| 11786 | // aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 11787 | at::Tensor upsample_trilinear3d_vec::call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 11788 | |
| 11789 | static auto op = create_upsample_trilinear3d_vec_typed_handle(); |
| 11790 | return op.call(input, output_size, align_corners, scale_factors); |
| 11791 | } |
| 11792 | |
| 11793 | // aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 11794 | at::Tensor upsample_trilinear3d_vec::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 11795 | |
| 11796 | static auto op = create_upsample_trilinear3d_vec_typed_handle(); |
| 11797 | return op.redispatch(dispatchKeySet, input, output_size, align_corners, scale_factors); |
| 11798 | } |
| 11799 | |
| 11800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_vec, name, "aten::_upsample_bicubic2d_aa") |
| 11801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_vec, overload_name, "vec") |
| 11802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_vec, schema_str, "_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor") |
| 11803 | |
| 11804 | // aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 11805 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bicubic2d_aa_vec::schema> create__upsample_bicubic2d_aa_vec_typed_handle() { |
| 11806 | return c10::Dispatcher::singleton() |
| 11807 | .findSchemaOrThrow(_upsample_bicubic2d_aa_vec::name, _upsample_bicubic2d_aa_vec::overload_name) |
| 11808 | .typed<_upsample_bicubic2d_aa_vec::schema>(); |
| 11809 | } |
| 11810 | |
| 11811 | // aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 11812 | at::Tensor _upsample_bicubic2d_aa_vec::call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 11813 | |
| 11814 | static auto op = create__upsample_bicubic2d_aa_vec_typed_handle(); |
| 11815 | return op.call(input, output_size, align_corners, scale_factors); |
| 11816 | } |
| 11817 | |
| 11818 | // aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 11819 | at::Tensor _upsample_bicubic2d_aa_vec::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 11820 | |
| 11821 | static auto op = create__upsample_bicubic2d_aa_vec_typed_handle(); |
| 11822 | return op.redispatch(dispatchKeySet, input, output_size, align_corners, scale_factors); |
| 11823 | } |
| 11824 | |
| 11825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d_vec, name, "aten::upsample_nearest3d") |
| 11826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d_vec, overload_name, "vec") |
| 11827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d_vec, schema_str, "upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor") |
| 11828 | |
| 11829 | // aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
| 11830 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_nearest3d_vec::schema> create_upsample_nearest3d_vec_typed_handle() { |
| 11831 | return c10::Dispatcher::singleton() |
| 11832 | .findSchemaOrThrow(upsample_nearest3d_vec::name, upsample_nearest3d_vec::overload_name) |
| 11833 | .typed<upsample_nearest3d_vec::schema>(); |
| 11834 | } |
| 11835 | |
| 11836 | // aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
| 11837 | at::Tensor upsample_nearest3d_vec::call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 11838 | |
| 11839 | static auto op = create_upsample_nearest3d_vec_typed_handle(); |
| 11840 | return op.call(input, output_size, scale_factors); |
| 11841 | } |
| 11842 | |
| 11843 | // aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
| 11844 | at::Tensor upsample_nearest3d_vec::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 11845 | |
| 11846 | static auto op = create_upsample_nearest3d_vec_typed_handle(); |
| 11847 | return op.redispatch(dispatchKeySet, input, output_size, scale_factors); |
| 11848 | } |
| 11849 | |
| 11850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_backward_grad_input, name, "aten::_upsample_bilinear2d_aa_backward") |
| 11851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_backward_grad_input, overload_name, "grad_input") |
| 11852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_backward_grad_input, schema_str, "_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 11853 | |
| 11854 | // aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11855 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bilinear2d_aa_backward_grad_input::schema> create__upsample_bilinear2d_aa_backward_grad_input_typed_handle() { |
| 11856 | return c10::Dispatcher::singleton() |
| 11857 | .findSchemaOrThrow(_upsample_bilinear2d_aa_backward_grad_input::name, _upsample_bilinear2d_aa_backward_grad_input::overload_name) |
| 11858 | .typed<_upsample_bilinear2d_aa_backward_grad_input::schema>(); |
| 11859 | } |
| 11860 | |
| 11861 | // aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11862 | at::Tensor & _upsample_bilinear2d_aa_backward_grad_input::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
| 11863 | |
| 11864 | static auto op = create__upsample_bilinear2d_aa_backward_grad_input_typed_handle(); |
| 11865 | return op.call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); |
| 11866 | } |
| 11867 | |
| 11868 | // aten::_upsample_bilinear2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 11869 | at::Tensor & _upsample_bilinear2d_aa_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
| 11870 | |
| 11871 | static auto op = create__upsample_bilinear2d_aa_backward_grad_input_typed_handle(); |
| 11872 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); |
| 11873 | } |
| 11874 | |
| 11875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_backward, name, "aten::_upsample_bilinear2d_aa_backward") |
| 11876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_backward, overload_name, "") |
| 11877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_backward, schema_str, "_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor") |
| 11878 | |
| 11879 | // aten::_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11880 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bilinear2d_aa_backward::schema> create__upsample_bilinear2d_aa_backward_typed_handle() { |
| 11881 | return c10::Dispatcher::singleton() |
| 11882 | .findSchemaOrThrow(_upsample_bilinear2d_aa_backward::name, _upsample_bilinear2d_aa_backward::overload_name) |
| 11883 | .typed<_upsample_bilinear2d_aa_backward::schema>(); |
| 11884 | } |
| 11885 | |
| 11886 | // aten::_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11887 | at::Tensor _upsample_bilinear2d_aa_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 11888 | |
| 11889 | static auto op = create__upsample_bilinear2d_aa_backward_typed_handle(); |
| 11890 | return op.call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); |
| 11891 | } |
| 11892 | |
| 11893 | // aten::_upsample_bilinear2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11894 | at::Tensor _upsample_bilinear2d_aa_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 11895 | |
| 11896 | static auto op = create__upsample_bilinear2d_aa_backward_typed_handle(); |
| 11897 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales_h, scales_w); |
| 11898 | } |
| 11899 | |
| 11900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_out, name, "aten::_upsample_bicubic2d_aa") |
| 11901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_out, overload_name, "out") |
| 11902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_out, schema_str, "_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 11903 | |
| 11904 | // aten::_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 11905 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bicubic2d_aa_out::schema> create__upsample_bicubic2d_aa_out_typed_handle() { |
| 11906 | return c10::Dispatcher::singleton() |
| 11907 | .findSchemaOrThrow(_upsample_bicubic2d_aa_out::name, _upsample_bicubic2d_aa_out::overload_name) |
| 11908 | .typed<_upsample_bicubic2d_aa_out::schema>(); |
| 11909 | } |
| 11910 | |
| 11911 | // aten::_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 11912 | at::Tensor & _upsample_bicubic2d_aa_out::call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
| 11913 | |
| 11914 | static auto op = create__upsample_bicubic2d_aa_out_typed_handle(); |
| 11915 | return op.call(self, output_size, align_corners, scales_h, scales_w, out); |
| 11916 | } |
| 11917 | |
| 11918 | // aten::_upsample_bicubic2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 11919 | at::Tensor & _upsample_bicubic2d_aa_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
| 11920 | |
| 11921 | static auto op = create__upsample_bicubic2d_aa_out_typed_handle(); |
| 11922 | return op.redispatch(dispatchKeySet, self, output_size, align_corners, scales_h, scales_w, out); |
| 11923 | } |
| 11924 | |
| 11925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa, name, "aten::_upsample_bicubic2d_aa") |
| 11926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa, overload_name, "") |
| 11927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa, schema_str, "_upsample_bicubic2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor") |
| 11928 | |
| 11929 | // aten::_upsample_bicubic2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11930 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bicubic2d_aa::schema> create__upsample_bicubic2d_aa_typed_handle() { |
| 11931 | return c10::Dispatcher::singleton() |
| 11932 | .findSchemaOrThrow(_upsample_bicubic2d_aa::name, _upsample_bicubic2d_aa::overload_name) |
| 11933 | .typed<_upsample_bicubic2d_aa::schema>(); |
| 11934 | } |
| 11935 | |
| 11936 | // aten::_upsample_bicubic2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11937 | at::Tensor _upsample_bicubic2d_aa::call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 11938 | |
| 11939 | static auto op = create__upsample_bicubic2d_aa_typed_handle(); |
| 11940 | return op.call(self, output_size, align_corners, scales_h, scales_w); |
| 11941 | } |
| 11942 | |
| 11943 | // aten::_upsample_bicubic2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11944 | at::Tensor _upsample_bicubic2d_aa::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 11945 | |
| 11946 | static auto op = create__upsample_bicubic2d_aa_typed_handle(); |
| 11947 | return op.redispatch(dispatchKeySet, self, output_size, align_corners, scales_h, scales_w); |
| 11948 | } |
| 11949 | |
| 11950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d_out, name, "aten::upsample_trilinear3d") |
| 11951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d_out, overload_name, "out") |
| 11952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d_out, schema_str, "upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 11953 | |
| 11954 | // aten::upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 11955 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_trilinear3d_out::schema> create_upsample_trilinear3d_out_typed_handle() { |
| 11956 | return c10::Dispatcher::singleton() |
| 11957 | .findSchemaOrThrow(upsample_trilinear3d_out::name, upsample_trilinear3d_out::overload_name) |
| 11958 | .typed<upsample_trilinear3d_out::schema>(); |
| 11959 | } |
| 11960 | |
| 11961 | // aten::upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 11962 | at::Tensor & upsample_trilinear3d_out::call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
| 11963 | |
| 11964 | static auto op = create_upsample_trilinear3d_out_typed_handle(); |
| 11965 | return op.call(self, output_size, align_corners, scales_d, scales_h, scales_w, out); |
| 11966 | } |
| 11967 | |
| 11968 | // aten::upsample_trilinear3d.out(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 11969 | at::Tensor & upsample_trilinear3d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
| 11970 | |
| 11971 | static auto op = create_upsample_trilinear3d_out_typed_handle(); |
| 11972 | return op.redispatch(dispatchKeySet, self, output_size, align_corners, scales_d, scales_h, scales_w, out); |
| 11973 | } |
| 11974 | |
| 11975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d, name, "aten::upsample_trilinear3d") |
| 11976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d, overload_name, "") |
| 11977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_trilinear3d, schema_str, "upsample_trilinear3d(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor") |
| 11978 | |
| 11979 | // aten::upsample_trilinear3d(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11980 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_trilinear3d::schema> create_upsample_trilinear3d_typed_handle() { |
| 11981 | return c10::Dispatcher::singleton() |
| 11982 | .findSchemaOrThrow(upsample_trilinear3d::name, upsample_trilinear3d::overload_name) |
| 11983 | .typed<upsample_trilinear3d::schema>(); |
| 11984 | } |
| 11985 | |
| 11986 | // aten::upsample_trilinear3d(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11987 | at::Tensor upsample_trilinear3d::call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 11988 | |
| 11989 | static auto op = create_upsample_trilinear3d_typed_handle(); |
| 11990 | return op.call(self, output_size, align_corners, scales_d, scales_h, scales_w); |
| 11991 | } |
| 11992 | |
| 11993 | // aten::upsample_trilinear3d(Tensor self, SymInt[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
| 11994 | at::Tensor upsample_trilinear3d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 11995 | |
| 11996 | static auto op = create_upsample_trilinear3d_typed_handle(); |
| 11997 | return op.redispatch(dispatchKeySet, self, output_size, align_corners, scales_d, scales_h, scales_w); |
| 11998 | } |
| 11999 | |
| 12000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d_out, name, "aten::upsample_nearest3d") |
| 12001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d_out, overload_name, "out") |
| 12002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d_out, schema_str, "upsample_nearest3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 12003 | |
| 12004 | // aten::upsample_nearest3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12005 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_nearest3d_out::schema> create_upsample_nearest3d_out_typed_handle() { |
| 12006 | return c10::Dispatcher::singleton() |
| 12007 | .findSchemaOrThrow(upsample_nearest3d_out::name, upsample_nearest3d_out::overload_name) |
| 12008 | .typed<upsample_nearest3d_out::schema>(); |
| 12009 | } |
| 12010 | |
| 12011 | // aten::upsample_nearest3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12012 | at::Tensor & upsample_nearest3d_out::call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
| 12013 | |
| 12014 | static auto op = create_upsample_nearest3d_out_typed_handle(); |
| 12015 | return op.call(self, output_size, scales_d, scales_h, scales_w, out); |
| 12016 | } |
| 12017 | |
| 12018 | // aten::upsample_nearest3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12019 | at::Tensor & upsample_nearest3d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
| 12020 | |
| 12021 | static auto op = create_upsample_nearest3d_out_typed_handle(); |
| 12022 | return op.redispatch(dispatchKeySet, self, output_size, scales_d, scales_h, scales_w, out); |
| 12023 | } |
| 12024 | |
| 12025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d, name, "aten::upsample_nearest3d") |
| 12026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d, overload_name, "") |
| 12027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest3d, schema_str, "upsample_nearest3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor") |
| 12028 | |
| 12029 | // aten::upsample_nearest3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
| 12030 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_nearest3d::schema> create_upsample_nearest3d_typed_handle() { |
| 12031 | return c10::Dispatcher::singleton() |
| 12032 | .findSchemaOrThrow(upsample_nearest3d::name, upsample_nearest3d::overload_name) |
| 12033 | .typed<upsample_nearest3d::schema>(); |
| 12034 | } |
| 12035 | |
| 12036 | // aten::upsample_nearest3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
| 12037 | at::Tensor upsample_nearest3d::call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 12038 | |
| 12039 | static auto op = create_upsample_nearest3d_typed_handle(); |
| 12040 | return op.call(self, output_size, scales_d, scales_h, scales_w); |
| 12041 | } |
| 12042 | |
| 12043 | // aten::upsample_nearest3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
| 12044 | at::Tensor upsample_nearest3d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 12045 | |
| 12046 | static auto op = create_upsample_nearest3d_typed_handle(); |
| 12047 | return op.redispatch(dispatchKeySet, self, output_size, scales_d, scales_h, scales_w); |
| 12048 | } |
| 12049 | |
| 12050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sigmoid_backward_grad_input, name, "aten::sigmoid_backward") |
| 12051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sigmoid_backward_grad_input, overload_name, "grad_input") |
| 12052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sigmoid_backward_grad_input, schema_str, "sigmoid_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 12053 | |
| 12054 | // aten::sigmoid_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 12055 | static C10_NOINLINE c10::TypedOperatorHandle<sigmoid_backward_grad_input::schema> create_sigmoid_backward_grad_input_typed_handle() { |
| 12056 | return c10::Dispatcher::singleton() |
| 12057 | .findSchemaOrThrow(sigmoid_backward_grad_input::name, sigmoid_backward_grad_input::overload_name) |
| 12058 | .typed<sigmoid_backward_grad_input::schema>(); |
| 12059 | } |
| 12060 | |
| 12061 | // aten::sigmoid_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 12062 | at::Tensor & sigmoid_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input) { |
| 12063 | |
| 12064 | static auto op = create_sigmoid_backward_grad_input_typed_handle(); |
| 12065 | return op.call(grad_output, output, grad_input); |
| 12066 | } |
| 12067 | |
| 12068 | // aten::sigmoid_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 12069 | at::Tensor & sigmoid_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input) { |
| 12070 | |
| 12071 | static auto op = create_sigmoid_backward_grad_input_typed_handle(); |
| 12072 | return op.redispatch(dispatchKeySet, grad_output, output, grad_input); |
| 12073 | } |
| 12074 | |
| 12075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sigmoid_backward, name, "aten::sigmoid_backward") |
| 12076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sigmoid_backward, overload_name, "") |
| 12077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sigmoid_backward, schema_str, "sigmoid_backward(Tensor grad_output, Tensor output) -> Tensor") |
| 12078 | |
| 12079 | // aten::sigmoid_backward(Tensor grad_output, Tensor output) -> Tensor |
| 12080 | static C10_NOINLINE c10::TypedOperatorHandle<sigmoid_backward::schema> create_sigmoid_backward_typed_handle() { |
| 12081 | return c10::Dispatcher::singleton() |
| 12082 | .findSchemaOrThrow(sigmoid_backward::name, sigmoid_backward::overload_name) |
| 12083 | .typed<sigmoid_backward::schema>(); |
| 12084 | } |
| 12085 | |
| 12086 | // aten::sigmoid_backward(Tensor grad_output, Tensor output) -> Tensor |
| 12087 | at::Tensor sigmoid_backward::call(const at::Tensor & grad_output, const at::Tensor & output) { |
| 12088 | |
| 12089 | static auto op = create_sigmoid_backward_typed_handle(); |
| 12090 | return op.call(grad_output, output); |
| 12091 | } |
| 12092 | |
| 12093 | // aten::sigmoid_backward(Tensor grad_output, Tensor output) -> Tensor |
| 12094 | at::Tensor sigmoid_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output) { |
| 12095 | |
| 12096 | static auto op = create_sigmoid_backward_typed_handle(); |
| 12097 | return op.redispatch(dispatchKeySet, grad_output, output); |
| 12098 | } |
| 12099 | |
| 12100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tanh_backward_grad_input, name, "aten::tanh_backward") |
| 12101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tanh_backward_grad_input, overload_name, "grad_input") |
| 12102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tanh_backward_grad_input, schema_str, "tanh_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 12103 | |
| 12104 | // aten::tanh_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 12105 | static C10_NOINLINE c10::TypedOperatorHandle<tanh_backward_grad_input::schema> create_tanh_backward_grad_input_typed_handle() { |
| 12106 | return c10::Dispatcher::singleton() |
| 12107 | .findSchemaOrThrow(tanh_backward_grad_input::name, tanh_backward_grad_input::overload_name) |
| 12108 | .typed<tanh_backward_grad_input::schema>(); |
| 12109 | } |
| 12110 | |
| 12111 | // aten::tanh_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 12112 | at::Tensor & tanh_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input) { |
| 12113 | |
| 12114 | static auto op = create_tanh_backward_grad_input_typed_handle(); |
| 12115 | return op.call(grad_output, output, grad_input); |
| 12116 | } |
| 12117 | |
| 12118 | // aten::tanh_backward.grad_input(Tensor grad_output, Tensor output, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 12119 | at::Tensor & tanh_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, at::Tensor & grad_input) { |
| 12120 | |
| 12121 | static auto op = create_tanh_backward_grad_input_typed_handle(); |
| 12122 | return op.redispatch(dispatchKeySet, grad_output, output, grad_input); |
| 12123 | } |
| 12124 | |
| 12125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tanh_backward, name, "aten::tanh_backward") |
| 12126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tanh_backward, overload_name, "") |
| 12127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tanh_backward, schema_str, "tanh_backward(Tensor grad_output, Tensor output) -> Tensor") |
| 12128 | |
| 12129 | // aten::tanh_backward(Tensor grad_output, Tensor output) -> Tensor |
| 12130 | static C10_NOINLINE c10::TypedOperatorHandle<tanh_backward::schema> create_tanh_backward_typed_handle() { |
| 12131 | return c10::Dispatcher::singleton() |
| 12132 | .findSchemaOrThrow(tanh_backward::name, tanh_backward::overload_name) |
| 12133 | .typed<tanh_backward::schema>(); |
| 12134 | } |
| 12135 | |
| 12136 | // aten::tanh_backward(Tensor grad_output, Tensor output) -> Tensor |
| 12137 | at::Tensor tanh_backward::call(const at::Tensor & grad_output, const at::Tensor & output) { |
| 12138 | |
| 12139 | static auto op = create_tanh_backward_typed_handle(); |
| 12140 | return op.call(grad_output, output); |
| 12141 | } |
| 12142 | |
| 12143 | // aten::tanh_backward(Tensor grad_output, Tensor output) -> Tensor |
| 12144 | at::Tensor tanh_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output) { |
| 12145 | |
| 12146 | static auto op = create_tanh_backward_typed_handle(); |
| 12147 | return op.redispatch(dispatchKeySet, grad_output, output); |
| 12148 | } |
| 12149 | |
| 12150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(thnn_conv2d_out, name, "aten::thnn_conv2d") |
| 12151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(thnn_conv2d_out, overload_name, "out") |
| 12152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(thnn_conv2d_out, schema_str, "thnn_conv2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, *, Tensor(a!) out) -> Tensor(a!)") |
| 12153 | |
| 12154 | // aten::thnn_conv2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, *, Tensor(a!) out) -> Tensor(a!) |
| 12155 | static C10_NOINLINE c10::TypedOperatorHandle<thnn_conv2d_out::schema> create_thnn_conv2d_out_typed_handle() { |
| 12156 | return c10::Dispatcher::singleton() |
| 12157 | .findSchemaOrThrow(thnn_conv2d_out::name, thnn_conv2d_out::overload_name) |
| 12158 | .typed<thnn_conv2d_out::schema>(); |
| 12159 | } |
| 12160 | |
| 12161 | // aten::thnn_conv2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, *, Tensor(a!) out) -> Tensor(a!) |
| 12162 | at::Tensor & thnn_conv2d_out::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { |
| 12163 | |
| 12164 | static auto op = create_thnn_conv2d_out_typed_handle(); |
| 12165 | return op.call(self, weight, kernel_size, bias, stride, padding, out); |
| 12166 | } |
| 12167 | |
| 12168 | // aten::thnn_conv2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, *, Tensor(a!) out) -> Tensor(a!) |
| 12169 | at::Tensor & thnn_conv2d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & out) { |
| 12170 | |
| 12171 | static auto op = create_thnn_conv2d_out_typed_handle(); |
| 12172 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding, out); |
| 12173 | } |
| 12174 | |
| 12175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(thnn_conv2d, name, "aten::thnn_conv2d") |
| 12176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(thnn_conv2d, overload_name, "") |
| 12177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(thnn_conv2d, schema_str, "thnn_conv2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0) -> Tensor") |
| 12178 | |
| 12179 | // aten::thnn_conv2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0) -> Tensor |
| 12180 | static C10_NOINLINE c10::TypedOperatorHandle<thnn_conv2d::schema> create_thnn_conv2d_typed_handle() { |
| 12181 | return c10::Dispatcher::singleton() |
| 12182 | .findSchemaOrThrow(thnn_conv2d::name, thnn_conv2d::overload_name) |
| 12183 | .typed<thnn_conv2d::schema>(); |
| 12184 | } |
| 12185 | |
| 12186 | // aten::thnn_conv2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0) -> Tensor |
| 12187 | at::Tensor thnn_conv2d::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding) { |
| 12188 | |
| 12189 | static auto op = create_thnn_conv2d_typed_handle(); |
| 12190 | return op.call(self, weight, kernel_size, bias, stride, padding); |
| 12191 | } |
| 12192 | |
| 12193 | // aten::thnn_conv2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0) -> Tensor |
| 12194 | at::Tensor thnn_conv2d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding) { |
| 12195 | |
| 12196 | static auto op = create_thnn_conv2d_typed_handle(); |
| 12197 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding); |
| 12198 | } |
| 12199 | |
| 12200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_slow_conv2d_forward_output, name, "aten::_slow_conv2d_forward") |
| 12201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_slow_conv2d_forward_output, overload_name, "output") |
| 12202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_slow_conv2d_forward_output, schema_str, "_slow_conv2d_forward.output(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, *, Tensor(a!) output) -> Tensor(a!)") |
| 12203 | |
| 12204 | // aten::_slow_conv2d_forward.output(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, *, Tensor(a!) output) -> Tensor(a!) |
| 12205 | static C10_NOINLINE c10::TypedOperatorHandle<_slow_conv2d_forward_output::schema> create__slow_conv2d_forward_output_typed_handle() { |
| 12206 | return c10::Dispatcher::singleton() |
| 12207 | .findSchemaOrThrow(_slow_conv2d_forward_output::name, _slow_conv2d_forward_output::overload_name) |
| 12208 | .typed<_slow_conv2d_forward_output::schema>(); |
| 12209 | } |
| 12210 | |
| 12211 | // aten::_slow_conv2d_forward.output(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, *, Tensor(a!) output) -> Tensor(a!) |
| 12212 | at::Tensor & _slow_conv2d_forward_output::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & output) { |
| 12213 | |
| 12214 | static auto op = create__slow_conv2d_forward_output_typed_handle(); |
| 12215 | return op.call(self, weight, kernel_size, bias, stride, padding, output); |
| 12216 | } |
| 12217 | |
| 12218 | // aten::_slow_conv2d_forward.output(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, *, Tensor(a!) output) -> Tensor(a!) |
| 12219 | at::Tensor & _slow_conv2d_forward_output::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::Tensor & output) { |
| 12220 | |
| 12221 | static auto op = create__slow_conv2d_forward_output_typed_handle(); |
| 12222 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding, output); |
| 12223 | } |
| 12224 | |
| 12225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_slow_conv2d_forward, name, "aten::_slow_conv2d_forward") |
| 12226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_slow_conv2d_forward, overload_name, "") |
| 12227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_slow_conv2d_forward, schema_str, "_slow_conv2d_forward(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding) -> Tensor") |
| 12228 | |
| 12229 | // aten::_slow_conv2d_forward(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding) -> Tensor |
| 12230 | static C10_NOINLINE c10::TypedOperatorHandle<_slow_conv2d_forward::schema> create__slow_conv2d_forward_typed_handle() { |
| 12231 | return c10::Dispatcher::singleton() |
| 12232 | .findSchemaOrThrow(_slow_conv2d_forward::name, _slow_conv2d_forward::overload_name) |
| 12233 | .typed<_slow_conv2d_forward::schema>(); |
| 12234 | } |
| 12235 | |
| 12236 | // aten::_slow_conv2d_forward(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding) -> Tensor |
| 12237 | at::Tensor _slow_conv2d_forward::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding) { |
| 12238 | |
| 12239 | static auto op = create__slow_conv2d_forward_typed_handle(); |
| 12240 | return op.call(self, weight, kernel_size, bias, stride, padding); |
| 12241 | } |
| 12242 | |
| 12243 | // aten::_slow_conv2d_forward(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding) -> Tensor |
| 12244 | at::Tensor _slow_conv2d_forward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding) { |
| 12245 | |
| 12246 | static auto op = create__slow_conv2d_forward_typed_handle(); |
| 12247 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding); |
| 12248 | } |
| 12249 | |
| 12250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(column_stack, name, "aten::column_stack") |
| 12251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(column_stack, overload_name, "") |
| 12252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(column_stack, schema_str, "column_stack(Tensor[] tensors) -> Tensor") |
| 12253 | |
| 12254 | // aten::column_stack(Tensor[] tensors) -> Tensor |
| 12255 | static C10_NOINLINE c10::TypedOperatorHandle<column_stack::schema> create_column_stack_typed_handle() { |
| 12256 | return c10::Dispatcher::singleton() |
| 12257 | .findSchemaOrThrow(column_stack::name, column_stack::overload_name) |
| 12258 | .typed<column_stack::schema>(); |
| 12259 | } |
| 12260 | |
| 12261 | // aten::column_stack(Tensor[] tensors) -> Tensor |
| 12262 | at::Tensor column_stack::call(at::TensorList tensors) { |
| 12263 | |
| 12264 | static auto op = create_column_stack_typed_handle(); |
| 12265 | return op.call(tensors); |
| 12266 | } |
| 12267 | |
| 12268 | // aten::column_stack(Tensor[] tensors) -> Tensor |
| 12269 | at::Tensor column_stack::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 12270 | |
| 12271 | static auto op = create_column_stack_typed_handle(); |
| 12272 | return op.redispatch(dispatchKeySet, tensors); |
| 12273 | } |
| 12274 | |
| 12275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(column_stack_out, name, "aten::column_stack") |
| 12276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(column_stack_out, overload_name, "out") |
| 12277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(column_stack_out, schema_str, "column_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)") |
| 12278 | |
| 12279 | // aten::column_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 12280 | static C10_NOINLINE c10::TypedOperatorHandle<column_stack_out::schema> create_column_stack_out_typed_handle() { |
| 12281 | return c10::Dispatcher::singleton() |
| 12282 | .findSchemaOrThrow(column_stack_out::name, column_stack_out::overload_name) |
| 12283 | .typed<column_stack_out::schema>(); |
| 12284 | } |
| 12285 | |
| 12286 | // aten::column_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 12287 | at::Tensor & column_stack_out::call(at::TensorList tensors, at::Tensor & out) { |
| 12288 | |
| 12289 | static auto op = create_column_stack_out_typed_handle(); |
| 12290 | return op.call(tensors, out); |
| 12291 | } |
| 12292 | |
| 12293 | // aten::column_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 12294 | at::Tensor & column_stack_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out) { |
| 12295 | |
| 12296 | static auto op = create_column_stack_out_typed_handle(); |
| 12297 | return op.redispatch(dispatchKeySet, tensors, out); |
| 12298 | } |
| 12299 | |
| 12300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_entr, name, "aten::special_entr") |
| 12301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_entr, overload_name, "") |
| 12302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_entr, schema_str, "special_entr(Tensor self) -> Tensor") |
| 12303 | |
| 12304 | // aten::special_entr(Tensor self) -> Tensor |
| 12305 | static C10_NOINLINE c10::TypedOperatorHandle<special_entr::schema> create_special_entr_typed_handle() { |
| 12306 | return c10::Dispatcher::singleton() |
| 12307 | .findSchemaOrThrow(special_entr::name, special_entr::overload_name) |
| 12308 | .typed<special_entr::schema>(); |
| 12309 | } |
| 12310 | |
| 12311 | // aten::special_entr(Tensor self) -> Tensor |
| 12312 | at::Tensor special_entr::call(const at::Tensor & self) { |
| 12313 | |
| 12314 | static auto op = create_special_entr_typed_handle(); |
| 12315 | return op.call(self); |
| 12316 | } |
| 12317 | |
| 12318 | // aten::special_entr(Tensor self) -> Tensor |
| 12319 | at::Tensor special_entr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 12320 | |
| 12321 | static auto op = create_special_entr_typed_handle(); |
| 12322 | return op.redispatch(dispatchKeySet, self); |
| 12323 | } |
| 12324 | |
| 12325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_entr_out, name, "aten::special_entr") |
| 12326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_entr_out, overload_name, "out") |
| 12327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_entr_out, schema_str, "special_entr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12328 | |
| 12329 | // aten::special_entr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12330 | static C10_NOINLINE c10::TypedOperatorHandle<special_entr_out::schema> create_special_entr_out_typed_handle() { |
| 12331 | return c10::Dispatcher::singleton() |
| 12332 | .findSchemaOrThrow(special_entr_out::name, special_entr_out::overload_name) |
| 12333 | .typed<special_entr_out::schema>(); |
| 12334 | } |
| 12335 | |
| 12336 | // aten::special_entr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12337 | at::Tensor & special_entr_out::call(const at::Tensor & self, at::Tensor & out) { |
| 12338 | |
| 12339 | static auto op = create_special_entr_out_typed_handle(); |
| 12340 | return op.call(self, out); |
| 12341 | } |
| 12342 | |
| 12343 | // aten::special_entr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12344 | at::Tensor & special_entr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 12345 | |
| 12346 | static auto op = create_special_entr_out_typed_handle(); |
| 12347 | return op.redispatch(dispatchKeySet, self, out); |
| 12348 | } |
| 12349 | |
| 12350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtri, name, "aten::special_ndtri") |
| 12351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtri, overload_name, "") |
| 12352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtri, schema_str, "special_ndtri(Tensor self) -> Tensor") |
| 12353 | |
| 12354 | // aten::special_ndtri(Tensor self) -> Tensor |
| 12355 | static C10_NOINLINE c10::TypedOperatorHandle<special_ndtri::schema> create_special_ndtri_typed_handle() { |
| 12356 | return c10::Dispatcher::singleton() |
| 12357 | .findSchemaOrThrow(special_ndtri::name, special_ndtri::overload_name) |
| 12358 | .typed<special_ndtri::schema>(); |
| 12359 | } |
| 12360 | |
| 12361 | // aten::special_ndtri(Tensor self) -> Tensor |
| 12362 | at::Tensor special_ndtri::call(const at::Tensor & self) { |
| 12363 | |
| 12364 | static auto op = create_special_ndtri_typed_handle(); |
| 12365 | return op.call(self); |
| 12366 | } |
| 12367 | |
| 12368 | // aten::special_ndtri(Tensor self) -> Tensor |
| 12369 | at::Tensor special_ndtri::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 12370 | |
| 12371 | static auto op = create_special_ndtri_typed_handle(); |
| 12372 | return op.redispatch(dispatchKeySet, self); |
| 12373 | } |
| 12374 | |
| 12375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtri_out, name, "aten::special_ndtri") |
| 12376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtri_out, overload_name, "out") |
| 12377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtri_out, schema_str, "special_ndtri.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12378 | |
| 12379 | // aten::special_ndtri.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12380 | static C10_NOINLINE c10::TypedOperatorHandle<special_ndtri_out::schema> create_special_ndtri_out_typed_handle() { |
| 12381 | return c10::Dispatcher::singleton() |
| 12382 | .findSchemaOrThrow(special_ndtri_out::name, special_ndtri_out::overload_name) |
| 12383 | .typed<special_ndtri_out::schema>(); |
| 12384 | } |
| 12385 | |
| 12386 | // aten::special_ndtri.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12387 | at::Tensor & special_ndtri_out::call(const at::Tensor & self, at::Tensor & out) { |
| 12388 | |
| 12389 | static auto op = create_special_ndtri_out_typed_handle(); |
| 12390 | return op.call(self, out); |
| 12391 | } |
| 12392 | |
| 12393 | // aten::special_ndtri.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12394 | at::Tensor & special_ndtri_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 12395 | |
| 12396 | static auto op = create_special_ndtri_out_typed_handle(); |
| 12397 | return op.redispatch(dispatchKeySet, self, out); |
| 12398 | } |
| 12399 | |
| 12400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfc, name, "aten::special_erfc") |
| 12401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfc, overload_name, "") |
| 12402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfc, schema_str, "special_erfc(Tensor self) -> Tensor") |
| 12403 | |
| 12404 | // aten::special_erfc(Tensor self) -> Tensor |
| 12405 | static C10_NOINLINE c10::TypedOperatorHandle<special_erfc::schema> create_special_erfc_typed_handle() { |
| 12406 | return c10::Dispatcher::singleton() |
| 12407 | .findSchemaOrThrow(special_erfc::name, special_erfc::overload_name) |
| 12408 | .typed<special_erfc::schema>(); |
| 12409 | } |
| 12410 | |
| 12411 | // aten::special_erfc(Tensor self) -> Tensor |
| 12412 | at::Tensor special_erfc::call(const at::Tensor & self) { |
| 12413 | |
| 12414 | static auto op = create_special_erfc_typed_handle(); |
| 12415 | return op.call(self); |
| 12416 | } |
| 12417 | |
| 12418 | // aten::special_erfc(Tensor self) -> Tensor |
| 12419 | at::Tensor special_erfc::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 12420 | |
| 12421 | static auto op = create_special_erfc_typed_handle(); |
| 12422 | return op.redispatch(dispatchKeySet, self); |
| 12423 | } |
| 12424 | |
| 12425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfc_out, name, "aten::special_erfc") |
| 12426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfc_out, overload_name, "out") |
| 12427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfc_out, schema_str, "special_erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12428 | |
| 12429 | // aten::special_erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12430 | static C10_NOINLINE c10::TypedOperatorHandle<special_erfc_out::schema> create_special_erfc_out_typed_handle() { |
| 12431 | return c10::Dispatcher::singleton() |
| 12432 | .findSchemaOrThrow(special_erfc_out::name, special_erfc_out::overload_name) |
| 12433 | .typed<special_erfc_out::schema>(); |
| 12434 | } |
| 12435 | |
| 12436 | // aten::special_erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12437 | at::Tensor & special_erfc_out::call(const at::Tensor & self, at::Tensor & out) { |
| 12438 | |
| 12439 | static auto op = create_special_erfc_out_typed_handle(); |
| 12440 | return op.call(self, out); |
| 12441 | } |
| 12442 | |
| 12443 | // aten::special_erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12444 | at::Tensor & special_erfc_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 12445 | |
| 12446 | static auto op = create_special_erfc_out_typed_handle(); |
| 12447 | return op.redispatch(dispatchKeySet, self, out); |
| 12448 | } |
| 12449 | |
| 12450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1e, name, "aten::special_i1e") |
| 12451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1e, overload_name, "") |
| 12452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1e, schema_str, "special_i1e(Tensor self) -> Tensor") |
| 12453 | |
| 12454 | // aten::special_i1e(Tensor self) -> Tensor |
| 12455 | static C10_NOINLINE c10::TypedOperatorHandle<special_i1e::schema> create_special_i1e_typed_handle() { |
| 12456 | return c10::Dispatcher::singleton() |
| 12457 | .findSchemaOrThrow(special_i1e::name, special_i1e::overload_name) |
| 12458 | .typed<special_i1e::schema>(); |
| 12459 | } |
| 12460 | |
| 12461 | // aten::special_i1e(Tensor self) -> Tensor |
| 12462 | at::Tensor special_i1e::call(const at::Tensor & self) { |
| 12463 | |
| 12464 | static auto op = create_special_i1e_typed_handle(); |
| 12465 | return op.call(self); |
| 12466 | } |
| 12467 | |
| 12468 | // aten::special_i1e(Tensor self) -> Tensor |
| 12469 | at::Tensor special_i1e::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 12470 | |
| 12471 | static auto op = create_special_i1e_typed_handle(); |
| 12472 | return op.redispatch(dispatchKeySet, self); |
| 12473 | } |
| 12474 | |
| 12475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1e_out, name, "aten::special_i1e") |
| 12476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1e_out, overload_name, "out") |
| 12477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1e_out, schema_str, "special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12478 | |
| 12479 | // aten::special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12480 | static C10_NOINLINE c10::TypedOperatorHandle<special_i1e_out::schema> create_special_i1e_out_typed_handle() { |
| 12481 | return c10::Dispatcher::singleton() |
| 12482 | .findSchemaOrThrow(special_i1e_out::name, special_i1e_out::overload_name) |
| 12483 | .typed<special_i1e_out::schema>(); |
| 12484 | } |
| 12485 | |
| 12486 | // aten::special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12487 | at::Tensor & special_i1e_out::call(const at::Tensor & self, at::Tensor & out) { |
| 12488 | |
| 12489 | static auto op = create_special_i1e_out_typed_handle(); |
| 12490 | return op.call(self, out); |
| 12491 | } |
| 12492 | |
| 12493 | // aten::special_i1e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12494 | at::Tensor & special_i1e_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 12495 | |
| 12496 | static auto op = create_special_i1e_out_typed_handle(); |
| 12497 | return op.redispatch(dispatchKeySet, self, out); |
| 12498 | } |
| 12499 | |
| 12500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logsumexp, name, "aten::special_logsumexp") |
| 12501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logsumexp, overload_name, "") |
| 12502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logsumexp, schema_str, "special_logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor") |
| 12503 | |
| 12504 | // aten::special_logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor |
| 12505 | static C10_NOINLINE c10::TypedOperatorHandle<special_logsumexp::schema> create_special_logsumexp_typed_handle() { |
| 12506 | return c10::Dispatcher::singleton() |
| 12507 | .findSchemaOrThrow(special_logsumexp::name, special_logsumexp::overload_name) |
| 12508 | .typed<special_logsumexp::schema>(); |
| 12509 | } |
| 12510 | |
| 12511 | // aten::special_logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor |
| 12512 | at::Tensor special_logsumexp::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim) { |
| 12513 | |
| 12514 | static auto op = create_special_logsumexp_typed_handle(); |
| 12515 | return op.call(self, dim, keepdim); |
| 12516 | } |
| 12517 | |
| 12518 | // aten::special_logsumexp(Tensor self, int[1] dim, bool keepdim=False) -> Tensor |
| 12519 | at::Tensor special_logsumexp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim) { |
| 12520 | |
| 12521 | static auto op = create_special_logsumexp_typed_handle(); |
| 12522 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 12523 | } |
| 12524 | |
| 12525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logsumexp_out, name, "aten::special_logsumexp") |
| 12526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logsumexp_out, overload_name, "out") |
| 12527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logsumexp_out, schema_str, "special_logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 12528 | |
| 12529 | // aten::special_logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 12530 | static C10_NOINLINE c10::TypedOperatorHandle<special_logsumexp_out::schema> create_special_logsumexp_out_typed_handle() { |
| 12531 | return c10::Dispatcher::singleton() |
| 12532 | .findSchemaOrThrow(special_logsumexp_out::name, special_logsumexp_out::overload_name) |
| 12533 | .typed<special_logsumexp_out::schema>(); |
| 12534 | } |
| 12535 | |
| 12536 | // aten::special_logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 12537 | at::Tensor & special_logsumexp_out::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
| 12538 | |
| 12539 | static auto op = create_special_logsumexp_out_typed_handle(); |
| 12540 | return op.call(self, dim, keepdim, out); |
| 12541 | } |
| 12542 | |
| 12543 | // aten::special_logsumexp.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 12544 | at::Tensor & special_logsumexp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
| 12545 | |
| 12546 | static auto op = create_special_logsumexp_out_typed_handle(); |
| 12547 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
| 12548 | } |
| 12549 | |
| 12550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammainc_out, name, "aten::special_gammainc") |
| 12551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammainc_out, overload_name, "out") |
| 12552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammainc_out, schema_str, "special_gammainc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 12553 | |
| 12554 | // aten::special_gammainc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12555 | static C10_NOINLINE c10::TypedOperatorHandle<special_gammainc_out::schema> create_special_gammainc_out_typed_handle() { |
| 12556 | return c10::Dispatcher::singleton() |
| 12557 | .findSchemaOrThrow(special_gammainc_out::name, special_gammainc_out::overload_name) |
| 12558 | .typed<special_gammainc_out::schema>(); |
| 12559 | } |
| 12560 | |
| 12561 | // aten::special_gammainc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12562 | at::Tensor & special_gammainc_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 12563 | |
| 12564 | static auto op = create_special_gammainc_out_typed_handle(); |
| 12565 | return op.call(self, other, out); |
| 12566 | } |
| 12567 | |
| 12568 | // aten::special_gammainc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12569 | at::Tensor & special_gammainc_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 12570 | |
| 12571 | static auto op = create_special_gammainc_out_typed_handle(); |
| 12572 | return op.redispatch(dispatchKeySet, self, other, out); |
| 12573 | } |
| 12574 | |
| 12575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammainc, name, "aten::special_gammainc") |
| 12576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammainc, overload_name, "") |
| 12577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammainc, schema_str, "special_gammainc(Tensor self, Tensor other) -> Tensor") |
| 12578 | |
| 12579 | // aten::special_gammainc(Tensor self, Tensor other) -> Tensor |
| 12580 | static C10_NOINLINE c10::TypedOperatorHandle<special_gammainc::schema> create_special_gammainc_typed_handle() { |
| 12581 | return c10::Dispatcher::singleton() |
| 12582 | .findSchemaOrThrow(special_gammainc::name, special_gammainc::overload_name) |
| 12583 | .typed<special_gammainc::schema>(); |
| 12584 | } |
| 12585 | |
| 12586 | // aten::special_gammainc(Tensor self, Tensor other) -> Tensor |
| 12587 | at::Tensor special_gammainc::call(const at::Tensor & self, const at::Tensor & other) { |
| 12588 | |
| 12589 | static auto op = create_special_gammainc_typed_handle(); |
| 12590 | return op.call(self, other); |
| 12591 | } |
| 12592 | |
| 12593 | // aten::special_gammainc(Tensor self, Tensor other) -> Tensor |
| 12594 | at::Tensor special_gammainc::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 12595 | |
| 12596 | static auto op = create_special_gammainc_typed_handle(); |
| 12597 | return op.redispatch(dispatchKeySet, self, other); |
| 12598 | } |
| 12599 | |
| 12600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_rfft2, name, "aten::fft_rfft2") |
| 12601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_rfft2, overload_name, "") |
| 12602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_rfft2, schema_str, "fft_rfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor") |
| 12603 | |
| 12604 | // aten::fft_rfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
| 12605 | static C10_NOINLINE c10::TypedOperatorHandle<fft_rfft2::schema> create_fft_rfft2_typed_handle() { |
| 12606 | return c10::Dispatcher::singleton() |
| 12607 | .findSchemaOrThrow(fft_rfft2::name, fft_rfft2::overload_name) |
| 12608 | .typed<fft_rfft2::schema>(); |
| 12609 | } |
| 12610 | |
| 12611 | // aten::fft_rfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
| 12612 | at::Tensor fft_rfft2::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 12613 | |
| 12614 | static auto op = create_fft_rfft2_typed_handle(); |
| 12615 | return op.call(self, s, dim, norm); |
| 12616 | } |
| 12617 | |
| 12618 | // aten::fft_rfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
| 12619 | at::Tensor fft_rfft2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 12620 | |
| 12621 | static auto op = create_fft_rfft2_typed_handle(); |
| 12622 | return op.redispatch(dispatchKeySet, self, s, dim, norm); |
| 12623 | } |
| 12624 | |
| 12625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_rfft2_out, name, "aten::fft_rfft2") |
| 12626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_rfft2_out, overload_name, "out") |
| 12627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_rfft2_out, schema_str, "fft_rfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 12628 | |
| 12629 | // aten::fft_rfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12630 | static C10_NOINLINE c10::TypedOperatorHandle<fft_rfft2_out::schema> create_fft_rfft2_out_typed_handle() { |
| 12631 | return c10::Dispatcher::singleton() |
| 12632 | .findSchemaOrThrow(fft_rfft2_out::name, fft_rfft2_out::overload_name) |
| 12633 | .typed<fft_rfft2_out::schema>(); |
| 12634 | } |
| 12635 | |
| 12636 | // aten::fft_rfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12637 | at::Tensor & fft_rfft2_out::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
| 12638 | |
| 12639 | static auto op = create_fft_rfft2_out_typed_handle(); |
| 12640 | return op.call(self, s, dim, norm, out); |
| 12641 | } |
| 12642 | |
| 12643 | // aten::fft_rfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12644 | at::Tensor & fft_rfft2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
| 12645 | |
| 12646 | static auto op = create_fft_rfft2_out_typed_handle(); |
| 12647 | return op.redispatch(dispatchKeySet, self, s, dim, norm, out); |
| 12648 | } |
| 12649 | |
| 12650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfftn, name, "aten::fft_hfftn") |
| 12651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfftn, overload_name, "") |
| 12652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfftn, schema_str, "fft_hfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor") |
| 12653 | |
| 12654 | // aten::fft_hfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
| 12655 | static C10_NOINLINE c10::TypedOperatorHandle<fft_hfftn::schema> create_fft_hfftn_typed_handle() { |
| 12656 | return c10::Dispatcher::singleton() |
| 12657 | .findSchemaOrThrow(fft_hfftn::name, fft_hfftn::overload_name) |
| 12658 | .typed<fft_hfftn::schema>(); |
| 12659 | } |
| 12660 | |
| 12661 | // aten::fft_hfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
| 12662 | at::Tensor fft_hfftn::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 12663 | |
| 12664 | static auto op = create_fft_hfftn_typed_handle(); |
| 12665 | return op.call(self, s, dim, norm); |
| 12666 | } |
| 12667 | |
| 12668 | // aten::fft_hfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
| 12669 | at::Tensor fft_hfftn::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 12670 | |
| 12671 | static auto op = create_fft_hfftn_typed_handle(); |
| 12672 | return op.redispatch(dispatchKeySet, self, s, dim, norm); |
| 12673 | } |
| 12674 | |
| 12675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfftn_out, name, "aten::fft_hfftn") |
| 12676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfftn_out, overload_name, "out") |
| 12677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfftn_out, schema_str, "fft_hfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 12678 | |
| 12679 | // aten::fft_hfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12680 | static C10_NOINLINE c10::TypedOperatorHandle<fft_hfftn_out::schema> create_fft_hfftn_out_typed_handle() { |
| 12681 | return c10::Dispatcher::singleton() |
| 12682 | .findSchemaOrThrow(fft_hfftn_out::name, fft_hfftn_out::overload_name) |
| 12683 | .typed<fft_hfftn_out::schema>(); |
| 12684 | } |
| 12685 | |
| 12686 | // aten::fft_hfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12687 | const at::Tensor & fft_hfftn_out::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm, const at::Tensor & out) { |
| 12688 | |
| 12689 | static auto op = create_fft_hfftn_out_typed_handle(); |
| 12690 | return op.call(self, s, dim, norm, out); |
| 12691 | } |
| 12692 | |
| 12693 | // aten::fft_hfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12694 | const at::Tensor & fft_hfftn_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm, const at::Tensor & out) { |
| 12695 | |
| 12696 | static auto op = create_fft_hfftn_out_typed_handle(); |
| 12697 | return op.redispatch(dispatchKeySet, self, s, dim, norm, out); |
| 12698 | } |
| 12699 | |
| 12700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu, name, "aten::linalg_lu") |
| 12701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu, overload_name, "") |
| 12702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu, schema_str, "linalg_lu(Tensor A, *, bool pivot=True) -> (Tensor P, Tensor L, Tensor U)") |
| 12703 | |
| 12704 | // aten::linalg_lu(Tensor A, *, bool pivot=True) -> (Tensor P, Tensor L, Tensor U) |
| 12705 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lu::schema> create_linalg_lu_typed_handle() { |
| 12706 | return c10::Dispatcher::singleton() |
| 12707 | .findSchemaOrThrow(linalg_lu::name, linalg_lu::overload_name) |
| 12708 | .typed<linalg_lu::schema>(); |
| 12709 | } |
| 12710 | |
| 12711 | // aten::linalg_lu(Tensor A, *, bool pivot=True) -> (Tensor P, Tensor L, Tensor U) |
| 12712 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> linalg_lu::call(const at::Tensor & A, bool pivot) { |
| 12713 | |
| 12714 | static auto op = create_linalg_lu_typed_handle(); |
| 12715 | return op.call(A, pivot); |
| 12716 | } |
| 12717 | |
| 12718 | // aten::linalg_lu(Tensor A, *, bool pivot=True) -> (Tensor P, Tensor L, Tensor U) |
| 12719 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> linalg_lu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot) { |
| 12720 | |
| 12721 | static auto op = create_linalg_lu_typed_handle(); |
| 12722 | return op.redispatch(dispatchKeySet, A, pivot); |
| 12723 | } |
| 12724 | |
| 12725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_out, name, "aten::linalg_lu") |
| 12726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_out, overload_name, "out") |
| 12727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_out, schema_str, "linalg_lu.out(Tensor A, *, bool pivot=True, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U)") |
| 12728 | |
| 12729 | // aten::linalg_lu.out(Tensor A, *, bool pivot=True, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) |
| 12730 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lu_out::schema> create_linalg_lu_out_typed_handle() { |
| 12731 | return c10::Dispatcher::singleton() |
| 12732 | .findSchemaOrThrow(linalg_lu_out::name, linalg_lu_out::overload_name) |
| 12733 | .typed<linalg_lu_out::schema>(); |
| 12734 | } |
| 12735 | |
| 12736 | // aten::linalg_lu.out(Tensor A, *, bool pivot=True, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) |
| 12737 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> linalg_lu_out::call(const at::Tensor & A, bool pivot, at::Tensor & P, at::Tensor & L, at::Tensor & U) { |
| 12738 | |
| 12739 | static auto op = create_linalg_lu_out_typed_handle(); |
| 12740 | return op.call(A, pivot, P, L, U); |
| 12741 | } |
| 12742 | |
| 12743 | // aten::linalg_lu.out(Tensor A, *, bool pivot=True, Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) -> (Tensor(a!) P, Tensor(b!) L, Tensor(c!) U) |
| 12744 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> linalg_lu_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot, at::Tensor & P, at::Tensor & L, at::Tensor & U) { |
| 12745 | |
| 12746 | static auto op = create_linalg_lu_out_typed_handle(); |
| 12747 | return op.redispatch(dispatchKeySet, A, pivot, P, L, U); |
| 12748 | } |
| 12749 | |
| 12750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_factor_ex, name, "aten::linalg_ldl_factor_ex") |
| 12751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_factor_ex, overload_name, "") |
| 12752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_factor_ex, schema_str, "linalg_ldl_factor_ex(Tensor self, *, bool hermitian=False, bool check_errors=False) -> (Tensor LD, Tensor pivots, Tensor info)") |
| 12753 | |
| 12754 | // aten::linalg_ldl_factor_ex(Tensor self, *, bool hermitian=False, bool check_errors=False) -> (Tensor LD, Tensor pivots, Tensor info) |
| 12755 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_ldl_factor_ex::schema> create_linalg_ldl_factor_ex_typed_handle() { |
| 12756 | return c10::Dispatcher::singleton() |
| 12757 | .findSchemaOrThrow(linalg_ldl_factor_ex::name, linalg_ldl_factor_ex::overload_name) |
| 12758 | .typed<linalg_ldl_factor_ex::schema>(); |
| 12759 | } |
| 12760 | |
| 12761 | // aten::linalg_ldl_factor_ex(Tensor self, *, bool hermitian=False, bool check_errors=False) -> (Tensor LD, Tensor pivots, Tensor info) |
| 12762 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> linalg_ldl_factor_ex::call(const at::Tensor & self, bool hermitian, bool check_errors) { |
| 12763 | |
| 12764 | static auto op = create_linalg_ldl_factor_ex_typed_handle(); |
| 12765 | return op.call(self, hermitian, check_errors); |
| 12766 | } |
| 12767 | |
| 12768 | // aten::linalg_ldl_factor_ex(Tensor self, *, bool hermitian=False, bool check_errors=False) -> (Tensor LD, Tensor pivots, Tensor info) |
| 12769 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> linalg_ldl_factor_ex::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool hermitian, bool check_errors) { |
| 12770 | |
| 12771 | static auto op = create_linalg_ldl_factor_ex_typed_handle(); |
| 12772 | return op.redispatch(dispatchKeySet, self, hermitian, check_errors); |
| 12773 | } |
| 12774 | |
| 12775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_factor_ex_out, name, "aten::linalg_ldl_factor_ex") |
| 12776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_factor_ex_out, overload_name, "out") |
| 12777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_factor_ex_out, schema_str, "linalg_ldl_factor_ex.out(Tensor self, *, bool hermitian=False, bool check_errors=False, Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info)") |
| 12778 | |
| 12779 | // aten::linalg_ldl_factor_ex.out(Tensor self, *, bool hermitian=False, bool check_errors=False, Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) |
| 12780 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_ldl_factor_ex_out::schema> create_linalg_ldl_factor_ex_out_typed_handle() { |
| 12781 | return c10::Dispatcher::singleton() |
| 12782 | .findSchemaOrThrow(linalg_ldl_factor_ex_out::name, linalg_ldl_factor_ex_out::overload_name) |
| 12783 | .typed<linalg_ldl_factor_ex_out::schema>(); |
| 12784 | } |
| 12785 | |
| 12786 | // aten::linalg_ldl_factor_ex.out(Tensor self, *, bool hermitian=False, bool check_errors=False, Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) |
| 12787 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> linalg_ldl_factor_ex_out::call(const at::Tensor & self, bool hermitian, bool check_errors, at::Tensor & LD, at::Tensor & pivots, at::Tensor & info) { |
| 12788 | |
| 12789 | static auto op = create_linalg_ldl_factor_ex_out_typed_handle(); |
| 12790 | return op.call(self, hermitian, check_errors, LD, pivots, info); |
| 12791 | } |
| 12792 | |
| 12793 | // aten::linalg_ldl_factor_ex.out(Tensor self, *, bool hermitian=False, bool check_errors=False, Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) -> (Tensor(a!) LD, Tensor(b!) pivots, Tensor(c!) info) |
| 12794 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> linalg_ldl_factor_ex_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool hermitian, bool check_errors, at::Tensor & LD, at::Tensor & pivots, at::Tensor & info) { |
| 12795 | |
| 12796 | static auto op = create_linalg_ldl_factor_ex_out_typed_handle(); |
| 12797 | return op.redispatch(dispatchKeySet, self, hermitian, check_errors, LD, pivots, info); |
| 12798 | } |
| 12799 | |
| 12800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_solve, name, "aten::linalg_ldl_solve") |
| 12801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_solve, overload_name, "") |
| 12802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_solve, schema_str, "linalg_ldl_solve(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False) -> Tensor") |
| 12803 | |
| 12804 | // aten::linalg_ldl_solve(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False) -> Tensor |
| 12805 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_ldl_solve::schema> create_linalg_ldl_solve_typed_handle() { |
| 12806 | return c10::Dispatcher::singleton() |
| 12807 | .findSchemaOrThrow(linalg_ldl_solve::name, linalg_ldl_solve::overload_name) |
| 12808 | .typed<linalg_ldl_solve::schema>(); |
| 12809 | } |
| 12810 | |
| 12811 | // aten::linalg_ldl_solve(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False) -> Tensor |
| 12812 | at::Tensor linalg_ldl_solve::call(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian) { |
| 12813 | |
| 12814 | static auto op = create_linalg_ldl_solve_typed_handle(); |
| 12815 | return op.call(LD, pivots, B, hermitian); |
| 12816 | } |
| 12817 | |
| 12818 | // aten::linalg_ldl_solve(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False) -> Tensor |
| 12819 | at::Tensor linalg_ldl_solve::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian) { |
| 12820 | |
| 12821 | static auto op = create_linalg_ldl_solve_typed_handle(); |
| 12822 | return op.redispatch(dispatchKeySet, LD, pivots, B, hermitian); |
| 12823 | } |
| 12824 | |
| 12825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_solve_out, name, "aten::linalg_ldl_solve") |
| 12826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_solve_out, overload_name, "out") |
| 12827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_ldl_solve_out, schema_str, "linalg_ldl_solve.out(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False, Tensor(a!) out) -> Tensor(a!)") |
| 12828 | |
| 12829 | // aten::linalg_ldl_solve.out(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False, Tensor(a!) out) -> Tensor(a!) |
| 12830 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_ldl_solve_out::schema> create_linalg_ldl_solve_out_typed_handle() { |
| 12831 | return c10::Dispatcher::singleton() |
| 12832 | .findSchemaOrThrow(linalg_ldl_solve_out::name, linalg_ldl_solve_out::overload_name) |
| 12833 | .typed<linalg_ldl_solve_out::schema>(); |
| 12834 | } |
| 12835 | |
| 12836 | // aten::linalg_ldl_solve.out(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False, Tensor(a!) out) -> Tensor(a!) |
| 12837 | at::Tensor & linalg_ldl_solve_out::call(const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out) { |
| 12838 | |
| 12839 | static auto op = create_linalg_ldl_solve_out_typed_handle(); |
| 12840 | return op.call(LD, pivots, B, hermitian, out); |
| 12841 | } |
| 12842 | |
| 12843 | // aten::linalg_ldl_solve.out(Tensor LD, Tensor pivots, Tensor B, *, bool hermitian=False, Tensor(a!) out) -> Tensor(a!) |
| 12844 | at::Tensor & linalg_ldl_solve_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LD, const at::Tensor & pivots, const at::Tensor & B, bool hermitian, at::Tensor & out) { |
| 12845 | |
| 12846 | static auto op = create_linalg_ldl_solve_out_typed_handle(); |
| 12847 | return op.redispatch(dispatchKeySet, LD, pivots, B, hermitian, out); |
| 12848 | } |
| 12849 | |
| 12850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lstsq, name, "aten::linalg_lstsq") |
| 12851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lstsq, overload_name, "") |
| 12852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lstsq, schema_str, "linalg_lstsq(Tensor self, Tensor b, float? rcond=None, *, str? driver=None) -> (Tensor solution, Tensor residuals, Tensor rank, Tensor singular_values)") |
| 12853 | |
| 12854 | // aten::linalg_lstsq(Tensor self, Tensor b, float? rcond=None, *, str? driver=None) -> (Tensor solution, Tensor residuals, Tensor rank, Tensor singular_values) |
| 12855 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lstsq::schema> create_linalg_lstsq_typed_handle() { |
| 12856 | return c10::Dispatcher::singleton() |
| 12857 | .findSchemaOrThrow(linalg_lstsq::name, linalg_lstsq::overload_name) |
| 12858 | .typed<linalg_lstsq::schema>(); |
| 12859 | } |
| 12860 | |
| 12861 | // aten::linalg_lstsq(Tensor self, Tensor b, float? rcond=None, *, str? driver=None) -> (Tensor solution, Tensor residuals, Tensor rank, Tensor singular_values) |
| 12862 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> linalg_lstsq::call(const at::Tensor & self, const at::Tensor & b, c10::optional<double> rcond, c10::optional<c10::string_view> driver) { |
| 12863 | |
| 12864 | static auto op = create_linalg_lstsq_typed_handle(); |
| 12865 | return op.call(self, b, rcond, driver); |
| 12866 | } |
| 12867 | |
| 12868 | // aten::linalg_lstsq(Tensor self, Tensor b, float? rcond=None, *, str? driver=None) -> (Tensor solution, Tensor residuals, Tensor rank, Tensor singular_values) |
| 12869 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> linalg_lstsq::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & b, c10::optional<double> rcond, c10::optional<c10::string_view> driver) { |
| 12870 | |
| 12871 | static auto op = create_linalg_lstsq_typed_handle(); |
| 12872 | return op.redispatch(dispatchKeySet, self, b, rcond, driver); |
| 12873 | } |
| 12874 | |
| 12875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lstsq_out, name, "aten::linalg_lstsq") |
| 12876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lstsq_out, overload_name, "out") |
| 12877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lstsq_out, schema_str, "linalg_lstsq.out(Tensor self, Tensor b, float? rcond=None, *, str? driver=None, Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values) -> (Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values)") |
| 12878 | |
| 12879 | // aten::linalg_lstsq.out(Tensor self, Tensor b, float? rcond=None, *, str? driver=None, Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values) -> (Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values) |
| 12880 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lstsq_out::schema> create_linalg_lstsq_out_typed_handle() { |
| 12881 | return c10::Dispatcher::singleton() |
| 12882 | .findSchemaOrThrow(linalg_lstsq_out::name, linalg_lstsq_out::overload_name) |
| 12883 | .typed<linalg_lstsq_out::schema>(); |
| 12884 | } |
| 12885 | |
| 12886 | // aten::linalg_lstsq.out(Tensor self, Tensor b, float? rcond=None, *, str? driver=None, Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values) -> (Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values) |
| 12887 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> linalg_lstsq_out::call(const at::Tensor & self, const at::Tensor & b, c10::optional<double> rcond, c10::optional<c10::string_view> driver, at::Tensor & solution, at::Tensor & residuals, at::Tensor & rank, at::Tensor & singular_values) { |
| 12888 | |
| 12889 | static auto op = create_linalg_lstsq_out_typed_handle(); |
| 12890 | return op.call(self, b, rcond, driver, solution, residuals, rank, singular_values); |
| 12891 | } |
| 12892 | |
| 12893 | // aten::linalg_lstsq.out(Tensor self, Tensor b, float? rcond=None, *, str? driver=None, Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values) -> (Tensor(a!) solution, Tensor(b!) residuals, Tensor(c!) rank, Tensor(d!) singular_values) |
| 12894 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> linalg_lstsq_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & b, c10::optional<double> rcond, c10::optional<c10::string_view> driver, at::Tensor & solution, at::Tensor & residuals, at::Tensor & rank, at::Tensor & singular_values) { |
| 12895 | |
| 12896 | static auto op = create_linalg_lstsq_out_typed_handle(); |
| 12897 | return op.redispatch(dispatchKeySet, self, b, rcond, driver, solution, residuals, rank, singular_values); |
| 12898 | } |
| 12899 | |
| 12900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_vecdot, name, "aten::linalg_vecdot") |
| 12901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_vecdot, overload_name, "") |
| 12902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_vecdot, schema_str, "linalg_vecdot(Tensor x, Tensor y, *, int dim=-1) -> Tensor") |
| 12903 | |
| 12904 | // aten::linalg_vecdot(Tensor x, Tensor y, *, int dim=-1) -> Tensor |
| 12905 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_vecdot::schema> create_linalg_vecdot_typed_handle() { |
| 12906 | return c10::Dispatcher::singleton() |
| 12907 | .findSchemaOrThrow(linalg_vecdot::name, linalg_vecdot::overload_name) |
| 12908 | .typed<linalg_vecdot::schema>(); |
| 12909 | } |
| 12910 | |
| 12911 | // aten::linalg_vecdot(Tensor x, Tensor y, *, int dim=-1) -> Tensor |
| 12912 | at::Tensor linalg_vecdot::call(const at::Tensor & x, const at::Tensor & y, int64_t dim) { |
| 12913 | |
| 12914 | static auto op = create_linalg_vecdot_typed_handle(); |
| 12915 | return op.call(x, y, dim); |
| 12916 | } |
| 12917 | |
| 12918 | // aten::linalg_vecdot(Tensor x, Tensor y, *, int dim=-1) -> Tensor |
| 12919 | at::Tensor linalg_vecdot::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & y, int64_t dim) { |
| 12920 | |
| 12921 | static auto op = create_linalg_vecdot_typed_handle(); |
| 12922 | return op.redispatch(dispatchKeySet, x, y, dim); |
| 12923 | } |
| 12924 | |
| 12925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_vecdot_out, name, "aten::linalg_vecdot") |
| 12926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_vecdot_out, overload_name, "out") |
| 12927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_vecdot_out, schema_str, "linalg_vecdot.out(Tensor x, Tensor y, *, int dim=-1, Tensor(a!) out) -> Tensor(a!)") |
| 12928 | |
| 12929 | // aten::linalg_vecdot.out(Tensor x, Tensor y, *, int dim=-1, Tensor(a!) out) -> Tensor(a!) |
| 12930 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_vecdot_out::schema> create_linalg_vecdot_out_typed_handle() { |
| 12931 | return c10::Dispatcher::singleton() |
| 12932 | .findSchemaOrThrow(linalg_vecdot_out::name, linalg_vecdot_out::overload_name) |
| 12933 | .typed<linalg_vecdot_out::schema>(); |
| 12934 | } |
| 12935 | |
| 12936 | // aten::linalg_vecdot.out(Tensor x, Tensor y, *, int dim=-1, Tensor(a!) out) -> Tensor(a!) |
| 12937 | at::Tensor & linalg_vecdot_out::call(const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out) { |
| 12938 | |
| 12939 | static auto op = create_linalg_vecdot_out_typed_handle(); |
| 12940 | return op.call(x, y, dim, out); |
| 12941 | } |
| 12942 | |
| 12943 | // aten::linalg_vecdot.out(Tensor x, Tensor y, *, int dim=-1, Tensor(a!) out) -> Tensor(a!) |
| 12944 | at::Tensor & linalg_vecdot_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & y, int64_t dim, at::Tensor & out) { |
| 12945 | |
| 12946 | static auto op = create_linalg_vecdot_out_typed_handle(); |
| 12947 | return op.redispatch(dispatchKeySet, x, y, dim, out); |
| 12948 | } |
| 12949 | |
| 12950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_exp, name, "aten::linalg_matrix_exp") |
| 12951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_exp, overload_name, "") |
| 12952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_exp, schema_str, "linalg_matrix_exp(Tensor self) -> Tensor") |
| 12953 | |
| 12954 | // aten::linalg_matrix_exp(Tensor self) -> Tensor |
| 12955 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_exp::schema> create_linalg_matrix_exp_typed_handle() { |
| 12956 | return c10::Dispatcher::singleton() |
| 12957 | .findSchemaOrThrow(linalg_matrix_exp::name, linalg_matrix_exp::overload_name) |
| 12958 | .typed<linalg_matrix_exp::schema>(); |
| 12959 | } |
| 12960 | |
| 12961 | // aten::linalg_matrix_exp(Tensor self) -> Tensor |
| 12962 | at::Tensor linalg_matrix_exp::call(const at::Tensor & self) { |
| 12963 | |
| 12964 | static auto op = create_linalg_matrix_exp_typed_handle(); |
| 12965 | return op.call(self); |
| 12966 | } |
| 12967 | |
| 12968 | // aten::linalg_matrix_exp(Tensor self) -> Tensor |
| 12969 | at::Tensor linalg_matrix_exp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 12970 | |
| 12971 | static auto op = create_linalg_matrix_exp_typed_handle(); |
| 12972 | return op.redispatch(dispatchKeySet, self); |
| 12973 | } |
| 12974 | |
| 12975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_eigh, name, "aten::_linalg_eigh") |
| 12976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_eigh, overload_name, "") |
| 12977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_eigh, schema_str, "_linalg_eigh(Tensor A, str UPLO=\"L\", bool compute_v=True) -> (Tensor eigenvalues, Tensor eigenvectors)") |
| 12978 | |
| 12979 | // aten::_linalg_eigh(Tensor A, str UPLO="L", bool compute_v=True) -> (Tensor eigenvalues, Tensor eigenvectors) |
| 12980 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_eigh::schema> create__linalg_eigh_typed_handle() { |
| 12981 | return c10::Dispatcher::singleton() |
| 12982 | .findSchemaOrThrow(_linalg_eigh::name, _linalg_eigh::overload_name) |
| 12983 | .typed<_linalg_eigh::schema>(); |
| 12984 | } |
| 12985 | |
| 12986 | // aten::_linalg_eigh(Tensor A, str UPLO="L", bool compute_v=True) -> (Tensor eigenvalues, Tensor eigenvectors) |
| 12987 | ::std::tuple<at::Tensor,at::Tensor> _linalg_eigh::call(const at::Tensor & A, c10::string_view UPLO, bool compute_v) { |
| 12988 | |
| 12989 | static auto op = create__linalg_eigh_typed_handle(); |
| 12990 | return op.call(A, UPLO, compute_v); |
| 12991 | } |
| 12992 | |
| 12993 | // aten::_linalg_eigh(Tensor A, str UPLO="L", bool compute_v=True) -> (Tensor eigenvalues, Tensor eigenvectors) |
| 12994 | ::std::tuple<at::Tensor,at::Tensor> _linalg_eigh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view UPLO, bool compute_v) { |
| 12995 | |
| 12996 | static auto op = create__linalg_eigh_typed_handle(); |
| 12997 | return op.redispatch(dispatchKeySet, A, UPLO, compute_v); |
| 12998 | } |
| 12999 | |
| 13000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_eigh_eigenvalues, name, "aten::_linalg_eigh") |
| 13001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_eigh_eigenvalues, overload_name, "eigenvalues") |
| 13002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_eigh_eigenvalues, schema_str, "_linalg_eigh.eigenvalues(Tensor A, str UPLO=\"L\", bool compute_v=True, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors)") |
| 13003 | |
| 13004 | // aten::_linalg_eigh.eigenvalues(Tensor A, str UPLO="L", bool compute_v=True, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
| 13005 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_eigh_eigenvalues::schema> create__linalg_eigh_eigenvalues_typed_handle() { |
| 13006 | return c10::Dispatcher::singleton() |
| 13007 | .findSchemaOrThrow(_linalg_eigh_eigenvalues::name, _linalg_eigh_eigenvalues::overload_name) |
| 13008 | .typed<_linalg_eigh_eigenvalues::schema>(); |
| 13009 | } |
| 13010 | |
| 13011 | // aten::_linalg_eigh.eigenvalues(Tensor A, str UPLO="L", bool compute_v=True, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
| 13012 | ::std::tuple<at::Tensor &,at::Tensor &> _linalg_eigh_eigenvalues::call(const at::Tensor & A, c10::string_view UPLO, bool compute_v, at::Tensor & eigenvalues, at::Tensor & eigenvectors) { |
| 13013 | |
| 13014 | static auto op = create__linalg_eigh_eigenvalues_typed_handle(); |
| 13015 | return op.call(A, UPLO, compute_v, eigenvalues, eigenvectors); |
| 13016 | } |
| 13017 | |
| 13018 | // aten::_linalg_eigh.eigenvalues(Tensor A, str UPLO="L", bool compute_v=True, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
| 13019 | ::std::tuple<at::Tensor &,at::Tensor &> _linalg_eigh_eigenvalues::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view UPLO, bool compute_v, at::Tensor & eigenvalues, at::Tensor & eigenvectors) { |
| 13020 | |
| 13021 | static auto op = create__linalg_eigh_eigenvalues_typed_handle(); |
| 13022 | return op.redispatch(dispatchKeySet, A, UPLO, compute_v, eigenvalues, eigenvectors); |
| 13023 | } |
| 13024 | |
| 13025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm, name, "aten::linalg_norm") |
| 13026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm, overload_name, "") |
| 13027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm, schema_str, "linalg_norm(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor") |
| 13028 | |
| 13029 | // aten::linalg_norm(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 13030 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_norm::schema> create_linalg_norm_typed_handle() { |
| 13031 | return c10::Dispatcher::singleton() |
| 13032 | .findSchemaOrThrow(linalg_norm::name, linalg_norm::overload_name) |
| 13033 | .typed<linalg_norm::schema>(); |
| 13034 | } |
| 13035 | |
| 13036 | // aten::linalg_norm(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 13037 | at::Tensor linalg_norm::call(const at::Tensor & self, const c10::optional<at::Scalar> & ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 13038 | |
| 13039 | static auto op = create_linalg_norm_typed_handle(); |
| 13040 | return op.call(self, ord, dim, keepdim, dtype); |
| 13041 | } |
| 13042 | |
| 13043 | // aten::linalg_norm(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 13044 | at::Tensor linalg_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 13045 | |
| 13046 | static auto op = create_linalg_norm_typed_handle(); |
| 13047 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype); |
| 13048 | } |
| 13049 | |
| 13050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_ord_str, name, "aten::linalg_norm") |
| 13051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_ord_str, overload_name, "ord_str") |
| 13052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_ord_str, schema_str, "linalg_norm.ord_str(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor") |
| 13053 | |
| 13054 | // aten::linalg_norm.ord_str(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 13055 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_norm_ord_str::schema> create_linalg_norm_ord_str_typed_handle() { |
| 13056 | return c10::Dispatcher::singleton() |
| 13057 | .findSchemaOrThrow(linalg_norm_ord_str::name, linalg_norm_ord_str::overload_name) |
| 13058 | .typed<linalg_norm_ord_str::schema>(); |
| 13059 | } |
| 13060 | |
| 13061 | // aten::linalg_norm.ord_str(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 13062 | at::Tensor linalg_norm_ord_str::call(const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 13063 | |
| 13064 | static auto op = create_linalg_norm_ord_str_typed_handle(); |
| 13065 | return op.call(self, ord, dim, keepdim, dtype); |
| 13066 | } |
| 13067 | |
| 13068 | // aten::linalg_norm.ord_str(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 13069 | at::Tensor linalg_norm_ord_str::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 13070 | |
| 13071 | static auto op = create_linalg_norm_ord_str_typed_handle(); |
| 13072 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype); |
| 13073 | } |
| 13074 | |
| 13075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_out, name, "aten::linalg_norm") |
| 13076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_out, overload_name, "out") |
| 13077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_out, schema_str, "linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") |
| 13078 | |
| 13079 | // aten::linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 13080 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_norm_out::schema> create_linalg_norm_out_typed_handle() { |
| 13081 | return c10::Dispatcher::singleton() |
| 13082 | .findSchemaOrThrow(linalg_norm_out::name, linalg_norm_out::overload_name) |
| 13083 | .typed<linalg_norm_out::schema>(); |
| 13084 | } |
| 13085 | |
| 13086 | // aten::linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 13087 | at::Tensor & linalg_norm_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 13088 | |
| 13089 | static auto op = create_linalg_norm_out_typed_handle(); |
| 13090 | return op.call(self, ord, dim, keepdim, dtype, out); |
| 13091 | } |
| 13092 | |
| 13093 | // aten::linalg_norm.out(Tensor self, Scalar? ord=None, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 13094 | at::Tensor & linalg_norm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 13095 | |
| 13096 | static auto op = create_linalg_norm_out_typed_handle(); |
| 13097 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype, out); |
| 13098 | } |
| 13099 | |
| 13100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_ord_str_out, name, "aten::linalg_norm") |
| 13101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_ord_str_out, overload_name, "ord_str_out") |
| 13102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_norm_ord_str_out, schema_str, "linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") |
| 13103 | |
| 13104 | // aten::linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 13105 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_norm_ord_str_out::schema> create_linalg_norm_ord_str_out_typed_handle() { |
| 13106 | return c10::Dispatcher::singleton() |
| 13107 | .findSchemaOrThrow(linalg_norm_ord_str_out::name, linalg_norm_ord_str_out::overload_name) |
| 13108 | .typed<linalg_norm_ord_str_out::schema>(); |
| 13109 | } |
| 13110 | |
| 13111 | // aten::linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 13112 | at::Tensor & linalg_norm_ord_str_out::call(const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 13113 | |
| 13114 | static auto op = create_linalg_norm_ord_str_out_typed_handle(); |
| 13115 | return op.call(self, ord, dim, keepdim, dtype, out); |
| 13116 | } |
| 13117 | |
| 13118 | // aten::linalg_norm.ord_str_out(Tensor self, str ord, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 13119 | at::Tensor & linalg_norm_ord_str_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view ord, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 13120 | |
| 13121 | static auto op = create_linalg_norm_ord_str_out_typed_handle(); |
| 13122 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype, out); |
| 13123 | } |
| 13124 | |
| 13125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svdvals, name, "aten::linalg_svdvals") |
| 13126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svdvals, overload_name, "") |
| 13127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svdvals, schema_str, "linalg_svdvals(Tensor A, *, str? driver=None) -> Tensor") |
| 13128 | |
| 13129 | // aten::linalg_svdvals(Tensor A, *, str? driver=None) -> Tensor |
| 13130 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_svdvals::schema> create_linalg_svdvals_typed_handle() { |
| 13131 | return c10::Dispatcher::singleton() |
| 13132 | .findSchemaOrThrow(linalg_svdvals::name, linalg_svdvals::overload_name) |
| 13133 | .typed<linalg_svdvals::schema>(); |
| 13134 | } |
| 13135 | |
| 13136 | // aten::linalg_svdvals(Tensor A, *, str? driver=None) -> Tensor |
| 13137 | at::Tensor linalg_svdvals::call(const at::Tensor & A, c10::optional<c10::string_view> driver) { |
| 13138 | |
| 13139 | static auto op = create_linalg_svdvals_typed_handle(); |
| 13140 | return op.call(A, driver); |
| 13141 | } |
| 13142 | |
| 13143 | // aten::linalg_svdvals(Tensor A, *, str? driver=None) -> Tensor |
| 13144 | at::Tensor linalg_svdvals::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::optional<c10::string_view> driver) { |
| 13145 | |
| 13146 | static auto op = create_linalg_svdvals_typed_handle(); |
| 13147 | return op.redispatch(dispatchKeySet, A, driver); |
| 13148 | } |
| 13149 | |
| 13150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svdvals_out, name, "aten::linalg_svdvals") |
| 13151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svdvals_out, overload_name, "out") |
| 13152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svdvals_out, schema_str, "linalg_svdvals.out(Tensor A, *, str? driver=None, Tensor(a!) out) -> Tensor(a!)") |
| 13153 | |
| 13154 | // aten::linalg_svdvals.out(Tensor A, *, str? driver=None, Tensor(a!) out) -> Tensor(a!) |
| 13155 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_svdvals_out::schema> create_linalg_svdvals_out_typed_handle() { |
| 13156 | return c10::Dispatcher::singleton() |
| 13157 | .findSchemaOrThrow(linalg_svdvals_out::name, linalg_svdvals_out::overload_name) |
| 13158 | .typed<linalg_svdvals_out::schema>(); |
| 13159 | } |
| 13160 | |
| 13161 | // aten::linalg_svdvals.out(Tensor A, *, str? driver=None, Tensor(a!) out) -> Tensor(a!) |
| 13162 | at::Tensor & linalg_svdvals_out::call(const at::Tensor & A, c10::optional<c10::string_view> driver, at::Tensor & out) { |
| 13163 | |
| 13164 | static auto op = create_linalg_svdvals_out_typed_handle(); |
| 13165 | return op.call(A, driver, out); |
| 13166 | } |
| 13167 | |
| 13168 | // aten::linalg_svdvals.out(Tensor A, *, str? driver=None, Tensor(a!) out) -> Tensor(a!) |
| 13169 | at::Tensor & linalg_svdvals_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::optional<c10::string_view> driver, at::Tensor & out) { |
| 13170 | |
| 13171 | static auto op = create_linalg_svdvals_out_typed_handle(); |
| 13172 | return op.redispatch(dispatchKeySet, A, driver, out); |
| 13173 | } |
| 13174 | |
| 13175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_power, name, "aten::linalg_matrix_power") |
| 13176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_power, overload_name, "") |
| 13177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_power, schema_str, "linalg_matrix_power(Tensor self, int n) -> Tensor") |
| 13178 | |
| 13179 | // aten::linalg_matrix_power(Tensor self, int n) -> Tensor |
| 13180 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_power::schema> create_linalg_matrix_power_typed_handle() { |
| 13181 | return c10::Dispatcher::singleton() |
| 13182 | .findSchemaOrThrow(linalg_matrix_power::name, linalg_matrix_power::overload_name) |
| 13183 | .typed<linalg_matrix_power::schema>(); |
| 13184 | } |
| 13185 | |
| 13186 | // aten::linalg_matrix_power(Tensor self, int n) -> Tensor |
| 13187 | at::Tensor linalg_matrix_power::call(const at::Tensor & self, int64_t n) { |
| 13188 | |
| 13189 | static auto op = create_linalg_matrix_power_typed_handle(); |
| 13190 | return op.call(self, n); |
| 13191 | } |
| 13192 | |
| 13193 | // aten::linalg_matrix_power(Tensor self, int n) -> Tensor |
| 13194 | at::Tensor linalg_matrix_power::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n) { |
| 13195 | |
| 13196 | static auto op = create_linalg_matrix_power_typed_handle(); |
| 13197 | return op.redispatch(dispatchKeySet, self, n); |
| 13198 | } |
| 13199 | |
| 13200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_power_out, name, "aten::linalg_matrix_power") |
| 13201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_power_out, overload_name, "out") |
| 13202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_power_out, schema_str, "linalg_matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!)") |
| 13203 | |
| 13204 | // aten::linalg_matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) |
| 13205 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_power_out::schema> create_linalg_matrix_power_out_typed_handle() { |
| 13206 | return c10::Dispatcher::singleton() |
| 13207 | .findSchemaOrThrow(linalg_matrix_power_out::name, linalg_matrix_power_out::overload_name) |
| 13208 | .typed<linalg_matrix_power_out::schema>(); |
| 13209 | } |
| 13210 | |
| 13211 | // aten::linalg_matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) |
| 13212 | at::Tensor & linalg_matrix_power_out::call(const at::Tensor & self, int64_t n, at::Tensor & out) { |
| 13213 | |
| 13214 | static auto op = create_linalg_matrix_power_out_typed_handle(); |
| 13215 | return op.call(self, n, out); |
| 13216 | } |
| 13217 | |
| 13218 | // aten::linalg_matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) |
| 13219 | at::Tensor & linalg_matrix_power_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n, at::Tensor & out) { |
| 13220 | |
| 13221 | static auto op = create_linalg_matrix_power_out_typed_handle(); |
| 13222 | return op.redispatch(dispatchKeySet, self, n, out); |
| 13223 | } |
| 13224 | |
| 13225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_serialization_subcmul, name, "aten::_test_serialization_subcmul") |
| 13226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_serialization_subcmul, overload_name, "") |
| 13227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_serialization_subcmul, schema_str, "_test_serialization_subcmul(Tensor self, Tensor other, Scalar alpha=1) -> Tensor") |
| 13228 | |
| 13229 | // aten::_test_serialization_subcmul(Tensor self, Tensor other, Scalar alpha=1) -> Tensor |
| 13230 | static C10_NOINLINE c10::TypedOperatorHandle<_test_serialization_subcmul::schema> create__test_serialization_subcmul_typed_handle() { |
| 13231 | return c10::Dispatcher::singleton() |
| 13232 | .findSchemaOrThrow(_test_serialization_subcmul::name, _test_serialization_subcmul::overload_name) |
| 13233 | .typed<_test_serialization_subcmul::schema>(); |
| 13234 | } |
| 13235 | |
| 13236 | // aten::_test_serialization_subcmul(Tensor self, Tensor other, Scalar alpha=1) -> Tensor |
| 13237 | at::Tensor _test_serialization_subcmul::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 13238 | |
| 13239 | static auto op = create__test_serialization_subcmul_typed_handle(); |
| 13240 | return op.call(self, other, alpha); |
| 13241 | } |
| 13242 | |
| 13243 | // aten::_test_serialization_subcmul(Tensor self, Tensor other, Scalar alpha=1) -> Tensor |
| 13244 | at::Tensor _test_serialization_subcmul::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 13245 | |
| 13246 | static auto op = create__test_serialization_subcmul_typed_handle(); |
| 13247 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 13248 | } |
| 13249 | |
| 13250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_intlist, name, "aten::_test_optional_intlist") |
| 13251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_intlist, overload_name, "") |
| 13252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_intlist, schema_str, "_test_optional_intlist(Tensor values, int[]? addends) -> Tensor") |
| 13253 | |
| 13254 | // aten::_test_optional_intlist(Tensor values, int[]? addends) -> Tensor |
| 13255 | static C10_NOINLINE c10::TypedOperatorHandle<_test_optional_intlist::schema> create__test_optional_intlist_typed_handle() { |
| 13256 | return c10::Dispatcher::singleton() |
| 13257 | .findSchemaOrThrow(_test_optional_intlist::name, _test_optional_intlist::overload_name) |
| 13258 | .typed<_test_optional_intlist::schema>(); |
| 13259 | } |
| 13260 | |
| 13261 | // aten::_test_optional_intlist(Tensor values, int[]? addends) -> Tensor |
| 13262 | at::Tensor _test_optional_intlist::call(const at::Tensor & values, at::OptionalIntArrayRef addends) { |
| 13263 | |
| 13264 | static auto op = create__test_optional_intlist_typed_handle(); |
| 13265 | return op.call(values, addends); |
| 13266 | } |
| 13267 | |
| 13268 | // aten::_test_optional_intlist(Tensor values, int[]? addends) -> Tensor |
| 13269 | at::Tensor _test_optional_intlist::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & values, at::OptionalIntArrayRef addends) { |
| 13270 | |
| 13271 | static auto op = create__test_optional_intlist_typed_handle(); |
| 13272 | return op.redispatch(dispatchKeySet, values, addends); |
| 13273 | } |
| 13274 | |
| 13275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_ambiguous_defaults_a, name, "aten::_test_ambiguous_defaults") |
| 13276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_ambiguous_defaults_a, overload_name, "a") |
| 13277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_ambiguous_defaults_a, schema_str, "_test_ambiguous_defaults.a(Tensor dummy, int a=1, int b=1) -> Tensor") |
| 13278 | |
| 13279 | // aten::_test_ambiguous_defaults.a(Tensor dummy, int a=1, int b=1) -> Tensor |
| 13280 | static C10_NOINLINE c10::TypedOperatorHandle<_test_ambiguous_defaults_a::schema> create__test_ambiguous_defaults_a_typed_handle() { |
| 13281 | return c10::Dispatcher::singleton() |
| 13282 | .findSchemaOrThrow(_test_ambiguous_defaults_a::name, _test_ambiguous_defaults_a::overload_name) |
| 13283 | .typed<_test_ambiguous_defaults_a::schema>(); |
| 13284 | } |
| 13285 | |
| 13286 | // aten::_test_ambiguous_defaults.a(Tensor dummy, int a=1, int b=1) -> Tensor |
| 13287 | at::Tensor _test_ambiguous_defaults_a::call(const at::Tensor & dummy, int64_t a, int64_t b) { |
| 13288 | |
| 13289 | static auto op = create__test_ambiguous_defaults_a_typed_handle(); |
| 13290 | return op.call(dummy, a, b); |
| 13291 | } |
| 13292 | |
| 13293 | // aten::_test_ambiguous_defaults.a(Tensor dummy, int a=1, int b=1) -> Tensor |
| 13294 | at::Tensor _test_ambiguous_defaults_a::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & dummy, int64_t a, int64_t b) { |
| 13295 | |
| 13296 | static auto op = create__test_ambiguous_defaults_a_typed_handle(); |
| 13297 | return op.redispatch(dispatchKeySet, dummy, a, b); |
| 13298 | } |
| 13299 | |
| 13300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_ambiguous_defaults_b, name, "aten::_test_ambiguous_defaults") |
| 13301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_ambiguous_defaults_b, overload_name, "b") |
| 13302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_ambiguous_defaults_b, schema_str, "_test_ambiguous_defaults.b(Tensor dummy, int a=2, str b=\"2\") -> Tensor") |
| 13303 | |
| 13304 | // aten::_test_ambiguous_defaults.b(Tensor dummy, int a=2, str b="2") -> Tensor |
| 13305 | static C10_NOINLINE c10::TypedOperatorHandle<_test_ambiguous_defaults_b::schema> create__test_ambiguous_defaults_b_typed_handle() { |
| 13306 | return c10::Dispatcher::singleton() |
| 13307 | .findSchemaOrThrow(_test_ambiguous_defaults_b::name, _test_ambiguous_defaults_b::overload_name) |
| 13308 | .typed<_test_ambiguous_defaults_b::schema>(); |
| 13309 | } |
| 13310 | |
| 13311 | // aten::_test_ambiguous_defaults.b(Tensor dummy, int a=2, str b="2") -> Tensor |
| 13312 | at::Tensor _test_ambiguous_defaults_b::call(const at::Tensor & dummy, int64_t a, c10::string_view b) { |
| 13313 | |
| 13314 | static auto op = create__test_ambiguous_defaults_b_typed_handle(); |
| 13315 | return op.call(dummy, a, b); |
| 13316 | } |
| 13317 | |
| 13318 | // aten::_test_ambiguous_defaults.b(Tensor dummy, int a=2, str b="2") -> Tensor |
| 13319 | at::Tensor _test_ambiguous_defaults_b::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & dummy, int64_t a, c10::string_view b) { |
| 13320 | |
| 13321 | static auto op = create__test_ambiguous_defaults_b_typed_handle(); |
| 13322 | return op.redispatch(dispatchKeySet, dummy, a, b); |
| 13323 | } |
| 13324 | |
| 13325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_fullcoverage, name, "aten::_test_autograd_multiple_dispatch") |
| 13326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_fullcoverage, overload_name, "fullcoverage") |
| 13327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_fullcoverage, schema_str, "_test_autograd_multiple_dispatch.fullcoverage(Tensor self) -> Tensor") |
| 13328 | |
| 13329 | // aten::_test_autograd_multiple_dispatch.fullcoverage(Tensor self) -> Tensor |
| 13330 | static C10_NOINLINE c10::TypedOperatorHandle<_test_autograd_multiple_dispatch_fullcoverage::schema> create__test_autograd_multiple_dispatch_fullcoverage_typed_handle() { |
| 13331 | return c10::Dispatcher::singleton() |
| 13332 | .findSchemaOrThrow(_test_autograd_multiple_dispatch_fullcoverage::name, _test_autograd_multiple_dispatch_fullcoverage::overload_name) |
| 13333 | .typed<_test_autograd_multiple_dispatch_fullcoverage::schema>(); |
| 13334 | } |
| 13335 | |
| 13336 | // aten::_test_autograd_multiple_dispatch.fullcoverage(Tensor self) -> Tensor |
| 13337 | at::Tensor _test_autograd_multiple_dispatch_fullcoverage::call(const at::Tensor & self) { |
| 13338 | |
| 13339 | static auto op = create__test_autograd_multiple_dispatch_fullcoverage_typed_handle(); |
| 13340 | return op.call(self); |
| 13341 | } |
| 13342 | |
| 13343 | // aten::_test_autograd_multiple_dispatch.fullcoverage(Tensor self) -> Tensor |
| 13344 | at::Tensor _test_autograd_multiple_dispatch_fullcoverage::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 13345 | |
| 13346 | static auto op = create__test_autograd_multiple_dispatch_fullcoverage_typed_handle(); |
| 13347 | return op.redispatch(dispatchKeySet, self); |
| 13348 | } |
| 13349 | |
| 13350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_ntonly, name, "aten::_test_autograd_multiple_dispatch") |
| 13351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_ntonly, overload_name, "ntonly") |
| 13352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_ntonly, schema_str, "_test_autograd_multiple_dispatch.ntonly(Tensor self, bool b) -> Tensor") |
| 13353 | |
| 13354 | // aten::_test_autograd_multiple_dispatch.ntonly(Tensor self, bool b) -> Tensor |
| 13355 | static C10_NOINLINE c10::TypedOperatorHandle<_test_autograd_multiple_dispatch_ntonly::schema> create__test_autograd_multiple_dispatch_ntonly_typed_handle() { |
| 13356 | return c10::Dispatcher::singleton() |
| 13357 | .findSchemaOrThrow(_test_autograd_multiple_dispatch_ntonly::name, _test_autograd_multiple_dispatch_ntonly::overload_name) |
| 13358 | .typed<_test_autograd_multiple_dispatch_ntonly::schema>(); |
| 13359 | } |
| 13360 | |
| 13361 | // aten::_test_autograd_multiple_dispatch.ntonly(Tensor self, bool b) -> Tensor |
| 13362 | at::Tensor _test_autograd_multiple_dispatch_ntonly::call(const at::Tensor & self, bool b) { |
| 13363 | |
| 13364 | static auto op = create__test_autograd_multiple_dispatch_ntonly_typed_handle(); |
| 13365 | return op.call(self, b); |
| 13366 | } |
| 13367 | |
| 13368 | // aten::_test_autograd_multiple_dispatch.ntonly(Tensor self, bool b) -> Tensor |
| 13369 | at::Tensor _test_autograd_multiple_dispatch_ntonly::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool b) { |
| 13370 | |
| 13371 | static auto op = create__test_autograd_multiple_dispatch_ntonly_typed_handle(); |
| 13372 | return op.redispatch(dispatchKeySet, self, b); |
| 13373 | } |
| 13374 | |
| 13375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(segment_reduce, name, "aten::segment_reduce") |
| 13376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(segment_reduce, overload_name, "") |
| 13377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(segment_reduce, schema_str, "segment_reduce(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None) -> Tensor") |
| 13378 | |
| 13379 | // aten::segment_reduce(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None) -> Tensor |
| 13380 | static C10_NOINLINE c10::TypedOperatorHandle<segment_reduce::schema> create_segment_reduce_typed_handle() { |
| 13381 | return c10::Dispatcher::singleton() |
| 13382 | .findSchemaOrThrow(segment_reduce::name, segment_reduce::overload_name) |
| 13383 | .typed<segment_reduce::schema>(); |
| 13384 | } |
| 13385 | |
| 13386 | // aten::segment_reduce(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None) -> Tensor |
| 13387 | at::Tensor segment_reduce::call(const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & indices, const c10::optional<at::Tensor> & offsets, int64_t axis, bool unsafe, const c10::optional<at::Scalar> & initial) { |
| 13388 | |
| 13389 | static auto op = create_segment_reduce_typed_handle(); |
| 13390 | return op.call(data, reduce, lengths, indices, offsets, axis, unsafe, initial); |
| 13391 | } |
| 13392 | |
| 13393 | // aten::segment_reduce(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None) -> Tensor |
| 13394 | at::Tensor segment_reduce::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & indices, const c10::optional<at::Tensor> & offsets, int64_t axis, bool unsafe, const c10::optional<at::Scalar> & initial) { |
| 13395 | |
| 13396 | static auto op = create_segment_reduce_typed_handle(); |
| 13397 | return op.redispatch(dispatchKeySet, data, reduce, lengths, indices, offsets, axis, unsafe, initial); |
| 13398 | } |
| 13399 | |
| 13400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_segment_reduce_backward, name, "aten::_segment_reduce_backward") |
| 13401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_segment_reduce_backward, overload_name, "") |
| 13402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_segment_reduce_backward, schema_str, "_segment_reduce_backward(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None) -> Tensor") |
| 13403 | |
| 13404 | // aten::_segment_reduce_backward(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None) -> Tensor |
| 13405 | static C10_NOINLINE c10::TypedOperatorHandle<_segment_reduce_backward::schema> create__segment_reduce_backward_typed_handle() { |
| 13406 | return c10::Dispatcher::singleton() |
| 13407 | .findSchemaOrThrow(_segment_reduce_backward::name, _segment_reduce_backward::overload_name) |
| 13408 | .typed<_segment_reduce_backward::schema>(); |
| 13409 | } |
| 13410 | |
| 13411 | // aten::_segment_reduce_backward(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None) -> Tensor |
| 13412 | at::Tensor _segment_reduce_backward::call(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & offsets, int64_t axis, const c10::optional<at::Scalar> & initial) { |
| 13413 | |
| 13414 | static auto op = create__segment_reduce_backward_typed_handle(); |
| 13415 | return op.call(grad, output, data, reduce, lengths, offsets, axis, initial); |
| 13416 | } |
| 13417 | |
| 13418 | // aten::_segment_reduce_backward(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None) -> Tensor |
| 13419 | at::Tensor _segment_reduce_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & offsets, int64_t axis, const c10::optional<at::Scalar> & initial) { |
| 13420 | |
| 13421 | static auto op = create__segment_reduce_backward_typed_handle(); |
| 13422 | return op.redispatch(dispatchKeySet, grad, output, data, reduce, lengths, offsets, axis, initial); |
| 13423 | } |
| 13424 | |
| 13425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_dual_copy, name, "aten::_make_dual_copy") |
| 13426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_dual_copy, overload_name, "") |
| 13427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_dual_copy, schema_str, "_make_dual_copy(Tensor primal, Tensor tangent, int level) -> Tensor") |
| 13428 | |
| 13429 | // aten::_make_dual_copy(Tensor primal, Tensor tangent, int level) -> Tensor |
| 13430 | static C10_NOINLINE c10::TypedOperatorHandle<_make_dual_copy::schema> create__make_dual_copy_typed_handle() { |
| 13431 | return c10::Dispatcher::singleton() |
| 13432 | .findSchemaOrThrow(_make_dual_copy::name, _make_dual_copy::overload_name) |
| 13433 | .typed<_make_dual_copy::schema>(); |
| 13434 | } |
| 13435 | |
| 13436 | // aten::_make_dual_copy(Tensor primal, Tensor tangent, int level) -> Tensor |
| 13437 | at::Tensor _make_dual_copy::call(const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { |
| 13438 | |
| 13439 | static auto op = create__make_dual_copy_typed_handle(); |
| 13440 | return op.call(primal, tangent, level); |
| 13441 | } |
| 13442 | |
| 13443 | // aten::_make_dual_copy(Tensor primal, Tensor tangent, int level) -> Tensor |
| 13444 | at::Tensor _make_dual_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & primal, const at::Tensor & tangent, int64_t level) { |
| 13445 | |
| 13446 | static auto op = create__make_dual_copy_typed_handle(); |
| 13447 | return op.redispatch(dispatchKeySet, primal, tangent, level); |
| 13448 | } |
| 13449 | |
| 13450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex_copy, name, "aten::view_as_complex_copy") |
| 13451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex_copy, overload_name, "") |
| 13452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex_copy, schema_str, "view_as_complex_copy(Tensor self) -> Tensor") |
| 13453 | |
| 13454 | // aten::view_as_complex_copy(Tensor self) -> Tensor |
| 13455 | static C10_NOINLINE c10::TypedOperatorHandle<view_as_complex_copy::schema> create_view_as_complex_copy_typed_handle() { |
| 13456 | return c10::Dispatcher::singleton() |
| 13457 | .findSchemaOrThrow(view_as_complex_copy::name, view_as_complex_copy::overload_name) |
| 13458 | .typed<view_as_complex_copy::schema>(); |
| 13459 | } |
| 13460 | |
| 13461 | // aten::view_as_complex_copy(Tensor self) -> Tensor |
| 13462 | at::Tensor view_as_complex_copy::call(const at::Tensor & self) { |
| 13463 | |
| 13464 | static auto op = create_view_as_complex_copy_typed_handle(); |
| 13465 | return op.call(self); |
| 13466 | } |
| 13467 | |
| 13468 | // aten::view_as_complex_copy(Tensor self) -> Tensor |
| 13469 | at::Tensor view_as_complex_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 13470 | |
| 13471 | static auto op = create_view_as_complex_copy_typed_handle(); |
| 13472 | return op.redispatch(dispatchKeySet, self); |
| 13473 | } |
| 13474 | |
| 13475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view_copy, name, "aten::_neg_view_copy") |
| 13476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view_copy, overload_name, "") |
| 13477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view_copy, schema_str, "_neg_view_copy(Tensor self) -> Tensor") |
| 13478 | |
| 13479 | // aten::_neg_view_copy(Tensor self) -> Tensor |
| 13480 | static C10_NOINLINE c10::TypedOperatorHandle<_neg_view_copy::schema> create__neg_view_copy_typed_handle() { |
| 13481 | return c10::Dispatcher::singleton() |
| 13482 | .findSchemaOrThrow(_neg_view_copy::name, _neg_view_copy::overload_name) |
| 13483 | .typed<_neg_view_copy::schema>(); |
| 13484 | } |
| 13485 | |
| 13486 | // aten::_neg_view_copy(Tensor self) -> Tensor |
| 13487 | at::Tensor _neg_view_copy::call(const at::Tensor & self) { |
| 13488 | |
| 13489 | static auto op = create__neg_view_copy_typed_handle(); |
| 13490 | return op.call(self); |
| 13491 | } |
| 13492 | |
| 13493 | // aten::_neg_view_copy(Tensor self) -> Tensor |
| 13494 | at::Tensor _neg_view_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 13495 | |
| 13496 | static auto op = create__neg_view_copy_typed_handle(); |
| 13497 | return op.redispatch(dispatchKeySet, self); |
| 13498 | } |
| 13499 | |
| 13500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_copy, name, "aten::expand_copy") |
| 13501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_copy, overload_name, "") |
| 13502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_copy, schema_str, "expand_copy(Tensor self, SymInt[] size, *, bool implicit=False) -> Tensor") |
| 13503 | |
| 13504 | // aten::expand_copy(Tensor self, SymInt[] size, *, bool implicit=False) -> Tensor |
| 13505 | static C10_NOINLINE c10::TypedOperatorHandle<expand_copy::schema> create_expand_copy_typed_handle() { |
| 13506 | return c10::Dispatcher::singleton() |
| 13507 | .findSchemaOrThrow(expand_copy::name, expand_copy::overload_name) |
| 13508 | .typed<expand_copy::schema>(); |
| 13509 | } |
| 13510 | |
| 13511 | // aten::expand_copy(Tensor self, SymInt[] size, *, bool implicit=False) -> Tensor |
| 13512 | at::Tensor expand_copy::call(const at::Tensor & self, c10::SymIntArrayRef size, bool implicit) { |
| 13513 | |
| 13514 | static auto op = create_expand_copy_typed_handle(); |
| 13515 | return op.call(self, size, implicit); |
| 13516 | } |
| 13517 | |
| 13518 | // aten::expand_copy(Tensor self, SymInt[] size, *, bool implicit=False) -> Tensor |
| 13519 | at::Tensor expand_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, bool implicit) { |
| 13520 | |
| 13521 | static auto op = create_expand_copy_typed_handle(); |
| 13522 | return op.redispatch(dispatchKeySet, self, size, implicit); |
| 13523 | } |
| 13524 | |
| 13525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_copy, name, "aten::unsqueeze_copy") |
| 13526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_copy, overload_name, "") |
| 13527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_copy, schema_str, "unsqueeze_copy(Tensor self, int dim) -> Tensor") |
| 13528 | |
| 13529 | // aten::unsqueeze_copy(Tensor self, int dim) -> Tensor |
| 13530 | static C10_NOINLINE c10::TypedOperatorHandle<unsqueeze_copy::schema> create_unsqueeze_copy_typed_handle() { |
| 13531 | return c10::Dispatcher::singleton() |
| 13532 | .findSchemaOrThrow(unsqueeze_copy::name, unsqueeze_copy::overload_name) |
| 13533 | .typed<unsqueeze_copy::schema>(); |
| 13534 | } |
| 13535 | |
| 13536 | // aten::unsqueeze_copy(Tensor self, int dim) -> Tensor |
| 13537 | at::Tensor unsqueeze_copy::call(const at::Tensor & self, int64_t dim) { |
| 13538 | |
| 13539 | static auto op = create_unsqueeze_copy_typed_handle(); |
| 13540 | return op.call(self, dim); |
| 13541 | } |
| 13542 | |
| 13543 | // aten::unsqueeze_copy(Tensor self, int dim) -> Tensor |
| 13544 | at::Tensor unsqueeze_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim) { |
| 13545 | |
| 13546 | static auto op = create_unsqueeze_copy_typed_handle(); |
| 13547 | return op.redispatch(dispatchKeySet, self, dim); |
| 13548 | } |
| 13549 | |
| 13550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(crow_indices_copy, name, "aten::crow_indices_copy") |
| 13551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(crow_indices_copy, overload_name, "") |
| 13552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(crow_indices_copy, schema_str, "crow_indices_copy(Tensor self) -> Tensor") |
| 13553 | |
| 13554 | // aten::crow_indices_copy(Tensor self) -> Tensor |
| 13555 | static C10_NOINLINE c10::TypedOperatorHandle<crow_indices_copy::schema> create_crow_indices_copy_typed_handle() { |
| 13556 | return c10::Dispatcher::singleton() |
| 13557 | .findSchemaOrThrow(crow_indices_copy::name, crow_indices_copy::overload_name) |
| 13558 | .typed<crow_indices_copy::schema>(); |
| 13559 | } |
| 13560 | |
| 13561 | // aten::crow_indices_copy(Tensor self) -> Tensor |
| 13562 | at::Tensor crow_indices_copy::call(const at::Tensor & self) { |
| 13563 | |
| 13564 | static auto op = create_crow_indices_copy_typed_handle(); |
| 13565 | return op.call(self); |
| 13566 | } |
| 13567 | |
| 13568 | // aten::crow_indices_copy(Tensor self) -> Tensor |
| 13569 | at::Tensor crow_indices_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 13570 | |
| 13571 | static auto op = create_crow_indices_copy_typed_handle(); |
| 13572 | return op.redispatch(dispatchKeySet, self); |
| 13573 | } |
| 13574 | |
| 13575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_padded_tensor, name, "aten::to_padded_tensor") |
| 13576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_padded_tensor, overload_name, "") |
| 13577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_padded_tensor, schema_str, "to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor") |
| 13578 | |
| 13579 | // aten::to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor |
| 13580 | static C10_NOINLINE c10::TypedOperatorHandle<to_padded_tensor::schema> create_to_padded_tensor_typed_handle() { |
| 13581 | return c10::Dispatcher::singleton() |
| 13582 | .findSchemaOrThrow(to_padded_tensor::name, to_padded_tensor::overload_name) |
| 13583 | .typed<to_padded_tensor::schema>(); |
| 13584 | } |
| 13585 | |
| 13586 | // aten::to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor |
| 13587 | at::Tensor to_padded_tensor::call(const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size) { |
| 13588 | |
| 13589 | static auto op = create_to_padded_tensor_typed_handle(); |
| 13590 | return op.call(self, padding, output_size); |
| 13591 | } |
| 13592 | |
| 13593 | // aten::to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor |
| 13594 | at::Tensor to_padded_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size) { |
| 13595 | |
| 13596 | static auto op = create_to_padded_tensor_typed_handle(); |
| 13597 | return op.redispatch(dispatchKeySet, self, padding, output_size); |
| 13598 | } |
| 13599 | |
| 13600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_softmax_with_shape, name, "aten::_nested_tensor_softmax_with_shape") |
| 13601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_softmax_with_shape, overload_name, "") |
| 13602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_softmax_with_shape, schema_str, "_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor") |
| 13603 | |
| 13604 | // aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor |
| 13605 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_softmax_with_shape::schema> create__nested_tensor_softmax_with_shape_typed_handle() { |
| 13606 | return c10::Dispatcher::singleton() |
| 13607 | .findSchemaOrThrow(_nested_tensor_softmax_with_shape::name, _nested_tensor_softmax_with_shape::overload_name) |
| 13608 | .typed<_nested_tensor_softmax_with_shape::schema>(); |
| 13609 | } |
| 13610 | |
| 13611 | // aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor |
| 13612 | at::Tensor _nested_tensor_softmax_with_shape::call(const at::Tensor & self, const at::Tensor & query) { |
| 13613 | |
| 13614 | static auto op = create__nested_tensor_softmax_with_shape_typed_handle(); |
| 13615 | return op.call(self, query); |
| 13616 | } |
| 13617 | |
| 13618 | // aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor |
| 13619 | at::Tensor _nested_tensor_softmax_with_shape::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & query) { |
| 13620 | |
| 13621 | static auto op = create__nested_tensor_softmax_with_shape_typed_handle(); |
| 13622 | return op.redispatch(dispatchKeySet, self, query); |
| 13623 | } |
| 13624 | |
| 13625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_flash_attention_forward, name, "aten::_flash_attention_forward") |
| 13626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_flash_attention_forward, overload_name, "") |
| 13627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_flash_attention_forward, schema_str, "_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask)") |
| 13628 | |
| 13629 | // aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask) |
| 13630 | static C10_NOINLINE c10::TypedOperatorHandle<_flash_attention_forward::schema> create__flash_attention_forward_typed_handle() { |
| 13631 | return c10::Dispatcher::singleton() |
| 13632 | .findSchemaOrThrow(_flash_attention_forward::name, _flash_attention_forward::overload_name) |
| 13633 | .typed<_flash_attention_forward::schema>(); |
| 13634 | } |
| 13635 | |
| 13636 | // aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask) |
| 13637 | ::std::tuple<at::Tensor,at::Tensor,int64_t,int64_t,at::Tensor> _flash_attention_forward::call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, bool return_debug_mask) { |
| 13638 | |
| 13639 | static auto op = create__flash_attention_forward_typed_handle(); |
| 13640 | return op.call(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask); |
| 13641 | } |
| 13642 | |
| 13643 | // aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask) |
| 13644 | ::std::tuple<at::Tensor,at::Tensor,int64_t,int64_t,at::Tensor> _flash_attention_forward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & cum_seq_q, const at::Tensor & cum_seq_k, int64_t max_q, int64_t max_k, double dropout_p, bool is_causal, bool return_debug_mask) { |
| 13645 | |
| 13646 | static auto op = create__flash_attention_forward_typed_handle(); |
| 13647 | return op.redispatch(dispatchKeySet, query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask); |
| 13648 | } |
| 13649 | |
| 13650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_j0, name, "aten::special_bessel_j0") |
| 13651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_j0, overload_name, "") |
| 13652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_j0, schema_str, "special_bessel_j0(Tensor self) -> Tensor") |
| 13653 | |
| 13654 | // aten::special_bessel_j0(Tensor self) -> Tensor |
| 13655 | static C10_NOINLINE c10::TypedOperatorHandle<special_bessel_j0::schema> create_special_bessel_j0_typed_handle() { |
| 13656 | return c10::Dispatcher::singleton() |
| 13657 | .findSchemaOrThrow(special_bessel_j0::name, special_bessel_j0::overload_name) |
| 13658 | .typed<special_bessel_j0::schema>(); |
| 13659 | } |
| 13660 | |
| 13661 | // aten::special_bessel_j0(Tensor self) -> Tensor |
| 13662 | at::Tensor special_bessel_j0::call(const at::Tensor & self) { |
| 13663 | |
| 13664 | static auto op = create_special_bessel_j0_typed_handle(); |
| 13665 | return op.call(self); |
| 13666 | } |
| 13667 | |
| 13668 | // aten::special_bessel_j0(Tensor self) -> Tensor |
| 13669 | at::Tensor special_bessel_j0::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 13670 | |
| 13671 | static auto op = create_special_bessel_j0_typed_handle(); |
| 13672 | return op.redispatch(dispatchKeySet, self); |
| 13673 | } |
| 13674 | |
| 13675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_j0_out, name, "aten::special_bessel_j0") |
| 13676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_j0_out, overload_name, "out") |
| 13677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_j0_out, schema_str, "special_bessel_j0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 13678 | |
| 13679 | // aten::special_bessel_j0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13680 | static C10_NOINLINE c10::TypedOperatorHandle<special_bessel_j0_out::schema> create_special_bessel_j0_out_typed_handle() { |
| 13681 | return c10::Dispatcher::singleton() |
| 13682 | .findSchemaOrThrow(special_bessel_j0_out::name, special_bessel_j0_out::overload_name) |
| 13683 | .typed<special_bessel_j0_out::schema>(); |
| 13684 | } |
| 13685 | |
| 13686 | // aten::special_bessel_j0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13687 | at::Tensor & special_bessel_j0_out::call(const at::Tensor & self, at::Tensor & out) { |
| 13688 | |
| 13689 | static auto op = create_special_bessel_j0_out_typed_handle(); |
| 13690 | return op.call(self, out); |
| 13691 | } |
| 13692 | |
| 13693 | // aten::special_bessel_j0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13694 | at::Tensor & special_bessel_j0_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 13695 | |
| 13696 | static auto op = create_special_bessel_j0_out_typed_handle(); |
| 13697 | return op.redispatch(dispatchKeySet, self, out); |
| 13698 | } |
| 13699 | |
| 13700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y0, name, "aten::special_bessel_y0") |
| 13701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y0, overload_name, "") |
| 13702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y0, schema_str, "special_bessel_y0(Tensor self) -> Tensor") |
| 13703 | |
| 13704 | // aten::special_bessel_y0(Tensor self) -> Tensor |
| 13705 | static C10_NOINLINE c10::TypedOperatorHandle<special_bessel_y0::schema> create_special_bessel_y0_typed_handle() { |
| 13706 | return c10::Dispatcher::singleton() |
| 13707 | .findSchemaOrThrow(special_bessel_y0::name, special_bessel_y0::overload_name) |
| 13708 | .typed<special_bessel_y0::schema>(); |
| 13709 | } |
| 13710 | |
| 13711 | // aten::special_bessel_y0(Tensor self) -> Tensor |
| 13712 | at::Tensor special_bessel_y0::call(const at::Tensor & self) { |
| 13713 | |
| 13714 | static auto op = create_special_bessel_y0_typed_handle(); |
| 13715 | return op.call(self); |
| 13716 | } |
| 13717 | |
| 13718 | // aten::special_bessel_y0(Tensor self) -> Tensor |
| 13719 | at::Tensor special_bessel_y0::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 13720 | |
| 13721 | static auto op = create_special_bessel_y0_typed_handle(); |
| 13722 | return op.redispatch(dispatchKeySet, self); |
| 13723 | } |
| 13724 | |
| 13725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y0_out, name, "aten::special_bessel_y0") |
| 13726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y0_out, overload_name, "out") |
| 13727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y0_out, schema_str, "special_bessel_y0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 13728 | |
| 13729 | // aten::special_bessel_y0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13730 | static C10_NOINLINE c10::TypedOperatorHandle<special_bessel_y0_out::schema> create_special_bessel_y0_out_typed_handle() { |
| 13731 | return c10::Dispatcher::singleton() |
| 13732 | .findSchemaOrThrow(special_bessel_y0_out::name, special_bessel_y0_out::overload_name) |
| 13733 | .typed<special_bessel_y0_out::schema>(); |
| 13734 | } |
| 13735 | |
| 13736 | // aten::special_bessel_y0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13737 | at::Tensor & special_bessel_y0_out::call(const at::Tensor & self, at::Tensor & out) { |
| 13738 | |
| 13739 | static auto op = create_special_bessel_y0_out_typed_handle(); |
| 13740 | return op.call(self, out); |
| 13741 | } |
| 13742 | |
| 13743 | // aten::special_bessel_y0.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13744 | at::Tensor & special_bessel_y0_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 13745 | |
| 13746 | static auto op = create_special_bessel_y0_out_typed_handle(); |
| 13747 | return op.redispatch(dispatchKeySet, self, out); |
| 13748 | } |
| 13749 | |
| 13750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u, name, "aten::special_chebyshev_polynomial_u") |
| 13751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u, overload_name, "") |
| 13752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u, schema_str, "special_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor") |
| 13753 | |
| 13754 | // aten::special_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor |
| 13755 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_u::schema> create_special_chebyshev_polynomial_u_typed_handle() { |
| 13756 | return c10::Dispatcher::singleton() |
| 13757 | .findSchemaOrThrow(special_chebyshev_polynomial_u::name, special_chebyshev_polynomial_u::overload_name) |
| 13758 | .typed<special_chebyshev_polynomial_u::schema>(); |
| 13759 | } |
| 13760 | |
| 13761 | // aten::special_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor |
| 13762 | at::Tensor special_chebyshev_polynomial_u::call(const at::Tensor & x, const at::Tensor & n) { |
| 13763 | |
| 13764 | static auto op = create_special_chebyshev_polynomial_u_typed_handle(); |
| 13765 | return op.call(x, n); |
| 13766 | } |
| 13767 | |
| 13768 | // aten::special_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor |
| 13769 | at::Tensor special_chebyshev_polynomial_u::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
| 13770 | |
| 13771 | static auto op = create_special_chebyshev_polynomial_u_typed_handle(); |
| 13772 | return op.redispatch(dispatchKeySet, x, n); |
| 13773 | } |
| 13774 | |
| 13775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_x_scalar, name, "aten::special_chebyshev_polynomial_u") |
| 13776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_x_scalar, overload_name, "x_scalar") |
| 13777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_x_scalar, schema_str, "special_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor") |
| 13778 | |
| 13779 | // aten::special_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor |
| 13780 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_u_x_scalar::schema> create_special_chebyshev_polynomial_u_x_scalar_typed_handle() { |
| 13781 | return c10::Dispatcher::singleton() |
| 13782 | .findSchemaOrThrow(special_chebyshev_polynomial_u_x_scalar::name, special_chebyshev_polynomial_u_x_scalar::overload_name) |
| 13783 | .typed<special_chebyshev_polynomial_u_x_scalar::schema>(); |
| 13784 | } |
| 13785 | |
| 13786 | // aten::special_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor |
| 13787 | at::Tensor special_chebyshev_polynomial_u_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
| 13788 | |
| 13789 | static auto op = create_special_chebyshev_polynomial_u_x_scalar_typed_handle(); |
| 13790 | return op.call(x, n); |
| 13791 | } |
| 13792 | |
| 13793 | // aten::special_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor |
| 13794 | at::Tensor special_chebyshev_polynomial_u_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
| 13795 | |
| 13796 | static auto op = create_special_chebyshev_polynomial_u_x_scalar_typed_handle(); |
| 13797 | return op.redispatch(dispatchKeySet, x, n); |
| 13798 | } |
| 13799 | |
| 13800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_n_scalar, name, "aten::special_chebyshev_polynomial_u") |
| 13801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_n_scalar, overload_name, "n_scalar") |
| 13802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_n_scalar, schema_str, "special_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor") |
| 13803 | |
| 13804 | // aten::special_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor |
| 13805 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_u_n_scalar::schema> create_special_chebyshev_polynomial_u_n_scalar_typed_handle() { |
| 13806 | return c10::Dispatcher::singleton() |
| 13807 | .findSchemaOrThrow(special_chebyshev_polynomial_u_n_scalar::name, special_chebyshev_polynomial_u_n_scalar::overload_name) |
| 13808 | .typed<special_chebyshev_polynomial_u_n_scalar::schema>(); |
| 13809 | } |
| 13810 | |
| 13811 | // aten::special_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor |
| 13812 | at::Tensor special_chebyshev_polynomial_u_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
| 13813 | |
| 13814 | static auto op = create_special_chebyshev_polynomial_u_n_scalar_typed_handle(); |
| 13815 | return op.call(x, n); |
| 13816 | } |
| 13817 | |
| 13818 | // aten::special_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor |
| 13819 | at::Tensor special_chebyshev_polynomial_u_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
| 13820 | |
| 13821 | static auto op = create_special_chebyshev_polynomial_u_n_scalar_typed_handle(); |
| 13822 | return op.redispatch(dispatchKeySet, x, n); |
| 13823 | } |
| 13824 | |
| 13825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_out, name, "aten::special_chebyshev_polynomial_u") |
| 13826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_out, overload_name, "out") |
| 13827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_out, schema_str, "special_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 13828 | |
| 13829 | // aten::special_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13830 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_u_out::schema> create_special_chebyshev_polynomial_u_out_typed_handle() { |
| 13831 | return c10::Dispatcher::singleton() |
| 13832 | .findSchemaOrThrow(special_chebyshev_polynomial_u_out::name, special_chebyshev_polynomial_u_out::overload_name) |
| 13833 | .typed<special_chebyshev_polynomial_u_out::schema>(); |
| 13834 | } |
| 13835 | |
| 13836 | // aten::special_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13837 | at::Tensor & special_chebyshev_polynomial_u_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 13838 | |
| 13839 | static auto op = create_special_chebyshev_polynomial_u_out_typed_handle(); |
| 13840 | return op.call(x, n, out); |
| 13841 | } |
| 13842 | |
| 13843 | // aten::special_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13844 | at::Tensor & special_chebyshev_polynomial_u_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 13845 | |
| 13846 | static auto op = create_special_chebyshev_polynomial_u_out_typed_handle(); |
| 13847 | return op.redispatch(dispatchKeySet, x, n, out); |
| 13848 | } |
| 13849 | |
| 13850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_x_scalar_out, name, "aten::special_chebyshev_polynomial_u") |
| 13851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_x_scalar_out, overload_name, "x_scalar_out") |
| 13852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_x_scalar_out, schema_str, "special_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 13853 | |
| 13854 | // aten::special_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13855 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_u_x_scalar_out::schema> create_special_chebyshev_polynomial_u_x_scalar_out_typed_handle() { |
| 13856 | return c10::Dispatcher::singleton() |
| 13857 | .findSchemaOrThrow(special_chebyshev_polynomial_u_x_scalar_out::name, special_chebyshev_polynomial_u_x_scalar_out::overload_name) |
| 13858 | .typed<special_chebyshev_polynomial_u_x_scalar_out::schema>(); |
| 13859 | } |
| 13860 | |
| 13861 | // aten::special_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13862 | at::Tensor & special_chebyshev_polynomial_u_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 13863 | |
| 13864 | static auto op = create_special_chebyshev_polynomial_u_x_scalar_out_typed_handle(); |
| 13865 | return op.call(x, n, out); |
| 13866 | } |
| 13867 | |
| 13868 | // aten::special_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13869 | at::Tensor & special_chebyshev_polynomial_u_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 13870 | |
| 13871 | static auto op = create_special_chebyshev_polynomial_u_x_scalar_out_typed_handle(); |
| 13872 | return op.redispatch(dispatchKeySet, x, n, out); |
| 13873 | } |
| 13874 | |
| 13875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_n_scalar_out, name, "aten::special_chebyshev_polynomial_u") |
| 13876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_n_scalar_out, overload_name, "n_scalar_out") |
| 13877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_u_n_scalar_out, schema_str, "special_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") |
| 13878 | |
| 13879 | // aten::special_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 13880 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_u_n_scalar_out::schema> create_special_chebyshev_polynomial_u_n_scalar_out_typed_handle() { |
| 13881 | return c10::Dispatcher::singleton() |
| 13882 | .findSchemaOrThrow(special_chebyshev_polynomial_u_n_scalar_out::name, special_chebyshev_polynomial_u_n_scalar_out::overload_name) |
| 13883 | .typed<special_chebyshev_polynomial_u_n_scalar_out::schema>(); |
| 13884 | } |
| 13885 | |
| 13886 | // aten::special_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 13887 | at::Tensor & special_chebyshev_polynomial_u_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 13888 | |
| 13889 | static auto op = create_special_chebyshev_polynomial_u_n_scalar_out_typed_handle(); |
| 13890 | return op.call(x, n, out); |
| 13891 | } |
| 13892 | |
| 13893 | // aten::special_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 13894 | at::Tensor & special_chebyshev_polynomial_u_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 13895 | |
| 13896 | static auto op = create_special_chebyshev_polynomial_u_n_scalar_out_typed_handle(); |
| 13897 | return op.redispatch(dispatchKeySet, x, n, out); |
| 13898 | } |
| 13899 | |
| 13900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he, name, "aten::special_hermite_polynomial_he") |
| 13901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he, overload_name, "") |
| 13902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he, schema_str, "special_hermite_polynomial_he(Tensor x, Tensor n) -> Tensor") |
| 13903 | |
| 13904 | // aten::special_hermite_polynomial_he(Tensor x, Tensor n) -> Tensor |
| 13905 | static C10_NOINLINE c10::TypedOperatorHandle<special_hermite_polynomial_he::schema> create_special_hermite_polynomial_he_typed_handle() { |
| 13906 | return c10::Dispatcher::singleton() |
| 13907 | .findSchemaOrThrow(special_hermite_polynomial_he::name, special_hermite_polynomial_he::overload_name) |
| 13908 | .typed<special_hermite_polynomial_he::schema>(); |
| 13909 | } |
| 13910 | |
| 13911 | // aten::special_hermite_polynomial_he(Tensor x, Tensor n) -> Tensor |
| 13912 | at::Tensor special_hermite_polynomial_he::call(const at::Tensor & x, const at::Tensor & n) { |
| 13913 | |
| 13914 | static auto op = create_special_hermite_polynomial_he_typed_handle(); |
| 13915 | return op.call(x, n); |
| 13916 | } |
| 13917 | |
| 13918 | // aten::special_hermite_polynomial_he(Tensor x, Tensor n) -> Tensor |
| 13919 | at::Tensor special_hermite_polynomial_he::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
| 13920 | |
| 13921 | static auto op = create_special_hermite_polynomial_he_typed_handle(); |
| 13922 | return op.redispatch(dispatchKeySet, x, n); |
| 13923 | } |
| 13924 | |
| 13925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_x_scalar, name, "aten::special_hermite_polynomial_he") |
| 13926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_x_scalar, overload_name, "x_scalar") |
| 13927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_x_scalar, schema_str, "special_hermite_polynomial_he.x_scalar(Scalar x, Tensor n) -> Tensor") |
| 13928 | |
| 13929 | // aten::special_hermite_polynomial_he.x_scalar(Scalar x, Tensor n) -> Tensor |
| 13930 | static C10_NOINLINE c10::TypedOperatorHandle<special_hermite_polynomial_he_x_scalar::schema> create_special_hermite_polynomial_he_x_scalar_typed_handle() { |
| 13931 | return c10::Dispatcher::singleton() |
| 13932 | .findSchemaOrThrow(special_hermite_polynomial_he_x_scalar::name, special_hermite_polynomial_he_x_scalar::overload_name) |
| 13933 | .typed<special_hermite_polynomial_he_x_scalar::schema>(); |
| 13934 | } |
| 13935 | |
| 13936 | // aten::special_hermite_polynomial_he.x_scalar(Scalar x, Tensor n) -> Tensor |
| 13937 | at::Tensor special_hermite_polynomial_he_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
| 13938 | |
| 13939 | static auto op = create_special_hermite_polynomial_he_x_scalar_typed_handle(); |
| 13940 | return op.call(x, n); |
| 13941 | } |
| 13942 | |
| 13943 | // aten::special_hermite_polynomial_he.x_scalar(Scalar x, Tensor n) -> Tensor |
| 13944 | at::Tensor special_hermite_polynomial_he_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
| 13945 | |
| 13946 | static auto op = create_special_hermite_polynomial_he_x_scalar_typed_handle(); |
| 13947 | return op.redispatch(dispatchKeySet, x, n); |
| 13948 | } |
| 13949 | |
| 13950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_n_scalar, name, "aten::special_hermite_polynomial_he") |
| 13951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_n_scalar, overload_name, "n_scalar") |
| 13952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_n_scalar, schema_str, "special_hermite_polynomial_he.n_scalar(Tensor x, Scalar n) -> Tensor") |
| 13953 | |
| 13954 | // aten::special_hermite_polynomial_he.n_scalar(Tensor x, Scalar n) -> Tensor |
| 13955 | static C10_NOINLINE c10::TypedOperatorHandle<special_hermite_polynomial_he_n_scalar::schema> create_special_hermite_polynomial_he_n_scalar_typed_handle() { |
| 13956 | return c10::Dispatcher::singleton() |
| 13957 | .findSchemaOrThrow(special_hermite_polynomial_he_n_scalar::name, special_hermite_polynomial_he_n_scalar::overload_name) |
| 13958 | .typed<special_hermite_polynomial_he_n_scalar::schema>(); |
| 13959 | } |
| 13960 | |
| 13961 | // aten::special_hermite_polynomial_he.n_scalar(Tensor x, Scalar n) -> Tensor |
| 13962 | at::Tensor special_hermite_polynomial_he_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
| 13963 | |
| 13964 | static auto op = create_special_hermite_polynomial_he_n_scalar_typed_handle(); |
| 13965 | return op.call(x, n); |
| 13966 | } |
| 13967 | |
| 13968 | // aten::special_hermite_polynomial_he.n_scalar(Tensor x, Scalar n) -> Tensor |
| 13969 | at::Tensor special_hermite_polynomial_he_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
| 13970 | |
| 13971 | static auto op = create_special_hermite_polynomial_he_n_scalar_typed_handle(); |
| 13972 | return op.redispatch(dispatchKeySet, x, n); |
| 13973 | } |
| 13974 | |
| 13975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_out, name, "aten::special_hermite_polynomial_he") |
| 13976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_out, overload_name, "out") |
| 13977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_out, schema_str, "special_hermite_polynomial_he.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 13978 | |
| 13979 | // aten::special_hermite_polynomial_he.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13980 | static C10_NOINLINE c10::TypedOperatorHandle<special_hermite_polynomial_he_out::schema> create_special_hermite_polynomial_he_out_typed_handle() { |
| 13981 | return c10::Dispatcher::singleton() |
| 13982 | .findSchemaOrThrow(special_hermite_polynomial_he_out::name, special_hermite_polynomial_he_out::overload_name) |
| 13983 | .typed<special_hermite_polynomial_he_out::schema>(); |
| 13984 | } |
| 13985 | |
| 13986 | // aten::special_hermite_polynomial_he.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13987 | at::Tensor & special_hermite_polynomial_he_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 13988 | |
| 13989 | static auto op = create_special_hermite_polynomial_he_out_typed_handle(); |
| 13990 | return op.call(x, n, out); |
| 13991 | } |
| 13992 | |
| 13993 | // aten::special_hermite_polynomial_he.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 13994 | at::Tensor & special_hermite_polynomial_he_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 13995 | |
| 13996 | static auto op = create_special_hermite_polynomial_he_out_typed_handle(); |
| 13997 | return op.redispatch(dispatchKeySet, x, n, out); |
| 13998 | } |
| 13999 | |
| 14000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_x_scalar_out, name, "aten::special_hermite_polynomial_he") |
| 14001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_x_scalar_out, overload_name, "x_scalar_out") |
| 14002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_x_scalar_out, schema_str, "special_hermite_polynomial_he.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14003 | |
| 14004 | // aten::special_hermite_polynomial_he.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14005 | static C10_NOINLINE c10::TypedOperatorHandle<special_hermite_polynomial_he_x_scalar_out::schema> create_special_hermite_polynomial_he_x_scalar_out_typed_handle() { |
| 14006 | return c10::Dispatcher::singleton() |
| 14007 | .findSchemaOrThrow(special_hermite_polynomial_he_x_scalar_out::name, special_hermite_polynomial_he_x_scalar_out::overload_name) |
| 14008 | .typed<special_hermite_polynomial_he_x_scalar_out::schema>(); |
| 14009 | } |
| 14010 | |
| 14011 | // aten::special_hermite_polynomial_he.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14012 | at::Tensor & special_hermite_polynomial_he_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 14013 | |
| 14014 | static auto op = create_special_hermite_polynomial_he_x_scalar_out_typed_handle(); |
| 14015 | return op.call(x, n, out); |
| 14016 | } |
| 14017 | |
| 14018 | // aten::special_hermite_polynomial_he.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14019 | at::Tensor & special_hermite_polynomial_he_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 14020 | |
| 14021 | static auto op = create_special_hermite_polynomial_he_x_scalar_out_typed_handle(); |
| 14022 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14023 | } |
| 14024 | |
| 14025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_n_scalar_out, name, "aten::special_hermite_polynomial_he") |
| 14026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_n_scalar_out, overload_name, "n_scalar_out") |
| 14027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_hermite_polynomial_he_n_scalar_out, schema_str, "special_hermite_polynomial_he.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14028 | |
| 14029 | // aten::special_hermite_polynomial_he.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14030 | static C10_NOINLINE c10::TypedOperatorHandle<special_hermite_polynomial_he_n_scalar_out::schema> create_special_hermite_polynomial_he_n_scalar_out_typed_handle() { |
| 14031 | return c10::Dispatcher::singleton() |
| 14032 | .findSchemaOrThrow(special_hermite_polynomial_he_n_scalar_out::name, special_hermite_polynomial_he_n_scalar_out::overload_name) |
| 14033 | .typed<special_hermite_polynomial_he_n_scalar_out::schema>(); |
| 14034 | } |
| 14035 | |
| 14036 | // aten::special_hermite_polynomial_he.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14037 | at::Tensor & special_hermite_polynomial_he_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 14038 | |
| 14039 | static auto op = create_special_hermite_polynomial_he_n_scalar_out_typed_handle(); |
| 14040 | return op.call(x, n, out); |
| 14041 | } |
| 14042 | |
| 14043 | // aten::special_hermite_polynomial_he.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14044 | at::Tensor & special_hermite_polynomial_he_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 14045 | |
| 14046 | static auto op = create_special_hermite_polynomial_he_n_scalar_out_typed_handle(); |
| 14047 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14048 | } |
| 14049 | |
| 14050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_modified_bessel_i1, name, "aten::special_modified_bessel_i1") |
| 14051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_modified_bessel_i1, overload_name, "") |
| 14052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_modified_bessel_i1, schema_str, "special_modified_bessel_i1(Tensor self) -> Tensor") |
| 14053 | |
| 14054 | // aten::special_modified_bessel_i1(Tensor self) -> Tensor |
| 14055 | static C10_NOINLINE c10::TypedOperatorHandle<special_modified_bessel_i1::schema> create_special_modified_bessel_i1_typed_handle() { |
| 14056 | return c10::Dispatcher::singleton() |
| 14057 | .findSchemaOrThrow(special_modified_bessel_i1::name, special_modified_bessel_i1::overload_name) |
| 14058 | .typed<special_modified_bessel_i1::schema>(); |
| 14059 | } |
| 14060 | |
| 14061 | // aten::special_modified_bessel_i1(Tensor self) -> Tensor |
| 14062 | at::Tensor special_modified_bessel_i1::call(const at::Tensor & self) { |
| 14063 | |
| 14064 | static auto op = create_special_modified_bessel_i1_typed_handle(); |
| 14065 | return op.call(self); |
| 14066 | } |
| 14067 | |
| 14068 | // aten::special_modified_bessel_i1(Tensor self) -> Tensor |
| 14069 | at::Tensor special_modified_bessel_i1::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 14070 | |
| 14071 | static auto op = create_special_modified_bessel_i1_typed_handle(); |
| 14072 | return op.redispatch(dispatchKeySet, self); |
| 14073 | } |
| 14074 | |
| 14075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_modified_bessel_i1_out, name, "aten::special_modified_bessel_i1") |
| 14076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_modified_bessel_i1_out, overload_name, "out") |
| 14077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_modified_bessel_i1_out, schema_str, "special_modified_bessel_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 14078 | |
| 14079 | // aten::special_modified_bessel_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 14080 | static C10_NOINLINE c10::TypedOperatorHandle<special_modified_bessel_i1_out::schema> create_special_modified_bessel_i1_out_typed_handle() { |
| 14081 | return c10::Dispatcher::singleton() |
| 14082 | .findSchemaOrThrow(special_modified_bessel_i1_out::name, special_modified_bessel_i1_out::overload_name) |
| 14083 | .typed<special_modified_bessel_i1_out::schema>(); |
| 14084 | } |
| 14085 | |
| 14086 | // aten::special_modified_bessel_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 14087 | at::Tensor & special_modified_bessel_i1_out::call(const at::Tensor & self, at::Tensor & out) { |
| 14088 | |
| 14089 | static auto op = create_special_modified_bessel_i1_out_typed_handle(); |
| 14090 | return op.call(self, out); |
| 14091 | } |
| 14092 | |
| 14093 | // aten::special_modified_bessel_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 14094 | at::Tensor & special_modified_bessel_i1_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 14095 | |
| 14096 | static auto op = create_special_modified_bessel_i1_out_typed_handle(); |
| 14097 | return op.redispatch(dispatchKeySet, self, out); |
| 14098 | } |
| 14099 | |
| 14100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v, name, "aten::special_shifted_chebyshev_polynomial_v") |
| 14101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v, overload_name, "") |
| 14102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v, schema_str, "special_shifted_chebyshev_polynomial_v(Tensor x, Tensor n) -> Tensor") |
| 14103 | |
| 14104 | // aten::special_shifted_chebyshev_polynomial_v(Tensor x, Tensor n) -> Tensor |
| 14105 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_v::schema> create_special_shifted_chebyshev_polynomial_v_typed_handle() { |
| 14106 | return c10::Dispatcher::singleton() |
| 14107 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_v::name, special_shifted_chebyshev_polynomial_v::overload_name) |
| 14108 | .typed<special_shifted_chebyshev_polynomial_v::schema>(); |
| 14109 | } |
| 14110 | |
| 14111 | // aten::special_shifted_chebyshev_polynomial_v(Tensor x, Tensor n) -> Tensor |
| 14112 | at::Tensor special_shifted_chebyshev_polynomial_v::call(const at::Tensor & x, const at::Tensor & n) { |
| 14113 | |
| 14114 | static auto op = create_special_shifted_chebyshev_polynomial_v_typed_handle(); |
| 14115 | return op.call(x, n); |
| 14116 | } |
| 14117 | |
| 14118 | // aten::special_shifted_chebyshev_polynomial_v(Tensor x, Tensor n) -> Tensor |
| 14119 | at::Tensor special_shifted_chebyshev_polynomial_v::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
| 14120 | |
| 14121 | static auto op = create_special_shifted_chebyshev_polynomial_v_typed_handle(); |
| 14122 | return op.redispatch(dispatchKeySet, x, n); |
| 14123 | } |
| 14124 | |
| 14125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_x_scalar, name, "aten::special_shifted_chebyshev_polynomial_v") |
| 14126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_x_scalar, overload_name, "x_scalar") |
| 14127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_x_scalar, schema_str, "special_shifted_chebyshev_polynomial_v.x_scalar(Scalar x, Tensor n) -> Tensor") |
| 14128 | |
| 14129 | // aten::special_shifted_chebyshev_polynomial_v.x_scalar(Scalar x, Tensor n) -> Tensor |
| 14130 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_v_x_scalar::schema> create_special_shifted_chebyshev_polynomial_v_x_scalar_typed_handle() { |
| 14131 | return c10::Dispatcher::singleton() |
| 14132 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_v_x_scalar::name, special_shifted_chebyshev_polynomial_v_x_scalar::overload_name) |
| 14133 | .typed<special_shifted_chebyshev_polynomial_v_x_scalar::schema>(); |
| 14134 | } |
| 14135 | |
| 14136 | // aten::special_shifted_chebyshev_polynomial_v.x_scalar(Scalar x, Tensor n) -> Tensor |
| 14137 | at::Tensor special_shifted_chebyshev_polynomial_v_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
| 14138 | |
| 14139 | static auto op = create_special_shifted_chebyshev_polynomial_v_x_scalar_typed_handle(); |
| 14140 | return op.call(x, n); |
| 14141 | } |
| 14142 | |
| 14143 | // aten::special_shifted_chebyshev_polynomial_v.x_scalar(Scalar x, Tensor n) -> Tensor |
| 14144 | at::Tensor special_shifted_chebyshev_polynomial_v_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
| 14145 | |
| 14146 | static auto op = create_special_shifted_chebyshev_polynomial_v_x_scalar_typed_handle(); |
| 14147 | return op.redispatch(dispatchKeySet, x, n); |
| 14148 | } |
| 14149 | |
| 14150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_n_scalar, name, "aten::special_shifted_chebyshev_polynomial_v") |
| 14151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_n_scalar, overload_name, "n_scalar") |
| 14152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_n_scalar, schema_str, "special_shifted_chebyshev_polynomial_v.n_scalar(Tensor x, Scalar n) -> Tensor") |
| 14153 | |
| 14154 | // aten::special_shifted_chebyshev_polynomial_v.n_scalar(Tensor x, Scalar n) -> Tensor |
| 14155 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_v_n_scalar::schema> create_special_shifted_chebyshev_polynomial_v_n_scalar_typed_handle() { |
| 14156 | return c10::Dispatcher::singleton() |
| 14157 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_v_n_scalar::name, special_shifted_chebyshev_polynomial_v_n_scalar::overload_name) |
| 14158 | .typed<special_shifted_chebyshev_polynomial_v_n_scalar::schema>(); |
| 14159 | } |
| 14160 | |
| 14161 | // aten::special_shifted_chebyshev_polynomial_v.n_scalar(Tensor x, Scalar n) -> Tensor |
| 14162 | at::Tensor special_shifted_chebyshev_polynomial_v_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
| 14163 | |
| 14164 | static auto op = create_special_shifted_chebyshev_polynomial_v_n_scalar_typed_handle(); |
| 14165 | return op.call(x, n); |
| 14166 | } |
| 14167 | |
| 14168 | // aten::special_shifted_chebyshev_polynomial_v.n_scalar(Tensor x, Scalar n) -> Tensor |
| 14169 | at::Tensor special_shifted_chebyshev_polynomial_v_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
| 14170 | |
| 14171 | static auto op = create_special_shifted_chebyshev_polynomial_v_n_scalar_typed_handle(); |
| 14172 | return op.redispatch(dispatchKeySet, x, n); |
| 14173 | } |
| 14174 | |
| 14175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_out, name, "aten::special_shifted_chebyshev_polynomial_v") |
| 14176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_out, overload_name, "out") |
| 14177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_out, schema_str, "special_shifted_chebyshev_polynomial_v.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14178 | |
| 14179 | // aten::special_shifted_chebyshev_polynomial_v.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14180 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_v_out::schema> create_special_shifted_chebyshev_polynomial_v_out_typed_handle() { |
| 14181 | return c10::Dispatcher::singleton() |
| 14182 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_v_out::name, special_shifted_chebyshev_polynomial_v_out::overload_name) |
| 14183 | .typed<special_shifted_chebyshev_polynomial_v_out::schema>(); |
| 14184 | } |
| 14185 | |
| 14186 | // aten::special_shifted_chebyshev_polynomial_v.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14187 | at::Tensor & special_shifted_chebyshev_polynomial_v_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 14188 | |
| 14189 | static auto op = create_special_shifted_chebyshev_polynomial_v_out_typed_handle(); |
| 14190 | return op.call(x, n, out); |
| 14191 | } |
| 14192 | |
| 14193 | // aten::special_shifted_chebyshev_polynomial_v.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14194 | at::Tensor & special_shifted_chebyshev_polynomial_v_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 14195 | |
| 14196 | static auto op = create_special_shifted_chebyshev_polynomial_v_out_typed_handle(); |
| 14197 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14198 | } |
| 14199 | |
| 14200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_x_scalar_out, name, "aten::special_shifted_chebyshev_polynomial_v") |
| 14201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_x_scalar_out, overload_name, "x_scalar_out") |
| 14202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_x_scalar_out, schema_str, "special_shifted_chebyshev_polynomial_v.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14203 | |
| 14204 | // aten::special_shifted_chebyshev_polynomial_v.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14205 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_v_x_scalar_out::schema> create_special_shifted_chebyshev_polynomial_v_x_scalar_out_typed_handle() { |
| 14206 | return c10::Dispatcher::singleton() |
| 14207 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_v_x_scalar_out::name, special_shifted_chebyshev_polynomial_v_x_scalar_out::overload_name) |
| 14208 | .typed<special_shifted_chebyshev_polynomial_v_x_scalar_out::schema>(); |
| 14209 | } |
| 14210 | |
| 14211 | // aten::special_shifted_chebyshev_polynomial_v.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14212 | at::Tensor & special_shifted_chebyshev_polynomial_v_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 14213 | |
| 14214 | static auto op = create_special_shifted_chebyshev_polynomial_v_x_scalar_out_typed_handle(); |
| 14215 | return op.call(x, n, out); |
| 14216 | } |
| 14217 | |
| 14218 | // aten::special_shifted_chebyshev_polynomial_v.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14219 | at::Tensor & special_shifted_chebyshev_polynomial_v_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 14220 | |
| 14221 | static auto op = create_special_shifted_chebyshev_polynomial_v_x_scalar_out_typed_handle(); |
| 14222 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14223 | } |
| 14224 | |
| 14225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_n_scalar_out, name, "aten::special_shifted_chebyshev_polynomial_v") |
| 14226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_n_scalar_out, overload_name, "n_scalar_out") |
| 14227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_v_n_scalar_out, schema_str, "special_shifted_chebyshev_polynomial_v.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14228 | |
| 14229 | // aten::special_shifted_chebyshev_polynomial_v.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14230 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_v_n_scalar_out::schema> create_special_shifted_chebyshev_polynomial_v_n_scalar_out_typed_handle() { |
| 14231 | return c10::Dispatcher::singleton() |
| 14232 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_v_n_scalar_out::name, special_shifted_chebyshev_polynomial_v_n_scalar_out::overload_name) |
| 14233 | .typed<special_shifted_chebyshev_polynomial_v_n_scalar_out::schema>(); |
| 14234 | } |
| 14235 | |
| 14236 | // aten::special_shifted_chebyshev_polynomial_v.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14237 | at::Tensor & special_shifted_chebyshev_polynomial_v_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 14238 | |
| 14239 | static auto op = create_special_shifted_chebyshev_polynomial_v_n_scalar_out_typed_handle(); |
| 14240 | return op.call(x, n, out); |
| 14241 | } |
| 14242 | |
| 14243 | // aten::special_shifted_chebyshev_polynomial_v.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14244 | at::Tensor & special_shifted_chebyshev_polynomial_v_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 14245 | |
| 14246 | static auto op = create_special_shifted_chebyshev_polynomial_v_n_scalar_out_typed_handle(); |
| 14247 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14248 | } |
| 14249 | |
| 14250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w, name, "aten::special_shifted_chebyshev_polynomial_w") |
| 14251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w, overload_name, "") |
| 14252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w, schema_str, "special_shifted_chebyshev_polynomial_w(Tensor x, Tensor n) -> Tensor") |
| 14253 | |
| 14254 | // aten::special_shifted_chebyshev_polynomial_w(Tensor x, Tensor n) -> Tensor |
| 14255 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_w::schema> create_special_shifted_chebyshev_polynomial_w_typed_handle() { |
| 14256 | return c10::Dispatcher::singleton() |
| 14257 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_w::name, special_shifted_chebyshev_polynomial_w::overload_name) |
| 14258 | .typed<special_shifted_chebyshev_polynomial_w::schema>(); |
| 14259 | } |
| 14260 | |
| 14261 | // aten::special_shifted_chebyshev_polynomial_w(Tensor x, Tensor n) -> Tensor |
| 14262 | at::Tensor special_shifted_chebyshev_polynomial_w::call(const at::Tensor & x, const at::Tensor & n) { |
| 14263 | |
| 14264 | static auto op = create_special_shifted_chebyshev_polynomial_w_typed_handle(); |
| 14265 | return op.call(x, n); |
| 14266 | } |
| 14267 | |
| 14268 | // aten::special_shifted_chebyshev_polynomial_w(Tensor x, Tensor n) -> Tensor |
| 14269 | at::Tensor special_shifted_chebyshev_polynomial_w::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
| 14270 | |
| 14271 | static auto op = create_special_shifted_chebyshev_polynomial_w_typed_handle(); |
| 14272 | return op.redispatch(dispatchKeySet, x, n); |
| 14273 | } |
| 14274 | |
| 14275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_x_scalar, name, "aten::special_shifted_chebyshev_polynomial_w") |
| 14276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_x_scalar, overload_name, "x_scalar") |
| 14277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_x_scalar, schema_str, "special_shifted_chebyshev_polynomial_w.x_scalar(Scalar x, Tensor n) -> Tensor") |
| 14278 | |
| 14279 | // aten::special_shifted_chebyshev_polynomial_w.x_scalar(Scalar x, Tensor n) -> Tensor |
| 14280 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_w_x_scalar::schema> create_special_shifted_chebyshev_polynomial_w_x_scalar_typed_handle() { |
| 14281 | return c10::Dispatcher::singleton() |
| 14282 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_w_x_scalar::name, special_shifted_chebyshev_polynomial_w_x_scalar::overload_name) |
| 14283 | .typed<special_shifted_chebyshev_polynomial_w_x_scalar::schema>(); |
| 14284 | } |
| 14285 | |
| 14286 | // aten::special_shifted_chebyshev_polynomial_w.x_scalar(Scalar x, Tensor n) -> Tensor |
| 14287 | at::Tensor special_shifted_chebyshev_polynomial_w_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
| 14288 | |
| 14289 | static auto op = create_special_shifted_chebyshev_polynomial_w_x_scalar_typed_handle(); |
| 14290 | return op.call(x, n); |
| 14291 | } |
| 14292 | |
| 14293 | // aten::special_shifted_chebyshev_polynomial_w.x_scalar(Scalar x, Tensor n) -> Tensor |
| 14294 | at::Tensor special_shifted_chebyshev_polynomial_w_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
| 14295 | |
| 14296 | static auto op = create_special_shifted_chebyshev_polynomial_w_x_scalar_typed_handle(); |
| 14297 | return op.redispatch(dispatchKeySet, x, n); |
| 14298 | } |
| 14299 | |
| 14300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_n_scalar, name, "aten::special_shifted_chebyshev_polynomial_w") |
| 14301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_n_scalar, overload_name, "n_scalar") |
| 14302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_n_scalar, schema_str, "special_shifted_chebyshev_polynomial_w.n_scalar(Tensor x, Scalar n) -> Tensor") |
| 14303 | |
| 14304 | // aten::special_shifted_chebyshev_polynomial_w.n_scalar(Tensor x, Scalar n) -> Tensor |
| 14305 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_w_n_scalar::schema> create_special_shifted_chebyshev_polynomial_w_n_scalar_typed_handle() { |
| 14306 | return c10::Dispatcher::singleton() |
| 14307 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_w_n_scalar::name, special_shifted_chebyshev_polynomial_w_n_scalar::overload_name) |
| 14308 | .typed<special_shifted_chebyshev_polynomial_w_n_scalar::schema>(); |
| 14309 | } |
| 14310 | |
| 14311 | // aten::special_shifted_chebyshev_polynomial_w.n_scalar(Tensor x, Scalar n) -> Tensor |
| 14312 | at::Tensor special_shifted_chebyshev_polynomial_w_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
| 14313 | |
| 14314 | static auto op = create_special_shifted_chebyshev_polynomial_w_n_scalar_typed_handle(); |
| 14315 | return op.call(x, n); |
| 14316 | } |
| 14317 | |
| 14318 | // aten::special_shifted_chebyshev_polynomial_w.n_scalar(Tensor x, Scalar n) -> Tensor |
| 14319 | at::Tensor special_shifted_chebyshev_polynomial_w_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
| 14320 | |
| 14321 | static auto op = create_special_shifted_chebyshev_polynomial_w_n_scalar_typed_handle(); |
| 14322 | return op.redispatch(dispatchKeySet, x, n); |
| 14323 | } |
| 14324 | |
| 14325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_out, name, "aten::special_shifted_chebyshev_polynomial_w") |
| 14326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_out, overload_name, "out") |
| 14327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_out, schema_str, "special_shifted_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14328 | |
| 14329 | // aten::special_shifted_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14330 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_w_out::schema> create_special_shifted_chebyshev_polynomial_w_out_typed_handle() { |
| 14331 | return c10::Dispatcher::singleton() |
| 14332 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_w_out::name, special_shifted_chebyshev_polynomial_w_out::overload_name) |
| 14333 | .typed<special_shifted_chebyshev_polynomial_w_out::schema>(); |
| 14334 | } |
| 14335 | |
| 14336 | // aten::special_shifted_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14337 | at::Tensor & special_shifted_chebyshev_polynomial_w_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 14338 | |
| 14339 | static auto op = create_special_shifted_chebyshev_polynomial_w_out_typed_handle(); |
| 14340 | return op.call(x, n, out); |
| 14341 | } |
| 14342 | |
| 14343 | // aten::special_shifted_chebyshev_polynomial_w.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14344 | at::Tensor & special_shifted_chebyshev_polynomial_w_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 14345 | |
| 14346 | static auto op = create_special_shifted_chebyshev_polynomial_w_out_typed_handle(); |
| 14347 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14348 | } |
| 14349 | |
| 14350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_x_scalar_out, name, "aten::special_shifted_chebyshev_polynomial_w") |
| 14351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_x_scalar_out, overload_name, "x_scalar_out") |
| 14352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_x_scalar_out, schema_str, "special_shifted_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14353 | |
| 14354 | // aten::special_shifted_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14355 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_w_x_scalar_out::schema> create_special_shifted_chebyshev_polynomial_w_x_scalar_out_typed_handle() { |
| 14356 | return c10::Dispatcher::singleton() |
| 14357 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_w_x_scalar_out::name, special_shifted_chebyshev_polynomial_w_x_scalar_out::overload_name) |
| 14358 | .typed<special_shifted_chebyshev_polynomial_w_x_scalar_out::schema>(); |
| 14359 | } |
| 14360 | |
| 14361 | // aten::special_shifted_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14362 | at::Tensor & special_shifted_chebyshev_polynomial_w_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 14363 | |
| 14364 | static auto op = create_special_shifted_chebyshev_polynomial_w_x_scalar_out_typed_handle(); |
| 14365 | return op.call(x, n, out); |
| 14366 | } |
| 14367 | |
| 14368 | // aten::special_shifted_chebyshev_polynomial_w.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 14369 | at::Tensor & special_shifted_chebyshev_polynomial_w_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 14370 | |
| 14371 | static auto op = create_special_shifted_chebyshev_polynomial_w_x_scalar_out_typed_handle(); |
| 14372 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14373 | } |
| 14374 | |
| 14375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_n_scalar_out, name, "aten::special_shifted_chebyshev_polynomial_w") |
| 14376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_n_scalar_out, overload_name, "n_scalar_out") |
| 14377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_w_n_scalar_out, schema_str, "special_shifted_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") |
| 14378 | |
| 14379 | // aten::special_shifted_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14380 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_w_n_scalar_out::schema> create_special_shifted_chebyshev_polynomial_w_n_scalar_out_typed_handle() { |
| 14381 | return c10::Dispatcher::singleton() |
| 14382 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_w_n_scalar_out::name, special_shifted_chebyshev_polynomial_w_n_scalar_out::overload_name) |
| 14383 | .typed<special_shifted_chebyshev_polynomial_w_n_scalar_out::schema>(); |
| 14384 | } |
| 14385 | |
| 14386 | // aten::special_shifted_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14387 | at::Tensor & special_shifted_chebyshev_polynomial_w_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 14388 | |
| 14389 | static auto op = create_special_shifted_chebyshev_polynomial_w_n_scalar_out_typed_handle(); |
| 14390 | return op.call(x, n, out); |
| 14391 | } |
| 14392 | |
| 14393 | // aten::special_shifted_chebyshev_polynomial_w.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 14394 | at::Tensor & special_shifted_chebyshev_polynomial_w_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 14395 | |
| 14396 | static auto op = create_special_shifted_chebyshev_polynomial_w_n_scalar_out_typed_handle(); |
| 14397 | return op.redispatch(dispatchKeySet, x, n, out); |
| 14398 | } |
| 14399 | |
| 14400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_spherical_bessel_j0, name, "aten::special_spherical_bessel_j0") |
| 14401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_spherical_bessel_j0, overload_name, "") |
| 14402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_spherical_bessel_j0, schema_str, "special_spherical_bessel_j0(Tensor x) -> Tensor") |
| 14403 | |
| 14404 | // aten::special_spherical_bessel_j0(Tensor x) -> Tensor |
| 14405 | static C10_NOINLINE c10::TypedOperatorHandle<special_spherical_bessel_j0::schema> create_special_spherical_bessel_j0_typed_handle() { |
| 14406 | return c10::Dispatcher::singleton() |
| 14407 | .findSchemaOrThrow(special_spherical_bessel_j0::name, special_spherical_bessel_j0::overload_name) |
| 14408 | .typed<special_spherical_bessel_j0::schema>(); |
| 14409 | } |
| 14410 | |
| 14411 | // aten::special_spherical_bessel_j0(Tensor x) -> Tensor |
| 14412 | at::Tensor special_spherical_bessel_j0::call(const at::Tensor & x) { |
| 14413 | |
| 14414 | static auto op = create_special_spherical_bessel_j0_typed_handle(); |
| 14415 | return op.call(x); |
| 14416 | } |
| 14417 | |
| 14418 | // aten::special_spherical_bessel_j0(Tensor x) -> Tensor |
| 14419 | at::Tensor special_spherical_bessel_j0::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x) { |
| 14420 | |
| 14421 | static auto op = create_special_spherical_bessel_j0_typed_handle(); |
| 14422 | return op.redispatch(dispatchKeySet, x); |
| 14423 | } |
| 14424 | |
| 14425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_spherical_bessel_j0_out, name, "aten::special_spherical_bessel_j0") |
| 14426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_spherical_bessel_j0_out, overload_name, "out") |
| 14427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_spherical_bessel_j0_out, schema_str, "special_spherical_bessel_j0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!)") |
| 14428 | |
| 14429 | // aten::special_spherical_bessel_j0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
| 14430 | static C10_NOINLINE c10::TypedOperatorHandle<special_spherical_bessel_j0_out::schema> create_special_spherical_bessel_j0_out_typed_handle() { |
| 14431 | return c10::Dispatcher::singleton() |
| 14432 | .findSchemaOrThrow(special_spherical_bessel_j0_out::name, special_spherical_bessel_j0_out::overload_name) |
| 14433 | .typed<special_spherical_bessel_j0_out::schema>(); |
| 14434 | } |
| 14435 | |
| 14436 | // aten::special_spherical_bessel_j0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
| 14437 | at::Tensor & special_spherical_bessel_j0_out::call(const at::Tensor & x, at::Tensor & out) { |
| 14438 | |
| 14439 | static auto op = create_special_spherical_bessel_j0_out_typed_handle(); |
| 14440 | return op.call(x, out); |
| 14441 | } |
| 14442 | |
| 14443 | // aten::special_spherical_bessel_j0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
| 14444 | at::Tensor & special_spherical_bessel_j0_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, at::Tensor & out) { |
| 14445 | |
| 14446 | static auto op = create_special_spherical_bessel_j0_out_typed_handle(); |
| 14447 | return op.redispatch(dispatchKeySet, x, out); |
| 14448 | } |
| 14449 | |
| 14450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss_out, name, "aten::_cudnn_ctc_loss") |
| 14451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss_out, overload_name, "out") |
| 14452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_ctc_loss_out, schema_str, "_cudnn_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 14453 | |
| 14454 | // aten::_cudnn_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14455 | static C10_NOINLINE c10::TypedOperatorHandle<_cudnn_ctc_loss_out::schema> create__cudnn_ctc_loss_out_typed_handle() { |
| 14456 | return c10::Dispatcher::singleton() |
| 14457 | .findSchemaOrThrow(_cudnn_ctc_loss_out::name, _cudnn_ctc_loss_out::overload_name) |
| 14458 | .typed<_cudnn_ctc_loss_out::schema>(); |
| 14459 | } |
| 14460 | |
| 14461 | // aten::_cudnn_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14462 | ::std::tuple<at::Tensor &,at::Tensor &> _cudnn_ctc_loss_out::call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { |
| 14463 | |
| 14464 | static auto op = create__cudnn_ctc_loss_out_typed_handle(); |
| 14465 | return op.call(log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity, out0, out1); |
| 14466 | } |
| 14467 | |
| 14468 | // aten::_cudnn_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank, bool deterministic, bool zero_infinity, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14469 | ::std::tuple<at::Tensor &,at::Tensor &> _cudnn_ctc_loss_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool deterministic, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { |
| 14470 | |
| 14471 | static auto op = create__cudnn_ctc_loss_out_typed_handle(); |
| 14472 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank, deterministic, zero_infinity, out0, out1); |
| 14473 | } |
| 14474 | |
| 14475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_rnn_out, name, "aten::_cudnn_rnn") |
| 14476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_rnn_out, overload_name, "out") |
| 14477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_rnn_out, schema_str, "_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))") |
| 14478 | |
| 14479 | // aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
| 14480 | static C10_NOINLINE c10::TypedOperatorHandle<_cudnn_rnn_out::schema> create__cudnn_rnn_out_typed_handle() { |
| 14481 | return c10::Dispatcher::singleton() |
| 14482 | .findSchemaOrThrow(_cudnn_rnn_out::name, _cudnn_rnn_out::overload_name) |
| 14483 | .typed<_cudnn_rnn_out::schema>(); |
| 14484 | } |
| 14485 | |
| 14486 | // aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
| 14487 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _cudnn_rnn_out::call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional<at::Tensor> & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { |
| 14488 | |
| 14489 | static auto op = create__cudnn_rnn_out_typed_handle(); |
| 14490 | return op.call(input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); |
| 14491 | } |
| 14492 | |
| 14493 | // aten::_cudnn_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor? weight_buf, Tensor hx, Tensor? cx, int mode, SymInt hidden_size, SymInt proj_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, SymInt[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
| 14494 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _cudnn_rnn_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const c10::optional<at::Tensor> & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, int64_t mode, c10::SymInt hidden_size, c10::SymInt proj_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, c10::SymIntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { |
| 14495 | |
| 14496 | static auto op = create__cudnn_rnn_out_typed_handle(); |
| 14497 | return op.redispatch(dispatchKeySet, input, weight, weight_stride0, weight_buf, hx, cx, mode, hidden_size, proj_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); |
| 14498 | } |
| 14499 | |
| 14500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_dropout_out, name, "aten::_fused_dropout") |
| 14501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_dropout_out, overload_name, "out") |
| 14502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_dropout_out, schema_str, "_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 14503 | |
| 14504 | // aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14505 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_dropout_out::schema> create__fused_dropout_out_typed_handle() { |
| 14506 | return c10::Dispatcher::singleton() |
| 14507 | .findSchemaOrThrow(_fused_dropout_out::name, _fused_dropout_out::overload_name) |
| 14508 | .typed<_fused_dropout_out::schema>(); |
| 14509 | } |
| 14510 | |
| 14511 | // aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14512 | ::std::tuple<at::Tensor &,at::Tensor &> _fused_dropout_out::call(const at::Tensor & self, double p, c10::optional<at::Generator> generator, at::Tensor & out0, at::Tensor & out1) { |
| 14513 | |
| 14514 | static auto op = create__fused_dropout_out_typed_handle(); |
| 14515 | return op.call(self, p, generator, out0, out1); |
| 14516 | } |
| 14517 | |
| 14518 | // aten::_fused_dropout.out(Tensor self, float p, Generator? generator=None, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14519 | ::std::tuple<at::Tensor &,at::Tensor &> _fused_dropout_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional<at::Generator> generator, at::Tensor & out0, at::Tensor & out1) { |
| 14520 | |
| 14521 | static auto op = create__fused_dropout_out_typed_handle(); |
| 14522 | return op.redispatch(dispatchKeySet, self, p, generator, out0, out1); |
| 14523 | } |
| 14524 | |
| 14525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj_physical_out, name, "aten::_conj_physical") |
| 14526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj_physical_out, overload_name, "out") |
| 14527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_conj_physical_out, schema_str, "_conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 14528 | |
| 14529 | // aten::_conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 14530 | static C10_NOINLINE c10::TypedOperatorHandle<_conj_physical_out::schema> create__conj_physical_out_typed_handle() { |
| 14531 | return c10::Dispatcher::singleton() |
| 14532 | .findSchemaOrThrow(_conj_physical_out::name, _conj_physical_out::overload_name) |
| 14533 | .typed<_conj_physical_out::schema>(); |
| 14534 | } |
| 14535 | |
| 14536 | // aten::_conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 14537 | at::Tensor & _conj_physical_out::call(const at::Tensor & self, at::Tensor & out) { |
| 14538 | |
| 14539 | static auto op = create__conj_physical_out_typed_handle(); |
| 14540 | return op.call(self, out); |
| 14541 | } |
| 14542 | |
| 14543 | // aten::_conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 14544 | at::Tensor & _conj_physical_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 14545 | |
| 14546 | static auto op = create__conj_physical_out_typed_handle(); |
| 14547 | return op.redispatch(dispatchKeySet, self, out); |
| 14548 | } |
| 14549 | |
| 14550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_out, name, "aten::blackman_window") |
| 14551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_out, overload_name, "out") |
| 14552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_out, schema_str, "blackman_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)") |
| 14553 | |
| 14554 | // aten::blackman_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) |
| 14555 | static C10_NOINLINE c10::TypedOperatorHandle<blackman_window_out::schema> create_blackman_window_out_typed_handle() { |
| 14556 | return c10::Dispatcher::singleton() |
| 14557 | .findSchemaOrThrow(blackman_window_out::name, blackman_window_out::overload_name) |
| 14558 | .typed<blackman_window_out::schema>(); |
| 14559 | } |
| 14560 | |
| 14561 | // aten::blackman_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) |
| 14562 | at::Tensor & blackman_window_out::call(int64_t window_length, at::Tensor & out) { |
| 14563 | |
| 14564 | static auto op = create_blackman_window_out_typed_handle(); |
| 14565 | return op.call(window_length, out); |
| 14566 | } |
| 14567 | |
| 14568 | // aten::blackman_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) |
| 14569 | at::Tensor & blackman_window_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, at::Tensor & out) { |
| 14570 | |
| 14571 | static auto op = create_blackman_window_out_typed_handle(); |
| 14572 | return op.redispatch(dispatchKeySet, window_length, out); |
| 14573 | } |
| 14574 | |
| 14575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_periodic_out, name, "aten::blackman_window") |
| 14576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_periodic_out, overload_name, "periodic_out") |
| 14577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(blackman_window_periodic_out, schema_str, "blackman_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)") |
| 14578 | |
| 14579 | // aten::blackman_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) |
| 14580 | static C10_NOINLINE c10::TypedOperatorHandle<blackman_window_periodic_out::schema> create_blackman_window_periodic_out_typed_handle() { |
| 14581 | return c10::Dispatcher::singleton() |
| 14582 | .findSchemaOrThrow(blackman_window_periodic_out::name, blackman_window_periodic_out::overload_name) |
| 14583 | .typed<blackman_window_periodic_out::schema>(); |
| 14584 | } |
| 14585 | |
| 14586 | // aten::blackman_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) |
| 14587 | at::Tensor & blackman_window_periodic_out::call(int64_t window_length, bool periodic, at::Tensor & out) { |
| 14588 | |
| 14589 | static auto op = create_blackman_window_periodic_out_typed_handle(); |
| 14590 | return op.call(window_length, periodic, out); |
| 14591 | } |
| 14592 | |
| 14593 | // aten::blackman_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) |
| 14594 | at::Tensor & blackman_window_periodic_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, at::Tensor & out) { |
| 14595 | |
| 14596 | static auto op = create_blackman_window_periodic_out_typed_handle(); |
| 14597 | return op.redispatch(dispatchKeySet, window_length, periodic, out); |
| 14598 | } |
| 14599 | |
| 14600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_out, name, "aten::convolution") |
| 14601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_out, overload_name, "out") |
| 14602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_out, schema_str, "convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!)") |
| 14603 | |
| 14604 | // aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 14605 | static C10_NOINLINE c10::TypedOperatorHandle<convolution_out::schema> create_convolution_out_typed_handle() { |
| 14606 | return c10::Dispatcher::singleton() |
| 14607 | .findSchemaOrThrow(convolution_out::name, convolution_out::overload_name) |
| 14608 | .typed<convolution_out::schema>(); |
| 14609 | } |
| 14610 | |
| 14611 | // aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 14612 | at::Tensor & convolution_out::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, at::Tensor & out) { |
| 14613 | |
| 14614 | static auto op = create_convolution_out_typed_handle(); |
| 14615 | return op.call(input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, out); |
| 14616 | } |
| 14617 | |
| 14618 | // aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 14619 | at::Tensor & convolution_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, at::Tensor & out) { |
| 14620 | |
| 14621 | static auto op = create_convolution_out_typed_handle(); |
| 14622 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, out); |
| 14623 | } |
| 14624 | |
| 14625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_overrideable_out, name, "aten::convolution_backward_overrideable") |
| 14626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_overrideable_out, overload_name, "out") |
| 14627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_overrideable_out, schema_str, "convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") |
| 14628 | |
| 14629 | // aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 14630 | static C10_NOINLINE c10::TypedOperatorHandle<convolution_backward_overrideable_out::schema> create_convolution_backward_overrideable_out_typed_handle() { |
| 14631 | return c10::Dispatcher::singleton() |
| 14632 | .findSchemaOrThrow(convolution_backward_overrideable_out::name, convolution_backward_overrideable_out::overload_name) |
| 14633 | .typed<convolution_backward_overrideable_out::schema>(); |
| 14634 | } |
| 14635 | |
| 14636 | // aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 14637 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> convolution_backward_overrideable_out::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 14638 | |
| 14639 | static auto op = create_convolution_backward_overrideable_out_typed_handle(); |
| 14640 | return op.call(grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); |
| 14641 | } |
| 14642 | |
| 14643 | // aten::convolution_backward_overrideable.out(Tensor grad_output, Tensor input, Tensor weight, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 14644 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> convolution_backward_overrideable_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool transposed, at::IntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 14645 | |
| 14646 | static auto op = create_convolution_backward_overrideable_out_typed_handle(); |
| 14647 | return op.redispatch(dispatchKeySet, grad_output, input, weight, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); |
| 14648 | } |
| 14649 | |
| 14650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_out, name, "aten::_convolution") |
| 14651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_out, overload_name, "out") |
| 14652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_out, schema_str, "_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!)") |
| 14653 | |
| 14654 | // aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) |
| 14655 | static C10_NOINLINE c10::TypedOperatorHandle<_convolution_out::schema> create__convolution_out_typed_handle() { |
| 14656 | return c10::Dispatcher::singleton() |
| 14657 | .findSchemaOrThrow(_convolution_out::name, _convolution_out::overload_name) |
| 14658 | .typed<_convolution_out::schema>(); |
| 14659 | } |
| 14660 | |
| 14661 | // aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) |
| 14662 | at::Tensor & _convolution_out::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, at::Tensor & out) { |
| 14663 | |
| 14664 | static auto op = create__convolution_out_typed_handle(); |
| 14665 | return op.call(input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, benchmark, deterministic, cudnn_enabled, allow_tf32, out); |
| 14666 | } |
| 14667 | |
| 14668 | // aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) |
| 14669 | at::Tensor & _convolution_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, at::Tensor & out) { |
| 14670 | |
| 14671 | static auto op = create__convolution_out_typed_handle(); |
| 14672 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, benchmark, deterministic, cudnn_enabled, allow_tf32, out); |
| 14673 | } |
| 14674 | |
| 14675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_affine_grid_generator_out, name, "aten::cudnn_affine_grid_generator") |
| 14676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_affine_grid_generator_out, overload_name, "out") |
| 14677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_affine_grid_generator_out, schema_str, "cudnn_affine_grid_generator.out(Tensor theta, int N, int C, int H, int W, *, Tensor(a!) out) -> Tensor(a!)") |
| 14678 | |
| 14679 | // aten::cudnn_affine_grid_generator.out(Tensor theta, int N, int C, int H, int W, *, Tensor(a!) out) -> Tensor(a!) |
| 14680 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_affine_grid_generator_out::schema> create_cudnn_affine_grid_generator_out_typed_handle() { |
| 14681 | return c10::Dispatcher::singleton() |
| 14682 | .findSchemaOrThrow(cudnn_affine_grid_generator_out::name, cudnn_affine_grid_generator_out::overload_name) |
| 14683 | .typed<cudnn_affine_grid_generator_out::schema>(); |
| 14684 | } |
| 14685 | |
| 14686 | // aten::cudnn_affine_grid_generator.out(Tensor theta, int N, int C, int H, int W, *, Tensor(a!) out) -> Tensor(a!) |
| 14687 | at::Tensor & cudnn_affine_grid_generator_out::call(const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W, at::Tensor & out) { |
| 14688 | |
| 14689 | static auto op = create_cudnn_affine_grid_generator_out_typed_handle(); |
| 14690 | return op.call(theta, N, C, H, W, out); |
| 14691 | } |
| 14692 | |
| 14693 | // aten::cudnn_affine_grid_generator.out(Tensor theta, int N, int C, int H, int W, *, Tensor(a!) out) -> Tensor(a!) |
| 14694 | at::Tensor & cudnn_affine_grid_generator_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & theta, int64_t N, int64_t C, int64_t H, int64_t W, at::Tensor & out) { |
| 14695 | |
| 14696 | static auto op = create_cudnn_affine_grid_generator_out_typed_handle(); |
| 14697 | return op.redispatch(dispatchKeySet, theta, N, C, H, W, out); |
| 14698 | } |
| 14699 | |
| 14700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_backward_out, name, "aten::cudnn_batch_norm_backward") |
| 14701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_backward_out, overload_name, "out") |
| 14702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_backward_out, schema_str, "cudnn_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") |
| 14703 | |
| 14704 | // aten::cudnn_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 14705 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_batch_norm_backward_out::schema> create_cudnn_batch_norm_backward_out_typed_handle() { |
| 14706 | return c10::Dispatcher::singleton() |
| 14707 | .findSchemaOrThrow(cudnn_batch_norm_backward_out::name, cudnn_batch_norm_backward_out::overload_name) |
| 14708 | .typed<cudnn_batch_norm_backward_out::schema>(); |
| 14709 | } |
| 14710 | |
| 14711 | // aten::cudnn_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 14712 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> cudnn_batch_norm_backward_out::call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon, const at::Tensor & reserveSpace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 14713 | |
| 14714 | static auto op = create_cudnn_batch_norm_backward_out_typed_handle(); |
| 14715 | return op.call(input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon, reserveSpace, out0, out1, out2); |
| 14716 | } |
| 14717 | |
| 14718 | // aten::cudnn_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, Tensor reserveSpace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 14719 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> cudnn_batch_norm_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon, const at::Tensor & reserveSpace, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 14720 | |
| 14721 | static auto op = create_cudnn_batch_norm_backward_out_typed_handle(); |
| 14722 | return op.redispatch(dispatchKeySet, input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon, reserveSpace, out0, out1, out2); |
| 14723 | } |
| 14724 | |
| 14725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_transpose_out, name, "aten::cudnn_convolution_transpose") |
| 14726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_transpose_out, overload_name, "out") |
| 14727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_transpose_out, schema_str, "cudnn_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!)") |
| 14728 | |
| 14729 | // aten::cudnn_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) |
| 14730 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_convolution_transpose_out::schema> create_cudnn_convolution_transpose_out_typed_handle() { |
| 14731 | return c10::Dispatcher::singleton() |
| 14732 | .findSchemaOrThrow(cudnn_convolution_transpose_out::name, cudnn_convolution_transpose_out::overload_name) |
| 14733 | .typed<cudnn_convolution_transpose_out::schema>(); |
| 14734 | } |
| 14735 | |
| 14736 | // aten::cudnn_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) |
| 14737 | at::Tensor & cudnn_convolution_transpose_out::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { |
| 14738 | |
| 14739 | static auto op = create_cudnn_convolution_transpose_out_typed_handle(); |
| 14740 | return op.call(self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); |
| 14741 | } |
| 14742 | |
| 14743 | // aten::cudnn_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) |
| 14744 | at::Tensor & cudnn_convolution_transpose_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, bool allow_tf32, at::Tensor & out) { |
| 14745 | |
| 14746 | static auto op = create_cudnn_convolution_transpose_out_typed_handle(); |
| 14747 | return op.redispatch(dispatchKeySet, self, weight, padding, output_padding, stride, dilation, groups, benchmark, deterministic, allow_tf32, out); |
| 14748 | } |
| 14749 | |
| 14750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_grid_sampler_backward_out, name, "aten::cudnn_grid_sampler_backward") |
| 14751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_grid_sampler_backward_out, overload_name, "out") |
| 14752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_grid_sampler_backward_out, schema_str, "cudnn_grid_sampler_backward.out(Tensor self, Tensor grid, Tensor grad_output, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 14753 | |
| 14754 | // aten::cudnn_grid_sampler_backward.out(Tensor self, Tensor grid, Tensor grad_output, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14755 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_grid_sampler_backward_out::schema> create_cudnn_grid_sampler_backward_out_typed_handle() { |
| 14756 | return c10::Dispatcher::singleton() |
| 14757 | .findSchemaOrThrow(cudnn_grid_sampler_backward_out::name, cudnn_grid_sampler_backward_out::overload_name) |
| 14758 | .typed<cudnn_grid_sampler_backward_out::schema>(); |
| 14759 | } |
| 14760 | |
| 14761 | // aten::cudnn_grid_sampler_backward.out(Tensor self, Tensor grid, Tensor grad_output, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14762 | ::std::tuple<at::Tensor &,at::Tensor &> cudnn_grid_sampler_backward_out::call(const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output, at::Tensor & out0, at::Tensor & out1) { |
| 14763 | |
| 14764 | static auto op = create_cudnn_grid_sampler_backward_out_typed_handle(); |
| 14765 | return op.call(self, grid, grad_output, out0, out1); |
| 14766 | } |
| 14767 | |
| 14768 | // aten::cudnn_grid_sampler_backward.out(Tensor self, Tensor grid, Tensor grad_output, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14769 | ::std::tuple<at::Tensor &,at::Tensor &> cudnn_grid_sampler_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grid, const at::Tensor & grad_output, at::Tensor & out0, at::Tensor & out1) { |
| 14770 | |
| 14771 | static auto op = create_cudnn_grid_sampler_backward_out_typed_handle(); |
| 14772 | return op.redispatch(dispatchKeySet, self, grid, grad_output, out0, out1); |
| 14773 | } |
| 14774 | |
| 14775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_out, name, "aten::_ctc_loss") |
| 14776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_out, overload_name, "out") |
| 14777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_out, schema_str, "_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 14778 | |
| 14779 | // aten::_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14780 | static C10_NOINLINE c10::TypedOperatorHandle<_ctc_loss_out::schema> create__ctc_loss_out_typed_handle() { |
| 14781 | return c10::Dispatcher::singleton() |
| 14782 | .findSchemaOrThrow(_ctc_loss_out::name, _ctc_loss_out::overload_name) |
| 14783 | .typed<_ctc_loss_out::schema>(); |
| 14784 | } |
| 14785 | |
| 14786 | // aten::_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14787 | ::std::tuple<at::Tensor &,at::Tensor &> _ctc_loss_out::call(const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { |
| 14788 | |
| 14789 | static auto op = create__ctc_loss_out_typed_handle(); |
| 14790 | return op.call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); |
| 14791 | } |
| 14792 | |
| 14793 | // aten::_ctc_loss.out(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14794 | ::std::tuple<at::Tensor &,at::Tensor &> _ctc_loss_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { |
| 14795 | |
| 14796 | static auto op = create__ctc_loss_out_typed_handle(); |
| 14797 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); |
| 14798 | } |
| 14799 | |
| 14800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_Tensor_out, name, "aten::_ctc_loss") |
| 14801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_Tensor_out, overload_name, "Tensor_out") |
| 14802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_Tensor_out, schema_str, "_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 14803 | |
| 14804 | // aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14805 | static C10_NOINLINE c10::TypedOperatorHandle<_ctc_loss_Tensor_out::schema> create__ctc_loss_Tensor_out_typed_handle() { |
| 14806 | return c10::Dispatcher::singleton() |
| 14807 | .findSchemaOrThrow(_ctc_loss_Tensor_out::name, _ctc_loss_Tensor_out::overload_name) |
| 14808 | .typed<_ctc_loss_Tensor_out::schema>(); |
| 14809 | } |
| 14810 | |
| 14811 | // aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14812 | ::std::tuple<at::Tensor &,at::Tensor &> _ctc_loss_Tensor_out::call(const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { |
| 14813 | |
| 14814 | static auto op = create__ctc_loss_Tensor_out_typed_handle(); |
| 14815 | return op.call(log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); |
| 14816 | } |
| 14817 | |
| 14818 | // aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14819 | ::std::tuple<at::Tensor &,at::Tensor &> _ctc_loss_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, int64_t blank, bool zero_infinity, at::Tensor & out0, at::Tensor & out1) { |
| 14820 | |
| 14821 | static auto op = create__ctc_loss_Tensor_out_typed_handle(); |
| 14822 | return op.redispatch(dispatchKeySet, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity, out0, out1); |
| 14823 | } |
| 14824 | |
| 14825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_dense_backward_out, name, "aten::embedding_dense_backward") |
| 14826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_dense_backward_out, overload_name, "out") |
| 14827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_dense_backward_out, schema_str, "embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!)") |
| 14828 | |
| 14829 | // aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) |
| 14830 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_dense_backward_out::schema> create_embedding_dense_backward_out_typed_handle() { |
| 14831 | return c10::Dispatcher::singleton() |
| 14832 | .findSchemaOrThrow(embedding_dense_backward_out::name, embedding_dense_backward_out::overload_name) |
| 14833 | .typed<embedding_dense_backward_out::schema>(); |
| 14834 | } |
| 14835 | |
| 14836 | // aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) |
| 14837 | at::Tensor & embedding_dense_backward_out::call(const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, at::Tensor & out) { |
| 14838 | |
| 14839 | static auto op = create_embedding_dense_backward_out_typed_handle(); |
| 14840 | return op.call(grad_output, indices, num_weights, padding_idx, scale_grad_by_freq, out); |
| 14841 | } |
| 14842 | |
| 14843 | // aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) |
| 14844 | at::Tensor & embedding_dense_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & indices, c10::SymInt num_weights, c10::SymInt padding_idx, bool scale_grad_by_freq, at::Tensor & out) { |
| 14845 | |
| 14846 | static auto op = create_embedding_dense_backward_out_typed_handle(); |
| 14847 | return op.redispatch(dispatchKeySet, grad_output, indices, num_weights, padding_idx, scale_grad_by_freq, out); |
| 14848 | } |
| 14849 | |
| 14850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_out, name, "aten::_embedding_bag") |
| 14851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_out, overload_name, "out") |
| 14852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_out, schema_str, "_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") |
| 14853 | |
| 14854 | // aten::_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
| 14855 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag_out::schema> create__embedding_bag_out_typed_handle() { |
| 14856 | return c10::Dispatcher::singleton() |
| 14857 | .findSchemaOrThrow(_embedding_bag_out::name, _embedding_bag_out::overload_name) |
| 14858 | .typed<_embedding_bag_out::schema>(); |
| 14859 | } |
| 14860 | |
| 14861 | // aten::_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
| 14862 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _embedding_bag_out::call(const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
| 14863 | |
| 14864 | static auto op = create__embedding_bag_out_typed_handle(); |
| 14865 | return op.call(weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); |
| 14866 | } |
| 14867 | |
| 14868 | // aten::_embedding_bag.out(Tensor weight, Tensor indices, Tensor offsets, bool scale_grad_by_freq=False, int mode=0, bool sparse=False, Tensor? per_sample_weights=None, bool include_last_offset=False, int padding_idx=-1, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
| 14869 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _embedding_bag_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, bool include_last_offset, int64_t padding_idx, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
| 14870 | |
| 14871 | static auto op = create__embedding_bag_out_typed_handle(); |
| 14872 | return op.redispatch(dispatchKeySet, weight, indices, offsets, scale_grad_by_freq, mode, sparse, per_sample_weights, include_last_offset, padding_idx, out0, out1, out2, out3); |
| 14873 | } |
| 14874 | |
| 14875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_out, name, "aten::new_empty") |
| 14876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_out, overload_name, "out") |
| 14877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_out, schema_str, "new_empty.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") |
| 14878 | |
| 14879 | // aten::new_empty.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 14880 | static C10_NOINLINE c10::TypedOperatorHandle<new_empty_out::schema> create_new_empty_out_typed_handle() { |
| 14881 | return c10::Dispatcher::singleton() |
| 14882 | .findSchemaOrThrow(new_empty_out::name, new_empty_out::overload_name) |
| 14883 | .typed<new_empty_out::schema>(); |
| 14884 | } |
| 14885 | |
| 14886 | // aten::new_empty.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 14887 | at::Tensor & new_empty_out::call(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
| 14888 | |
| 14889 | static auto op = create_new_empty_out_typed_handle(); |
| 14890 | return op.call(self, size, out); |
| 14891 | } |
| 14892 | |
| 14893 | // aten::new_empty.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 14894 | at::Tensor & new_empty_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
| 14895 | |
| 14896 | static auto op = create_new_empty_out_typed_handle(); |
| 14897 | return op.redispatch(dispatchKeySet, self, size, out); |
| 14898 | } |
| 14899 | |
| 14900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Scalar_out, name, "aten::fill") |
| 14901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Scalar_out, overload_name, "Scalar_out") |
| 14902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Scalar_out, schema_str, "fill.Scalar_out(Tensor self, Scalar value, *, Tensor(a!) out) -> Tensor(a!)") |
| 14903 | |
| 14904 | // aten::fill.Scalar_out(Tensor self, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
| 14905 | static C10_NOINLINE c10::TypedOperatorHandle<fill_Scalar_out::schema> create_fill_Scalar_out_typed_handle() { |
| 14906 | return c10::Dispatcher::singleton() |
| 14907 | .findSchemaOrThrow(fill_Scalar_out::name, fill_Scalar_out::overload_name) |
| 14908 | .typed<fill_Scalar_out::schema>(); |
| 14909 | } |
| 14910 | |
| 14911 | // aten::fill.Scalar_out(Tensor self, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
| 14912 | at::Tensor & fill_Scalar_out::call(const at::Tensor & self, const at::Scalar & value, at::Tensor & out) { |
| 14913 | |
| 14914 | static auto op = create_fill_Scalar_out_typed_handle(); |
| 14915 | return op.call(self, value, out); |
| 14916 | } |
| 14917 | |
| 14918 | // aten::fill.Scalar_out(Tensor self, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
| 14919 | at::Tensor & fill_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & value, at::Tensor & out) { |
| 14920 | |
| 14921 | static auto op = create_fill_Scalar_out_typed_handle(); |
| 14922 | return op.redispatch(dispatchKeySet, self, value, out); |
| 14923 | } |
| 14924 | |
| 14925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Tensor_out, name, "aten::fill") |
| 14926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Tensor_out, overload_name, "Tensor_out") |
| 14927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_Tensor_out, schema_str, "fill.Tensor_out(Tensor self, Tensor value, *, Tensor(a!) out) -> Tensor(a!)") |
| 14928 | |
| 14929 | // aten::fill.Tensor_out(Tensor self, Tensor value, *, Tensor(a!) out) -> Tensor(a!) |
| 14930 | static C10_NOINLINE c10::TypedOperatorHandle<fill_Tensor_out::schema> create_fill_Tensor_out_typed_handle() { |
| 14931 | return c10::Dispatcher::singleton() |
| 14932 | .findSchemaOrThrow(fill_Tensor_out::name, fill_Tensor_out::overload_name) |
| 14933 | .typed<fill_Tensor_out::schema>(); |
| 14934 | } |
| 14935 | |
| 14936 | // aten::fill.Tensor_out(Tensor self, Tensor value, *, Tensor(a!) out) -> Tensor(a!) |
| 14937 | at::Tensor & fill_Tensor_out::call(const at::Tensor & self, const at::Tensor & value, at::Tensor & out) { |
| 14938 | |
| 14939 | static auto op = create_fill_Tensor_out_typed_handle(); |
| 14940 | return op.call(self, value, out); |
| 14941 | } |
| 14942 | |
| 14943 | // aten::fill.Tensor_out(Tensor self, Tensor value, *, Tensor(a!) out) -> Tensor(a!) |
| 14944 | at::Tensor & fill_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & value, at::Tensor & out) { |
| 14945 | |
| 14946 | static auto op = create_fill_Tensor_out_typed_handle(); |
| 14947 | return op.redispatch(dispatchKeySet, self, value, out); |
| 14948 | } |
| 14949 | |
| 14950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_backward_out, name, "aten::grid_sampler_2d_backward") |
| 14951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_backward_out, overload_name, "out") |
| 14952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_backward_out, schema_str, "grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 14953 | |
| 14954 | // aten::grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14955 | static C10_NOINLINE c10::TypedOperatorHandle<grid_sampler_2d_backward_out::schema> create_grid_sampler_2d_backward_out_typed_handle() { |
| 14956 | return c10::Dispatcher::singleton() |
| 14957 | .findSchemaOrThrow(grid_sampler_2d_backward_out::name, grid_sampler_2d_backward_out::overload_name) |
| 14958 | .typed<grid_sampler_2d_backward_out::schema>(); |
| 14959 | } |
| 14960 | |
| 14961 | // aten::grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14962 | ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_2d_backward_out::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1) { |
| 14963 | |
| 14964 | static auto op = create_grid_sampler_2d_backward_out_typed_handle(); |
| 14965 | return op.call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); |
| 14966 | } |
| 14967 | |
| 14968 | // aten::grid_sampler_2d_backward.out(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 14969 | ::std::tuple<at::Tensor &,at::Tensor &> grid_sampler_2d_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1) { |
| 14970 | |
| 14971 | static auto op = create_grid_sampler_2d_backward_out_typed_handle(); |
| 14972 | return op.redispatch(dispatchKeySet, grad_output, input, grid, interpolation_mode, padding_mode, align_corners, output_mask, out0, out1); |
| 14973 | } |
| 14974 | |
| 14975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl_out, name, "aten::_index_put_impl") |
| 14976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl_out, overload_name, "out") |
| 14977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl_out, schema_str, "_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 14978 | |
| 14979 | // aten::_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!) |
| 14980 | static C10_NOINLINE c10::TypedOperatorHandle<_index_put_impl_out::schema> create__index_put_impl_out_typed_handle() { |
| 14981 | return c10::Dispatcher::singleton() |
| 14982 | .findSchemaOrThrow(_index_put_impl_out::name, _index_put_impl_out::overload_name) |
| 14983 | .typed<_index_put_impl_out::schema>(); |
| 14984 | } |
| 14985 | |
| 14986 | // aten::_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!) |
| 14987 | at::Tensor & _index_put_impl_out::call(const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out) { |
| 14988 | |
| 14989 | static auto op = create__index_put_impl_out_typed_handle(); |
| 14990 | return op.call(self, indices, values, accumulate, unsafe, out); |
| 14991 | } |
| 14992 | |
| 14993 | // aten::_index_put_impl.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False, *, Tensor(a!) out) -> Tensor(a!) |
| 14994 | at::Tensor & _index_put_impl_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, bool unsafe, at::Tensor & out) { |
| 14995 | |
| 14996 | static auto op = create__index_put_impl_out_typed_handle(); |
| 14997 | return op.redispatch(dispatchKeySet, self, indices, values, accumulate, unsafe, out); |
| 14998 | } |
| 14999 | |
| 15000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl, name, "aten::_index_put_impl") |
| 15001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl, overload_name, "") |
| 15002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_index_put_impl, schema_str, "_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor") |
| 15003 | |
| 15004 | // aten::_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor |
| 15005 | static C10_NOINLINE c10::TypedOperatorHandle<_index_put_impl::schema> create__index_put_impl_typed_handle() { |
| 15006 | return c10::Dispatcher::singleton() |
| 15007 | .findSchemaOrThrow(_index_put_impl::name, _index_put_impl::overload_name) |
| 15008 | .typed<_index_put_impl::schema>(); |
| 15009 | } |
| 15010 | |
| 15011 | // aten::_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor |
| 15012 | at::Tensor _index_put_impl::call(const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, bool unsafe) { |
| 15013 | |
| 15014 | static auto op = create__index_put_impl_typed_handle(); |
| 15015 | return op.call(self, indices, values, accumulate, unsafe); |
| 15016 | } |
| 15017 | |
| 15018 | // aten::_index_put_impl(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, bool unsafe=False) -> Tensor |
| 15019 | at::Tensor _index_put_impl::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, bool unsafe) { |
| 15020 | |
| 15021 | static auto op = create__index_put_impl_typed_handle(); |
| 15022 | return op.redispatch(dispatchKeySet, self, indices, values, accumulate, unsafe); |
| 15023 | } |
| 15024 | |
| 15025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_out, name, "aten::mkldnn_linear") |
| 15026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_out, overload_name, "out") |
| 15027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_out, schema_str, "mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 15028 | |
| 15029 | // aten::mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15030 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_linear_out::schema> create_mkldnn_linear_out_typed_handle() { |
| 15031 | return c10::Dispatcher::singleton() |
| 15032 | .findSchemaOrThrow(mkldnn_linear_out::name, mkldnn_linear_out::overload_name) |
| 15033 | .typed<mkldnn_linear_out::schema>(); |
| 15034 | } |
| 15035 | |
| 15036 | // aten::mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15037 | at::Tensor & mkldnn_linear_out::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::Tensor & out) { |
| 15038 | |
| 15039 | static auto op = create_mkldnn_linear_out_typed_handle(); |
| 15040 | return op.call(self, weight, bias, out); |
| 15041 | } |
| 15042 | |
| 15043 | // aten::mkldnn_linear.out(Tensor self, Tensor weight, Tensor? bias=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15044 | at::Tensor & mkldnn_linear_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::Tensor & out) { |
| 15045 | |
| 15046 | static auto op = create_mkldnn_linear_out_typed_handle(); |
| 15047 | return op.redispatch(dispatchKeySet, self, weight, bias, out); |
| 15048 | } |
| 15049 | |
| 15050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_backward_weights_out, name, "aten::mkldnn_linear_backward_weights") |
| 15051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_backward_weights_out, overload_name, "out") |
| 15052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_linear_backward_weights_out, schema_str, "mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 15053 | |
| 15054 | // aten::mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15055 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_linear_backward_weights_out::schema> create_mkldnn_linear_backward_weights_out_typed_handle() { |
| 15056 | return c10::Dispatcher::singleton() |
| 15057 | .findSchemaOrThrow(mkldnn_linear_backward_weights_out::name, mkldnn_linear_backward_weights_out::overload_name) |
| 15058 | .typed<mkldnn_linear_backward_weights_out::schema>(); |
| 15059 | } |
| 15060 | |
| 15061 | // aten::mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15062 | ::std::tuple<at::Tensor &,at::Tensor &> mkldnn_linear_backward_weights_out::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1) { |
| 15063 | |
| 15064 | static auto op = create_mkldnn_linear_backward_weights_out_typed_handle(); |
| 15065 | return op.call(grad_output, input, weight, bias_defined, out0, out1); |
| 15066 | } |
| 15067 | |
| 15068 | // aten::mkldnn_linear_backward_weights.out(Tensor grad_output, Tensor input, Tensor weight, bool bias_defined, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15069 | ::std::tuple<at::Tensor &,at::Tensor &> mkldnn_linear_backward_weights_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, bool bias_defined, at::Tensor & out0, at::Tensor & out1) { |
| 15070 | |
| 15071 | static auto op = create_mkldnn_linear_backward_weights_out_typed_handle(); |
| 15072 | return op.redispatch(dispatchKeySet, grad_output, input, weight, bias_defined, out0, out1); |
| 15073 | } |
| 15074 | |
| 15075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_out, name, "aten::_aminmax") |
| 15076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_out, overload_name, "out") |
| 15077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_out, schema_str, "_aminmax.out(Tensor self, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 15078 | |
| 15079 | // aten::_aminmax.out(Tensor self, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15080 | static C10_NOINLINE c10::TypedOperatorHandle<_aminmax_out::schema> create__aminmax_out_typed_handle() { |
| 15081 | return c10::Dispatcher::singleton() |
| 15082 | .findSchemaOrThrow(_aminmax_out::name, _aminmax_out::overload_name) |
| 15083 | .typed<_aminmax_out::schema>(); |
| 15084 | } |
| 15085 | |
| 15086 | // aten::_aminmax.out(Tensor self, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15087 | ::std::tuple<at::Tensor &,at::Tensor &> _aminmax_out::call(const at::Tensor & self, at::Tensor & out0, at::Tensor & out1) { |
| 15088 | |
| 15089 | static auto op = create__aminmax_out_typed_handle(); |
| 15090 | return op.call(self, out0, out1); |
| 15091 | } |
| 15092 | |
| 15093 | // aten::_aminmax.out(Tensor self, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15094 | ::std::tuple<at::Tensor &,at::Tensor &> _aminmax_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out0, at::Tensor & out1) { |
| 15095 | |
| 15096 | static auto op = create__aminmax_out_typed_handle(); |
| 15097 | return op.redispatch(dispatchKeySet, self, out0, out1); |
| 15098 | } |
| 15099 | |
| 15100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_dim_out, name, "aten::_aminmax") |
| 15101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_dim_out, overload_name, "dim_out") |
| 15102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_aminmax_dim_out, schema_str, "_aminmax.dim_out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 15103 | |
| 15104 | // aten::_aminmax.dim_out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15105 | static C10_NOINLINE c10::TypedOperatorHandle<_aminmax_dim_out::schema> create__aminmax_dim_out_typed_handle() { |
| 15106 | return c10::Dispatcher::singleton() |
| 15107 | .findSchemaOrThrow(_aminmax_dim_out::name, _aminmax_dim_out::overload_name) |
| 15108 | .typed<_aminmax_dim_out::schema>(); |
| 15109 | } |
| 15110 | |
| 15111 | // aten::_aminmax.dim_out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15112 | ::std::tuple<at::Tensor &,at::Tensor &> _aminmax_dim_out::call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out0, at::Tensor & out1) { |
| 15113 | |
| 15114 | static auto op = create__aminmax_dim_out_typed_handle(); |
| 15115 | return op.call(self, dim, keepdim, out0, out1); |
| 15116 | } |
| 15117 | |
| 15118 | // aten::_aminmax.dim_out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15119 | ::std::tuple<at::Tensor &,at::Tensor &> _aminmax_dim_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out0, at::Tensor & out1) { |
| 15120 | |
| 15121 | static auto op = create__aminmax_dim_out_typed_handle(); |
| 15122 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out0, out1); |
| 15123 | } |
| 15124 | |
| 15125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_backward_out, name, "aten::mkldnn_max_pool3d_backward") |
| 15126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_backward_out, overload_name, "out") |
| 15127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_backward_out, schema_str, "mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 15128 | |
| 15129 | // aten::mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15130 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_max_pool3d_backward_out::schema> create_mkldnn_max_pool3d_backward_out_typed_handle() { |
| 15131 | return c10::Dispatcher::singleton() |
| 15132 | .findSchemaOrThrow(mkldnn_max_pool3d_backward_out::name, mkldnn_max_pool3d_backward_out::overload_name) |
| 15133 | .typed<mkldnn_max_pool3d_backward_out::schema>(); |
| 15134 | } |
| 15135 | |
| 15136 | // aten::mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15137 | at::Tensor & mkldnn_max_pool3d_backward_out::call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { |
| 15138 | |
| 15139 | static auto op = create_mkldnn_max_pool3d_backward_out_typed_handle(); |
| 15140 | return op.call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); |
| 15141 | } |
| 15142 | |
| 15143 | // aten::mkldnn_max_pool3d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15144 | at::Tensor & mkldnn_max_pool3d_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & input, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { |
| 15145 | |
| 15146 | static auto op = create_mkldnn_max_pool3d_backward_out_typed_handle(); |
| 15147 | return op.redispatch(dispatchKeySet, grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); |
| 15148 | } |
| 15149 | |
| 15150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_max_pool1d_out, name, "aten::quantized_max_pool1d") |
| 15151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_max_pool1d_out, overload_name, "out") |
| 15152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_max_pool1d_out, schema_str, "quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 15153 | |
| 15154 | // aten::quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15155 | static C10_NOINLINE c10::TypedOperatorHandle<quantized_max_pool1d_out::schema> create_quantized_max_pool1d_out_typed_handle() { |
| 15156 | return c10::Dispatcher::singleton() |
| 15157 | .findSchemaOrThrow(quantized_max_pool1d_out::name, quantized_max_pool1d_out::overload_name) |
| 15158 | .typed<quantized_max_pool1d_out::schema>(); |
| 15159 | } |
| 15160 | |
| 15161 | // aten::quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15162 | at::Tensor & quantized_max_pool1d_out::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { |
| 15163 | |
| 15164 | static auto op = create_quantized_max_pool1d_out_typed_handle(); |
| 15165 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode, out); |
| 15166 | } |
| 15167 | |
| 15168 | // aten::quantized_max_pool1d.out(Tensor self, int[1] kernel_size, int[1] stride=[], int[1] padding=0, int[1] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15169 | at::Tensor & quantized_max_pool1d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, at::Tensor & out) { |
| 15170 | |
| 15171 | static auto op = create_quantized_max_pool1d_out_typed_handle(); |
| 15172 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode, out); |
| 15173 | } |
| 15174 | |
| 15175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_convolution_out, name, "aten::mkldnn_convolution") |
| 15176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_convolution_out, overload_name, "out") |
| 15177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_convolution_out, schema_str, "mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!)") |
| 15178 | |
| 15179 | // aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 15180 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_convolution_out::schema> create_mkldnn_convolution_out_typed_handle() { |
| 15181 | return c10::Dispatcher::singleton() |
| 15182 | .findSchemaOrThrow(mkldnn_convolution_out::name, mkldnn_convolution_out::overload_name) |
| 15183 | .typed<mkldnn_convolution_out::schema>(); |
| 15184 | } |
| 15185 | |
| 15186 | // aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 15187 | at::Tensor & mkldnn_convolution_out::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { |
| 15188 | |
| 15189 | static auto op = create_mkldnn_convolution_out_typed_handle(); |
| 15190 | return op.call(self, weight, bias, padding, stride, dilation, groups, out); |
| 15191 | } |
| 15192 | |
| 15193 | // aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 15194 | at::Tensor & mkldnn_convolution_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { |
| 15195 | |
| 15196 | static auto op = create_mkldnn_convolution_out_typed_handle(); |
| 15197 | return op.redispatch(dispatchKeySet, self, weight, bias, padding, stride, dilation, groups, out); |
| 15198 | } |
| 15199 | |
| 15200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_backward_out, name, "aten::miopen_batch_norm_backward") |
| 15201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_backward_out, overload_name, "out") |
| 15202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_backward_out, schema_str, "miopen_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") |
| 15203 | |
| 15204 | // aten::miopen_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 15205 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_batch_norm_backward_out::schema> create_miopen_batch_norm_backward_out_typed_handle() { |
| 15206 | return c10::Dispatcher::singleton() |
| 15207 | .findSchemaOrThrow(miopen_batch_norm_backward_out::name, miopen_batch_norm_backward_out::overload_name) |
| 15208 | .typed<miopen_batch_norm_backward_out::schema>(); |
| 15209 | } |
| 15210 | |
| 15211 | // aten::miopen_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 15212 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> miopen_batch_norm_backward_out::call(const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 15213 | |
| 15214 | static auto op = create_miopen_batch_norm_backward_out_typed_handle(); |
| 15215 | return op.call(input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon, out0, out1, out2); |
| 15216 | } |
| 15217 | |
| 15218 | // aten::miopen_batch_norm_backward.out(Tensor input, Tensor grad_output, Tensor weight, Tensor? running_mean, Tensor? running_var, Tensor? save_mean, Tensor? save_var, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 15219 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> miopen_batch_norm_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grad_output, const at::Tensor & weight, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, const c10::optional<at::Tensor> & save_mean, const c10::optional<at::Tensor> & save_var, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 15220 | |
| 15221 | static auto op = create_miopen_batch_norm_backward_out_typed_handle(); |
| 15222 | return op.redispatch(dispatchKeySet, input, grad_output, weight, running_mean, running_var, save_mean, save_var, epsilon, out0, out1, out2); |
| 15223 | } |
| 15224 | |
| 15225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Scalar_out, name, "aten::mul") |
| 15226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Scalar_out, overload_name, "Scalar_out") |
| 15227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mul_Scalar_out, schema_str, "mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 15228 | |
| 15229 | // aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 15230 | static C10_NOINLINE c10::TypedOperatorHandle<mul_Scalar_out::schema> create_mul_Scalar_out_typed_handle() { |
| 15231 | return c10::Dispatcher::singleton() |
| 15232 | .findSchemaOrThrow(mul_Scalar_out::name, mul_Scalar_out::overload_name) |
| 15233 | .typed<mul_Scalar_out::schema>(); |
| 15234 | } |
| 15235 | |
| 15236 | // aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 15237 | at::Tensor & mul_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 15238 | |
| 15239 | static auto op = create_mul_Scalar_out_typed_handle(); |
| 15240 | return op.call(self, other, out); |
| 15241 | } |
| 15242 | |
| 15243 | // aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 15244 | at::Tensor & mul_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 15245 | |
| 15246 | static auto op = create_mul_Scalar_out_typed_handle(); |
| 15247 | return op.redispatch(dispatchKeySet, self, other, out); |
| 15248 | } |
| 15249 | |
| 15250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_backward_elemt_out, name, "aten::batch_norm_backward_elemt") |
| 15251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_backward_elemt_out, overload_name, "out") |
| 15252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_backward_elemt_out, schema_str, "batch_norm_backward_elemt.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count, *, Tensor(a!) out) -> Tensor(a!)") |
| 15253 | |
| 15254 | // aten::batch_norm_backward_elemt.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count, *, Tensor(a!) out) -> Tensor(a!) |
| 15255 | static C10_NOINLINE c10::TypedOperatorHandle<batch_norm_backward_elemt_out::schema> create_batch_norm_backward_elemt_out_typed_handle() { |
| 15256 | return c10::Dispatcher::singleton() |
| 15257 | .findSchemaOrThrow(batch_norm_backward_elemt_out::name, batch_norm_backward_elemt_out::overload_name) |
| 15258 | .typed<batch_norm_backward_elemt_out::schema>(); |
| 15259 | } |
| 15260 | |
| 15261 | // aten::batch_norm_backward_elemt.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count, *, Tensor(a!) out) -> Tensor(a!) |
| 15262 | at::Tensor & batch_norm_backward_elemt_out::call(const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional<at::Tensor> & weight, const at::Tensor & mean_dy, const at::Tensor & mean_dy_xmu, const at::Tensor & count, at::Tensor & out) { |
| 15263 | |
| 15264 | static auto op = create_batch_norm_backward_elemt_out_typed_handle(); |
| 15265 | return op.call(grad_out, input, mean, invstd, weight, mean_dy, mean_dy_xmu, count, out); |
| 15266 | } |
| 15267 | |
| 15268 | // aten::batch_norm_backward_elemt.out(Tensor grad_out, Tensor input, Tensor mean, Tensor invstd, Tensor? weight, Tensor mean_dy, Tensor mean_dy_xmu, Tensor count, *, Tensor(a!) out) -> Tensor(a!) |
| 15269 | at::Tensor & batch_norm_backward_elemt_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, const at::Tensor & mean, const at::Tensor & invstd, const c10::optional<at::Tensor> & weight, const at::Tensor & mean_dy, const at::Tensor & mean_dy_xmu, const at::Tensor & count, at::Tensor & out) { |
| 15270 | |
| 15271 | static auto op = create_batch_norm_backward_elemt_out_typed_handle(); |
| 15272 | return op.redispatch(dispatchKeySet, grad_out, input, mean, invstd, weight, mean_dy, mean_dy_xmu, count, out); |
| 15273 | } |
| 15274 | |
| 15275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pixel_unshuffle_out, name, "aten::pixel_unshuffle") |
| 15276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pixel_unshuffle_out, overload_name, "out") |
| 15277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(pixel_unshuffle_out, schema_str, "pixel_unshuffle.out(Tensor self, int downscale_factor, *, Tensor(a!) out) -> Tensor(a!)") |
| 15278 | |
| 15279 | // aten::pixel_unshuffle.out(Tensor self, int downscale_factor, *, Tensor(a!) out) -> Tensor(a!) |
| 15280 | static C10_NOINLINE c10::TypedOperatorHandle<pixel_unshuffle_out::schema> create_pixel_unshuffle_out_typed_handle() { |
| 15281 | return c10::Dispatcher::singleton() |
| 15282 | .findSchemaOrThrow(pixel_unshuffle_out::name, pixel_unshuffle_out::overload_name) |
| 15283 | .typed<pixel_unshuffle_out::schema>(); |
| 15284 | } |
| 15285 | |
| 15286 | // aten::pixel_unshuffle.out(Tensor self, int downscale_factor, *, Tensor(a!) out) -> Tensor(a!) |
| 15287 | at::Tensor & pixel_unshuffle_out::call(const at::Tensor & self, int64_t downscale_factor, at::Tensor & out) { |
| 15288 | |
| 15289 | static auto op = create_pixel_unshuffle_out_typed_handle(); |
| 15290 | return op.call(self, downscale_factor, out); |
| 15291 | } |
| 15292 | |
| 15293 | // aten::pixel_unshuffle.out(Tensor self, int downscale_factor, *, Tensor(a!) out) -> Tensor(a!) |
| 15294 | at::Tensor & pixel_unshuffle_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t downscale_factor, at::Tensor & out) { |
| 15295 | |
| 15296 | static auto op = create_pixel_unshuffle_out_typed_handle(); |
| 15297 | return op.redispatch(dispatchKeySet, self, downscale_factor, out); |
| 15298 | } |
| 15299 | |
| 15300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pin_memory_out, name, "aten::_pin_memory") |
| 15301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pin_memory_out, overload_name, "out") |
| 15302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pin_memory_out, schema_str, "_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 15303 | |
| 15304 | // aten::_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15305 | static C10_NOINLINE c10::TypedOperatorHandle<_pin_memory_out::schema> create__pin_memory_out_typed_handle() { |
| 15306 | return c10::Dispatcher::singleton() |
| 15307 | .findSchemaOrThrow(_pin_memory_out::name, _pin_memory_out::overload_name) |
| 15308 | .typed<_pin_memory_out::schema>(); |
| 15309 | } |
| 15310 | |
| 15311 | // aten::_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15312 | at::Tensor & _pin_memory_out::call(const at::Tensor & self, c10::optional<at::Device> device, at::Tensor & out) { |
| 15313 | |
| 15314 | static auto op = create__pin_memory_out_typed_handle(); |
| 15315 | return op.call(self, device, out); |
| 15316 | } |
| 15317 | |
| 15318 | // aten::_pin_memory.out(Tensor self, Device? device=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15319 | at::Tensor & _pin_memory_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Device> device, at::Tensor & out) { |
| 15320 | |
| 15321 | static auto op = create__pin_memory_out_typed_handle(); |
| 15322 | return op.redispatch(dispatchKeySet, self, device, out); |
| 15323 | } |
| 15324 | |
| 15325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_names_out, name, "aten::randn") |
| 15326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_names_out, overload_name, "names_out") |
| 15327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_names_out, schema_str, "randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") |
| 15328 | |
| 15329 | // aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15330 | static C10_NOINLINE c10::TypedOperatorHandle<randn_names_out::schema> create_randn_names_out_typed_handle() { |
| 15331 | return c10::Dispatcher::singleton() |
| 15332 | .findSchemaOrThrow(randn_names_out::name, randn_names_out::overload_name) |
| 15333 | .typed<randn_names_out::schema>(); |
| 15334 | } |
| 15335 | |
| 15336 | // aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15337 | at::Tensor & randn_names_out::call(c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 15338 | |
| 15339 | static auto op = create_randn_names_out_typed_handle(); |
| 15340 | return op.call(size, names, out); |
| 15341 | } |
| 15342 | |
| 15343 | // aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15344 | at::Tensor & randn_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 15345 | |
| 15346 | static auto op = create_randn_names_out_typed_handle(); |
| 15347 | return op.redispatch(dispatchKeySet, size, names, out); |
| 15348 | } |
| 15349 | |
| 15350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_with_names_out, name, "aten::randn") |
| 15351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_with_names_out, overload_name, "generator_with_names_out") |
| 15352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_generator_with_names_out, schema_str, "randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") |
| 15353 | |
| 15354 | // aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15355 | static C10_NOINLINE c10::TypedOperatorHandle<randn_generator_with_names_out::schema> create_randn_generator_with_names_out_typed_handle() { |
| 15356 | return c10::Dispatcher::singleton() |
| 15357 | .findSchemaOrThrow(randn_generator_with_names_out::name, randn_generator_with_names_out::overload_name) |
| 15358 | .typed<randn_generator_with_names_out::schema>(); |
| 15359 | } |
| 15360 | |
| 15361 | // aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15362 | at::Tensor & randn_generator_with_names_out::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 15363 | |
| 15364 | static auto op = create_randn_generator_with_names_out_typed_handle(); |
| 15365 | return op.call(size, generator, names, out); |
| 15366 | } |
| 15367 | |
| 15368 | // aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15369 | at::Tensor & randn_generator_with_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 15370 | |
| 15371 | static auto op = create_randn_generator_with_names_out_typed_handle(); |
| 15372 | return op.redispatch(dispatchKeySet, size, generator, names, out); |
| 15373 | } |
| 15374 | |
| 15375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_scatter_out, name, "aten::diagonal_scatter") |
| 15376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_scatter_out, overload_name, "out") |
| 15377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_scatter_out, schema_str, "diagonal_scatter.out(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 15378 | |
| 15379 | // aten::diagonal_scatter.out(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) |
| 15380 | static C10_NOINLINE c10::TypedOperatorHandle<diagonal_scatter_out::schema> create_diagonal_scatter_out_typed_handle() { |
| 15381 | return c10::Dispatcher::singleton() |
| 15382 | .findSchemaOrThrow(diagonal_scatter_out::name, diagonal_scatter_out::overload_name) |
| 15383 | .typed<diagonal_scatter_out::schema>(); |
| 15384 | } |
| 15385 | |
| 15386 | // aten::diagonal_scatter.out(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) |
| 15387 | at::Tensor & diagonal_scatter_out::call(const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out) { |
| 15388 | |
| 15389 | static auto op = create_diagonal_scatter_out_typed_handle(); |
| 15390 | return op.call(self, src, offset, dim1, dim2, out); |
| 15391 | } |
| 15392 | |
| 15393 | // aten::diagonal_scatter.out(Tensor self, Tensor src, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) |
| 15394 | at::Tensor & diagonal_scatter_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out) { |
| 15395 | |
| 15396 | static auto op = create_diagonal_scatter_out_typed_handle(); |
| 15397 | return op.redispatch(dispatchKeySet, self, src, offset, dim1, dim2, out); |
| 15398 | } |
| 15399 | |
| 15400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_scatter_out, name, "aten::as_strided_scatter") |
| 15401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_scatter_out, overload_name, "out") |
| 15402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(as_strided_scatter_out, schema_str, "as_strided_scatter.out(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 15403 | |
| 15404 | // aten::as_strided_scatter.out(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15405 | static C10_NOINLINE c10::TypedOperatorHandle<as_strided_scatter_out::schema> create_as_strided_scatter_out_typed_handle() { |
| 15406 | return c10::Dispatcher::singleton() |
| 15407 | .findSchemaOrThrow(as_strided_scatter_out::name, as_strided_scatter_out::overload_name) |
| 15408 | .typed<as_strided_scatter_out::schema>(); |
| 15409 | } |
| 15410 | |
| 15411 | // aten::as_strided_scatter.out(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15412 | at::Tensor & as_strided_scatter_out::call(const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset, at::Tensor & out) { |
| 15413 | |
| 15414 | static auto op = create_as_strided_scatter_out_typed_handle(); |
| 15415 | return op.call(self, src, size, stride, storage_offset, out); |
| 15416 | } |
| 15417 | |
| 15418 | // aten::as_strided_scatter.out(Tensor self, Tensor src, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15419 | at::Tensor & as_strided_scatter_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<c10::SymInt> storage_offset, at::Tensor & out) { |
| 15420 | |
| 15421 | static auto op = create_as_strided_scatter_out_typed_handle(); |
| 15422 | return op.redispatch(dispatchKeySet, self, src, size, stride, storage_offset, out); |
| 15423 | } |
| 15424 | |
| 15425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_transform_bias_rescale_qkv_out, name, "aten::_transform_bias_rescale_qkv") |
| 15426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_transform_bias_rescale_qkv_out, overload_name, "out") |
| 15427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_transform_bias_rescale_qkv_out, schema_str, "_transform_bias_rescale_qkv.out(Tensor qkv, Tensor qkv_bias, int num_heads, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") |
| 15428 | |
| 15429 | // aten::_transform_bias_rescale_qkv.out(Tensor qkv, Tensor qkv_bias, int num_heads, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 15430 | static C10_NOINLINE c10::TypedOperatorHandle<_transform_bias_rescale_qkv_out::schema> create__transform_bias_rescale_qkv_out_typed_handle() { |
| 15431 | return c10::Dispatcher::singleton() |
| 15432 | .findSchemaOrThrow(_transform_bias_rescale_qkv_out::name, _transform_bias_rescale_qkv_out::overload_name) |
| 15433 | .typed<_transform_bias_rescale_qkv_out::schema>(); |
| 15434 | } |
| 15435 | |
| 15436 | // aten::_transform_bias_rescale_qkv.out(Tensor qkv, Tensor qkv_bias, int num_heads, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 15437 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _transform_bias_rescale_qkv_out::call(const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 15438 | |
| 15439 | static auto op = create__transform_bias_rescale_qkv_out_typed_handle(); |
| 15440 | return op.call(qkv, qkv_bias, num_heads, out0, out1, out2); |
| 15441 | } |
| 15442 | |
| 15443 | // aten::_transform_bias_rescale_qkv.out(Tensor qkv, Tensor qkv_bias, int num_heads, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 15444 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _transform_bias_rescale_qkv_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & qkv, const at::Tensor & qkv_bias, int64_t num_heads, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 15445 | |
| 15446 | static auto op = create__transform_bias_rescale_qkv_out_typed_handle(); |
| 15447 | return op.redispatch(dispatchKeySet, qkv, qkv_bias, num_heads, out0, out1, out2); |
| 15448 | } |
| 15449 | |
| 15450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unique_out, name, "aten::_unique") |
| 15451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unique_out, overload_name, "out") |
| 15452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unique_out, schema_str, "_unique.out(Tensor self, bool sorted=True, bool return_inverse=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 15453 | |
| 15454 | // aten::_unique.out(Tensor self, bool sorted=True, bool return_inverse=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15455 | static C10_NOINLINE c10::TypedOperatorHandle<_unique_out::schema> create__unique_out_typed_handle() { |
| 15456 | return c10::Dispatcher::singleton() |
| 15457 | .findSchemaOrThrow(_unique_out::name, _unique_out::overload_name) |
| 15458 | .typed<_unique_out::schema>(); |
| 15459 | } |
| 15460 | |
| 15461 | // aten::_unique.out(Tensor self, bool sorted=True, bool return_inverse=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15462 | ::std::tuple<at::Tensor &,at::Tensor &> _unique_out::call(const at::Tensor & self, bool sorted, bool return_inverse, at::Tensor & out0, at::Tensor & out1) { |
| 15463 | |
| 15464 | static auto op = create__unique_out_typed_handle(); |
| 15465 | return op.call(self, sorted, return_inverse, out0, out1); |
| 15466 | } |
| 15467 | |
| 15468 | // aten::_unique.out(Tensor self, bool sorted=True, bool return_inverse=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15469 | ::std::tuple<at::Tensor &,at::Tensor &> _unique_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool sorted, bool return_inverse, at::Tensor & out0, at::Tensor & out1) { |
| 15470 | |
| 15471 | static auto op = create__unique_out_typed_handle(); |
| 15472 | return op.redispatch(dispatchKeySet, self, sorted, return_inverse, out0, out1); |
| 15473 | } |
| 15474 | |
| 15475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_interface_out, name, "aten::_weight_norm_interface") |
| 15476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_interface_out, overload_name, "out") |
| 15477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_weight_norm_interface_out, schema_str, "_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 15478 | |
| 15479 | // aten::_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15480 | static C10_NOINLINE c10::TypedOperatorHandle<_weight_norm_interface_out::schema> create__weight_norm_interface_out_typed_handle() { |
| 15481 | return c10::Dispatcher::singleton() |
| 15482 | .findSchemaOrThrow(_weight_norm_interface_out::name, _weight_norm_interface_out::overload_name) |
| 15483 | .typed<_weight_norm_interface_out::schema>(); |
| 15484 | } |
| 15485 | |
| 15486 | // aten::_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15487 | ::std::tuple<at::Tensor &,at::Tensor &> _weight_norm_interface_out::call(const at::Tensor & v, const at::Tensor & g, int64_t dim, at::Tensor & out0, at::Tensor & out1) { |
| 15488 | |
| 15489 | static auto op = create__weight_norm_interface_out_typed_handle(); |
| 15490 | return op.call(v, g, dim, out0, out1); |
| 15491 | } |
| 15492 | |
| 15493 | // aten::_weight_norm_interface.out(Tensor v, Tensor g, int dim=0, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15494 | ::std::tuple<at::Tensor &,at::Tensor &> _weight_norm_interface_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & v, const at::Tensor & g, int64_t dim, at::Tensor & out0, at::Tensor & out1) { |
| 15495 | |
| 15496 | static auto op = create__weight_norm_interface_out_typed_handle(); |
| 15497 | return op.redispatch(dispatchKeySet, v, g, dim, out0, out1); |
| 15498 | } |
| 15499 | |
| 15500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_names_out, name, "aten::zeros") |
| 15501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_names_out, overload_name, "names_out") |
| 15502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(zeros_names_out, schema_str, "zeros.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") |
| 15503 | |
| 15504 | // aten::zeros.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15505 | static C10_NOINLINE c10::TypedOperatorHandle<zeros_names_out::schema> create_zeros_names_out_typed_handle() { |
| 15506 | return c10::Dispatcher::singleton() |
| 15507 | .findSchemaOrThrow(zeros_names_out::name, zeros_names_out::overload_name) |
| 15508 | .typed<zeros_names_out::schema>(); |
| 15509 | } |
| 15510 | |
| 15511 | // aten::zeros.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15512 | at::Tensor & zeros_names_out::call(at::IntArrayRef size, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 15513 | |
| 15514 | static auto op = create_zeros_names_out_typed_handle(); |
| 15515 | return op.call(size, names, out); |
| 15516 | } |
| 15517 | |
| 15518 | // aten::zeros.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 15519 | at::Tensor & zeros_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 15520 | |
| 15521 | static auto op = create_zeros_names_out_typed_handle(); |
| 15522 | return op.redispatch(dispatchKeySet, size, names, out); |
| 15523 | } |
| 15524 | |
| 15525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_out, name, "aten::_standard_gamma") |
| 15526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_out, overload_name, "out") |
| 15527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_out, schema_str, "_standard_gamma.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 15528 | |
| 15529 | // aten::_standard_gamma.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15530 | static C10_NOINLINE c10::TypedOperatorHandle<_standard_gamma_out::schema> create__standard_gamma_out_typed_handle() { |
| 15531 | return c10::Dispatcher::singleton() |
| 15532 | .findSchemaOrThrow(_standard_gamma_out::name, _standard_gamma_out::overload_name) |
| 15533 | .typed<_standard_gamma_out::schema>(); |
| 15534 | } |
| 15535 | |
| 15536 | // aten::_standard_gamma.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15537 | at::Tensor & _standard_gamma_out::call(const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 15538 | |
| 15539 | static auto op = create__standard_gamma_out_typed_handle(); |
| 15540 | return op.call(self, generator, out); |
| 15541 | } |
| 15542 | |
| 15543 | // aten::_standard_gamma.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15544 | at::Tensor & _standard_gamma_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 15545 | |
| 15546 | static auto op = create__standard_gamma_out_typed_handle(); |
| 15547 | return op.redispatch(dispatchKeySet, self, generator, out); |
| 15548 | } |
| 15549 | |
| 15550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sample_dirichlet_out, name, "aten::_sample_dirichlet") |
| 15551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sample_dirichlet_out, overload_name, "out") |
| 15552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sample_dirichlet_out, schema_str, "_sample_dirichlet.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 15553 | |
| 15554 | // aten::_sample_dirichlet.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15555 | static C10_NOINLINE c10::TypedOperatorHandle<_sample_dirichlet_out::schema> create__sample_dirichlet_out_typed_handle() { |
| 15556 | return c10::Dispatcher::singleton() |
| 15557 | .findSchemaOrThrow(_sample_dirichlet_out::name, _sample_dirichlet_out::overload_name) |
| 15558 | .typed<_sample_dirichlet_out::schema>(); |
| 15559 | } |
| 15560 | |
| 15561 | // aten::_sample_dirichlet.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15562 | at::Tensor & _sample_dirichlet_out::call(const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 15563 | |
| 15564 | static auto op = create__sample_dirichlet_out_typed_handle(); |
| 15565 | return op.call(self, generator, out); |
| 15566 | } |
| 15567 | |
| 15568 | // aten::_sample_dirichlet.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15569 | at::Tensor & _sample_dirichlet_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 15570 | |
| 15571 | static auto op = create__sample_dirichlet_out_typed_handle(); |
| 15572 | return op.redispatch(dispatchKeySet, self, generator, out); |
| 15573 | } |
| 15574 | |
| 15575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binomial_out, name, "aten::binomial") |
| 15576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binomial_out, overload_name, "out") |
| 15577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binomial_out, schema_str, "binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 15578 | |
| 15579 | // aten::binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15580 | static C10_NOINLINE c10::TypedOperatorHandle<binomial_out::schema> create_binomial_out_typed_handle() { |
| 15581 | return c10::Dispatcher::singleton() |
| 15582 | .findSchemaOrThrow(binomial_out::name, binomial_out::overload_name) |
| 15583 | .typed<binomial_out::schema>(); |
| 15584 | } |
| 15585 | |
| 15586 | // aten::binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15587 | at::Tensor & binomial_out::call(const at::Tensor & count, const at::Tensor & prob, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 15588 | |
| 15589 | static auto op = create_binomial_out_typed_handle(); |
| 15590 | return op.call(count, prob, generator, out); |
| 15591 | } |
| 15592 | |
| 15593 | // aten::binomial.out(Tensor count, Tensor prob, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15594 | at::Tensor & binomial_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & count, const at::Tensor & prob, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 15595 | |
| 15596 | static auto op = create_binomial_out_typed_handle(); |
| 15597 | return op.redispatch(dispatchKeySet, count, prob, generator, out); |
| 15598 | } |
| 15599 | |
| 15600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim_out, name, "aten::_sparse_sum") |
| 15601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim_out, overload_name, "dim_out") |
| 15602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_dim_out, schema_str, "_sparse_sum.dim_out(Tensor self, int[1] dim, *, Tensor(a!) out) -> Tensor(a!)") |
| 15603 | |
| 15604 | // aten::_sparse_sum.dim_out(Tensor self, int[1] dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15605 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sum_dim_out::schema> create__sparse_sum_dim_out_typed_handle() { |
| 15606 | return c10::Dispatcher::singleton() |
| 15607 | .findSchemaOrThrow(_sparse_sum_dim_out::name, _sparse_sum_dim_out::overload_name) |
| 15608 | .typed<_sparse_sum_dim_out::schema>(); |
| 15609 | } |
| 15610 | |
| 15611 | // aten::_sparse_sum.dim_out(Tensor self, int[1] dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15612 | at::Tensor & _sparse_sum_dim_out::call(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { |
| 15613 | |
| 15614 | static auto op = create__sparse_sum_dim_out_typed_handle(); |
| 15615 | return op.call(self, dim, out); |
| 15616 | } |
| 15617 | |
| 15618 | // aten::_sparse_sum.dim_out(Tensor self, int[1] dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15619 | at::Tensor & _sparse_sum_dim_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { |
| 15620 | |
| 15621 | static auto op = create__sparse_sum_dim_out_typed_handle(); |
| 15622 | return op.redispatch(dispatchKeySet, self, dim, out); |
| 15623 | } |
| 15624 | |
| 15625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_addmm_out, name, "aten::_sparse_addmm") |
| 15626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_addmm_out, overload_name, "out") |
| 15627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_addmm_out, schema_str, "_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") |
| 15628 | |
| 15629 | // aten::_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 15630 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_addmm_out::schema> create__sparse_addmm_out_typed_handle() { |
| 15631 | return c10::Dispatcher::singleton() |
| 15632 | .findSchemaOrThrow(_sparse_addmm_out::name, _sparse_addmm_out::overload_name) |
| 15633 | .typed<_sparse_addmm_out::schema>(); |
| 15634 | } |
| 15635 | |
| 15636 | // aten::_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 15637 | at::Tensor & _sparse_addmm_out::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
| 15638 | |
| 15639 | static auto op = create__sparse_addmm_out_typed_handle(); |
| 15640 | return op.call(self, mat1, mat2, beta, alpha, out); |
| 15641 | } |
| 15642 | |
| 15643 | // aten::_sparse_addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 15644 | at::Tensor & _sparse_addmm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
| 15645 | |
| 15646 | static auto op = create__sparse_addmm_out_typed_handle(); |
| 15647 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha, out); |
| 15648 | } |
| 15649 | |
| 15650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_out, name, "aten::sparse_resize") |
| 15651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_out, overload_name, "out") |
| 15652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_out, schema_str, "sparse_resize.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!)") |
| 15653 | |
| 15654 | // aten::sparse_resize.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15655 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_resize_out::schema> create_sparse_resize_out_typed_handle() { |
| 15656 | return c10::Dispatcher::singleton() |
| 15657 | .findSchemaOrThrow(sparse_resize_out::name, sparse_resize_out::overload_name) |
| 15658 | .typed<sparse_resize_out::schema>(); |
| 15659 | } |
| 15660 | |
| 15661 | // aten::sparse_resize.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15662 | const at::Tensor & sparse_resize_out::call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out) { |
| 15663 | |
| 15664 | static auto op = create_sparse_resize_out_typed_handle(); |
| 15665 | return op.call(self, size, sparse_dim, dense_dim, out); |
| 15666 | } |
| 15667 | |
| 15668 | // aten::sparse_resize.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15669 | const at::Tensor & sparse_resize_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out) { |
| 15670 | |
| 15671 | static auto op = create_sparse_resize_out_typed_handle(); |
| 15672 | return op.redispatch(dispatchKeySet, self, size, sparse_dim, dense_dim, out); |
| 15673 | } |
| 15674 | |
| 15675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize, name, "aten::sparse_resize") |
| 15676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize, overload_name, "") |
| 15677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize, schema_str, "sparse_resize(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor") |
| 15678 | |
| 15679 | // aten::sparse_resize(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor |
| 15680 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_resize::schema> create_sparse_resize_typed_handle() { |
| 15681 | return c10::Dispatcher::singleton() |
| 15682 | .findSchemaOrThrow(sparse_resize::name, sparse_resize::overload_name) |
| 15683 | .typed<sparse_resize::schema>(); |
| 15684 | } |
| 15685 | |
| 15686 | // aten::sparse_resize(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor |
| 15687 | at::Tensor sparse_resize::call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 15688 | |
| 15689 | static auto op = create_sparse_resize_typed_handle(); |
| 15690 | return op.call(self, size, sparse_dim, dense_dim); |
| 15691 | } |
| 15692 | |
| 15693 | // aten::sparse_resize(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor |
| 15694 | at::Tensor sparse_resize::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 15695 | |
| 15696 | static auto op = create_sparse_resize_typed_handle(); |
| 15697 | return op.redispatch(dispatchKeySet, self, size, sparse_dim, dense_dim); |
| 15698 | } |
| 15699 | |
| 15700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_mask_out, name, "aten::sparse_mask") |
| 15701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_mask_out, overload_name, "out") |
| 15702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_mask_out, schema_str, "sparse_mask.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!)") |
| 15703 | |
| 15704 | // aten::sparse_mask.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) |
| 15705 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_mask_out::schema> create_sparse_mask_out_typed_handle() { |
| 15706 | return c10::Dispatcher::singleton() |
| 15707 | .findSchemaOrThrow(sparse_mask_out::name, sparse_mask_out::overload_name) |
| 15708 | .typed<sparse_mask_out::schema>(); |
| 15709 | } |
| 15710 | |
| 15711 | // aten::sparse_mask.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) |
| 15712 | at::Tensor & sparse_mask_out::call(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out) { |
| 15713 | |
| 15714 | static auto op = create_sparse_mask_out_typed_handle(); |
| 15715 | return op.call(self, mask, out); |
| 15716 | } |
| 15717 | |
| 15718 | // aten::sparse_mask.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) |
| 15719 | at::Tensor & sparse_mask_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, at::Tensor & out) { |
| 15720 | |
| 15721 | static auto op = create_sparse_mask_out_typed_handle(); |
| 15722 | return op.redispatch(dispatchKeySet, self, mask, out); |
| 15723 | } |
| 15724 | |
| 15725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse_out, name, "aten::copy_sparse_to_sparse") |
| 15726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse_out, overload_name, "out") |
| 15727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse_out, schema_str, "copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 15728 | |
| 15729 | // aten::copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15730 | static C10_NOINLINE c10::TypedOperatorHandle<copy_sparse_to_sparse_out::schema> create_copy_sparse_to_sparse_out_typed_handle() { |
| 15731 | return c10::Dispatcher::singleton() |
| 15732 | .findSchemaOrThrow(copy_sparse_to_sparse_out::name, copy_sparse_to_sparse_out::overload_name) |
| 15733 | .typed<copy_sparse_to_sparse_out::schema>(); |
| 15734 | } |
| 15735 | |
| 15736 | // aten::copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15737 | at::Tensor & copy_sparse_to_sparse_out::call(const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out) { |
| 15738 | |
| 15739 | static auto op = create_copy_sparse_to_sparse_out_typed_handle(); |
| 15740 | return op.call(self, src, non_blocking, out); |
| 15741 | } |
| 15742 | |
| 15743 | // aten::copy_sparse_to_sparse.out(Tensor self, Tensor src, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) |
| 15744 | at::Tensor & copy_sparse_to_sparse_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, bool non_blocking, at::Tensor & out) { |
| 15745 | |
| 15746 | static auto op = create_copy_sparse_to_sparse_out_typed_handle(); |
| 15747 | return op.redispatch(dispatchKeySet, self, src, non_blocking, out); |
| 15748 | } |
| 15749 | |
| 15750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse, name, "aten::copy_sparse_to_sparse") |
| 15751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse, overload_name, "") |
| 15752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copy_sparse_to_sparse, schema_str, "copy_sparse_to_sparse(Tensor self, Tensor src, bool non_blocking=False) -> Tensor") |
| 15753 | |
| 15754 | // aten::copy_sparse_to_sparse(Tensor self, Tensor src, bool non_blocking=False) -> Tensor |
| 15755 | static C10_NOINLINE c10::TypedOperatorHandle<copy_sparse_to_sparse::schema> create_copy_sparse_to_sparse_typed_handle() { |
| 15756 | return c10::Dispatcher::singleton() |
| 15757 | .findSchemaOrThrow(copy_sparse_to_sparse::name, copy_sparse_to_sparse::overload_name) |
| 15758 | .typed<copy_sparse_to_sparse::schema>(); |
| 15759 | } |
| 15760 | |
| 15761 | // aten::copy_sparse_to_sparse(Tensor self, Tensor src, bool non_blocking=False) -> Tensor |
| 15762 | at::Tensor copy_sparse_to_sparse::call(const at::Tensor & self, const at::Tensor & src, bool non_blocking) { |
| 15763 | |
| 15764 | static auto op = create_copy_sparse_to_sparse_typed_handle(); |
| 15765 | return op.call(self, src, non_blocking); |
| 15766 | } |
| 15767 | |
| 15768 | // aten::copy_sparse_to_sparse(Tensor self, Tensor src, bool non_blocking=False) -> Tensor |
| 15769 | at::Tensor copy_sparse_to_sparse::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, bool non_blocking) { |
| 15770 | |
| 15771 | static auto op = create_copy_sparse_to_sparse_typed_handle(); |
| 15772 | return op.redispatch(dispatchKeySet, self, src, non_blocking); |
| 15773 | } |
| 15774 | |
| 15775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_sparse_dim_out, name, "aten::to_sparse") |
| 15776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_sparse_dim_out, overload_name, "sparse_dim_out") |
| 15777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_sparse_dim_out, schema_str, "to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!)") |
| 15778 | |
| 15779 | // aten::to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15780 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_sparse_dim_out::schema> create_to_sparse_sparse_dim_out_typed_handle() { |
| 15781 | return c10::Dispatcher::singleton() |
| 15782 | .findSchemaOrThrow(to_sparse_sparse_dim_out::name, to_sparse_sparse_dim_out::overload_name) |
| 15783 | .typed<to_sparse_sparse_dim_out::schema>(); |
| 15784 | } |
| 15785 | |
| 15786 | // aten::to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15787 | at::Tensor & to_sparse_sparse_dim_out::call(const at::Tensor & self, int64_t sparse_dim, at::Tensor & out) { |
| 15788 | |
| 15789 | static auto op = create_to_sparse_sparse_dim_out_typed_handle(); |
| 15790 | return op.call(self, sparse_dim, out); |
| 15791 | } |
| 15792 | |
| 15793 | // aten::to_sparse.sparse_dim_out(Tensor self, int sparse_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 15794 | at::Tensor & to_sparse_sparse_dim_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t sparse_dim, at::Tensor & out) { |
| 15795 | |
| 15796 | static auto op = create_to_sparse_sparse_dim_out_typed_handle(); |
| 15797 | return op.redispatch(dispatchKeySet, self, sparse_dim, out); |
| 15798 | } |
| 15799 | |
| 15800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_out, name, "aten::to_sparse") |
| 15801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_out, overload_name, "out") |
| 15802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_out, schema_str, "to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!)") |
| 15803 | |
| 15804 | // aten::to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) |
| 15805 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_out::schema> create_to_sparse_out_typed_handle() { |
| 15806 | return c10::Dispatcher::singleton() |
| 15807 | .findSchemaOrThrow(to_sparse_out::name, to_sparse_out::overload_name) |
| 15808 | .typed<to_sparse_out::schema>(); |
| 15809 | } |
| 15810 | |
| 15811 | // aten::to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) |
| 15812 | at::Tensor & to_sparse_out::call(const at::Tensor & self, c10::optional<at::Layout> layout, at::OptionalIntArrayRef blocksize, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
| 15813 | |
| 15814 | static auto op = create_to_sparse_out_typed_handle(); |
| 15815 | return op.call(self, layout, blocksize, dense_dim, out); |
| 15816 | } |
| 15817 | |
| 15818 | // aten::to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) |
| 15819 | at::Tensor & to_sparse_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Layout> layout, at::OptionalIntArrayRef blocksize, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
| 15820 | |
| 15821 | static auto op = create_to_sparse_out_typed_handle(); |
| 15822 | return op.redispatch(dispatchKeySet, self, layout, blocksize, dense_dim, out); |
| 15823 | } |
| 15824 | |
| 15825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn_out, name, "aten::to_mkldnn") |
| 15826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn_out, overload_name, "out") |
| 15827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_mkldnn_out, schema_str, "to_mkldnn.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 15828 | |
| 15829 | // aten::to_mkldnn.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15830 | static C10_NOINLINE c10::TypedOperatorHandle<to_mkldnn_out::schema> create_to_mkldnn_out_typed_handle() { |
| 15831 | return c10::Dispatcher::singleton() |
| 15832 | .findSchemaOrThrow(to_mkldnn_out::name, to_mkldnn_out::overload_name) |
| 15833 | .typed<to_mkldnn_out::schema>(); |
| 15834 | } |
| 15835 | |
| 15836 | // aten::to_mkldnn.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15837 | at::Tensor & to_mkldnn_out::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 15838 | |
| 15839 | static auto op = create_to_mkldnn_out_typed_handle(); |
| 15840 | return op.call(self, dtype, out); |
| 15841 | } |
| 15842 | |
| 15843 | // aten::to_mkldnn.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
| 15844 | at::Tensor & to_mkldnn_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 15845 | |
| 15846 | static auto op = create_to_mkldnn_out_typed_handle(); |
| 15847 | return op.redispatch(dispatchKeySet, self, dtype, out); |
| 15848 | } |
| 15849 | |
| 15850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(int_repr_out, name, "aten::int_repr") |
| 15851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(int_repr_out, overload_name, "out") |
| 15852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(int_repr_out, schema_str, "int_repr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 15853 | |
| 15854 | // aten::int_repr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 15855 | static C10_NOINLINE c10::TypedOperatorHandle<int_repr_out::schema> create_int_repr_out_typed_handle() { |
| 15856 | return c10::Dispatcher::singleton() |
| 15857 | .findSchemaOrThrow(int_repr_out::name, int_repr_out::overload_name) |
| 15858 | .typed<int_repr_out::schema>(); |
| 15859 | } |
| 15860 | |
| 15861 | // aten::int_repr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 15862 | at::Tensor & int_repr_out::call(const at::Tensor & self, at::Tensor & out) { |
| 15863 | |
| 15864 | static auto op = create_int_repr_out_typed_handle(); |
| 15865 | return op.call(self, out); |
| 15866 | } |
| 15867 | |
| 15868 | // aten::int_repr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 15869 | at::Tensor & int_repr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 15870 | |
| 15871 | static auto op = create_int_repr_out_typed_handle(); |
| 15872 | return op.redispatch(dispatchKeySet, self, out); |
| 15873 | } |
| 15874 | |
| 15875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask_out, name, "aten::fake_quantize_per_channel_affine_cachemask") |
| 15876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask_out, overload_name, "out") |
| 15877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask_out, schema_str, "fake_quantize_per_channel_affine_cachemask.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 15878 | |
| 15879 | // aten::fake_quantize_per_channel_affine_cachemask.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15880 | static C10_NOINLINE c10::TypedOperatorHandle<fake_quantize_per_channel_affine_cachemask_out::schema> create_fake_quantize_per_channel_affine_cachemask_out_typed_handle() { |
| 15881 | return c10::Dispatcher::singleton() |
| 15882 | .findSchemaOrThrow(fake_quantize_per_channel_affine_cachemask_out::name, fake_quantize_per_channel_affine_cachemask_out::overload_name) |
| 15883 | .typed<fake_quantize_per_channel_affine_cachemask_out::schema>(); |
| 15884 | } |
| 15885 | |
| 15886 | // aten::fake_quantize_per_channel_affine_cachemask.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15887 | ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_channel_affine_cachemask_out::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { |
| 15888 | |
| 15889 | static auto op = create_fake_quantize_per_channel_affine_cachemask_out_typed_handle(); |
| 15890 | return op.call(self, scale, zero_point, axis, quant_min, quant_max, out0, out1); |
| 15891 | } |
| 15892 | |
| 15893 | // aten::fake_quantize_per_channel_affine_cachemask.out(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 15894 | ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_channel_affine_cachemask_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { |
| 15895 | |
| 15896 | static auto op = create_fake_quantize_per_channel_affine_cachemask_out_typed_handle(); |
| 15897 | return op.redispatch(dispatchKeySet, self, scale, zero_point, axis, quant_min, quant_max, out0, out1); |
| 15898 | } |
| 15899 | |
| 15900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper_out, name, "aten::_fused_moving_avg_obs_fq_helper") |
| 15901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper_out, overload_name, "out") |
| 15902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper_out, schema_str, "_fused_moving_avg_obs_fq_helper.out(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False, *, Tensor(e!) out0, Tensor(f!) out1) -> (Tensor(e!), Tensor(f!))") |
| 15903 | |
| 15904 | // aten::_fused_moving_avg_obs_fq_helper.out(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False, *, Tensor(e!) out0, Tensor(f!) out1) -> (Tensor(e!), Tensor(f!)) |
| 15905 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_moving_avg_obs_fq_helper_out::schema> create__fused_moving_avg_obs_fq_helper_out_typed_handle() { |
| 15906 | return c10::Dispatcher::singleton() |
| 15907 | .findSchemaOrThrow(_fused_moving_avg_obs_fq_helper_out::name, _fused_moving_avg_obs_fq_helper_out::overload_name) |
| 15908 | .typed<_fused_moving_avg_obs_fq_helper_out::schema>(); |
| 15909 | } |
| 15910 | |
| 15911 | // aten::_fused_moving_avg_obs_fq_helper.out(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False, *, Tensor(e!) out0, Tensor(f!) out1) -> (Tensor(e!), Tensor(f!)) |
| 15912 | ::std::tuple<at::Tensor &,at::Tensor &> _fused_moving_avg_obs_fq_helper_out::call(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant, at::Tensor & out0, at::Tensor & out1) { |
| 15913 | |
| 15914 | static auto op = create__fused_moving_avg_obs_fq_helper_out_typed_handle(); |
| 15915 | return op.call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant, out0, out1); |
| 15916 | } |
| 15917 | |
| 15918 | // aten::_fused_moving_avg_obs_fq_helper.out(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor(a!) running_min, Tensor(b!) running_max, Tensor(c!) scale, Tensor(d!) zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False, *, Tensor(e!) out0, Tensor(f!) out1) -> (Tensor(e!), Tensor(f!)) |
| 15919 | ::std::tuple<at::Tensor &,at::Tensor &> _fused_moving_avg_obs_fq_helper_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, at::Tensor & running_min, at::Tensor & running_max, at::Tensor & scale, at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant, at::Tensor & out0, at::Tensor & out1) { |
| 15920 | |
| 15921 | static auto op = create__fused_moving_avg_obs_fq_helper_out_typed_handle(); |
| 15922 | return op.redispatch(dispatchKeySet, self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant, out0, out1); |
| 15923 | } |
| 15924 | |
| 15925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper_functional, name, "aten::_fused_moving_avg_obs_fq_helper_functional") |
| 15926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper_functional, overload_name, "") |
| 15927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_moving_avg_obs_fq_helper_functional, schema_str, "_fused_moving_avg_obs_fq_helper_functional(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor running_min, Tensor running_max, Tensor scale, Tensor zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask, Tensor running_min_out, Tensor running_max_out, Tensor scale_out, Tensor zero_point_out)") |
| 15928 | |
| 15929 | // aten::_fused_moving_avg_obs_fq_helper_functional(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor running_min, Tensor running_max, Tensor scale, Tensor zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask, Tensor running_min_out, Tensor running_max_out, Tensor scale_out, Tensor zero_point_out) |
| 15930 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_moving_avg_obs_fq_helper_functional::schema> create__fused_moving_avg_obs_fq_helper_functional_typed_handle() { |
| 15931 | return c10::Dispatcher::singleton() |
| 15932 | .findSchemaOrThrow(_fused_moving_avg_obs_fq_helper_functional::name, _fused_moving_avg_obs_fq_helper_functional::overload_name) |
| 15933 | .typed<_fused_moving_avg_obs_fq_helper_functional::schema>(); |
| 15934 | } |
| 15935 | |
| 15936 | // aten::_fused_moving_avg_obs_fq_helper_functional(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor running_min, Tensor running_max, Tensor scale, Tensor zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask, Tensor running_min_out, Tensor running_max_out, Tensor scale_out, Tensor zero_point_out) |
| 15937 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _fused_moving_avg_obs_fq_helper_functional::call(const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, const at::Tensor & running_min, const at::Tensor & running_max, const at::Tensor & scale, const at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant) { |
| 15938 | |
| 15939 | static auto op = create__fused_moving_avg_obs_fq_helper_functional_typed_handle(); |
| 15940 | return op.call(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); |
| 15941 | } |
| 15942 | |
| 15943 | // aten::_fused_moving_avg_obs_fq_helper_functional(Tensor self, Tensor observer_on, Tensor fake_quant_on, Tensor running_min, Tensor running_max, Tensor scale, Tensor zero_point, float averaging_const, int quant_min, int quant_max, int ch_axis, bool per_row_fake_quant=False, bool symmetric_quant=False) -> (Tensor output, Tensor mask, Tensor running_min_out, Tensor running_max_out, Tensor scale_out, Tensor zero_point_out) |
| 15944 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _fused_moving_avg_obs_fq_helper_functional::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & observer_on, const at::Tensor & fake_quant_on, const at::Tensor & running_min, const at::Tensor & running_max, const at::Tensor & scale, const at::Tensor & zero_point, double averaging_const, int64_t quant_min, int64_t quant_max, int64_t ch_axis, bool per_row_fake_quant, bool symmetric_quant) { |
| 15945 | |
| 15946 | static auto op = create__fused_moving_avg_obs_fq_helper_functional_typed_handle(); |
| 15947 | return op.redispatch(dispatchKeySet, self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); |
| 15948 | } |
| 15949 | |
| 15950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_copy_out, name, "aten::_to_copy") |
| 15951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_copy_out, overload_name, "out") |
| 15952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_copy_out, schema_str, "_to_copy.out(Tensor self, *, bool non_blocking=False, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)") |
| 15953 | |
| 15954 | // aten::_to_copy.out(Tensor self, *, bool non_blocking=False, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 15955 | static C10_NOINLINE c10::TypedOperatorHandle<_to_copy_out::schema> create__to_copy_out_typed_handle() { |
| 15956 | return c10::Dispatcher::singleton() |
| 15957 | .findSchemaOrThrow(_to_copy_out::name, _to_copy_out::overload_name) |
| 15958 | .typed<_to_copy_out::schema>(); |
| 15959 | } |
| 15960 | |
| 15961 | // aten::_to_copy.out(Tensor self, *, bool non_blocking=False, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 15962 | at::Tensor & _to_copy_out::call(const at::Tensor & self, bool non_blocking, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
| 15963 | |
| 15964 | static auto op = create__to_copy_out_typed_handle(); |
| 15965 | return op.call(self, non_blocking, memory_format, out); |
| 15966 | } |
| 15967 | |
| 15968 | // aten::_to_copy.out(Tensor self, *, bool non_blocking=False, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 15969 | at::Tensor & _to_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
| 15970 | |
| 15971 | static auto op = create__to_copy_out_typed_handle(); |
| 15972 | return op.redispatch(dispatchKeySet, self, non_blocking, memory_format, out); |
| 15973 | } |
| 15974 | |
| 15975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift_out, name, "aten::lift") |
| 15976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift_out, overload_name, "out") |
| 15977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lift_out, schema_str, "lift.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 15978 | |
| 15979 | // aten::lift.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 15980 | static C10_NOINLINE c10::TypedOperatorHandle<lift_out::schema> create_lift_out_typed_handle() { |
| 15981 | return c10::Dispatcher::singleton() |
| 15982 | .findSchemaOrThrow(lift_out::name, lift_out::overload_name) |
| 15983 | .typed<lift_out::schema>(); |
| 15984 | } |
| 15985 | |
| 15986 | // aten::lift.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 15987 | at::Tensor & lift_out::call(const at::Tensor & self, at::Tensor & out) { |
| 15988 | |
| 15989 | static auto op = create_lift_out_typed_handle(); |
| 15990 | return op.call(self, out); |
| 15991 | } |
| 15992 | |
| 15993 | // aten::lift.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 15994 | at::Tensor & lift_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 15995 | |
| 15996 | static auto op = create_lift_out_typed_handle(); |
| 15997 | return op.redispatch(dispatchKeySet, self, out); |
| 15998 | } |
| 15999 | |
| 16000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_Tensor_out, name, "aten::bitwise_and") |
| 16001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_Tensor_out, overload_name, "Scalar_Tensor_out") |
| 16002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_and_Scalar_Tensor_out, schema_str, "bitwise_and.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16003 | |
| 16004 | // aten::bitwise_and.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16005 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_and_Scalar_Tensor_out::schema> create_bitwise_and_Scalar_Tensor_out_typed_handle() { |
| 16006 | return c10::Dispatcher::singleton() |
| 16007 | .findSchemaOrThrow(bitwise_and_Scalar_Tensor_out::name, bitwise_and_Scalar_Tensor_out::overload_name) |
| 16008 | .typed<bitwise_and_Scalar_Tensor_out::schema>(); |
| 16009 | } |
| 16010 | |
| 16011 | // aten::bitwise_and.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16012 | at::Tensor & bitwise_and_Scalar_Tensor_out::call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16013 | |
| 16014 | static auto op = create_bitwise_and_Scalar_Tensor_out_typed_handle(); |
| 16015 | return op.call(self, other, out); |
| 16016 | } |
| 16017 | |
| 16018 | // aten::bitwise_and.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16019 | at::Tensor & bitwise_and_Scalar_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16020 | |
| 16021 | static auto op = create_bitwise_and_Scalar_Tensor_out_typed_handle(); |
| 16022 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16023 | } |
| 16024 | |
| 16025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_Tensor_out, name, "aten::bitwise_xor") |
| 16026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_Tensor_out, overload_name, "Scalar_Tensor_out") |
| 16027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_xor_Scalar_Tensor_out, schema_str, "bitwise_xor.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16028 | |
| 16029 | // aten::bitwise_xor.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16030 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_xor_Scalar_Tensor_out::schema> create_bitwise_xor_Scalar_Tensor_out_typed_handle() { |
| 16031 | return c10::Dispatcher::singleton() |
| 16032 | .findSchemaOrThrow(bitwise_xor_Scalar_Tensor_out::name, bitwise_xor_Scalar_Tensor_out::overload_name) |
| 16033 | .typed<bitwise_xor_Scalar_Tensor_out::schema>(); |
| 16034 | } |
| 16035 | |
| 16036 | // aten::bitwise_xor.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16037 | at::Tensor & bitwise_xor_Scalar_Tensor_out::call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16038 | |
| 16039 | static auto op = create_bitwise_xor_Scalar_Tensor_out_typed_handle(); |
| 16040 | return op.call(self, other, out); |
| 16041 | } |
| 16042 | |
| 16043 | // aten::bitwise_xor.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16044 | at::Tensor & bitwise_xor_Scalar_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16045 | |
| 16046 | static auto op = create_bitwise_xor_Scalar_Tensor_out_typed_handle(); |
| 16047 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16048 | } |
| 16049 | |
| 16050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Scalar_out, name, "aten::__lshift__") |
| 16051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Scalar_out, overload_name, "Scalar_out") |
| 16052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Scalar_out, schema_str, "__lshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16053 | |
| 16054 | // aten::__lshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 16055 | static C10_NOINLINE c10::TypedOperatorHandle<__lshift___Scalar_out::schema> create___lshift___Scalar_out_typed_handle() { |
| 16056 | return c10::Dispatcher::singleton() |
| 16057 | .findSchemaOrThrow(__lshift___Scalar_out::name, __lshift___Scalar_out::overload_name) |
| 16058 | .typed<__lshift___Scalar_out::schema>(); |
| 16059 | } |
| 16060 | |
| 16061 | // aten::__lshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 16062 | at::Tensor & __lshift___Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 16063 | |
| 16064 | static auto op = create___lshift___Scalar_out_typed_handle(); |
| 16065 | return op.call(self, other, out); |
| 16066 | } |
| 16067 | |
| 16068 | // aten::__lshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 16069 | at::Tensor & __lshift___Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 16070 | |
| 16071 | static auto op = create___lshift___Scalar_out_typed_handle(); |
| 16072 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16073 | } |
| 16074 | |
| 16075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Tensor_out, name, "aten::__lshift__") |
| 16076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Tensor_out, overload_name, "Tensor_out") |
| 16077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__lshift___Tensor_out, schema_str, "__lshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16078 | |
| 16079 | // aten::__lshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16080 | static C10_NOINLINE c10::TypedOperatorHandle<__lshift___Tensor_out::schema> create___lshift___Tensor_out_typed_handle() { |
| 16081 | return c10::Dispatcher::singleton() |
| 16082 | .findSchemaOrThrow(__lshift___Tensor_out::name, __lshift___Tensor_out::overload_name) |
| 16083 | .typed<__lshift___Tensor_out::schema>(); |
| 16084 | } |
| 16085 | |
| 16086 | // aten::__lshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16087 | at::Tensor & __lshift___Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 16088 | |
| 16089 | static auto op = create___lshift___Tensor_out_typed_handle(); |
| 16090 | return op.call(self, other, out); |
| 16091 | } |
| 16092 | |
| 16093 | // aten::__lshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16094 | at::Tensor & __lshift___Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 16095 | |
| 16096 | static auto op = create___lshift___Tensor_out_typed_handle(); |
| 16097 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16098 | } |
| 16099 | |
| 16100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Scalar_Tensor_out, name, "aten::bitwise_left_shift") |
| 16101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Scalar_Tensor_out, overload_name, "Scalar_Tensor_out") |
| 16102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_left_shift_Scalar_Tensor_out, schema_str, "bitwise_left_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16103 | |
| 16104 | // aten::bitwise_left_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16105 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_left_shift_Scalar_Tensor_out::schema> create_bitwise_left_shift_Scalar_Tensor_out_typed_handle() { |
| 16106 | return c10::Dispatcher::singleton() |
| 16107 | .findSchemaOrThrow(bitwise_left_shift_Scalar_Tensor_out::name, bitwise_left_shift_Scalar_Tensor_out::overload_name) |
| 16108 | .typed<bitwise_left_shift_Scalar_Tensor_out::schema>(); |
| 16109 | } |
| 16110 | |
| 16111 | // aten::bitwise_left_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16112 | at::Tensor & bitwise_left_shift_Scalar_Tensor_out::call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16113 | |
| 16114 | static auto op = create_bitwise_left_shift_Scalar_Tensor_out_typed_handle(); |
| 16115 | return op.call(self, other, out); |
| 16116 | } |
| 16117 | |
| 16118 | // aten::bitwise_left_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16119 | at::Tensor & bitwise_left_shift_Scalar_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16120 | |
| 16121 | static auto op = create_bitwise_left_shift_Scalar_Tensor_out_typed_handle(); |
| 16122 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16123 | } |
| 16124 | |
| 16125 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Scalar_out, name, "aten::__rshift__") |
| 16126 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Scalar_out, overload_name, "Scalar_out") |
| 16127 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Scalar_out, schema_str, "__rshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16128 | |
| 16129 | // aten::__rshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 16130 | static C10_NOINLINE c10::TypedOperatorHandle<__rshift___Scalar_out::schema> create___rshift___Scalar_out_typed_handle() { |
| 16131 | return c10::Dispatcher::singleton() |
| 16132 | .findSchemaOrThrow(__rshift___Scalar_out::name, __rshift___Scalar_out::overload_name) |
| 16133 | .typed<__rshift___Scalar_out::schema>(); |
| 16134 | } |
| 16135 | |
| 16136 | // aten::__rshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 16137 | at::Tensor & __rshift___Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 16138 | |
| 16139 | static auto op = create___rshift___Scalar_out_typed_handle(); |
| 16140 | return op.call(self, other, out); |
| 16141 | } |
| 16142 | |
| 16143 | // aten::__rshift__.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 16144 | at::Tensor & __rshift___Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 16145 | |
| 16146 | static auto op = create___rshift___Scalar_out_typed_handle(); |
| 16147 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16148 | } |
| 16149 | |
| 16150 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Tensor_out, name, "aten::__rshift__") |
| 16151 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Tensor_out, overload_name, "Tensor_out") |
| 16152 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__rshift___Tensor_out, schema_str, "__rshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16153 | |
| 16154 | // aten::__rshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16155 | static C10_NOINLINE c10::TypedOperatorHandle<__rshift___Tensor_out::schema> create___rshift___Tensor_out_typed_handle() { |
| 16156 | return c10::Dispatcher::singleton() |
| 16157 | .findSchemaOrThrow(__rshift___Tensor_out::name, __rshift___Tensor_out::overload_name) |
| 16158 | .typed<__rshift___Tensor_out::schema>(); |
| 16159 | } |
| 16160 | |
| 16161 | // aten::__rshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16162 | at::Tensor & __rshift___Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 16163 | |
| 16164 | static auto op = create___rshift___Tensor_out_typed_handle(); |
| 16165 | return op.call(self, other, out); |
| 16166 | } |
| 16167 | |
| 16168 | // aten::__rshift__.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16169 | at::Tensor & __rshift___Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 16170 | |
| 16171 | static auto op = create___rshift___Tensor_out_typed_handle(); |
| 16172 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16173 | } |
| 16174 | |
| 16175 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Scalar_Tensor_out, name, "aten::bitwise_right_shift") |
| 16176 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Scalar_Tensor_out, overload_name, "Scalar_Tensor_out") |
| 16177 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_right_shift_Scalar_Tensor_out, schema_str, "bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 16178 | |
| 16179 | // aten::bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16180 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_right_shift_Scalar_Tensor_out::schema> create_bitwise_right_shift_Scalar_Tensor_out_typed_handle() { |
| 16181 | return c10::Dispatcher::singleton() |
| 16182 | .findSchemaOrThrow(bitwise_right_shift_Scalar_Tensor_out::name, bitwise_right_shift_Scalar_Tensor_out::overload_name) |
| 16183 | .typed<bitwise_right_shift_Scalar_Tensor_out::schema>(); |
| 16184 | } |
| 16185 | |
| 16186 | // aten::bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16187 | at::Tensor & bitwise_right_shift_Scalar_Tensor_out::call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16188 | |
| 16189 | static auto op = create_bitwise_right_shift_Scalar_Tensor_out_typed_handle(); |
| 16190 | return op.call(self, other, out); |
| 16191 | } |
| 16192 | |
| 16193 | // aten::bitwise_right_shift.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 16194 | at::Tensor & bitwise_right_shift_Scalar_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 16195 | |
| 16196 | static auto op = create_bitwise_right_shift_Scalar_Tensor_out_typed_handle(); |
| 16197 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16198 | } |
| 16199 | |
| 16200 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential_out, name, "aten::exponential") |
| 16201 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential_out, overload_name, "out") |
| 16202 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential_out, schema_str, "exponential.out(Tensor self, float lambd=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)") |
| 16203 | |
| 16204 | // aten::exponential.out(Tensor self, float lambd=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 16205 | static C10_NOINLINE c10::TypedOperatorHandle<exponential_out::schema> create_exponential_out_typed_handle() { |
| 16206 | return c10::Dispatcher::singleton() |
| 16207 | .findSchemaOrThrow(exponential_out::name, exponential_out::overload_name) |
| 16208 | .typed<exponential_out::schema>(); |
| 16209 | } |
| 16210 | |
| 16211 | // aten::exponential.out(Tensor self, float lambd=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 16212 | at::Tensor & exponential_out::call(const at::Tensor & self, double lambd, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 16213 | |
| 16214 | static auto op = create_exponential_out_typed_handle(); |
| 16215 | return op.call(self, lambd, generator, out); |
| 16216 | } |
| 16217 | |
| 16218 | // aten::exponential.out(Tensor self, float lambd=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 16219 | at::Tensor & exponential_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double lambd, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 16220 | |
| 16221 | static auto op = create_exponential_out_typed_handle(); |
| 16222 | return op.redispatch(dispatchKeySet, self, lambd, generator, out); |
| 16223 | } |
| 16224 | |
| 16225 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential, name, "aten::exponential") |
| 16226 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential, overload_name, "") |
| 16227 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exponential, schema_str, "exponential(Tensor self, float lambd=1, *, Generator? generator=None) -> Tensor") |
| 16228 | |
| 16229 | // aten::exponential(Tensor self, float lambd=1, *, Generator? generator=None) -> Tensor |
| 16230 | static C10_NOINLINE c10::TypedOperatorHandle<exponential::schema> create_exponential_typed_handle() { |
| 16231 | return c10::Dispatcher::singleton() |
| 16232 | .findSchemaOrThrow(exponential::name, exponential::overload_name) |
| 16233 | .typed<exponential::schema>(); |
| 16234 | } |
| 16235 | |
| 16236 | // aten::exponential(Tensor self, float lambd=1, *, Generator? generator=None) -> Tensor |
| 16237 | at::Tensor exponential::call(const at::Tensor & self, double lambd, c10::optional<at::Generator> generator) { |
| 16238 | |
| 16239 | static auto op = create_exponential_typed_handle(); |
| 16240 | return op.call(self, lambd, generator); |
| 16241 | } |
| 16242 | |
| 16243 | // aten::exponential(Tensor self, float lambd=1, *, Generator? generator=None) -> Tensor |
| 16244 | at::Tensor exponential::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double lambd, c10::optional<at::Generator> generator) { |
| 16245 | |
| 16246 | static auto op = create_exponential_typed_handle(); |
| 16247 | return op.redispatch(dispatchKeySet, self, lambd, generator); |
| 16248 | } |
| 16249 | |
| 16250 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric_out, name, "aten::geometric") |
| 16251 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric_out, overload_name, "out") |
| 16252 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric_out, schema_str, "geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)") |
| 16253 | |
| 16254 | // aten::geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 16255 | static C10_NOINLINE c10::TypedOperatorHandle<geometric_out::schema> create_geometric_out_typed_handle() { |
| 16256 | return c10::Dispatcher::singleton() |
| 16257 | .findSchemaOrThrow(geometric_out::name, geometric_out::overload_name) |
| 16258 | .typed<geometric_out::schema>(); |
| 16259 | } |
| 16260 | |
| 16261 | // aten::geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 16262 | at::Tensor & geometric_out::call(const at::Tensor & self, double p, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 16263 | |
| 16264 | static auto op = create_geometric_out_typed_handle(); |
| 16265 | return op.call(self, p, generator, out); |
| 16266 | } |
| 16267 | |
| 16268 | // aten::geometric.out(Tensor self, float p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
| 16269 | at::Tensor & geometric_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 16270 | |
| 16271 | static auto op = create_geometric_out_typed_handle(); |
| 16272 | return op.redispatch(dispatchKeySet, self, p, generator, out); |
| 16273 | } |
| 16274 | |
| 16275 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric, name, "aten::geometric") |
| 16276 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric, overload_name, "") |
| 16277 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geometric, schema_str, "geometric(Tensor self, float p, *, Generator? generator=None) -> Tensor") |
| 16278 | |
| 16279 | // aten::geometric(Tensor self, float p, *, Generator? generator=None) -> Tensor |
| 16280 | static C10_NOINLINE c10::TypedOperatorHandle<geometric::schema> create_geometric_typed_handle() { |
| 16281 | return c10::Dispatcher::singleton() |
| 16282 | .findSchemaOrThrow(geometric::name, geometric::overload_name) |
| 16283 | .typed<geometric::schema>(); |
| 16284 | } |
| 16285 | |
| 16286 | // aten::geometric(Tensor self, float p, *, Generator? generator=None) -> Tensor |
| 16287 | at::Tensor geometric::call(const at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
| 16288 | |
| 16289 | static auto op = create_geometric_typed_handle(); |
| 16290 | return op.call(self, p, generator); |
| 16291 | } |
| 16292 | |
| 16293 | // aten::geometric(Tensor self, float p, *, Generator? generator=None) -> Tensor |
| 16294 | at::Tensor geometric::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
| 16295 | |
| 16296 | static auto op = create_geometric_typed_handle(); |
| 16297 | return op.redispatch(dispatchKeySet, self, p, generator); |
| 16298 | } |
| 16299 | |
| 16300 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale_out, name, "aten::_amp_foreach_non_finite_check_and_unscale") |
| 16301 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale_out, overload_name, "out") |
| 16302 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale_out, schema_str, "_amp_foreach_non_finite_check_and_unscale.out(Tensor[] self, Tensor(b!) found_inf, Tensor inv_scale, *, Tensor(a!)[] out) -> ()") |
| 16303 | |
| 16304 | // aten::_amp_foreach_non_finite_check_and_unscale.out(Tensor[] self, Tensor(b!) found_inf, Tensor inv_scale, *, Tensor(a!)[] out) -> () |
| 16305 | static C10_NOINLINE c10::TypedOperatorHandle<_amp_foreach_non_finite_check_and_unscale_out::schema> create__amp_foreach_non_finite_check_and_unscale_out_typed_handle() { |
| 16306 | return c10::Dispatcher::singleton() |
| 16307 | .findSchemaOrThrow(_amp_foreach_non_finite_check_and_unscale_out::name, _amp_foreach_non_finite_check_and_unscale_out::overload_name) |
| 16308 | .typed<_amp_foreach_non_finite_check_and_unscale_out::schema>(); |
| 16309 | } |
| 16310 | |
| 16311 | // aten::_amp_foreach_non_finite_check_and_unscale.out(Tensor[] self, Tensor(b!) found_inf, Tensor inv_scale, *, Tensor(a!)[] out) -> () |
| 16312 | void _amp_foreach_non_finite_check_and_unscale_out::call(at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale, at::TensorList out) { |
| 16313 | |
| 16314 | static auto op = create__amp_foreach_non_finite_check_and_unscale_out_typed_handle(); |
| 16315 | return op.call(self, found_inf, inv_scale, out); |
| 16316 | } |
| 16317 | |
| 16318 | // aten::_amp_foreach_non_finite_check_and_unscale.out(Tensor[] self, Tensor(b!) found_inf, Tensor inv_scale, *, Tensor(a!)[] out) -> () |
| 16319 | void _amp_foreach_non_finite_check_and_unscale_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::Tensor & found_inf, const at::Tensor & inv_scale, at::TensorList out) { |
| 16320 | |
| 16321 | static auto op = create__amp_foreach_non_finite_check_and_unscale_out_typed_handle(); |
| 16322 | return op.redispatch(dispatchKeySet, self, found_inf, inv_scale, out); |
| 16323 | } |
| 16324 | |
| 16325 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale, name, "aten::_amp_foreach_non_finite_check_and_unscale") |
| 16326 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale, overload_name, "") |
| 16327 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_foreach_non_finite_check_and_unscale, schema_str, "_amp_foreach_non_finite_check_and_unscale(Tensor[] self, Tensor found_inf, Tensor inv_scale) -> (Tensor[] self_out, Tensor found_inf_out)") |
| 16328 | |
| 16329 | // aten::_amp_foreach_non_finite_check_and_unscale(Tensor[] self, Tensor found_inf, Tensor inv_scale) -> (Tensor[] self_out, Tensor found_inf_out) |
| 16330 | static C10_NOINLINE c10::TypedOperatorHandle<_amp_foreach_non_finite_check_and_unscale::schema> create__amp_foreach_non_finite_check_and_unscale_typed_handle() { |
| 16331 | return c10::Dispatcher::singleton() |
| 16332 | .findSchemaOrThrow(_amp_foreach_non_finite_check_and_unscale::name, _amp_foreach_non_finite_check_and_unscale::overload_name) |
| 16333 | .typed<_amp_foreach_non_finite_check_and_unscale::schema>(); |
| 16334 | } |
| 16335 | |
| 16336 | // aten::_amp_foreach_non_finite_check_and_unscale(Tensor[] self, Tensor found_inf, Tensor inv_scale) -> (Tensor[] self_out, Tensor found_inf_out) |
| 16337 | ::std::tuple<::std::vector<at::Tensor>,at::Tensor> _amp_foreach_non_finite_check_and_unscale::call(at::TensorList self, const at::Tensor & found_inf, const at::Tensor & inv_scale) { |
| 16338 | |
| 16339 | static auto op = create__amp_foreach_non_finite_check_and_unscale_typed_handle(); |
| 16340 | return op.call(self, found_inf, inv_scale); |
| 16341 | } |
| 16342 | |
| 16343 | // aten::_amp_foreach_non_finite_check_and_unscale(Tensor[] self, Tensor found_inf, Tensor inv_scale) -> (Tensor[] self_out, Tensor found_inf_out) |
| 16344 | ::std::tuple<::std::vector<at::Tensor>,at::Tensor> _amp_foreach_non_finite_check_and_unscale::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Tensor & found_inf, const at::Tensor & inv_scale) { |
| 16345 | |
| 16346 | static auto op = create__amp_foreach_non_finite_check_and_unscale_typed_handle(); |
| 16347 | return op.redispatch(dispatchKeySet, self, found_inf, inv_scale); |
| 16348 | } |
| 16349 | |
| 16350 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_Scalar_out, name, "aten::_foreach_add") |
| 16351 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_Scalar_out, overload_name, "Scalar_out") |
| 16352 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_Scalar_out, schema_str, "_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()") |
| 16353 | |
| 16354 | // aten::_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16355 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add_Scalar_out::schema> create__foreach_add_Scalar_out_typed_handle() { |
| 16356 | return c10::Dispatcher::singleton() |
| 16357 | .findSchemaOrThrow(_foreach_add_Scalar_out::name, _foreach_add_Scalar_out::overload_name) |
| 16358 | .typed<_foreach_add_Scalar_out::schema>(); |
| 16359 | } |
| 16360 | |
| 16361 | // aten::_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16362 | void _foreach_add_Scalar_out::call(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 16363 | |
| 16364 | static auto op = create__foreach_add_Scalar_out_typed_handle(); |
| 16365 | return op.call(self, scalar, out); |
| 16366 | } |
| 16367 | |
| 16368 | // aten::_foreach_add.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16369 | void _foreach_add_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 16370 | |
| 16371 | static auto op = create__foreach_add_Scalar_out_typed_handle(); |
| 16372 | return op.redispatch(dispatchKeySet, self, scalar, out); |
| 16373 | } |
| 16374 | |
| 16375 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_Scalar_out, name, "aten::_foreach_clamp_min") |
| 16376 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_Scalar_out, overload_name, "Scalar_out") |
| 16377 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_Scalar_out, schema_str, "_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()") |
| 16378 | |
| 16379 | // aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16380 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min_Scalar_out::schema> create__foreach_clamp_min_Scalar_out_typed_handle() { |
| 16381 | return c10::Dispatcher::singleton() |
| 16382 | .findSchemaOrThrow(_foreach_clamp_min_Scalar_out::name, _foreach_clamp_min_Scalar_out::overload_name) |
| 16383 | .typed<_foreach_clamp_min_Scalar_out::schema>(); |
| 16384 | } |
| 16385 | |
| 16386 | // aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16387 | void _foreach_clamp_min_Scalar_out::call(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 16388 | |
| 16389 | static auto op = create__foreach_clamp_min_Scalar_out_typed_handle(); |
| 16390 | return op.call(self, scalar, out); |
| 16391 | } |
| 16392 | |
| 16393 | // aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16394 | void _foreach_clamp_min_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 16395 | |
| 16396 | static auto op = create__foreach_clamp_min_Scalar_out_typed_handle(); |
| 16397 | return op.redispatch(dispatchKeySet, self, scalar, out); |
| 16398 | } |
| 16399 | |
| 16400 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_Scalar_out, name, "aten::_foreach_minimum") |
| 16401 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_Scalar_out, overload_name, "Scalar_out") |
| 16402 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_Scalar_out, schema_str, "_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()") |
| 16403 | |
| 16404 | // aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16405 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum_Scalar_out::schema> create__foreach_minimum_Scalar_out_typed_handle() { |
| 16406 | return c10::Dispatcher::singleton() |
| 16407 | .findSchemaOrThrow(_foreach_minimum_Scalar_out::name, _foreach_minimum_Scalar_out::overload_name) |
| 16408 | .typed<_foreach_minimum_Scalar_out::schema>(); |
| 16409 | } |
| 16410 | |
| 16411 | // aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16412 | void _foreach_minimum_Scalar_out::call(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 16413 | |
| 16414 | static auto op = create__foreach_minimum_Scalar_out_typed_handle(); |
| 16415 | return op.call(self, scalar, out); |
| 16416 | } |
| 16417 | |
| 16418 | // aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 16419 | void _foreach_minimum_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 16420 | |
| 16421 | static auto op = create__foreach_minimum_Scalar_out_typed_handle(); |
| 16422 | return op.redispatch(dispatchKeySet, self, scalar, out); |
| 16423 | } |
| 16424 | |
| 16425 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_List_out, name, "aten::_foreach_add") |
| 16426 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_List_out, overload_name, "List_out") |
| 16427 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_List_out, schema_str, "_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> ()") |
| 16428 | |
| 16429 | // aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () |
| 16430 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add_List_out::schema> create__foreach_add_List_out_typed_handle() { |
| 16431 | return c10::Dispatcher::singleton() |
| 16432 | .findSchemaOrThrow(_foreach_add_List_out::name, _foreach_add_List_out::overload_name) |
| 16433 | .typed<_foreach_add_List_out::schema>(); |
| 16434 | } |
| 16435 | |
| 16436 | // aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () |
| 16437 | void _foreach_add_List_out::call(at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out) { |
| 16438 | |
| 16439 | static auto op = create__foreach_add_List_out_typed_handle(); |
| 16440 | return op.call(self, other, alpha, out); |
| 16441 | } |
| 16442 | |
| 16443 | // aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () |
| 16444 | void _foreach_add_List_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, const at::Scalar & alpha, at::TensorList out) { |
| 16445 | |
| 16446 | static auto op = create__foreach_add_List_out_typed_handle(); |
| 16447 | return op.redispatch(dispatchKeySet, self, other, alpha, out); |
| 16448 | } |
| 16449 | |
| 16450 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_List_out, name, "aten::_foreach_clamp_min") |
| 16451 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_List_out, overload_name, "List_out") |
| 16452 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_List_out, schema_str, "_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()") |
| 16453 | |
| 16454 | // aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 16455 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min_List_out::schema> create__foreach_clamp_min_List_out_typed_handle() { |
| 16456 | return c10::Dispatcher::singleton() |
| 16457 | .findSchemaOrThrow(_foreach_clamp_min_List_out::name, _foreach_clamp_min_List_out::overload_name) |
| 16458 | .typed<_foreach_clamp_min_List_out::schema>(); |
| 16459 | } |
| 16460 | |
| 16461 | // aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 16462 | void _foreach_clamp_min_List_out::call(at::TensorList self, at::TensorList other, at::TensorList out) { |
| 16463 | |
| 16464 | static auto op = create__foreach_clamp_min_List_out_typed_handle(); |
| 16465 | return op.call(self, other, out); |
| 16466 | } |
| 16467 | |
| 16468 | // aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 16469 | void _foreach_clamp_min_List_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out) { |
| 16470 | |
| 16471 | static auto op = create__foreach_clamp_min_List_out_typed_handle(); |
| 16472 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16473 | } |
| 16474 | |
| 16475 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_List_out, name, "aten::_foreach_minimum") |
| 16476 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_List_out, overload_name, "List_out") |
| 16477 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_List_out, schema_str, "_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()") |
| 16478 | |
| 16479 | // aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 16480 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum_List_out::schema> create__foreach_minimum_List_out_typed_handle() { |
| 16481 | return c10::Dispatcher::singleton() |
| 16482 | .findSchemaOrThrow(_foreach_minimum_List_out::name, _foreach_minimum_List_out::overload_name) |
| 16483 | .typed<_foreach_minimum_List_out::schema>(); |
| 16484 | } |
| 16485 | |
| 16486 | // aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 16487 | void _foreach_minimum_List_out::call(at::TensorList self, at::TensorList other, at::TensorList out) { |
| 16488 | |
| 16489 | static auto op = create__foreach_minimum_List_out_typed_handle(); |
| 16490 | return op.call(self, other, out); |
| 16491 | } |
| 16492 | |
| 16493 | // aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 16494 | void _foreach_minimum_List_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out) { |
| 16495 | |
| 16496 | static auto op = create__foreach_minimum_List_out_typed_handle(); |
| 16497 | return op.redispatch(dispatchKeySet, self, other, out); |
| 16498 | } |
| 16499 | |
| 16500 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_ScalarList_out, name, "aten::_foreach_add") |
| 16501 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_ScalarList_out, overload_name, "ScalarList_out") |
| 16502 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_add_ScalarList_out, schema_str, "_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()") |
| 16503 | |
| 16504 | // aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16505 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_add_ScalarList_out::schema> create__foreach_add_ScalarList_out_typed_handle() { |
| 16506 | return c10::Dispatcher::singleton() |
| 16507 | .findSchemaOrThrow(_foreach_add_ScalarList_out::name, _foreach_add_ScalarList_out::overload_name) |
| 16508 | .typed<_foreach_add_ScalarList_out::schema>(); |
| 16509 | } |
| 16510 | |
| 16511 | // aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16512 | void _foreach_add_ScalarList_out::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 16513 | |
| 16514 | static auto op = create__foreach_add_ScalarList_out_typed_handle(); |
| 16515 | return op.call(self, scalars, out); |
| 16516 | } |
| 16517 | |
| 16518 | // aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16519 | void _foreach_add_ScalarList_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 16520 | |
| 16521 | static auto op = create__foreach_add_ScalarList_out_typed_handle(); |
| 16522 | return op.redispatch(dispatchKeySet, self, scalars, out); |
| 16523 | } |
| 16524 | |
| 16525 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_ScalarList_out, name, "aten::_foreach_clamp_min") |
| 16526 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_ScalarList_out, overload_name, "ScalarList_out") |
| 16527 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_min_ScalarList_out, schema_str, "_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()") |
| 16528 | |
| 16529 | // aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16530 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_min_ScalarList_out::schema> create__foreach_clamp_min_ScalarList_out_typed_handle() { |
| 16531 | return c10::Dispatcher::singleton() |
| 16532 | .findSchemaOrThrow(_foreach_clamp_min_ScalarList_out::name, _foreach_clamp_min_ScalarList_out::overload_name) |
| 16533 | .typed<_foreach_clamp_min_ScalarList_out::schema>(); |
| 16534 | } |
| 16535 | |
| 16536 | // aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16537 | void _foreach_clamp_min_ScalarList_out::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 16538 | |
| 16539 | static auto op = create__foreach_clamp_min_ScalarList_out_typed_handle(); |
| 16540 | return op.call(self, scalars, out); |
| 16541 | } |
| 16542 | |
| 16543 | // aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16544 | void _foreach_clamp_min_ScalarList_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 16545 | |
| 16546 | static auto op = create__foreach_clamp_min_ScalarList_out_typed_handle(); |
| 16547 | return op.redispatch(dispatchKeySet, self, scalars, out); |
| 16548 | } |
| 16549 | |
| 16550 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_ScalarList_out, name, "aten::_foreach_minimum") |
| 16551 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_ScalarList_out, overload_name, "ScalarList_out") |
| 16552 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_minimum_ScalarList_out, schema_str, "_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()") |
| 16553 | |
| 16554 | // aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16555 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_minimum_ScalarList_out::schema> create__foreach_minimum_ScalarList_out_typed_handle() { |
| 16556 | return c10::Dispatcher::singleton() |
| 16557 | .findSchemaOrThrow(_foreach_minimum_ScalarList_out::name, _foreach_minimum_ScalarList_out::overload_name) |
| 16558 | .typed<_foreach_minimum_ScalarList_out::schema>(); |
| 16559 | } |
| 16560 | |
| 16561 | // aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16562 | void _foreach_minimum_ScalarList_out::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 16563 | |
| 16564 | static auto op = create__foreach_minimum_ScalarList_out_typed_handle(); |
| 16565 | return op.call(self, scalars, out); |
| 16566 | } |
| 16567 | |
| 16568 | // aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 16569 | void _foreach_minimum_ScalarList_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 16570 | |
| 16571 | static auto op = create__foreach_minimum_ScalarList_out_typed_handle(); |
| 16572 | return op.redispatch(dispatchKeySet, self, scalars, out); |
| 16573 | } |
| 16574 | |
| 16575 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh_out, name, "aten::_foreach_cosh") |
| 16576 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh_out, overload_name, "out") |
| 16577 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_cosh_out, schema_str, "_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 16578 | |
| 16579 | // aten::_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16580 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_cosh_out::schema> create__foreach_cosh_out_typed_handle() { |
| 16581 | return c10::Dispatcher::singleton() |
| 16582 | .findSchemaOrThrow(_foreach_cosh_out::name, _foreach_cosh_out::overload_name) |
| 16583 | .typed<_foreach_cosh_out::schema>(); |
| 16584 | } |
| 16585 | |
| 16586 | // aten::_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16587 | void _foreach_cosh_out::call(at::TensorList self, at::TensorList out) { |
| 16588 | |
| 16589 | static auto op = create__foreach_cosh_out_typed_handle(); |
| 16590 | return op.call(self, out); |
| 16591 | } |
| 16592 | |
| 16593 | // aten::_foreach_cosh.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16594 | void _foreach_cosh_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 16595 | |
| 16596 | static auto op = create__foreach_cosh_out_typed_handle(); |
| 16597 | return op.redispatch(dispatchKeySet, self, out); |
| 16598 | } |
| 16599 | |
| 16600 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc_out, name, "aten::_foreach_erfc") |
| 16601 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc_out, overload_name, "out") |
| 16602 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_erfc_out, schema_str, "_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 16603 | |
| 16604 | // aten::_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16605 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_erfc_out::schema> create__foreach_erfc_out_typed_handle() { |
| 16606 | return c10::Dispatcher::singleton() |
| 16607 | .findSchemaOrThrow(_foreach_erfc_out::name, _foreach_erfc_out::overload_name) |
| 16608 | .typed<_foreach_erfc_out::schema>(); |
| 16609 | } |
| 16610 | |
| 16611 | // aten::_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16612 | void _foreach_erfc_out::call(at::TensorList self, at::TensorList out) { |
| 16613 | |
| 16614 | static auto op = create__foreach_erfc_out_typed_handle(); |
| 16615 | return op.call(self, out); |
| 16616 | } |
| 16617 | |
| 16618 | // aten::_foreach_erfc.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16619 | void _foreach_erfc_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 16620 | |
| 16621 | static auto op = create__foreach_erfc_out_typed_handle(); |
| 16622 | return op.redispatch(dispatchKeySet, self, out); |
| 16623 | } |
| 16624 | |
| 16625 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round_out, name, "aten::_foreach_round") |
| 16626 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round_out, overload_name, "out") |
| 16627 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_round_out, schema_str, "_foreach_round.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 16628 | |
| 16629 | // aten::_foreach_round.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16630 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_round_out::schema> create__foreach_round_out_typed_handle() { |
| 16631 | return c10::Dispatcher::singleton() |
| 16632 | .findSchemaOrThrow(_foreach_round_out::name, _foreach_round_out::overload_name) |
| 16633 | .typed<_foreach_round_out::schema>(); |
| 16634 | } |
| 16635 | |
| 16636 | // aten::_foreach_round.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16637 | void _foreach_round_out::call(at::TensorList self, at::TensorList out) { |
| 16638 | |
| 16639 | static auto op = create__foreach_round_out_typed_handle(); |
| 16640 | return op.call(self, out); |
| 16641 | } |
| 16642 | |
| 16643 | // aten::_foreach_round.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16644 | void _foreach_round_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 16645 | |
| 16646 | static auto op = create__foreach_round_out_typed_handle(); |
| 16647 | return op.redispatch(dispatchKeySet, self, out); |
| 16648 | } |
| 16649 | |
| 16650 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma_out, name, "aten::_foreach_lgamma") |
| 16651 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma_out, overload_name, "out") |
| 16652 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lgamma_out, schema_str, "_foreach_lgamma.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 16653 | |
| 16654 | // aten::_foreach_lgamma.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16655 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lgamma_out::schema> create__foreach_lgamma_out_typed_handle() { |
| 16656 | return c10::Dispatcher::singleton() |
| 16657 | .findSchemaOrThrow(_foreach_lgamma_out::name, _foreach_lgamma_out::overload_name) |
| 16658 | .typed<_foreach_lgamma_out::schema>(); |
| 16659 | } |
| 16660 | |
| 16661 | // aten::_foreach_lgamma.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16662 | void _foreach_lgamma_out::call(at::TensorList self, at::TensorList out) { |
| 16663 | |
| 16664 | static auto op = create__foreach_lgamma_out_typed_handle(); |
| 16665 | return op.call(self, out); |
| 16666 | } |
| 16667 | |
| 16668 | // aten::_foreach_lgamma.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16669 | void _foreach_lgamma_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 16670 | |
| 16671 | static auto op = create__foreach_lgamma_out_typed_handle(); |
| 16672 | return op.redispatch(dispatchKeySet, self, out); |
| 16673 | } |
| 16674 | |
| 16675 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac_out, name, "aten::_foreach_frac") |
| 16676 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac_out, overload_name, "out") |
| 16677 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_frac_out, schema_str, "_foreach_frac.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 16678 | |
| 16679 | // aten::_foreach_frac.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16680 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_frac_out::schema> create__foreach_frac_out_typed_handle() { |
| 16681 | return c10::Dispatcher::singleton() |
| 16682 | .findSchemaOrThrow(_foreach_frac_out::name, _foreach_frac_out::overload_name) |
| 16683 | .typed<_foreach_frac_out::schema>(); |
| 16684 | } |
| 16685 | |
| 16686 | // aten::_foreach_frac.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16687 | void _foreach_frac_out::call(at::TensorList self, at::TensorList out) { |
| 16688 | |
| 16689 | static auto op = create__foreach_frac_out_typed_handle(); |
| 16690 | return op.call(self, out); |
| 16691 | } |
| 16692 | |
| 16693 | // aten::_foreach_frac.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16694 | void _foreach_frac_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 16695 | |
| 16696 | static auto op = create__foreach_frac_out_typed_handle(); |
| 16697 | return op.redispatch(dispatchKeySet, self, out); |
| 16698 | } |
| 16699 | |
| 16700 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc_out, name, "aten::_foreach_trunc") |
| 16701 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc_out, overload_name, "out") |
| 16702 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_trunc_out, schema_str, "_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 16703 | |
| 16704 | // aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16705 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_trunc_out::schema> create__foreach_trunc_out_typed_handle() { |
| 16706 | return c10::Dispatcher::singleton() |
| 16707 | .findSchemaOrThrow(_foreach_trunc_out::name, _foreach_trunc_out::overload_name) |
| 16708 | .typed<_foreach_trunc_out::schema>(); |
| 16709 | } |
| 16710 | |
| 16711 | // aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16712 | void _foreach_trunc_out::call(at::TensorList self, at::TensorList out) { |
| 16713 | |
| 16714 | static auto op = create__foreach_trunc_out_typed_handle(); |
| 16715 | return op.call(self, out); |
| 16716 | } |
| 16717 | |
| 16718 | // aten::_foreach_trunc.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 16719 | void _foreach_trunc_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 16720 | |
| 16721 | static auto op = create__foreach_trunc_out_typed_handle(); |
| 16722 | return op.redispatch(dispatchKeySet, self, out); |
| 16723 | } |
| 16724 | |
| 16725 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_List_out, name, "aten::_foreach_lerp") |
| 16726 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_List_out, overload_name, "List_out") |
| 16727 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_List_out, schema_str, "_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> ()") |
| 16728 | |
| 16729 | // aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () |
| 16730 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lerp_List_out::schema> create__foreach_lerp_List_out_typed_handle() { |
| 16731 | return c10::Dispatcher::singleton() |
| 16732 | .findSchemaOrThrow(_foreach_lerp_List_out::name, _foreach_lerp_List_out::overload_name) |
| 16733 | .typed<_foreach_lerp_List_out::schema>(); |
| 16734 | } |
| 16735 | |
| 16736 | // aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () |
| 16737 | void _foreach_lerp_List_out::call(at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out) { |
| 16738 | |
| 16739 | static auto op = create__foreach_lerp_List_out_typed_handle(); |
| 16740 | return op.call(self, tensors1, weights, out); |
| 16741 | } |
| 16742 | |
| 16743 | // aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () |
| 16744 | void _foreach_lerp_List_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, at::TensorList weights, at::TensorList out) { |
| 16745 | |
| 16746 | static auto op = create__foreach_lerp_List_out_typed_handle(); |
| 16747 | return op.redispatch(dispatchKeySet, self, tensors1, weights, out); |
| 16748 | } |
| 16749 | |
| 16750 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_Scalar_out, name, "aten::_foreach_lerp") |
| 16751 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_Scalar_out, overload_name, "Scalar_out") |
| 16752 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_lerp_Scalar_out, schema_str, "_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> ()") |
| 16753 | |
| 16754 | // aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () |
| 16755 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_lerp_Scalar_out::schema> create__foreach_lerp_Scalar_out_typed_handle() { |
| 16756 | return c10::Dispatcher::singleton() |
| 16757 | .findSchemaOrThrow(_foreach_lerp_Scalar_out::name, _foreach_lerp_Scalar_out::overload_name) |
| 16758 | .typed<_foreach_lerp_Scalar_out::schema>(); |
| 16759 | } |
| 16760 | |
| 16761 | // aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () |
| 16762 | void _foreach_lerp_Scalar_out::call(at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out) { |
| 16763 | |
| 16764 | static auto op = create__foreach_lerp_Scalar_out_typed_handle(); |
| 16765 | return op.call(self, tensors1, weight, out); |
| 16766 | } |
| 16767 | |
| 16768 | // aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () |
| 16769 | void _foreach_lerp_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensors1, const at::Scalar & weight, at::TensorList out) { |
| 16770 | |
| 16771 | static auto op = create__foreach_lerp_Scalar_out_typed_handle(); |
| 16772 | return op.redispatch(dispatchKeySet, self, tensors1, weight, out); |
| 16773 | } |
| 16774 | |
| 16775 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_backward_out, name, "aten::rrelu_with_noise_backward") |
| 16776 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_backward_out, overload_name, "out") |
| 16777 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_backward_out, schema_str, "rrelu_with_noise_backward.out(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result, *, Tensor(a!) out) -> Tensor(a!)") |
| 16778 | |
| 16779 | // aten::rrelu_with_noise_backward.out(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result, *, Tensor(a!) out) -> Tensor(a!) |
| 16780 | static C10_NOINLINE c10::TypedOperatorHandle<rrelu_with_noise_backward_out::schema> create_rrelu_with_noise_backward_out_typed_handle() { |
| 16781 | return c10::Dispatcher::singleton() |
| 16782 | .findSchemaOrThrow(rrelu_with_noise_backward_out::name, rrelu_with_noise_backward_out::overload_name) |
| 16783 | .typed<rrelu_with_noise_backward_out::schema>(); |
| 16784 | } |
| 16785 | |
| 16786 | // aten::rrelu_with_noise_backward.out(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result, *, Tensor(a!) out) -> Tensor(a!) |
| 16787 | at::Tensor & rrelu_with_noise_backward_out::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result, at::Tensor & out) { |
| 16788 | |
| 16789 | static auto op = create_rrelu_with_noise_backward_out_typed_handle(); |
| 16790 | return op.call(grad_output, self, noise, lower, upper, training, self_is_result, out); |
| 16791 | } |
| 16792 | |
| 16793 | // aten::rrelu_with_noise_backward.out(Tensor grad_output, Tensor self, Tensor noise, Scalar lower, Scalar upper, bool training, bool self_is_result, *, Tensor(a!) out) -> Tensor(a!) |
| 16794 | at::Tensor & rrelu_with_noise_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, bool self_is_result, at::Tensor & out) { |
| 16795 | |
| 16796 | static auto op = create_rrelu_with_noise_backward_out_typed_handle(); |
| 16797 | return op.redispatch(dispatchKeySet, grad_output, self, noise, lower, upper, training, self_is_result, out); |
| 16798 | } |
| 16799 | |
| 16800 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_backward_out, name, "aten::mkldnn_adaptive_avg_pool2d_backward") |
| 16801 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_backward_out, overload_name, "out") |
| 16802 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_backward_out, schema_str, "mkldnn_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 16803 | |
| 16804 | // aten::mkldnn_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16805 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_adaptive_avg_pool2d_backward_out::schema> create_mkldnn_adaptive_avg_pool2d_backward_out_typed_handle() { |
| 16806 | return c10::Dispatcher::singleton() |
| 16807 | .findSchemaOrThrow(mkldnn_adaptive_avg_pool2d_backward_out::name, mkldnn_adaptive_avg_pool2d_backward_out::overload_name) |
| 16808 | .typed<mkldnn_adaptive_avg_pool2d_backward_out::schema>(); |
| 16809 | } |
| 16810 | |
| 16811 | // aten::mkldnn_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16812 | at::Tensor & mkldnn_adaptive_avg_pool2d_backward_out::call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { |
| 16813 | |
| 16814 | static auto op = create_mkldnn_adaptive_avg_pool2d_backward_out_typed_handle(); |
| 16815 | return op.call(grad_output, self, out); |
| 16816 | } |
| 16817 | |
| 16818 | // aten::mkldnn_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16819 | at::Tensor & mkldnn_adaptive_avg_pool2d_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { |
| 16820 | |
| 16821 | static auto op = create_mkldnn_adaptive_avg_pool2d_backward_out_typed_handle(); |
| 16822 | return op.redispatch(dispatchKeySet, grad_output, self, out); |
| 16823 | } |
| 16824 | |
| 16825 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_exp_out, name, "aten::linalg_matrix_exp") |
| 16826 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_exp_out, overload_name, "out") |
| 16827 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_exp_out, schema_str, "linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 16828 | |
| 16829 | // aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16830 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_exp_out::schema> create_linalg_matrix_exp_out_typed_handle() { |
| 16831 | return c10::Dispatcher::singleton() |
| 16832 | .findSchemaOrThrow(linalg_matrix_exp_out::name, linalg_matrix_exp_out::overload_name) |
| 16833 | .typed<linalg_matrix_exp_out::schema>(); |
| 16834 | } |
| 16835 | |
| 16836 | // aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16837 | at::Tensor & linalg_matrix_exp_out::call(const at::Tensor & self, at::Tensor & out) { |
| 16838 | |
| 16839 | static auto op = create_linalg_matrix_exp_out_typed_handle(); |
| 16840 | return op.call(self, out); |
| 16841 | } |
| 16842 | |
| 16843 | // aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16844 | at::Tensor & linalg_matrix_exp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 16845 | |
| 16846 | static auto op = create_linalg_matrix_exp_out_typed_handle(); |
| 16847 | return op.redispatch(dispatchKeySet, self, out); |
| 16848 | } |
| 16849 | |
| 16850 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_intlist_out, name, "aten::_test_optional_intlist") |
| 16851 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_intlist_out, overload_name, "out") |
| 16852 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_intlist_out, schema_str, "_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!)") |
| 16853 | |
| 16854 | // aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) |
| 16855 | static C10_NOINLINE c10::TypedOperatorHandle<_test_optional_intlist_out::schema> create__test_optional_intlist_out_typed_handle() { |
| 16856 | return c10::Dispatcher::singleton() |
| 16857 | .findSchemaOrThrow(_test_optional_intlist_out::name, _test_optional_intlist_out::overload_name) |
| 16858 | .typed<_test_optional_intlist_out::schema>(); |
| 16859 | } |
| 16860 | |
| 16861 | // aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) |
| 16862 | at::Tensor & _test_optional_intlist_out::call(const at::Tensor & values, at::OptionalIntArrayRef addends, at::Tensor & out) { |
| 16863 | |
| 16864 | static auto op = create__test_optional_intlist_out_typed_handle(); |
| 16865 | return op.call(values, addends, out); |
| 16866 | } |
| 16867 | |
| 16868 | // aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) |
| 16869 | at::Tensor & _test_optional_intlist_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & values, at::OptionalIntArrayRef addends, at::Tensor & out) { |
| 16870 | |
| 16871 | static auto op = create__test_optional_intlist_out_typed_handle(); |
| 16872 | return op.redispatch(dispatchKeySet, values, addends, out); |
| 16873 | } |
| 16874 | |
| 16875 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_fullcoverage_out, name, "aten::_test_autograd_multiple_dispatch") |
| 16876 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_fullcoverage_out, overload_name, "fullcoverage_out") |
| 16877 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_fullcoverage_out, schema_str, "_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 16878 | |
| 16879 | // aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16880 | static C10_NOINLINE c10::TypedOperatorHandle<_test_autograd_multiple_dispatch_fullcoverage_out::schema> create__test_autograd_multiple_dispatch_fullcoverage_out_typed_handle() { |
| 16881 | return c10::Dispatcher::singleton() |
| 16882 | .findSchemaOrThrow(_test_autograd_multiple_dispatch_fullcoverage_out::name, _test_autograd_multiple_dispatch_fullcoverage_out::overload_name) |
| 16883 | .typed<_test_autograd_multiple_dispatch_fullcoverage_out::schema>(); |
| 16884 | } |
| 16885 | |
| 16886 | // aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16887 | at::Tensor & _test_autograd_multiple_dispatch_fullcoverage_out::call(const at::Tensor & self, at::Tensor & out) { |
| 16888 | |
| 16889 | static auto op = create__test_autograd_multiple_dispatch_fullcoverage_out_typed_handle(); |
| 16890 | return op.call(self, out); |
| 16891 | } |
| 16892 | |
| 16893 | // aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16894 | at::Tensor & _test_autograd_multiple_dispatch_fullcoverage_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 16895 | |
| 16896 | static auto op = create__test_autograd_multiple_dispatch_fullcoverage_out_typed_handle(); |
| 16897 | return op.redispatch(dispatchKeySet, self, out); |
| 16898 | } |
| 16899 | |
| 16900 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(segment_reduce_out, name, "aten::segment_reduce") |
| 16901 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(segment_reduce_out, overload_name, "out") |
| 16902 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(segment_reduce_out, schema_str, "segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!)") |
| 16903 | |
| 16904 | // aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) |
| 16905 | static C10_NOINLINE c10::TypedOperatorHandle<segment_reduce_out::schema> create_segment_reduce_out_typed_handle() { |
| 16906 | return c10::Dispatcher::singleton() |
| 16907 | .findSchemaOrThrow(segment_reduce_out::name, segment_reduce_out::overload_name) |
| 16908 | .typed<segment_reduce_out::schema>(); |
| 16909 | } |
| 16910 | |
| 16911 | // aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) |
| 16912 | at::Tensor & segment_reduce_out::call(const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & indices, const c10::optional<at::Tensor> & offsets, int64_t axis, bool unsafe, const c10::optional<at::Scalar> & initial, at::Tensor & out) { |
| 16913 | |
| 16914 | static auto op = create_segment_reduce_out_typed_handle(); |
| 16915 | return op.call(data, reduce, lengths, indices, offsets, axis, unsafe, initial, out); |
| 16916 | } |
| 16917 | |
| 16918 | // aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) |
| 16919 | at::Tensor & segment_reduce_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & indices, const c10::optional<at::Tensor> & offsets, int64_t axis, bool unsafe, const c10::optional<at::Scalar> & initial, at::Tensor & out) { |
| 16920 | |
| 16921 | static auto op = create_segment_reduce_out_typed_handle(); |
| 16922 | return op.redispatch(dispatchKeySet, data, reduce, lengths, indices, offsets, axis, unsafe, initial, out); |
| 16923 | } |
| 16924 | |
| 16925 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_segment_reduce_backward_out, name, "aten::_segment_reduce_backward") |
| 16926 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_segment_reduce_backward_out, overload_name, "out") |
| 16927 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_segment_reduce_backward_out, schema_str, "_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!)") |
| 16928 | |
| 16929 | // aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) |
| 16930 | static C10_NOINLINE c10::TypedOperatorHandle<_segment_reduce_backward_out::schema> create__segment_reduce_backward_out_typed_handle() { |
| 16931 | return c10::Dispatcher::singleton() |
| 16932 | .findSchemaOrThrow(_segment_reduce_backward_out::name, _segment_reduce_backward_out::overload_name) |
| 16933 | .typed<_segment_reduce_backward_out::schema>(); |
| 16934 | } |
| 16935 | |
| 16936 | // aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) |
| 16937 | at::Tensor & _segment_reduce_backward_out::call(const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & offsets, int64_t axis, const c10::optional<at::Scalar> & initial, at::Tensor & out) { |
| 16938 | |
| 16939 | static auto op = create__segment_reduce_backward_out_typed_handle(); |
| 16940 | return op.call(grad, output, data, reduce, lengths, offsets, axis, initial, out); |
| 16941 | } |
| 16942 | |
| 16943 | // aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) |
| 16944 | at::Tensor & _segment_reduce_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & output, const at::Tensor & data, c10::string_view reduce, const c10::optional<at::Tensor> & lengths, const c10::optional<at::Tensor> & offsets, int64_t axis, const c10::optional<at::Scalar> & initial, at::Tensor & out) { |
| 16945 | |
| 16946 | static auto op = create__segment_reduce_backward_out_typed_handle(); |
| 16947 | return op.redispatch(dispatchKeySet, grad, output, data, reduce, lengths, offsets, axis, initial, out); |
| 16948 | } |
| 16949 | |
| 16950 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_dual_copy_out, name, "aten::_make_dual_copy") |
| 16951 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_dual_copy_out, overload_name, "out") |
| 16952 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_dual_copy_out, schema_str, "_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!)") |
| 16953 | |
| 16954 | // aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) |
| 16955 | static C10_NOINLINE c10::TypedOperatorHandle<_make_dual_copy_out::schema> create__make_dual_copy_out_typed_handle() { |
| 16956 | return c10::Dispatcher::singleton() |
| 16957 | .findSchemaOrThrow(_make_dual_copy_out::name, _make_dual_copy_out::overload_name) |
| 16958 | .typed<_make_dual_copy_out::schema>(); |
| 16959 | } |
| 16960 | |
| 16961 | // aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) |
| 16962 | at::Tensor & _make_dual_copy_out::call(const at::Tensor & primal, const at::Tensor & tangent, int64_t level, at::Tensor & out) { |
| 16963 | |
| 16964 | static auto op = create__make_dual_copy_out_typed_handle(); |
| 16965 | return op.call(primal, tangent, level, out); |
| 16966 | } |
| 16967 | |
| 16968 | // aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) |
| 16969 | at::Tensor & _make_dual_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & primal, const at::Tensor & tangent, int64_t level, at::Tensor & out) { |
| 16970 | |
| 16971 | static auto op = create__make_dual_copy_out_typed_handle(); |
| 16972 | return op.redispatch(dispatchKeySet, primal, tangent, level, out); |
| 16973 | } |
| 16974 | |
| 16975 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex_copy_out, name, "aten::view_as_complex_copy") |
| 16976 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex_copy_out, overload_name, "out") |
| 16977 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex_copy_out, schema_str, "view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 16978 | |
| 16979 | // aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16980 | static C10_NOINLINE c10::TypedOperatorHandle<view_as_complex_copy_out::schema> create_view_as_complex_copy_out_typed_handle() { |
| 16981 | return c10::Dispatcher::singleton() |
| 16982 | .findSchemaOrThrow(view_as_complex_copy_out::name, view_as_complex_copy_out::overload_name) |
| 16983 | .typed<view_as_complex_copy_out::schema>(); |
| 16984 | } |
| 16985 | |
| 16986 | // aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16987 | at::Tensor & view_as_complex_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
| 16988 | |
| 16989 | static auto op = create_view_as_complex_copy_out_typed_handle(); |
| 16990 | return op.call(self, out); |
| 16991 | } |
| 16992 | |
| 16993 | // aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 16994 | at::Tensor & view_as_complex_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 16995 | |
| 16996 | static auto op = create_view_as_complex_copy_out_typed_handle(); |
| 16997 | return op.redispatch(dispatchKeySet, self, out); |
| 16998 | } |
| 16999 | |
| 17000 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view_copy_out, name, "aten::_neg_view_copy") |
| 17001 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view_copy_out, overload_name, "out") |
| 17002 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_neg_view_copy_out, schema_str, "_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 17003 | |
| 17004 | // aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 17005 | static C10_NOINLINE c10::TypedOperatorHandle<_neg_view_copy_out::schema> create__neg_view_copy_out_typed_handle() { |
| 17006 | return c10::Dispatcher::singleton() |
| 17007 | .findSchemaOrThrow(_neg_view_copy_out::name, _neg_view_copy_out::overload_name) |
| 17008 | .typed<_neg_view_copy_out::schema>(); |
| 17009 | } |
| 17010 | |
| 17011 | // aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 17012 | at::Tensor & _neg_view_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
| 17013 | |
| 17014 | static auto op = create__neg_view_copy_out_typed_handle(); |
| 17015 | return op.call(self, out); |
| 17016 | } |
| 17017 | |
| 17018 | // aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 17019 | at::Tensor & _neg_view_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 17020 | |
| 17021 | static auto op = create__neg_view_copy_out_typed_handle(); |
| 17022 | return op.redispatch(dispatchKeySet, self, out); |
| 17023 | } |
| 17024 | |
| 17025 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_copy_out, name, "aten::expand_copy") |
| 17026 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_copy_out, overload_name, "out") |
| 17027 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(expand_copy_out, schema_str, "expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!)") |
| 17028 | |
| 17029 | // aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) |
| 17030 | static C10_NOINLINE c10::TypedOperatorHandle<expand_copy_out::schema> create_expand_copy_out_typed_handle() { |
| 17031 | return c10::Dispatcher::singleton() |
| 17032 | .findSchemaOrThrow(expand_copy_out::name, expand_copy_out::overload_name) |
| 17033 | .typed<expand_copy_out::schema>(); |
| 17034 | } |
| 17035 | |
| 17036 | // aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) |
| 17037 | at::Tensor & expand_copy_out::call(const at::Tensor & self, c10::SymIntArrayRef size, bool implicit, at::Tensor & out) { |
| 17038 | |
| 17039 | static auto op = create_expand_copy_out_typed_handle(); |
| 17040 | return op.call(self, size, implicit, out); |
| 17041 | } |
| 17042 | |
| 17043 | // aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) |
| 17044 | at::Tensor & expand_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, bool implicit, at::Tensor & out) { |
| 17045 | |
| 17046 | static auto op = create_expand_copy_out_typed_handle(); |
| 17047 | return op.redispatch(dispatchKeySet, self, size, implicit, out); |
| 17048 | } |
| 17049 | |
| 17050 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_copy_out, name, "aten::unsqueeze_copy") |
| 17051 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_copy_out, overload_name, "out") |
| 17052 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_copy_out, schema_str, "unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!)") |
| 17053 | |
| 17054 | // aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) |
| 17055 | static C10_NOINLINE c10::TypedOperatorHandle<unsqueeze_copy_out::schema> create_unsqueeze_copy_out_typed_handle() { |
| 17056 | return c10::Dispatcher::singleton() |
| 17057 | .findSchemaOrThrow(unsqueeze_copy_out::name, unsqueeze_copy_out::overload_name) |
| 17058 | .typed<unsqueeze_copy_out::schema>(); |
| 17059 | } |
| 17060 | |
| 17061 | // aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) |
| 17062 | at::Tensor & unsqueeze_copy_out::call(const at::Tensor & self, int64_t dim, at::Tensor & out) { |
| 17063 | |
| 17064 | static auto op = create_unsqueeze_copy_out_typed_handle(); |
| 17065 | return op.call(self, dim, out); |
| 17066 | } |
| 17067 | |
| 17068 | // aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) |
| 17069 | at::Tensor & unsqueeze_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::Tensor & out) { |
| 17070 | |
| 17071 | static auto op = create_unsqueeze_copy_out_typed_handle(); |
| 17072 | return op.redispatch(dispatchKeySet, self, dim, out); |
| 17073 | } |
| 17074 | |
| 17075 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(crow_indices_copy_out, name, "aten::crow_indices_copy") |
| 17076 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(crow_indices_copy_out, overload_name, "out") |
| 17077 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(crow_indices_copy_out, schema_str, "crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 17078 | |
| 17079 | // aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 17080 | static C10_NOINLINE c10::TypedOperatorHandle<crow_indices_copy_out::schema> create_crow_indices_copy_out_typed_handle() { |
| 17081 | return c10::Dispatcher::singleton() |
| 17082 | .findSchemaOrThrow(crow_indices_copy_out::name, crow_indices_copy_out::overload_name) |
| 17083 | .typed<crow_indices_copy_out::schema>(); |
| 17084 | } |
| 17085 | |
| 17086 | // aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 17087 | at::Tensor & crow_indices_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
| 17088 | |
| 17089 | static auto op = create_crow_indices_copy_out_typed_handle(); |
| 17090 | return op.call(self, out); |
| 17091 | } |
| 17092 | |
| 17093 | // aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 17094 | at::Tensor & crow_indices_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 17095 | |
| 17096 | static auto op = create_crow_indices_copy_out_typed_handle(); |
| 17097 | return op.redispatch(dispatchKeySet, self, out); |
| 17098 | } |
| 17099 | |
| 17100 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_padded_tensor_out, name, "aten::to_padded_tensor") |
| 17101 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_padded_tensor_out, overload_name, "out") |
| 17102 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_padded_tensor_out, schema_str, "to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 17103 | |
| 17104 | // aten::to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) |
| 17105 | static C10_NOINLINE c10::TypedOperatorHandle<to_padded_tensor_out::schema> create_to_padded_tensor_out_typed_handle() { |
| 17106 | return c10::Dispatcher::singleton() |
| 17107 | .findSchemaOrThrow(to_padded_tensor_out::name, to_padded_tensor_out::overload_name) |
| 17108 | .typed<to_padded_tensor_out::schema>(); |
| 17109 | } |
| 17110 | |
| 17111 | // aten::to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) |
| 17112 | at::Tensor & to_padded_tensor_out::call(const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size, at::Tensor & out) { |
| 17113 | |
| 17114 | static auto op = create_to_padded_tensor_out_typed_handle(); |
| 17115 | return op.call(self, padding, output_size, out); |
| 17116 | } |
| 17117 | |
| 17118 | // aten::to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) |
| 17119 | at::Tensor & to_padded_tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double padding, at::OptionalSymIntArrayRef output_size, at::Tensor & out) { |
| 17120 | |
| 17121 | static auto op = create_to_padded_tensor_out_typed_handle(); |
| 17122 | return op.redispatch(dispatchKeySet, self, padding, output_size, out); |
| 17123 | } |
| 17124 | |
| 17125 | }} // namespace at::_ops |
| 17126 |
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