| 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/set_data.h> |
| 11 | #include <ATen/ops/_fw_primal.h> |
| 12 | #include <ATen/ops/align_tensors.h> |
| 13 | #include <ATen/ops/_assert_async.h> |
| 14 | #include <ATen/ops/_masked_scale.h> |
| 15 | #include <ATen/ops/_sobol_engine_draw.h> |
| 16 | #include <ATen/ops/_reshape_from_tensor.h> |
| 17 | #include <ATen/ops/alpha_dropout.h> |
| 18 | #include <ATen/ops/alpha_dropout.h> |
| 19 | #include <ATen/ops/view_as_real.h> |
| 20 | #include <ATen/ops/view_as_complex.h> |
| 21 | #include <ATen/ops/chalf.h> |
| 22 | #include <ATen/ops/conj_physical.h> |
| 23 | #include <ATen/ops/conj_physical.h> |
| 24 | #include <ATen/ops/conj_physical.h> |
| 25 | #include <ATen/ops/acos.h> |
| 26 | #include <ATen/ops/acos.h> |
| 27 | #include <ATen/ops/acos.h> |
| 28 | #include <ATen/ops/arccos.h> |
| 29 | #include <ATen/ops/arccos.h> |
| 30 | #include <ATen/ops/arccos.h> |
| 31 | #include <ATen/ops/any.h> |
| 32 | #include <ATen/ops/any.h> |
| 33 | #include <ATen/ops/any.h> |
| 34 | #include <ATen/ops/any.h> |
| 35 | #include <ATen/ops/arccosh.h> |
| 36 | #include <ATen/ops/arccosh.h> |
| 37 | #include <ATen/ops/arccosh.h> |
| 38 | #include <ATen/ops/asin.h> |
| 39 | #include <ATen/ops/asin.h> |
| 40 | #include <ATen/ops/asin.h> |
| 41 | #include <ATen/ops/atleast_1d.h> |
| 42 | #include <ATen/ops/atleast_1d.h> |
| 43 | #include <ATen/ops/copysign.h> |
| 44 | #include <ATen/ops/copysign.h> |
| 45 | #include <ATen/ops/copysign.h> |
| 46 | #include <ATen/ops/copysign.h> |
| 47 | #include <ATen/ops/copysign.h> |
| 48 | #include <ATen/ops/copysign.h> |
| 49 | #include <ATen/ops/logical_xor.h> |
| 50 | #include <ATen/ops/logical_xor.h> |
| 51 | #include <ATen/ops/logical_xor.h> |
| 52 | #include <ATen/ops/broadcast_to.h> |
| 53 | #include <ATen/ops/constant_pad_nd.h> |
| 54 | #include <ATen/ops/contiguous.h> |
| 55 | #include <ATen/ops/convolution_backward.h> |
| 56 | #include <ATen/ops/convolution_overrideable.h> |
| 57 | #include <ATen/ops/_convolution_double_backward.h> |
| 58 | #include <ATen/ops/conv2d.h> |
| 59 | #include <ATen/ops/conv2d.h> |
| 60 | #include <ATen/ops/_copy_from.h> |
| 61 | #include <ATen/ops/corrcoef.h> |
| 62 | #include <ATen/ops/cudnn_batch_norm.h> |
| 63 | #include <ATen/ops/_mps_convolution_transpose.h> |
| 64 | #include <ATen/ops/mps_convolution_transpose_backward.h> |
| 65 | #include <ATen/ops/cummaxmin_backward.h> |
| 66 | #include <ATen/ops/cumprod_backward.h> |
| 67 | #include <ATen/ops/fill_diagonal.h> |
| 68 | #include <ATen/ops/embedding.h> |
| 69 | #include <ATen/ops/_rowwise_prune.h> |
| 70 | #include <ATen/ops/row_stack.h> |
| 71 | #include <ATen/ops/row_stack.h> |
| 72 | #include <ATen/ops/_embedding_bag_backward.h> |
| 73 | #include <ATen/ops/_embedding_bag_dense_backward.h> |
| 74 | #include <ATen/ops/resize.h> |
| 75 | #include <ATen/ops/erfc.h> |
| 76 | #include <ATen/ops/erfc.h> |
| 77 | #include <ATen/ops/erfc.h> |
| 78 | #include <ATen/ops/floor_divide.h> |
| 79 | #include <ATen/ops/floor_divide.h> |
| 80 | #include <ATen/ops/floor_divide.h> |
| 81 | #include <ATen/ops/floor_divide.h> |
| 82 | #include <ATen/ops/floor_divide.h> |
| 83 | #include <ATen/ops/full.h> |
| 84 | #include <ATen/ops/full.h> |
| 85 | #include <ATen/ops/full.h> |
| 86 | #include <ATen/ops/full_like.h> |
| 87 | #include <ATen/ops/grid_sampler_2d.h> |
| 88 | #include <ATen/ops/_grid_sampler_2d_cpu_fallback_backward.h> |
| 89 | #include <ATen/ops/kaiser_window.h> |
| 90 | #include <ATen/ops/kaiser_window.h> |
| 91 | #include <ATen/ops/kaiser_window.h> |
| 92 | #include <ATen/ops/_fft_c2r.h> |
| 93 | #include <ATen/ops/_fft_c2r.h> |
| 94 | #include <ATen/ops/_cufft_set_plan_cache_max_size.h> |
| 95 | #include <ATen/ops/index_put.h> |
| 96 | #include <ATen/ops/index_put.h> |
| 97 | #include <ATen/ops/instance_norm.h> |
| 98 | #include <ATen/ops/isclose.h> |
| 99 | #include <ATen/ops/is_floating_point.h> |
| 100 | #include <ATen/ops/is_complex.h> |
| 101 | #include <ATen/ops/is_same_size.h> |
| 102 | #include <ATen/ops/kl_div.h> |
| 103 | #include <ATen/ops/fbgemm_pack_gemm_matrix_fp16.h> |
| 104 | #include <ATen/ops/margin_ranking_loss.h> |
| 105 | #include <ATen/ops/matmul.h> |
| 106 | #include <ATen/ops/matmul_backward.h> |
| 107 | #include <ATen/ops/matmul.h> |
| 108 | #include <ATen/ops/matrix_exp.h> |
| 109 | #include <ATen/ops/_compute_linear_combination.h> |
| 110 | #include <ATen/ops/_compute_linear_combination.h> |
| 111 | #include <ATen/ops/mkldnn_max_pool2d_backward.h> |
| 112 | #include <ATen/ops/max_pool3d.h> |
| 113 | #include <ATen/ops/median.h> |
| 114 | #include <ATen/ops/median.h> |
| 115 | #include <ATen/ops/median.h> |
| 116 | #include <ATen/ops/median.h> |
| 117 | #include <ATen/ops/median.h> |
| 118 | #include <ATen/ops/nanmedian.h> |
| 119 | #include <ATen/ops/nanmedian.h> |
| 120 | #include <ATen/ops/nanmedian.h> |
| 121 | #include <ATen/ops/nanmedian.h> |
| 122 | #include <ATen/ops/nanmedian.h> |
| 123 | #include <ATen/ops/miopen_batch_norm.h> |
| 124 | #include <ATen/ops/miopen_convolution_transpose.h> |
| 125 | #include <ATen/ops/miopen_convolution_add_relu.h> |
| 126 | #include <ATen/ops/miopen_rnn_backward.h> |
| 127 | #include <ATen/ops/multiply.h> |
| 128 | #include <ATen/ops/multiply.h> |
| 129 | #include <ATen/ops/multiply.h> |
| 130 | #include <ATen/ops/multiply.h> |
| 131 | #include <ATen/ops/multiply.h> |
| 132 | #include <ATen/ops/batch_norm_elemt.h> |
| 133 | #include <ATen/ops/batch_norm_elemt.h> |
| 134 | #include <ATen/ops/cdist.h> |
| 135 | #include <ATen/ops/mT.h> |
| 136 | #include <ATen/ops/adjoint.h> |
| 137 | #include <ATen/ops/channel_shuffle.h> |
| 138 | #include <ATen/ops/poisson_nll_loss.h> |
| 139 | #include <ATen/ops/deg2rad.h> |
| 140 | #include <ATen/ops/deg2rad.h> |
| 141 | #include <ATen/ops/deg2rad.h> |
| 142 | #include <ATen/ops/randperm.h> |
| 143 | #include <ATen/ops/randperm.h> |
| 144 | #include <ATen/ops/randperm.h> |
| 145 | #include <ATen/ops/randperm.h> |
| 146 | #include <ATen/ops/negative.h> |
| 147 | #include <ATen/ops/negative.h> |
| 148 | #include <ATen/ops/negative.h> |
| 149 | #include <ATen/ops/_reshape_copy.h> |
| 150 | #include <ATen/ops/relu.h> |
| 151 | #include <ATen/ops/relu.h> |
| 152 | #include <ATen/ops/infinitely_differentiable_gelu_backward.h> |
| 153 | #include <ATen/ops/hardshrink_backward.h> |
| 154 | #include <ATen/ops/hardshrink_backward.h> |
| 155 | #include <ATen/ops/sinc.h> |
| 156 | #include <ATen/ops/sinc.h> |
| 157 | #include <ATen/ops/sinc.h> |
| 158 | #include <ATen/ops/slice.h> |
| 159 | #include <ATen/ops/select_scatter.h> |
| 160 | #include <ATen/ops/smm.h> |
| 161 | #include <ATen/ops/unsafe_split_with_sizes.h> |
| 162 | #include <ATen/ops/dstack.h> |
| 163 | #include <ATen/ops/dstack.h> |
| 164 | #include <ATen/ops/prod.h> |
| 165 | #include <ATen/ops/prod.h> |
| 166 | #include <ATen/ops/prod.h> |
| 167 | #include <ATen/ops/prod.h> |
| 168 | #include <ATen/ops/prod.h> |
| 169 | #include <ATen/ops/tan.h> |
| 170 | #include <ATen/ops/tan.h> |
| 171 | #include <ATen/ops/tan.h> |
| 172 | #include <ATen/ops/trapezoid.h> |
| 173 | #include <ATen/ops/trapezoid.h> |
| 174 | #include <ATen/ops/_nested_tensor_from_mask.h> |
| 175 | #include <ATen/ops/_nested_tensor_from_mask_left_aligned.h> |
| 176 | #include <ATen/ops/_nested_tensor_size.h> |
| 177 | #include <ATen/ops/_nested_view_from_buffer_copy.h> |
| 178 | #include <ATen/ops/unique_dim_consecutive.h> |
| 179 | #include <ATen/ops/_unsafe_view.h> |
| 180 | #include <ATen/ops/unsqueeze.h> |
| 181 | #include <ATen/ops/unsqueeze.h> |
| 182 | #include <ATen/ops/_efficientzerotensor.h> |
| 183 | #include <ATen/ops/poisson.h> |
| 184 | #include <ATen/ops/sub.h> |
| 185 | #include <ATen/ops/sub.h> |
| 186 | #include <ATen/ops/sub.h> |
| 187 | #include <ATen/ops/sub.h> |
| 188 | #include <ATen/ops/sub.h> |
| 189 | #include <ATen/ops/subtract.h> |
| 190 | #include <ATen/ops/subtract.h> |
| 191 | #include <ATen/ops/subtract.h> |
| 192 | #include <ATen/ops/subtract.h> |
| 193 | #include <ATen/ops/subtract.h> |
| 194 | #include <ATen/ops/heaviside.h> |
| 195 | #include <ATen/ops/heaviside.h> |
| 196 | #include <ATen/ops/heaviside.h> |
| 197 | #include <ATen/ops/_addmm_activation.h> |
| 198 | #include <ATen/ops/_addmm_activation.h> |
| 199 | #include <ATen/ops/sparse_compressed_tensor.h> |
| 200 | #include <ATen/ops/sparse_bsr_tensor.h> |
| 201 | #include <ATen/ops/sparse_compressed_tensor.h> |
| 202 | #include <ATen/ops/sparse_bsr_tensor.h> |
| 203 | #include <ATen/ops/sparse_coo_tensor.h> |
| 204 | #include <ATen/ops/sparse_coo_tensor.h> |
| 205 | #include <ATen/ops/sparse_coo_tensor.h> |
| 206 | #include <ATen/ops/_validate_sparse_compressed_tensor_args.h> |
| 207 | #include <ATen/ops/sparse_resize_and_clear.h> |
| 208 | #include <ATen/ops/to_dense.h> |
| 209 | #include <ATen/ops/sparse_dim.h> |
| 210 | #include <ATen/ops/_dimI.h> |
| 211 | #include <ATen/ops/_nnz.h> |
| 212 | #include <ATen/ops/ccol_indices.h> |
| 213 | #include <ATen/ops/to_sparse_csr.h> |
| 214 | #include <ATen/ops/to_sparse_bsr.h> |
| 215 | #include <ATen/ops/mkldnn_reorder_conv3d_weight.h> |
| 216 | #include <ATen/ops/q_scale.h> |
| 217 | #include <ATen/ops/q_per_channel_axis.h> |
| 218 | #include <ATen/ops/_make_per_tensor_quantized_tensor.h> |
| 219 | #include <ATen/ops/_make_per_channel_quantized_tensor.h> |
| 220 | #include <ATen/ops/fake_quantize_per_tensor_affine_cachemask_backward.h> |
| 221 | #include <ATen/ops/fake_quantize_per_channel_affine_cachemask_backward.h> |
| 222 | #include <ATen/ops/_saturate_weight_to_fp16.h> |
| 223 | #include <ATen/ops/_autocast_to_reduced_precision.h> |
| 224 | #include <ATen/ops/result_type.h> |
| 225 | #include <ATen/ops/result_type.h> |
| 226 | #include <ATen/ops/result_type.h> |
| 227 | #include <ATen/ops/result_type.h> |
| 228 | #include <ATen/ops/_thnn_fused_lstm_cell_backward.h> |
| 229 | #include <ATen/ops/lstm_cell.h> |
| 230 | #include <ATen/ops/quantized_rnn_relu_cell.h> |
| 231 | #include <ATen/ops/masked_fill.h> |
| 232 | #include <ATen/ops/masked_fill.h> |
| 233 | #include <ATen/ops/masked_fill.h> |
| 234 | #include <ATen/ops/masked_fill.h> |
| 235 | #include <ATen/ops/masked_scatter.h> |
| 236 | #include <ATen/ops/masked_scatter.h> |
| 237 | #include <ATen/ops/_masked_softmax_backward.h> |
| 238 | #include <ATen/ops/index_add.h> |
| 239 | #include <ATen/ops/index_add.h> |
| 240 | #include <ATen/ops/index_add.h> |
| 241 | #include <ATen/ops/index_add.h> |
| 242 | #include <ATen/ops/bitwise_or.h> |
| 243 | #include <ATen/ops/bitwise_or.h> |
| 244 | #include <ATen/ops/bitwise_or.h> |
| 245 | #include <ATen/ops/bitwise_or.h> |
| 246 | #include <ATen/ops/bitwise_or.h> |
| 247 | #include <ATen/ops/bitwise_or.h> |
| 248 | #include <ATen/ops/bitwise_or.h> |
| 249 | #include <ATen/ops/diag.h> |
| 250 | #include <ATen/ops/diag.h> |
| 251 | #include <ATen/ops/triu_indices.h> |
| 252 | #include <ATen/ops/trace.h> |
| 253 | #include <ATen/ops/greater_equal.h> |
| 254 | #include <ATen/ops/greater_equal.h> |
| 255 | #include <ATen/ops/greater_equal.h> |
| 256 | #include <ATen/ops/greater_equal.h> |
| 257 | #include <ATen/ops/greater_equal.h> |
| 258 | #include <ATen/ops/greater_equal.h> |
| 259 | #include <ATen/ops/take.h> |
| 260 | #include <ATen/ops/take.h> |
| 261 | #include <ATen/ops/index_select_backward.h> |
| 262 | #include <ATen/ops/argwhere.h> |
| 263 | #include <ATen/ops/svd.h> |
| 264 | #include <ATen/ops/svd.h> |
| 265 | #include <ATen/ops/geqrf.h> |
| 266 | #include <ATen/ops/geqrf.h> |
| 267 | #include <ATen/ops/orgqr.h> |
| 268 | #include <ATen/ops/orgqr.h> |
| 269 | #include <ATen/ops/erfinv.h> |
| 270 | #include <ATen/ops/erfinv.h> |
| 271 | #include <ATen/ops/erfinv.h> |
| 272 | #include <ATen/ops/signbit.h> |
| 273 | #include <ATen/ops/signbit.h> |
| 274 | #include <ATen/ops/dist.h> |
| 275 | #include <ATen/ops/_histogramdd_from_bin_cts.h> |
| 276 | #include <ATen/ops/fmod.h> |
| 277 | #include <ATen/ops/fmod.h> |
| 278 | #include <ATen/ops/fmod.h> |
| 279 | #include <ATen/ops/fmod.h> |
| 280 | #include <ATen/ops/fmod.h> |
| 281 | #include <ATen/ops/fmod.h> |
| 282 | #include <ATen/ops/remainder.h> |
| 283 | #include <ATen/ops/remainder.h> |
| 284 | #include <ATen/ops/remainder.h> |
| 285 | #include <ATen/ops/remainder.h> |
| 286 | #include <ATen/ops/remainder.h> |
| 287 | #include <ATen/ops/remainder.h> |
| 288 | #include <ATen/ops/remainder.h> |
| 289 | #include <ATen/ops/nanquantile.h> |
| 290 | #include <ATen/ops/nanquantile.h> |
| 291 | #include <ATen/ops/nanquantile.h> |
| 292 | #include <ATen/ops/nanquantile.h> |
| 293 | #include <ATen/ops/any.h> |
| 294 | #include <ATen/ops/any.h> |
| 295 | #include <ATen/ops/renorm.h> |
| 296 | #include <ATen/ops/renorm.h> |
| 297 | #include <ATen/ops/renorm.h> |
| 298 | #include <ATen/ops/unfold.h> |
| 299 | #include <ATen/ops/float_power.h> |
| 300 | #include <ATen/ops/float_power.h> |
| 301 | #include <ATen/ops/float_power.h> |
| 302 | #include <ATen/ops/float_power.h> |
| 303 | #include <ATen/ops/float_power.h> |
| 304 | #include <ATen/ops/float_power.h> |
| 305 | #include <ATen/ops/float_power.h> |
| 306 | #include <ATen/ops/float_power.h> |
| 307 | #include <ATen/ops/_foreach_clamp_max.h> |
| 308 | #include <ATen/ops/_foreach_clamp_max.h> |
| 309 | #include <ATen/ops/_foreach_clamp_max.h> |
| 310 | #include <ATen/ops/_foreach_clamp_max.h> |
| 311 | #include <ATen/ops/_foreach_clamp_max.h> |
| 312 | #include <ATen/ops/_foreach_clamp_max.h> |
| 313 | #include <ATen/ops/_foreach_abs.h> |
| 314 | #include <ATen/ops/_foreach_abs.h> |
| 315 | #include <ATen/ops/_foreach_expm1.h> |
| 316 | #include <ATen/ops/_foreach_expm1.h> |
| 317 | #include <ATen/ops/_foreach_log10.h> |
| 318 | #include <ATen/ops/_foreach_log10.h> |
| 319 | #include <ATen/ops/_foreach_tan.h> |
| 320 | #include <ATen/ops/_foreach_tan.h> |
| 321 | #include <ATen/ops/_foreach_sinh.h> |
| 322 | #include <ATen/ops/_foreach_sinh.h> |
| 323 | #include <ATen/ops/searchsorted.h> |
| 324 | #include <ATen/ops/searchsorted.h> |
| 325 | #include <ATen/ops/searchsorted.h> |
| 326 | #include <ATen/ops/smooth_l1_loss.h> |
| 327 | #include <ATen/ops/smooth_l1_loss.h> |
| 328 | #include <ATen/ops/elu.h> |
| 329 | #include <ATen/ops/elu.h> |
| 330 | #include <ATen/ops/elu.h> |
| 331 | #include <ATen/ops/glu_backward.h> |
| 332 | #include <ATen/ops/glu_backward.h> |
| 333 | #include <ATen/ops/hardtanh_backward.h> |
| 334 | #include <ATen/ops/hardtanh_backward.h> |
| 335 | #include <ATen/ops/leaky_relu_backward.h> |
| 336 | #include <ATen/ops/leaky_relu_backward.h> |
| 337 | #include <ATen/ops/softplus.h> |
| 338 | #include <ATen/ops/softplus.h> |
| 339 | #include <ATen/ops/mkldnn_adaptive_avg_pool2d.h> |
| 340 | #include <ATen/ops/mkldnn_adaptive_avg_pool2d.h> |
| 341 | #include <ATen/ops/_adaptive_avg_pool2d.h> |
| 342 | #include <ATen/ops/avg_pool3d.h> |
| 343 | #include <ATen/ops/avg_pool3d.h> |
| 344 | #include <ATen/ops/avg_pool3d_backward.h> |
| 345 | #include <ATen/ops/avg_pool3d_backward.h> |
| 346 | #include <ATen/ops/max_pool2d_with_indices_backward.h> |
| 347 | #include <ATen/ops/max_pool2d_with_indices_backward.h> |
| 348 | #include <ATen/ops/max_pool3d_with_indices.h> |
| 349 | #include <ATen/ops/max_pool3d_with_indices.h> |
| 350 | #include <ATen/ops/reflection_pad2d.h> |
| 351 | #include <ATen/ops/reflection_pad2d.h> |
| 352 | #include <ATen/ops/_upsample_bilinear2d_aa.h> |
| 353 | #include <ATen/ops/upsample_linear1d_backward.h> |
| 354 | #include <ATen/ops/upsample_linear1d_backward.h> |
| 355 | #include <ATen/ops/_upsample_bilinear2d_aa.h> |
| 356 | #include <ATen/ops/_upsample_bilinear2d_aa.h> |
| 357 | #include <ATen/ops/upsample_nearest1d_backward.h> |
| 358 | #include <ATen/ops/upsample_nearest1d_backward.h> |
| 359 | #include <ATen/ops/upsample_nearest2d_backward.h> |
| 360 | #include <ATen/ops/upsample_nearest2d_backward.h> |
| 361 | #include <ATen/ops/slow_conv_transpose3d.h> |
| 362 | #include <ATen/ops/slow_conv_transpose3d.h> |
| 363 | #include <ATen/ops/slow_conv3d_forward.h> |
| 364 | #include <ATen/ops/slow_conv3d_forward.h> |
| 365 | #include <ATen/ops/im2col.h> |
| 366 | #include <ATen/ops/im2col.h> |
| 367 | #include <ATen/ops/isneginf.h> |
| 368 | #include <ATen/ops/isneginf.h> |
| 369 | #include <ATen/ops/_add_batch_dim.h> |
| 370 | #include <ATen/ops/special_psi.h> |
| 371 | #include <ATen/ops/special_psi.h> |
| 372 | #include <ATen/ops/special_erfcx.h> |
| 373 | #include <ATen/ops/special_erfcx.h> |
| 374 | #include <ATen/ops/special_i0e.h> |
| 375 | #include <ATen/ops/special_i0e.h> |
| 376 | #include <ATen/ops/special_i1.h> |
| 377 | #include <ATen/ops/special_i1.h> |
| 378 | #include <ATen/ops/special_logit.h> |
| 379 | #include <ATen/ops/special_logit.h> |
| 380 | #include <ATen/ops/special_log_softmax.h> |
| 381 | #include <ATen/ops/special_gammaincc.h> |
| 382 | #include <ATen/ops/special_gammaincc.h> |
| 383 | #include <ATen/ops/special_multigammaln.h> |
| 384 | #include <ATen/ops/special_multigammaln.h> |
| 385 | #include <ATen/ops/fft_fft2.h> |
| 386 | #include <ATen/ops/fft_fft2.h> |
| 387 | #include <ATen/ops/fft_fftn.h> |
| 388 | #include <ATen/ops/fft_fftn.h> |
| 389 | #include <ATen/ops/fft_fftshift.h> |
| 390 | #include <ATen/ops/linalg_lu_factor.h> |
| 391 | #include <ATen/ops/linalg_lu_factor.h> |
| 392 | #include <ATen/ops/linalg_lu_solve.h> |
| 393 | #include <ATen/ops/linalg_lu_solve.h> |
| 394 | #include <ATen/ops/linalg_det.h> |
| 395 | #include <ATen/ops/linalg_det.h> |
| 396 | #include <ATen/ops/_linalg_slogdet.h> |
| 397 | #include <ATen/ops/_linalg_slogdet.h> |
| 398 | #include <ATen/ops/linalg_inv.h> |
| 399 | #include <ATen/ops/linalg_inv.h> |
| 400 | #include <ATen/ops/outer.h> |
| 401 | #include <ATen/ops/outer.h> |
| 402 | #include <ATen/ops/ger.h> |
| 403 | #include <ATen/ops/ger.h> |
| 404 | #include <ATen/ops/_linalg_svd.h> |
| 405 | #include <ATen/ops/_linalg_svd.h> |
| 406 | #include <ATen/ops/_linalg_solve_ex.h> |
| 407 | #include <ATen/ops/_linalg_solve_ex.h> |
| 408 | #include <ATen/ops/linalg_qr.h> |
| 409 | #include <ATen/ops/linalg_qr.h> |
| 410 | #include <ATen/ops/nested_to_padded_tensor.h> |
| 411 | #include <ATen/ops/_test_warn_in_autograd.h> |
| 412 | #include <ATen/ops/_test_autograd_multiple_dispatch_view.h> |
| 413 | #include <ATen/ops/diagonal_copy.h> |
| 414 | #include <ATen/ops/permute_copy.h> |
| 415 | #include <ATen/ops/select_copy.h> |
| 416 | #include <ATen/ops/slice_copy.h> |
| 417 | #include <ATen/ops/split_with_sizes_copy.h> |
| 418 | #include <ATen/ops/t_copy.h> |
| 419 | #include <ATen/ops/col_indices_copy.h> |
| 420 | #include <ATen/ops/unbind_copy.h> |
| 421 | #include <ATen/ops/unbind_copy.h> |
| 422 | #include <ATen/ops/split_with_sizes_copy.h> |
| 423 | #include <ATen/ops/alias_copy.h> |
| 424 | #include <ATen/ops/_scaled_dot_product_attention_math.h> |
| 425 | #include <ATen/ops/_scaled_dot_product_flash_attention_backward.h> |
| 426 | #include <ATen/ops/_triton_scaled_dot_attention.h> |
| 427 | #include <ATen/ops/special_chebyshev_polynomial_t.h> |
| 428 | #include <ATen/ops/special_chebyshev_polynomial_t.h> |
| 429 | #include <ATen/ops/special_chebyshev_polynomial_t.h> |
| 430 | #include <ATen/ops/special_chebyshev_polynomial_t.h> |
| 431 | #include <ATen/ops/special_chebyshev_polynomial_t.h> |
| 432 | #include <ATen/ops/special_chebyshev_polynomial_t.h> |
| 433 | #include <ATen/ops/special_scaled_modified_bessel_k1.h> |
| 434 | #include <ATen/ops/special_scaled_modified_bessel_k1.h> |
| 435 | #include <ATen/ops/_foobar.h> |
| 436 | #include <ATen/ops/_masked_scale.h> |
| 437 | #include <ATen/ops/constant_pad_nd.h> |
| 438 | #include <ATen/ops/convolution_backward.h> |
| 439 | #include <ATen/ops/convolution_overrideable.h> |
| 440 | #include <ATen/ops/_copy_from.h> |
| 441 | #include <ATen/ops/cudnn_batch_norm.h> |
| 442 | #include <ATen/ops/_mps_convolution_transpose.h> |
| 443 | #include <ATen/ops/mps_convolution_transpose_backward.h> |
| 444 | #include <ATen/ops/embedding.h> |
| 445 | #include <ATen/ops/_embedding_bag_dense_backward.h> |
| 446 | #include <ATen/ops/resize.h> |
| 447 | #include <ATen/ops/resize.h> |
| 448 | #include <ATen/ops/full.h> |
| 449 | #include <ATen/ops/full_like.h> |
| 450 | #include <ATen/ops/grid_sampler_2d.h> |
| 451 | #include <ATen/ops/kaiser_window.h> |
| 452 | #include <ATen/ops/kaiser_window.h> |
| 453 | #include <ATen/ops/kaiser_window.h> |
| 454 | #include <ATen/ops/index_put.h> |
| 455 | #include <ATen/ops/matmul_backward.h> |
| 456 | #include <ATen/ops/mkldnn_max_pool2d_backward.h> |
| 457 | #include <ATen/ops/median.h> |
| 458 | #include <ATen/ops/nanmedian.h> |
| 459 | #include <ATen/ops/miopen_batch_norm.h> |
| 460 | #include <ATen/ops/miopen_convolution_transpose.h> |
| 461 | #include <ATen/ops/miopen_rnn_backward.h> |
| 462 | #include <ATen/ops/channel_shuffle.h> |
| 463 | #include <ATen/ops/relu.h> |
| 464 | #include <ATen/ops/select_scatter.h> |
| 465 | #include <ATen/ops/unsafe_split_with_sizes.h> |
| 466 | #include <ATen/ops/prod.h> |
| 467 | #include <ATen/ops/_nested_tensor_from_mask.h> |
| 468 | #include <ATen/ops/_nested_tensor_size.h> |
| 469 | #include <ATen/ops/_nested_view_from_buffer_copy.h> |
| 470 | #include <ATen/ops/unique_dim_consecutive.h> |
| 471 | #include <ATen/ops/_unsafe_view.h> |
| 472 | #include <ATen/ops/_efficientzerotensor.h> |
| 473 | #include <ATen/ops/poisson.h> |
| 474 | #include <ATen/ops/sub.h> |
| 475 | #include <ATen/ops/sparse_coo_tensor.h> |
| 476 | #include <ATen/ops/sparse_resize_and_clear.h> |
| 477 | #include <ATen/ops/sparse_resize_and_clear.h> |
| 478 | #include <ATen/ops/to_sparse_csr.h> |
| 479 | #include <ATen/ops/to_sparse_bsr.h> |
| 480 | #include <ATen/ops/mkldnn_reorder_conv3d_weight.h> |
| 481 | #include <ATen/ops/_make_per_tensor_quantized_tensor.h> |
| 482 | #include <ATen/ops/_make_per_channel_quantized_tensor.h> |
| 483 | #include <ATen/ops/masked_fill.h> |
| 484 | #include <ATen/ops/masked_fill.h> |
| 485 | #include <ATen/ops/masked_scatter.h> |
| 486 | #include <ATen/ops/_masked_softmax_backward.h> |
| 487 | #include <ATen/ops/bitwise_or.h> |
| 488 | #include <ATen/ops/triu_indices.h> |
| 489 | #include <ATen/ops/trace.h> |
| 490 | #include <ATen/ops/dist.h> |
| 491 | #include <ATen/ops/_histogramdd_from_bin_cts.h> |
| 492 | #include <ATen/ops/remainder.h> |
| 493 | #include <ATen/ops/_foreach_clamp_max.h> |
| 494 | #include <ATen/ops/_foreach_clamp_max.h> |
| 495 | #include <ATen/ops/_foreach_clamp_max.h> |
| 496 | #include <ATen/ops/_foreach_abs.h> |
| 497 | #include <ATen/ops/_foreach_expm1.h> |
| 498 | #include <ATen/ops/_foreach_log10.h> |
| 499 | #include <ATen/ops/_foreach_tan.h> |
| 500 | #include <ATen/ops/_foreach_sinh.h> |
| 501 | #include <ATen/ops/searchsorted.h> |
| 502 | #include <ATen/ops/_adaptive_avg_pool2d.h> |
| 503 | #include <ATen/ops/_test_warn_in_autograd.h> |
| 504 | #include <ATen/ops/diagonal_copy.h> |
| 505 | #include <ATen/ops/permute_copy.h> |
| 506 | #include <ATen/ops/select_copy.h> |
| 507 | #include <ATen/ops/slice_copy.h> |
| 508 | #include <ATen/ops/t_copy.h> |
| 509 | #include <ATen/ops/col_indices_copy.h> |
| 510 | #include <ATen/ops/alias_copy.h> |
| 511 | #include <ATen/ops/_triton_scaled_dot_attention.h> |
| 512 | #include <ATen/ops/_foobar.h> |
| 513 | #endif |
| 514 | |
| 515 | |
| 516 | |
| 517 | namespace at { namespace _ops { |
| 518 | |
| 519 | |
| 520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_data, name, "aten::set_data") |
| 521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_data, overload_name, "") |
| 522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_data, schema_str, "set_data(Tensor(a!) self, Tensor new_data) -> ()") |
| 523 | |
| 524 | // aten::set_data(Tensor(a!) self, Tensor new_data) -> () |
| 525 | static C10_NOINLINE c10::TypedOperatorHandle<set_data::schema> create_set_data_typed_handle() { |
| 526 | return c10::Dispatcher::singleton() |
| 527 | .findSchemaOrThrow(set_data::name, set_data::overload_name) |
| 528 | .typed<set_data::schema>(); |
| 529 | } |
| 530 | |
| 531 | // aten::set_data(Tensor(a!) self, Tensor new_data) -> () |
| 532 | void set_data::call(at::Tensor & self, const at::Tensor & new_data) { |
| 533 | |
| 534 | static auto op = create_set_data_typed_handle(); |
| 535 | return op.call(self, new_data); |
| 536 | } |
| 537 | |
| 538 | // aten::set_data(Tensor(a!) self, Tensor new_data) -> () |
| 539 | void set_data::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & new_data) { |
| 540 | |
| 541 | static auto op = create_set_data_typed_handle(); |
| 542 | return op.redispatch(dispatchKeySet, self, new_data); |
| 543 | } |
| 544 | |
| 545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fw_primal, name, "aten::_fw_primal") |
| 546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fw_primal, overload_name, "") |
| 547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fw_primal, schema_str, "_fw_primal(Tensor(a) self, int level) -> Tensor(a)") |
| 548 | |
| 549 | // aten::_fw_primal(Tensor(a) self, int level) -> Tensor(a) |
| 550 | static C10_NOINLINE c10::TypedOperatorHandle<_fw_primal::schema> create__fw_primal_typed_handle() { |
| 551 | return c10::Dispatcher::singleton() |
| 552 | .findSchemaOrThrow(_fw_primal::name, _fw_primal::overload_name) |
| 553 | .typed<_fw_primal::schema>(); |
| 554 | } |
| 555 | |
| 556 | // aten::_fw_primal(Tensor(a) self, int level) -> Tensor(a) |
| 557 | at::Tensor _fw_primal::call(const at::Tensor & self, int64_t level) { |
| 558 | |
| 559 | static auto op = create__fw_primal_typed_handle(); |
| 560 | return op.call(self, level); |
| 561 | } |
| 562 | |
| 563 | // aten::_fw_primal(Tensor(a) self, int level) -> Tensor(a) |
| 564 | at::Tensor _fw_primal::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t level) { |
| 565 | |
| 566 | static auto op = create__fw_primal_typed_handle(); |
| 567 | return op.redispatch(dispatchKeySet, self, level); |
| 568 | } |
| 569 | |
| 570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_tensors, name, "aten::align_tensors") |
| 571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_tensors, overload_name, "") |
| 572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(align_tensors, schema_str, "align_tensors(Tensor[] tensors) -> Tensor[]") |
| 573 | |
| 574 | // aten::align_tensors(Tensor[] tensors) -> Tensor[] |
| 575 | static C10_NOINLINE c10::TypedOperatorHandle<align_tensors::schema> create_align_tensors_typed_handle() { |
| 576 | return c10::Dispatcher::singleton() |
| 577 | .findSchemaOrThrow(align_tensors::name, align_tensors::overload_name) |
| 578 | .typed<align_tensors::schema>(); |
| 579 | } |
| 580 | |
| 581 | // aten::align_tensors(Tensor[] tensors) -> Tensor[] |
| 582 | ::std::vector<at::Tensor> align_tensors::call(at::TensorList tensors) { |
| 583 | |
| 584 | static auto op = create_align_tensors_typed_handle(); |
| 585 | return op.call(tensors); |
| 586 | } |
| 587 | |
| 588 | // aten::align_tensors(Tensor[] tensors) -> Tensor[] |
| 589 | ::std::vector<at::Tensor> align_tensors::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 590 | |
| 591 | static auto op = create_align_tensors_typed_handle(); |
| 592 | return op.redispatch(dispatchKeySet, tensors); |
| 593 | } |
| 594 | |
| 595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_assert_async, name, "aten::_assert_async") |
| 596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_assert_async, overload_name, "") |
| 597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_assert_async, schema_str, "_assert_async(Tensor self) -> ()") |
| 598 | |
| 599 | // aten::_assert_async(Tensor self) -> () |
| 600 | static C10_NOINLINE c10::TypedOperatorHandle<_assert_async::schema> create__assert_async_typed_handle() { |
| 601 | return c10::Dispatcher::singleton() |
| 602 | .findSchemaOrThrow(_assert_async::name, _assert_async::overload_name) |
| 603 | .typed<_assert_async::schema>(); |
| 604 | } |
| 605 | |
| 606 | // aten::_assert_async(Tensor self) -> () |
| 607 | void _assert_async::call(const at::Tensor & self) { |
| 608 | |
| 609 | static auto op = create__assert_async_typed_handle(); |
| 610 | return op.call(self); |
| 611 | } |
| 612 | |
| 613 | // aten::_assert_async(Tensor self) -> () |
| 614 | void _assert_async::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 615 | |
| 616 | static auto op = create__assert_async_typed_handle(); |
| 617 | return op.redispatch(dispatchKeySet, self); |
| 618 | } |
| 619 | |
| 620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_scale, name, "aten::_masked_scale") |
| 621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_scale, overload_name, "") |
| 622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_scale, schema_str, "_masked_scale(Tensor self, Tensor mask, float scale) -> Tensor") |
| 623 | |
| 624 | // aten::_masked_scale(Tensor self, Tensor mask, float scale) -> Tensor |
| 625 | static C10_NOINLINE c10::TypedOperatorHandle<_masked_scale::schema> create__masked_scale_typed_handle() { |
| 626 | return c10::Dispatcher::singleton() |
| 627 | .findSchemaOrThrow(_masked_scale::name, _masked_scale::overload_name) |
| 628 | .typed<_masked_scale::schema>(); |
| 629 | } |
| 630 | |
| 631 | // aten::_masked_scale(Tensor self, Tensor mask, float scale) -> Tensor |
| 632 | at::Tensor _masked_scale::call(const at::Tensor & self, const at::Tensor & mask, double scale) { |
| 633 | |
| 634 | static auto op = create__masked_scale_typed_handle(); |
| 635 | return op.call(self, mask, scale); |
| 636 | } |
| 637 | |
| 638 | // aten::_masked_scale(Tensor self, Tensor mask, float scale) -> Tensor |
| 639 | at::Tensor _masked_scale::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, double scale) { |
| 640 | |
| 641 | static auto op = create__masked_scale_typed_handle(); |
| 642 | return op.redispatch(dispatchKeySet, self, mask, scale); |
| 643 | } |
| 644 | |
| 645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sobol_engine_draw, name, "aten::_sobol_engine_draw") |
| 646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sobol_engine_draw, overload_name, "") |
| 647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sobol_engine_draw, schema_str, "_sobol_engine_draw(Tensor quasi, int n, Tensor sobolstate, int dimension, int num_generated, ScalarType? dtype) -> (Tensor, Tensor)") |
| 648 | |
| 649 | // aten::_sobol_engine_draw(Tensor quasi, int n, Tensor sobolstate, int dimension, int num_generated, ScalarType? dtype) -> (Tensor, Tensor) |
| 650 | static C10_NOINLINE c10::TypedOperatorHandle<_sobol_engine_draw::schema> create__sobol_engine_draw_typed_handle() { |
| 651 | return c10::Dispatcher::singleton() |
| 652 | .findSchemaOrThrow(_sobol_engine_draw::name, _sobol_engine_draw::overload_name) |
| 653 | .typed<_sobol_engine_draw::schema>(); |
| 654 | } |
| 655 | |
| 656 | // aten::_sobol_engine_draw(Tensor quasi, int n, Tensor sobolstate, int dimension, int num_generated, ScalarType? dtype) -> (Tensor, Tensor) |
| 657 | ::std::tuple<at::Tensor,at::Tensor> _sobol_engine_draw::call(const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, c10::optional<at::ScalarType> dtype) { |
| 658 | |
| 659 | static auto op = create__sobol_engine_draw_typed_handle(); |
| 660 | return op.call(quasi, n, sobolstate, dimension, num_generated, dtype); |
| 661 | } |
| 662 | |
| 663 | // aten::_sobol_engine_draw(Tensor quasi, int n, Tensor sobolstate, int dimension, int num_generated, ScalarType? dtype) -> (Tensor, Tensor) |
| 664 | ::std::tuple<at::Tensor,at::Tensor> _sobol_engine_draw::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & quasi, int64_t n, const at::Tensor & sobolstate, int64_t dimension, int64_t num_generated, c10::optional<at::ScalarType> dtype) { |
| 665 | |
| 666 | static auto op = create__sobol_engine_draw_typed_handle(); |
| 667 | return op.redispatch(dispatchKeySet, quasi, n, sobolstate, dimension, num_generated, dtype); |
| 668 | } |
| 669 | |
| 670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_reshape_from_tensor, name, "aten::_reshape_from_tensor") |
| 671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_reshape_from_tensor, overload_name, "") |
| 672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_reshape_from_tensor, schema_str, "_reshape_from_tensor(Tensor self, Tensor shape) -> Tensor") |
| 673 | |
| 674 | // aten::_reshape_from_tensor(Tensor self, Tensor shape) -> Tensor |
| 675 | static C10_NOINLINE c10::TypedOperatorHandle<_reshape_from_tensor::schema> create__reshape_from_tensor_typed_handle() { |
| 676 | return c10::Dispatcher::singleton() |
| 677 | .findSchemaOrThrow(_reshape_from_tensor::name, _reshape_from_tensor::overload_name) |
| 678 | .typed<_reshape_from_tensor::schema>(); |
| 679 | } |
| 680 | |
| 681 | // aten::_reshape_from_tensor(Tensor self, Tensor shape) -> Tensor |
| 682 | at::Tensor _reshape_from_tensor::call(const at::Tensor & self, const at::Tensor & shape) { |
| 683 | |
| 684 | static auto op = create__reshape_from_tensor_typed_handle(); |
| 685 | return op.call(self, shape); |
| 686 | } |
| 687 | |
| 688 | // aten::_reshape_from_tensor(Tensor self, Tensor shape) -> Tensor |
| 689 | at::Tensor _reshape_from_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & shape) { |
| 690 | |
| 691 | static auto op = create__reshape_from_tensor_typed_handle(); |
| 692 | return op.redispatch(dispatchKeySet, self, shape); |
| 693 | } |
| 694 | |
| 695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alpha_dropout, name, "aten::alpha_dropout") |
| 696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alpha_dropout, overload_name, "") |
| 697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alpha_dropout, schema_str, "alpha_dropout(Tensor input, float p, bool train) -> Tensor") |
| 698 | |
| 699 | // aten::alpha_dropout(Tensor input, float p, bool train) -> Tensor |
| 700 | static C10_NOINLINE c10::TypedOperatorHandle<alpha_dropout::schema> create_alpha_dropout_typed_handle() { |
| 701 | return c10::Dispatcher::singleton() |
| 702 | .findSchemaOrThrow(alpha_dropout::name, alpha_dropout::overload_name) |
| 703 | .typed<alpha_dropout::schema>(); |
| 704 | } |
| 705 | |
| 706 | // aten::alpha_dropout(Tensor input, float p, bool train) -> Tensor |
| 707 | at::Tensor alpha_dropout::call(const at::Tensor & input, double p, bool train) { |
| 708 | |
| 709 | static auto op = create_alpha_dropout_typed_handle(); |
| 710 | return op.call(input, p, train); |
| 711 | } |
| 712 | |
| 713 | // aten::alpha_dropout(Tensor input, float p, bool train) -> Tensor |
| 714 | at::Tensor alpha_dropout::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, bool train) { |
| 715 | |
| 716 | static auto op = create_alpha_dropout_typed_handle(); |
| 717 | return op.redispatch(dispatchKeySet, input, p, train); |
| 718 | } |
| 719 | |
| 720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alpha_dropout_, name, "aten::alpha_dropout_") |
| 721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alpha_dropout_, overload_name, "") |
| 722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alpha_dropout_, schema_str, "alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!)") |
| 723 | |
| 724 | // aten::alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) |
| 725 | static C10_NOINLINE c10::TypedOperatorHandle<alpha_dropout_::schema> create_alpha_dropout__typed_handle() { |
| 726 | return c10::Dispatcher::singleton() |
| 727 | .findSchemaOrThrow(alpha_dropout_::name, alpha_dropout_::overload_name) |
| 728 | .typed<alpha_dropout_::schema>(); |
| 729 | } |
| 730 | |
| 731 | // aten::alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) |
| 732 | at::Tensor & alpha_dropout_::call(at::Tensor & self, double p, bool train) { |
| 733 | |
| 734 | static auto op = create_alpha_dropout__typed_handle(); |
| 735 | return op.call(self, p, train); |
| 736 | } |
| 737 | |
| 738 | // aten::alpha_dropout_(Tensor(a!) self, float p, bool train) -> Tensor(a!) |
| 739 | at::Tensor & alpha_dropout_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, bool train) { |
| 740 | |
| 741 | static auto op = create_alpha_dropout__typed_handle(); |
| 742 | return op.redispatch(dispatchKeySet, self, p, train); |
| 743 | } |
| 744 | |
| 745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_real, name, "aten::view_as_real") |
| 746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_real, overload_name, "") |
| 747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_real, schema_str, "view_as_real(Tensor(a) self) -> Tensor(a)") |
| 748 | |
| 749 | // aten::view_as_real(Tensor(a) self) -> Tensor(a) |
| 750 | static C10_NOINLINE c10::TypedOperatorHandle<view_as_real::schema> create_view_as_real_typed_handle() { |
| 751 | return c10::Dispatcher::singleton() |
| 752 | .findSchemaOrThrow(view_as_real::name, view_as_real::overload_name) |
| 753 | .typed<view_as_real::schema>(); |
| 754 | } |
| 755 | |
| 756 | // aten::view_as_real(Tensor(a) self) -> Tensor(a) |
| 757 | at::Tensor view_as_real::call(const at::Tensor & self) { |
| 758 | |
| 759 | static auto op = create_view_as_real_typed_handle(); |
| 760 | return op.call(self); |
| 761 | } |
| 762 | |
| 763 | // aten::view_as_real(Tensor(a) self) -> Tensor(a) |
| 764 | at::Tensor view_as_real::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 765 | |
| 766 | static auto op = create_view_as_real_typed_handle(); |
| 767 | return op.redispatch(dispatchKeySet, self); |
| 768 | } |
| 769 | |
| 770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex, name, "aten::view_as_complex") |
| 771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex, overload_name, "") |
| 772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_as_complex, schema_str, "view_as_complex(Tensor(a) self) -> Tensor(a)") |
| 773 | |
| 774 | // aten::view_as_complex(Tensor(a) self) -> Tensor(a) |
| 775 | static C10_NOINLINE c10::TypedOperatorHandle<view_as_complex::schema> create_view_as_complex_typed_handle() { |
| 776 | return c10::Dispatcher::singleton() |
| 777 | .findSchemaOrThrow(view_as_complex::name, view_as_complex::overload_name) |
| 778 | .typed<view_as_complex::schema>(); |
| 779 | } |
| 780 | |
| 781 | // aten::view_as_complex(Tensor(a) self) -> Tensor(a) |
| 782 | at::Tensor view_as_complex::call(const at::Tensor & self) { |
| 783 | |
| 784 | static auto op = create_view_as_complex_typed_handle(); |
| 785 | return op.call(self); |
| 786 | } |
| 787 | |
| 788 | // aten::view_as_complex(Tensor(a) self) -> Tensor(a) |
| 789 | at::Tensor view_as_complex::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 790 | |
| 791 | static auto op = create_view_as_complex_typed_handle(); |
| 792 | return op.redispatch(dispatchKeySet, self); |
| 793 | } |
| 794 | |
| 795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(chalf, name, "aten::chalf") |
| 796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(chalf, overload_name, "") |
| 797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(chalf, schema_str, "chalf(Tensor self, *, MemoryFormat? memory_format=None) -> Tensor") |
| 798 | |
| 799 | // aten::chalf(Tensor self, *, MemoryFormat? memory_format=None) -> Tensor |
| 800 | static C10_NOINLINE c10::TypedOperatorHandle<chalf::schema> create_chalf_typed_handle() { |
| 801 | return c10::Dispatcher::singleton() |
| 802 | .findSchemaOrThrow(chalf::name, chalf::overload_name) |
| 803 | .typed<chalf::schema>(); |
| 804 | } |
| 805 | |
| 806 | // aten::chalf(Tensor self, *, MemoryFormat? memory_format=None) -> Tensor |
| 807 | at::Tensor chalf::call(const at::Tensor & self, c10::optional<at::MemoryFormat> memory_format) { |
| 808 | |
| 809 | static auto op = create_chalf_typed_handle(); |
| 810 | return op.call(self, memory_format); |
| 811 | } |
| 812 | |
| 813 | // aten::chalf(Tensor self, *, MemoryFormat? memory_format=None) -> Tensor |
| 814 | at::Tensor chalf::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::MemoryFormat> memory_format) { |
| 815 | |
| 816 | static auto op = create_chalf_typed_handle(); |
| 817 | return op.redispatch(dispatchKeySet, self, memory_format); |
| 818 | } |
| 819 | |
| 820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical, name, "aten::conj_physical") |
| 821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical, overload_name, "") |
| 822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical, schema_str, "conj_physical(Tensor self) -> Tensor") |
| 823 | |
| 824 | // aten::conj_physical(Tensor self) -> Tensor |
| 825 | static C10_NOINLINE c10::TypedOperatorHandle<conj_physical::schema> create_conj_physical_typed_handle() { |
| 826 | return c10::Dispatcher::singleton() |
| 827 | .findSchemaOrThrow(conj_physical::name, conj_physical::overload_name) |
| 828 | .typed<conj_physical::schema>(); |
| 829 | } |
| 830 | |
| 831 | // aten::conj_physical(Tensor self) -> Tensor |
| 832 | at::Tensor conj_physical::call(const at::Tensor & self) { |
| 833 | |
| 834 | static auto op = create_conj_physical_typed_handle(); |
| 835 | return op.call(self); |
| 836 | } |
| 837 | |
| 838 | // aten::conj_physical(Tensor self) -> Tensor |
| 839 | at::Tensor conj_physical::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 840 | |
| 841 | static auto op = create_conj_physical_typed_handle(); |
| 842 | return op.redispatch(dispatchKeySet, self); |
| 843 | } |
| 844 | |
| 845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical_out, name, "aten::conj_physical") |
| 846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical_out, overload_name, "out") |
| 847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical_out, schema_str, "conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 848 | |
| 849 | // aten::conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 850 | static C10_NOINLINE c10::TypedOperatorHandle<conj_physical_out::schema> create_conj_physical_out_typed_handle() { |
| 851 | return c10::Dispatcher::singleton() |
| 852 | .findSchemaOrThrow(conj_physical_out::name, conj_physical_out::overload_name) |
| 853 | .typed<conj_physical_out::schema>(); |
| 854 | } |
| 855 | |
| 856 | // aten::conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 857 | at::Tensor & conj_physical_out::call(const at::Tensor & self, at::Tensor & out) { |
| 858 | |
| 859 | static auto op = create_conj_physical_out_typed_handle(); |
| 860 | return op.call(self, out); |
| 861 | } |
| 862 | |
| 863 | // aten::conj_physical.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 864 | at::Tensor & conj_physical_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 865 | |
| 866 | static auto op = create_conj_physical_out_typed_handle(); |
| 867 | return op.redispatch(dispatchKeySet, self, out); |
| 868 | } |
| 869 | |
| 870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical_, name, "aten::conj_physical_") |
| 871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical_, overload_name, "") |
| 872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conj_physical_, schema_str, "conj_physical_(Tensor(a!) self) -> Tensor(a!)") |
| 873 | |
| 874 | // aten::conj_physical_(Tensor(a!) self) -> Tensor(a!) |
| 875 | static C10_NOINLINE c10::TypedOperatorHandle<conj_physical_::schema> create_conj_physical__typed_handle() { |
| 876 | return c10::Dispatcher::singleton() |
| 877 | .findSchemaOrThrow(conj_physical_::name, conj_physical_::overload_name) |
| 878 | .typed<conj_physical_::schema>(); |
| 879 | } |
| 880 | |
| 881 | // aten::conj_physical_(Tensor(a!) self) -> Tensor(a!) |
| 882 | at::Tensor & conj_physical_::call(at::Tensor & self) { |
| 883 | |
| 884 | static auto op = create_conj_physical__typed_handle(); |
| 885 | return op.call(self); |
| 886 | } |
| 887 | |
| 888 | // aten::conj_physical_(Tensor(a!) self) -> Tensor(a!) |
| 889 | at::Tensor & conj_physical_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 890 | |
| 891 | static auto op = create_conj_physical__typed_handle(); |
| 892 | return op.redispatch(dispatchKeySet, self); |
| 893 | } |
| 894 | |
| 895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos, name, "aten::acos") |
| 896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos, overload_name, "") |
| 897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos, schema_str, "acos(Tensor self) -> Tensor") |
| 898 | |
| 899 | // aten::acos(Tensor self) -> Tensor |
| 900 | static C10_NOINLINE c10::TypedOperatorHandle<acos::schema> create_acos_typed_handle() { |
| 901 | return c10::Dispatcher::singleton() |
| 902 | .findSchemaOrThrow(acos::name, acos::overload_name) |
| 903 | .typed<acos::schema>(); |
| 904 | } |
| 905 | |
| 906 | // aten::acos(Tensor self) -> Tensor |
| 907 | at::Tensor acos::call(const at::Tensor & self) { |
| 908 | |
| 909 | static auto op = create_acos_typed_handle(); |
| 910 | return op.call(self); |
| 911 | } |
| 912 | |
| 913 | // aten::acos(Tensor self) -> Tensor |
| 914 | at::Tensor acos::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 915 | |
| 916 | static auto op = create_acos_typed_handle(); |
| 917 | return op.redispatch(dispatchKeySet, self); |
| 918 | } |
| 919 | |
| 920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos_, name, "aten::acos_") |
| 921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos_, overload_name, "") |
| 922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos_, schema_str, "acos_(Tensor(a!) self) -> Tensor(a!)") |
| 923 | |
| 924 | // aten::acos_(Tensor(a!) self) -> Tensor(a!) |
| 925 | static C10_NOINLINE c10::TypedOperatorHandle<acos_::schema> create_acos__typed_handle() { |
| 926 | return c10::Dispatcher::singleton() |
| 927 | .findSchemaOrThrow(acos_::name, acos_::overload_name) |
| 928 | .typed<acos_::schema>(); |
| 929 | } |
| 930 | |
| 931 | // aten::acos_(Tensor(a!) self) -> Tensor(a!) |
| 932 | at::Tensor & acos_::call(at::Tensor & self) { |
| 933 | |
| 934 | static auto op = create_acos__typed_handle(); |
| 935 | return op.call(self); |
| 936 | } |
| 937 | |
| 938 | // aten::acos_(Tensor(a!) self) -> Tensor(a!) |
| 939 | at::Tensor & acos_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 940 | |
| 941 | static auto op = create_acos__typed_handle(); |
| 942 | return op.redispatch(dispatchKeySet, self); |
| 943 | } |
| 944 | |
| 945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos_out, name, "aten::acos") |
| 946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos_out, overload_name, "out") |
| 947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(acos_out, schema_str, "acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 948 | |
| 949 | // aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 950 | static C10_NOINLINE c10::TypedOperatorHandle<acos_out::schema> create_acos_out_typed_handle() { |
| 951 | return c10::Dispatcher::singleton() |
| 952 | .findSchemaOrThrow(acos_out::name, acos_out::overload_name) |
| 953 | .typed<acos_out::schema>(); |
| 954 | } |
| 955 | |
| 956 | // aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 957 | at::Tensor & acos_out::call(const at::Tensor & self, at::Tensor & out) { |
| 958 | |
| 959 | static auto op = create_acos_out_typed_handle(); |
| 960 | return op.call(self, out); |
| 961 | } |
| 962 | |
| 963 | // aten::acos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 964 | at::Tensor & acos_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 965 | |
| 966 | static auto op = create_acos_out_typed_handle(); |
| 967 | return op.redispatch(dispatchKeySet, self, out); |
| 968 | } |
| 969 | |
| 970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos, name, "aten::arccos") |
| 971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos, overload_name, "") |
| 972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos, schema_str, "arccos(Tensor self) -> Tensor") |
| 973 | |
| 974 | // aten::arccos(Tensor self) -> Tensor |
| 975 | static C10_NOINLINE c10::TypedOperatorHandle<arccos::schema> create_arccos_typed_handle() { |
| 976 | return c10::Dispatcher::singleton() |
| 977 | .findSchemaOrThrow(arccos::name, arccos::overload_name) |
| 978 | .typed<arccos::schema>(); |
| 979 | } |
| 980 | |
| 981 | // aten::arccos(Tensor self) -> Tensor |
| 982 | at::Tensor arccos::call(const at::Tensor & self) { |
| 983 | |
| 984 | static auto op = create_arccos_typed_handle(); |
| 985 | return op.call(self); |
| 986 | } |
| 987 | |
| 988 | // aten::arccos(Tensor self) -> Tensor |
| 989 | at::Tensor arccos::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 990 | |
| 991 | static auto op = create_arccos_typed_handle(); |
| 992 | return op.redispatch(dispatchKeySet, self); |
| 993 | } |
| 994 | |
| 995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos_, name, "aten::arccos_") |
| 996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos_, overload_name, "") |
| 997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos_, schema_str, "arccos_(Tensor(a!) self) -> Tensor(a!)") |
| 998 | |
| 999 | // aten::arccos_(Tensor(a!) self) -> Tensor(a!) |
| 1000 | static C10_NOINLINE c10::TypedOperatorHandle<arccos_::schema> create_arccos__typed_handle() { |
| 1001 | return c10::Dispatcher::singleton() |
| 1002 | .findSchemaOrThrow(arccos_::name, arccos_::overload_name) |
| 1003 | .typed<arccos_::schema>(); |
| 1004 | } |
| 1005 | |
| 1006 | // aten::arccos_(Tensor(a!) self) -> Tensor(a!) |
| 1007 | at::Tensor & arccos_::call(at::Tensor & self) { |
| 1008 | |
| 1009 | static auto op = create_arccos__typed_handle(); |
| 1010 | return op.call(self); |
| 1011 | } |
| 1012 | |
| 1013 | // aten::arccos_(Tensor(a!) self) -> Tensor(a!) |
| 1014 | at::Tensor & arccos_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 1015 | |
| 1016 | static auto op = create_arccos__typed_handle(); |
| 1017 | return op.redispatch(dispatchKeySet, self); |
| 1018 | } |
| 1019 | |
| 1020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos_out, name, "aten::arccos") |
| 1021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos_out, overload_name, "out") |
| 1022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccos_out, schema_str, "arccos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 1023 | |
| 1024 | // aten::arccos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1025 | static C10_NOINLINE c10::TypedOperatorHandle<arccos_out::schema> create_arccos_out_typed_handle() { |
| 1026 | return c10::Dispatcher::singleton() |
| 1027 | .findSchemaOrThrow(arccos_out::name, arccos_out::overload_name) |
| 1028 | .typed<arccos_out::schema>(); |
| 1029 | } |
| 1030 | |
| 1031 | // aten::arccos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1032 | at::Tensor & arccos_out::call(const at::Tensor & self, at::Tensor & out) { |
| 1033 | |
| 1034 | static auto op = create_arccos_out_typed_handle(); |
| 1035 | return op.call(self, out); |
| 1036 | } |
| 1037 | |
| 1038 | // aten::arccos.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1039 | at::Tensor & arccos_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 1040 | |
| 1041 | static auto op = create_arccos_out_typed_handle(); |
| 1042 | return op.redispatch(dispatchKeySet, self, out); |
| 1043 | } |
| 1044 | |
| 1045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dim, name, "aten::any") |
| 1046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dim, overload_name, "dim") |
| 1047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dim, schema_str, "any.dim(Tensor self, int dim, bool keepdim=False) -> Tensor") |
| 1048 | |
| 1049 | // aten::any.dim(Tensor self, int dim, bool keepdim=False) -> Tensor |
| 1050 | static C10_NOINLINE c10::TypedOperatorHandle<any_dim::schema> create_any_dim_typed_handle() { |
| 1051 | return c10::Dispatcher::singleton() |
| 1052 | .findSchemaOrThrow(any_dim::name, any_dim::overload_name) |
| 1053 | .typed<any_dim::schema>(); |
| 1054 | } |
| 1055 | |
| 1056 | // aten::any.dim(Tensor self, int dim, bool keepdim=False) -> Tensor |
| 1057 | at::Tensor any_dim::call(const at::Tensor & self, int64_t dim, bool keepdim) { |
| 1058 | |
| 1059 | static auto op = create_any_dim_typed_handle(); |
| 1060 | return op.call(self, dim, keepdim); |
| 1061 | } |
| 1062 | |
| 1063 | // aten::any.dim(Tensor self, int dim, bool keepdim=False) -> Tensor |
| 1064 | at::Tensor any_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim) { |
| 1065 | |
| 1066 | static auto op = create_any_dim_typed_handle(); |
| 1067 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 1068 | } |
| 1069 | |
| 1070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_out, name, "aten::any") |
| 1071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_out, overload_name, "out") |
| 1072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_out, schema_str, "any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 1073 | |
| 1074 | // aten::any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1075 | static C10_NOINLINE c10::TypedOperatorHandle<any_out::schema> create_any_out_typed_handle() { |
| 1076 | return c10::Dispatcher::singleton() |
| 1077 | .findSchemaOrThrow(any_out::name, any_out::overload_name) |
| 1078 | .typed<any_out::schema>(); |
| 1079 | } |
| 1080 | |
| 1081 | // aten::any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1082 | at::Tensor & any_out::call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out) { |
| 1083 | |
| 1084 | static auto op = create_any_out_typed_handle(); |
| 1085 | return op.call(self, dim, keepdim, out); |
| 1086 | } |
| 1087 | |
| 1088 | // aten::any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1089 | at::Tensor & any_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out) { |
| 1090 | |
| 1091 | static auto op = create_any_out_typed_handle(); |
| 1092 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
| 1093 | } |
| 1094 | |
| 1095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dimname, name, "aten::any") |
| 1096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dimname, overload_name, "dimname") |
| 1097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dimname, schema_str, "any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor") |
| 1098 | |
| 1099 | // aten::any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor |
| 1100 | static C10_NOINLINE c10::TypedOperatorHandle<any_dimname::schema> create_any_dimname_typed_handle() { |
| 1101 | return c10::Dispatcher::singleton() |
| 1102 | .findSchemaOrThrow(any_dimname::name, any_dimname::overload_name) |
| 1103 | .typed<any_dimname::schema>(); |
| 1104 | } |
| 1105 | |
| 1106 | // aten::any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor |
| 1107 | at::Tensor any_dimname::call(const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 1108 | |
| 1109 | static auto op = create_any_dimname_typed_handle(); |
| 1110 | return op.call(self, dim, keepdim); |
| 1111 | } |
| 1112 | |
| 1113 | // aten::any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor |
| 1114 | at::Tensor any_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 1115 | |
| 1116 | static auto op = create_any_dimname_typed_handle(); |
| 1117 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 1118 | } |
| 1119 | |
| 1120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dimname_out, name, "aten::any") |
| 1121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dimname_out, overload_name, "dimname_out") |
| 1122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_dimname_out, schema_str, "any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 1123 | |
| 1124 | // aten::any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1125 | static C10_NOINLINE c10::TypedOperatorHandle<any_dimname_out::schema> create_any_dimname_out_typed_handle() { |
| 1126 | return c10::Dispatcher::singleton() |
| 1127 | .findSchemaOrThrow(any_dimname_out::name, any_dimname_out::overload_name) |
| 1128 | .typed<any_dimname_out::schema>(); |
| 1129 | } |
| 1130 | |
| 1131 | // aten::any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1132 | at::Tensor & any_dimname_out::call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out) { |
| 1133 | |
| 1134 | static auto op = create_any_dimname_out_typed_handle(); |
| 1135 | return op.call(self, dim, keepdim, out); |
| 1136 | } |
| 1137 | |
| 1138 | // aten::any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
| 1139 | at::Tensor & any_dimname_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out) { |
| 1140 | |
| 1141 | static auto op = create_any_dimname_out_typed_handle(); |
| 1142 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
| 1143 | } |
| 1144 | |
| 1145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh, name, "aten::arccosh") |
| 1146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh, overload_name, "") |
| 1147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh, schema_str, "arccosh(Tensor self) -> Tensor") |
| 1148 | |
| 1149 | // aten::arccosh(Tensor self) -> Tensor |
| 1150 | static C10_NOINLINE c10::TypedOperatorHandle<arccosh::schema> create_arccosh_typed_handle() { |
| 1151 | return c10::Dispatcher::singleton() |
| 1152 | .findSchemaOrThrow(arccosh::name, arccosh::overload_name) |
| 1153 | .typed<arccosh::schema>(); |
| 1154 | } |
| 1155 | |
| 1156 | // aten::arccosh(Tensor self) -> Tensor |
| 1157 | at::Tensor arccosh::call(const at::Tensor & self) { |
| 1158 | |
| 1159 | static auto op = create_arccosh_typed_handle(); |
| 1160 | return op.call(self); |
| 1161 | } |
| 1162 | |
| 1163 | // aten::arccosh(Tensor self) -> Tensor |
| 1164 | at::Tensor arccosh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1165 | |
| 1166 | static auto op = create_arccosh_typed_handle(); |
| 1167 | return op.redispatch(dispatchKeySet, self); |
| 1168 | } |
| 1169 | |
| 1170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh_, name, "aten::arccosh_") |
| 1171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh_, overload_name, "") |
| 1172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh_, schema_str, "arccosh_(Tensor(a!) self) -> Tensor(a!)") |
| 1173 | |
| 1174 | // aten::arccosh_(Tensor(a!) self) -> Tensor(a!) |
| 1175 | static C10_NOINLINE c10::TypedOperatorHandle<arccosh_::schema> create_arccosh__typed_handle() { |
| 1176 | return c10::Dispatcher::singleton() |
| 1177 | .findSchemaOrThrow(arccosh_::name, arccosh_::overload_name) |
| 1178 | .typed<arccosh_::schema>(); |
| 1179 | } |
| 1180 | |
| 1181 | // aten::arccosh_(Tensor(a!) self) -> Tensor(a!) |
| 1182 | at::Tensor & arccosh_::call(at::Tensor & self) { |
| 1183 | |
| 1184 | static auto op = create_arccosh__typed_handle(); |
| 1185 | return op.call(self); |
| 1186 | } |
| 1187 | |
| 1188 | // aten::arccosh_(Tensor(a!) self) -> Tensor(a!) |
| 1189 | at::Tensor & arccosh_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 1190 | |
| 1191 | static auto op = create_arccosh__typed_handle(); |
| 1192 | return op.redispatch(dispatchKeySet, self); |
| 1193 | } |
| 1194 | |
| 1195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh_out, name, "aten::arccosh") |
| 1196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh_out, overload_name, "out") |
| 1197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(arccosh_out, schema_str, "arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 1198 | |
| 1199 | // aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1200 | static C10_NOINLINE c10::TypedOperatorHandle<arccosh_out::schema> create_arccosh_out_typed_handle() { |
| 1201 | return c10::Dispatcher::singleton() |
| 1202 | .findSchemaOrThrow(arccosh_out::name, arccosh_out::overload_name) |
| 1203 | .typed<arccosh_out::schema>(); |
| 1204 | } |
| 1205 | |
| 1206 | // aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1207 | at::Tensor & arccosh_out::call(const at::Tensor & self, at::Tensor & out) { |
| 1208 | |
| 1209 | static auto op = create_arccosh_out_typed_handle(); |
| 1210 | return op.call(self, out); |
| 1211 | } |
| 1212 | |
| 1213 | // aten::arccosh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1214 | at::Tensor & arccosh_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 1215 | |
| 1216 | static auto op = create_arccosh_out_typed_handle(); |
| 1217 | return op.redispatch(dispatchKeySet, self, out); |
| 1218 | } |
| 1219 | |
| 1220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin, name, "aten::asin") |
| 1221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin, overload_name, "") |
| 1222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin, schema_str, "asin(Tensor self) -> Tensor") |
| 1223 | |
| 1224 | // aten::asin(Tensor self) -> Tensor |
| 1225 | static C10_NOINLINE c10::TypedOperatorHandle<asin::schema> create_asin_typed_handle() { |
| 1226 | return c10::Dispatcher::singleton() |
| 1227 | .findSchemaOrThrow(asin::name, asin::overload_name) |
| 1228 | .typed<asin::schema>(); |
| 1229 | } |
| 1230 | |
| 1231 | // aten::asin(Tensor self) -> Tensor |
| 1232 | at::Tensor asin::call(const at::Tensor & self) { |
| 1233 | |
| 1234 | static auto op = create_asin_typed_handle(); |
| 1235 | return op.call(self); |
| 1236 | } |
| 1237 | |
| 1238 | // aten::asin(Tensor self) -> Tensor |
| 1239 | at::Tensor asin::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1240 | |
| 1241 | static auto op = create_asin_typed_handle(); |
| 1242 | return op.redispatch(dispatchKeySet, self); |
| 1243 | } |
| 1244 | |
| 1245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin_, name, "aten::asin_") |
| 1246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin_, overload_name, "") |
| 1247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin_, schema_str, "asin_(Tensor(a!) self) -> Tensor(a!)") |
| 1248 | |
| 1249 | // aten::asin_(Tensor(a!) self) -> Tensor(a!) |
| 1250 | static C10_NOINLINE c10::TypedOperatorHandle<asin_::schema> create_asin__typed_handle() { |
| 1251 | return c10::Dispatcher::singleton() |
| 1252 | .findSchemaOrThrow(asin_::name, asin_::overload_name) |
| 1253 | .typed<asin_::schema>(); |
| 1254 | } |
| 1255 | |
| 1256 | // aten::asin_(Tensor(a!) self) -> Tensor(a!) |
| 1257 | at::Tensor & asin_::call(at::Tensor & self) { |
| 1258 | |
| 1259 | static auto op = create_asin__typed_handle(); |
| 1260 | return op.call(self); |
| 1261 | } |
| 1262 | |
| 1263 | // aten::asin_(Tensor(a!) self) -> Tensor(a!) |
| 1264 | at::Tensor & asin_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 1265 | |
| 1266 | static auto op = create_asin__typed_handle(); |
| 1267 | return op.redispatch(dispatchKeySet, self); |
| 1268 | } |
| 1269 | |
| 1270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin_out, name, "aten::asin") |
| 1271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin_out, overload_name, "out") |
| 1272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asin_out, schema_str, "asin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 1273 | |
| 1274 | // aten::asin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1275 | static C10_NOINLINE c10::TypedOperatorHandle<asin_out::schema> create_asin_out_typed_handle() { |
| 1276 | return c10::Dispatcher::singleton() |
| 1277 | .findSchemaOrThrow(asin_out::name, asin_out::overload_name) |
| 1278 | .typed<asin_out::schema>(); |
| 1279 | } |
| 1280 | |
| 1281 | // aten::asin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1282 | at::Tensor & asin_out::call(const at::Tensor & self, at::Tensor & out) { |
| 1283 | |
| 1284 | static auto op = create_asin_out_typed_handle(); |
| 1285 | return op.call(self, out); |
| 1286 | } |
| 1287 | |
| 1288 | // aten::asin.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 1289 | at::Tensor & asin_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 1290 | |
| 1291 | static auto op = create_asin_out_typed_handle(); |
| 1292 | return op.redispatch(dispatchKeySet, self, out); |
| 1293 | } |
| 1294 | |
| 1295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_1d, name, "aten::atleast_1d") |
| 1296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_1d, overload_name, "") |
| 1297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_1d, schema_str, "atleast_1d(Tensor self) -> Tensor") |
| 1298 | |
| 1299 | // aten::atleast_1d(Tensor self) -> Tensor |
| 1300 | static C10_NOINLINE c10::TypedOperatorHandle<atleast_1d::schema> create_atleast_1d_typed_handle() { |
| 1301 | return c10::Dispatcher::singleton() |
| 1302 | .findSchemaOrThrow(atleast_1d::name, atleast_1d::overload_name) |
| 1303 | .typed<atleast_1d::schema>(); |
| 1304 | } |
| 1305 | |
| 1306 | // aten::atleast_1d(Tensor self) -> Tensor |
| 1307 | at::Tensor atleast_1d::call(const at::Tensor & self) { |
| 1308 | |
| 1309 | static auto op = create_atleast_1d_typed_handle(); |
| 1310 | return op.call(self); |
| 1311 | } |
| 1312 | |
| 1313 | // aten::atleast_1d(Tensor self) -> Tensor |
| 1314 | at::Tensor atleast_1d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1315 | |
| 1316 | static auto op = create_atleast_1d_typed_handle(); |
| 1317 | return op.redispatch(dispatchKeySet, self); |
| 1318 | } |
| 1319 | |
| 1320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_1d_Sequence, name, "aten::atleast_1d") |
| 1321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_1d_Sequence, overload_name, "Sequence") |
| 1322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_1d_Sequence, schema_str, "atleast_1d.Sequence(Tensor[] tensors) -> Tensor[]") |
| 1323 | |
| 1324 | // aten::atleast_1d.Sequence(Tensor[] tensors) -> Tensor[] |
| 1325 | static C10_NOINLINE c10::TypedOperatorHandle<atleast_1d_Sequence::schema> create_atleast_1d_Sequence_typed_handle() { |
| 1326 | return c10::Dispatcher::singleton() |
| 1327 | .findSchemaOrThrow(atleast_1d_Sequence::name, atleast_1d_Sequence::overload_name) |
| 1328 | .typed<atleast_1d_Sequence::schema>(); |
| 1329 | } |
| 1330 | |
| 1331 | // aten::atleast_1d.Sequence(Tensor[] tensors) -> Tensor[] |
| 1332 | ::std::vector<at::Tensor> atleast_1d_Sequence::call(at::TensorList tensors) { |
| 1333 | |
| 1334 | static auto op = create_atleast_1d_Sequence_typed_handle(); |
| 1335 | return op.call(tensors); |
| 1336 | } |
| 1337 | |
| 1338 | // aten::atleast_1d.Sequence(Tensor[] tensors) -> Tensor[] |
| 1339 | ::std::vector<at::Tensor> atleast_1d_Sequence::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 1340 | |
| 1341 | static auto op = create_atleast_1d_Sequence_typed_handle(); |
| 1342 | return op.redispatch(dispatchKeySet, tensors); |
| 1343 | } |
| 1344 | |
| 1345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_out, name, "aten::copysign") |
| 1346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_out, overload_name, "out") |
| 1347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_out, schema_str, "copysign.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 1348 | |
| 1349 | // aten::copysign.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1350 | static C10_NOINLINE c10::TypedOperatorHandle<copysign_out::schema> create_copysign_out_typed_handle() { |
| 1351 | return c10::Dispatcher::singleton() |
| 1352 | .findSchemaOrThrow(copysign_out::name, copysign_out::overload_name) |
| 1353 | .typed<copysign_out::schema>(); |
| 1354 | } |
| 1355 | |
| 1356 | // aten::copysign.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1357 | at::Tensor & copysign_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 1358 | |
| 1359 | static auto op = create_copysign_out_typed_handle(); |
| 1360 | return op.call(self, other, out); |
| 1361 | } |
| 1362 | |
| 1363 | // aten::copysign.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1364 | at::Tensor & copysign_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 1365 | |
| 1366 | static auto op = create_copysign_out_typed_handle(); |
| 1367 | return op.redispatch(dispatchKeySet, self, other, out); |
| 1368 | } |
| 1369 | |
| 1370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Tensor, name, "aten::copysign") |
| 1371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Tensor, overload_name, "Tensor") |
| 1372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Tensor, schema_str, "copysign.Tensor(Tensor self, Tensor other) -> Tensor") |
| 1373 | |
| 1374 | // aten::copysign.Tensor(Tensor self, Tensor other) -> Tensor |
| 1375 | static C10_NOINLINE c10::TypedOperatorHandle<copysign_Tensor::schema> create_copysign_Tensor_typed_handle() { |
| 1376 | return c10::Dispatcher::singleton() |
| 1377 | .findSchemaOrThrow(copysign_Tensor::name, copysign_Tensor::overload_name) |
| 1378 | .typed<copysign_Tensor::schema>(); |
| 1379 | } |
| 1380 | |
| 1381 | // aten::copysign.Tensor(Tensor self, Tensor other) -> Tensor |
| 1382 | at::Tensor copysign_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 1383 | |
| 1384 | static auto op = create_copysign_Tensor_typed_handle(); |
| 1385 | return op.call(self, other); |
| 1386 | } |
| 1387 | |
| 1388 | // aten::copysign.Tensor(Tensor self, Tensor other) -> Tensor |
| 1389 | at::Tensor copysign_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 1390 | |
| 1391 | static auto op = create_copysign_Tensor_typed_handle(); |
| 1392 | return op.redispatch(dispatchKeySet, self, other); |
| 1393 | } |
| 1394 | |
| 1395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign__Tensor, name, "aten::copysign_") |
| 1396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign__Tensor, overload_name, "Tensor") |
| 1397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign__Tensor, schema_str, "copysign_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 1398 | |
| 1399 | // aten::copysign_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1400 | static C10_NOINLINE c10::TypedOperatorHandle<copysign__Tensor::schema> create_copysign__Tensor_typed_handle() { |
| 1401 | return c10::Dispatcher::singleton() |
| 1402 | .findSchemaOrThrow(copysign__Tensor::name, copysign__Tensor::overload_name) |
| 1403 | .typed<copysign__Tensor::schema>(); |
| 1404 | } |
| 1405 | |
| 1406 | // aten::copysign_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1407 | at::Tensor & copysign__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 1408 | |
| 1409 | static auto op = create_copysign__Tensor_typed_handle(); |
| 1410 | return op.call(self, other); |
| 1411 | } |
| 1412 | |
| 1413 | // aten::copysign_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1414 | at::Tensor & copysign__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 1415 | |
| 1416 | static auto op = create_copysign__Tensor_typed_handle(); |
| 1417 | return op.redispatch(dispatchKeySet, self, other); |
| 1418 | } |
| 1419 | |
| 1420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Scalar, name, "aten::copysign") |
| 1421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Scalar, overload_name, "Scalar") |
| 1422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Scalar, schema_str, "copysign.Scalar(Tensor self, Scalar other) -> Tensor") |
| 1423 | |
| 1424 | // aten::copysign.Scalar(Tensor self, Scalar other) -> Tensor |
| 1425 | static C10_NOINLINE c10::TypedOperatorHandle<copysign_Scalar::schema> create_copysign_Scalar_typed_handle() { |
| 1426 | return c10::Dispatcher::singleton() |
| 1427 | .findSchemaOrThrow(copysign_Scalar::name, copysign_Scalar::overload_name) |
| 1428 | .typed<copysign_Scalar::schema>(); |
| 1429 | } |
| 1430 | |
| 1431 | // aten::copysign.Scalar(Tensor self, Scalar other) -> Tensor |
| 1432 | at::Tensor copysign_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 1433 | |
| 1434 | static auto op = create_copysign_Scalar_typed_handle(); |
| 1435 | return op.call(self, other); |
| 1436 | } |
| 1437 | |
| 1438 | // aten::copysign.Scalar(Tensor self, Scalar other) -> Tensor |
| 1439 | at::Tensor copysign_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 1440 | |
| 1441 | static auto op = create_copysign_Scalar_typed_handle(); |
| 1442 | return op.redispatch(dispatchKeySet, self, other); |
| 1443 | } |
| 1444 | |
| 1445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign__Scalar, name, "aten::copysign_") |
| 1446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign__Scalar, overload_name, "Scalar") |
| 1447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign__Scalar, schema_str, "copysign_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 1448 | |
| 1449 | // aten::copysign_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 1450 | static C10_NOINLINE c10::TypedOperatorHandle<copysign__Scalar::schema> create_copysign__Scalar_typed_handle() { |
| 1451 | return c10::Dispatcher::singleton() |
| 1452 | .findSchemaOrThrow(copysign__Scalar::name, copysign__Scalar::overload_name) |
| 1453 | .typed<copysign__Scalar::schema>(); |
| 1454 | } |
| 1455 | |
| 1456 | // aten::copysign_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 1457 | at::Tensor & copysign__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 1458 | |
| 1459 | static auto op = create_copysign__Scalar_typed_handle(); |
| 1460 | return op.call(self, other); |
| 1461 | } |
| 1462 | |
| 1463 | // aten::copysign_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 1464 | at::Tensor & copysign__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 1465 | |
| 1466 | static auto op = create_copysign__Scalar_typed_handle(); |
| 1467 | return op.redispatch(dispatchKeySet, self, other); |
| 1468 | } |
| 1469 | |
| 1470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Scalar_out, name, "aten::copysign") |
| 1471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Scalar_out, overload_name, "Scalar_out") |
| 1472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(copysign_Scalar_out, schema_str, "copysign.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 1473 | |
| 1474 | // aten::copysign.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 1475 | static C10_NOINLINE c10::TypedOperatorHandle<copysign_Scalar_out::schema> create_copysign_Scalar_out_typed_handle() { |
| 1476 | return c10::Dispatcher::singleton() |
| 1477 | .findSchemaOrThrow(copysign_Scalar_out::name, copysign_Scalar_out::overload_name) |
| 1478 | .typed<copysign_Scalar_out::schema>(); |
| 1479 | } |
| 1480 | |
| 1481 | // aten::copysign.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 1482 | at::Tensor & copysign_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 1483 | |
| 1484 | static auto op = create_copysign_Scalar_out_typed_handle(); |
| 1485 | return op.call(self, other, out); |
| 1486 | } |
| 1487 | |
| 1488 | // aten::copysign.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 1489 | at::Tensor & copysign_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 1490 | |
| 1491 | static auto op = create_copysign_Scalar_out_typed_handle(); |
| 1492 | return op.redispatch(dispatchKeySet, self, other, out); |
| 1493 | } |
| 1494 | |
| 1495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor, name, "aten::logical_xor") |
| 1496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor, overload_name, "") |
| 1497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor, schema_str, "logical_xor(Tensor self, Tensor other) -> Tensor") |
| 1498 | |
| 1499 | // aten::logical_xor(Tensor self, Tensor other) -> Tensor |
| 1500 | static C10_NOINLINE c10::TypedOperatorHandle<logical_xor::schema> create_logical_xor_typed_handle() { |
| 1501 | return c10::Dispatcher::singleton() |
| 1502 | .findSchemaOrThrow(logical_xor::name, logical_xor::overload_name) |
| 1503 | .typed<logical_xor::schema>(); |
| 1504 | } |
| 1505 | |
| 1506 | // aten::logical_xor(Tensor self, Tensor other) -> Tensor |
| 1507 | at::Tensor logical_xor::call(const at::Tensor & self, const at::Tensor & other) { |
| 1508 | |
| 1509 | static auto op = create_logical_xor_typed_handle(); |
| 1510 | return op.call(self, other); |
| 1511 | } |
| 1512 | |
| 1513 | // aten::logical_xor(Tensor self, Tensor other) -> Tensor |
| 1514 | at::Tensor logical_xor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 1515 | |
| 1516 | static auto op = create_logical_xor_typed_handle(); |
| 1517 | return op.redispatch(dispatchKeySet, self, other); |
| 1518 | } |
| 1519 | |
| 1520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor_, name, "aten::logical_xor_") |
| 1521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor_, overload_name, "") |
| 1522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor_, schema_str, "logical_xor_(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 1523 | |
| 1524 | // aten::logical_xor_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1525 | static C10_NOINLINE c10::TypedOperatorHandle<logical_xor_::schema> create_logical_xor__typed_handle() { |
| 1526 | return c10::Dispatcher::singleton() |
| 1527 | .findSchemaOrThrow(logical_xor_::name, logical_xor_::overload_name) |
| 1528 | .typed<logical_xor_::schema>(); |
| 1529 | } |
| 1530 | |
| 1531 | // aten::logical_xor_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1532 | at::Tensor & logical_xor_::call(at::Tensor & self, const at::Tensor & other) { |
| 1533 | |
| 1534 | static auto op = create_logical_xor__typed_handle(); |
| 1535 | return op.call(self, other); |
| 1536 | } |
| 1537 | |
| 1538 | // aten::logical_xor_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 1539 | at::Tensor & logical_xor_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 1540 | |
| 1541 | static auto op = create_logical_xor__typed_handle(); |
| 1542 | return op.redispatch(dispatchKeySet, self, other); |
| 1543 | } |
| 1544 | |
| 1545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor_out, name, "aten::logical_xor") |
| 1546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor_out, overload_name, "out") |
| 1547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_xor_out, schema_str, "logical_xor.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 1548 | |
| 1549 | // aten::logical_xor.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1550 | static C10_NOINLINE c10::TypedOperatorHandle<logical_xor_out::schema> create_logical_xor_out_typed_handle() { |
| 1551 | return c10::Dispatcher::singleton() |
| 1552 | .findSchemaOrThrow(logical_xor_out::name, logical_xor_out::overload_name) |
| 1553 | .typed<logical_xor_out::schema>(); |
| 1554 | } |
| 1555 | |
| 1556 | // aten::logical_xor.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1557 | at::Tensor & logical_xor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 1558 | |
| 1559 | static auto op = create_logical_xor_out_typed_handle(); |
| 1560 | return op.call(self, other, out); |
| 1561 | } |
| 1562 | |
| 1563 | // aten::logical_xor.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 1564 | at::Tensor & logical_xor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 1565 | |
| 1566 | static auto op = create_logical_xor_out_typed_handle(); |
| 1567 | return op.redispatch(dispatchKeySet, self, other, out); |
| 1568 | } |
| 1569 | |
| 1570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(broadcast_to, name, "aten::broadcast_to") |
| 1571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(broadcast_to, overload_name, "") |
| 1572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(broadcast_to, schema_str, "broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a)") |
| 1573 | |
| 1574 | // aten::broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a) |
| 1575 | static C10_NOINLINE c10::TypedOperatorHandle<broadcast_to::schema> create_broadcast_to_typed_handle() { |
| 1576 | return c10::Dispatcher::singleton() |
| 1577 | .findSchemaOrThrow(broadcast_to::name, broadcast_to::overload_name) |
| 1578 | .typed<broadcast_to::schema>(); |
| 1579 | } |
| 1580 | |
| 1581 | // aten::broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a) |
| 1582 | at::Tensor broadcast_to::call(const at::Tensor & self, c10::SymIntArrayRef size) { |
| 1583 | |
| 1584 | static auto op = create_broadcast_to_typed_handle(); |
| 1585 | return op.call(self, size); |
| 1586 | } |
| 1587 | |
| 1588 | // aten::broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a) |
| 1589 | at::Tensor broadcast_to::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size) { |
| 1590 | |
| 1591 | static auto op = create_broadcast_to_typed_handle(); |
| 1592 | return op.redispatch(dispatchKeySet, self, size); |
| 1593 | } |
| 1594 | |
| 1595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(constant_pad_nd, name, "aten::constant_pad_nd") |
| 1596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(constant_pad_nd, overload_name, "") |
| 1597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(constant_pad_nd, schema_str, "constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor") |
| 1598 | |
| 1599 | // aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor |
| 1600 | static C10_NOINLINE c10::TypedOperatorHandle<constant_pad_nd::schema> create_constant_pad_nd_typed_handle() { |
| 1601 | return c10::Dispatcher::singleton() |
| 1602 | .findSchemaOrThrow(constant_pad_nd::name, constant_pad_nd::overload_name) |
| 1603 | .typed<constant_pad_nd::schema>(); |
| 1604 | } |
| 1605 | |
| 1606 | // aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor |
| 1607 | at::Tensor constant_pad_nd::call(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value) { |
| 1608 | |
| 1609 | static auto op = create_constant_pad_nd_typed_handle(); |
| 1610 | return op.call(self, pad, value); |
| 1611 | } |
| 1612 | |
| 1613 | // aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor |
| 1614 | at::Tensor constant_pad_nd::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value) { |
| 1615 | |
| 1616 | static auto op = create_constant_pad_nd_typed_handle(); |
| 1617 | return op.redispatch(dispatchKeySet, self, pad, value); |
| 1618 | } |
| 1619 | |
| 1620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(contiguous, name, "aten::contiguous") |
| 1621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(contiguous, overload_name, "") |
| 1622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(contiguous, schema_str, "contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a)") |
| 1623 | |
| 1624 | // aten::contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a) |
| 1625 | static C10_NOINLINE c10::TypedOperatorHandle<contiguous::schema> create_contiguous_typed_handle() { |
| 1626 | return c10::Dispatcher::singleton() |
| 1627 | .findSchemaOrThrow(contiguous::name, contiguous::overload_name) |
| 1628 | .typed<contiguous::schema>(); |
| 1629 | } |
| 1630 | |
| 1631 | // aten::contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a) |
| 1632 | at::Tensor contiguous::call(const at::Tensor & self, at::MemoryFormat memory_format) { |
| 1633 | |
| 1634 | static auto op = create_contiguous_typed_handle(); |
| 1635 | return op.call(self, memory_format); |
| 1636 | } |
| 1637 | |
| 1638 | // aten::contiguous(Tensor(a) self, *, MemoryFormat memory_format=contiguous_format) -> Tensor(a) |
| 1639 | at::Tensor contiguous::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::MemoryFormat memory_format) { |
| 1640 | |
| 1641 | static auto op = create_contiguous_typed_handle(); |
| 1642 | return op.redispatch(dispatchKeySet, self, memory_format); |
| 1643 | } |
| 1644 | |
| 1645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward, name, "aten::convolution_backward") |
| 1646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward, overload_name, "") |
| 1647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward, schema_str, "convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)") |
| 1648 | |
| 1649 | // aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
| 1650 | static C10_NOINLINE c10::TypedOperatorHandle<convolution_backward::schema> create_convolution_backward_typed_handle() { |
| 1651 | return c10::Dispatcher::singleton() |
| 1652 | .findSchemaOrThrow(convolution_backward::name, convolution_backward::overload_name) |
| 1653 | .typed<convolution_backward::schema>(); |
| 1654 | } |
| 1655 | |
| 1656 | // aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
| 1657 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> convolution_backward::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask) { |
| 1658 | |
| 1659 | static auto op = create_convolution_backward_typed_handle(); |
| 1660 | return op.call(grad_output, input, weight, bias_sizes, stride, padding, dilation, transposed, output_padding, groups, output_mask); |
| 1661 | } |
| 1662 | |
| 1663 | // aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
| 1664 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> convolution_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask) { |
| 1665 | |
| 1666 | static auto op = create_convolution_backward_typed_handle(); |
| 1667 | return op.redispatch(dispatchKeySet, grad_output, input, weight, bias_sizes, stride, padding, dilation, transposed, output_padding, groups, output_mask); |
| 1668 | } |
| 1669 | |
| 1670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_overrideable, name, "aten::convolution_overrideable") |
| 1671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_overrideable, overload_name, "") |
| 1672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_overrideable, schema_str, "convolution_overrideable(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor") |
| 1673 | |
| 1674 | // aten::convolution_overrideable(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor |
| 1675 | static C10_NOINLINE c10::TypedOperatorHandle<convolution_overrideable::schema> create_convolution_overrideable_typed_handle() { |
| 1676 | return c10::Dispatcher::singleton() |
| 1677 | .findSchemaOrThrow(convolution_overrideable::name, convolution_overrideable::overload_name) |
| 1678 | .typed<convolution_overrideable::schema>(); |
| 1679 | } |
| 1680 | |
| 1681 | // aten::convolution_overrideable(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor |
| 1682 | at::Tensor convolution_overrideable::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) { |
| 1683 | |
| 1684 | static auto op = create_convolution_overrideable_typed_handle(); |
| 1685 | return op.call(input, weight, bias, stride, padding, dilation, transposed, output_padding, groups); |
| 1686 | } |
| 1687 | |
| 1688 | // aten::convolution_overrideable(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor |
| 1689 | at::Tensor convolution_overrideable::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) { |
| 1690 | |
| 1691 | static auto op = create_convolution_overrideable_typed_handle(); |
| 1692 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, transposed, output_padding, groups); |
| 1693 | } |
| 1694 | |
| 1695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_double_backward, name, "aten::_convolution_double_backward") |
| 1696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_double_backward, overload_name, "") |
| 1697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convolution_double_backward, schema_str, "_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)") |
| 1698 | |
| 1699 | // aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
| 1700 | static C10_NOINLINE c10::TypedOperatorHandle<_convolution_double_backward::schema> create__convolution_double_backward_typed_handle() { |
| 1701 | return c10::Dispatcher::singleton() |
| 1702 | .findSchemaOrThrow(_convolution_double_backward::name, _convolution_double_backward::overload_name) |
| 1703 | .typed<_convolution_double_backward::schema>(); |
| 1704 | } |
| 1705 | |
| 1706 | // aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
| 1707 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _convolution_double_backward::call(const c10::optional<at::Tensor> & ggI, const c10::optional<at::Tensor> & ggW, const c10::optional<at::Tensor> & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask) { |
| 1708 | |
| 1709 | static auto op = create__convolution_double_backward_typed_handle(); |
| 1710 | return op.call(ggI, ggW, ggb, gO, weight, self, stride, padding, dilation, transposed, output_padding, groups, output_mask); |
| 1711 | } |
| 1712 | |
| 1713 | // aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
| 1714 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _convolution_double_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const c10::optional<at::Tensor> & ggI, const c10::optional<at::Tensor> & ggW, const c10::optional<at::Tensor> & ggb, const at::Tensor & gO, const at::Tensor & weight, const at::Tensor & self, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask) { |
| 1715 | |
| 1716 | static auto op = create__convolution_double_backward_typed_handle(); |
| 1717 | return op.redispatch(dispatchKeySet, ggI, ggW, ggb, gO, weight, self, stride, padding, dilation, transposed, output_padding, groups, output_mask); |
| 1718 | } |
| 1719 | |
| 1720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv2d, name, "aten::conv2d") |
| 1721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv2d, overload_name, "") |
| 1722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv2d, schema_str, "conv2d(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, int groups=1) -> Tensor") |
| 1723 | |
| 1724 | // aten::conv2d(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, int groups=1) -> Tensor |
| 1725 | static C10_NOINLINE c10::TypedOperatorHandle<conv2d::schema> create_conv2d_typed_handle() { |
| 1726 | return c10::Dispatcher::singleton() |
| 1727 | .findSchemaOrThrow(conv2d::name, conv2d::overload_name) |
| 1728 | .typed<conv2d::schema>(); |
| 1729 | } |
| 1730 | |
| 1731 | // aten::conv2d(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, int groups=1) -> Tensor |
| 1732 | at::Tensor conv2d::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { |
| 1733 | |
| 1734 | static auto op = create_conv2d_typed_handle(); |
| 1735 | return op.call(input, weight, bias, stride, padding, dilation, groups); |
| 1736 | } |
| 1737 | |
| 1738 | // aten::conv2d(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, int groups=1) -> Tensor |
| 1739 | at::Tensor conv2d::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, int64_t groups) { |
| 1740 | |
| 1741 | static auto op = create_conv2d_typed_handle(); |
| 1742 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, groups); |
| 1743 | } |
| 1744 | |
| 1745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv2d_padding, name, "aten::conv2d") |
| 1746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv2d_padding, overload_name, "padding") |
| 1747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv2d_padding, schema_str, "conv2d.padding(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, str padding=\"valid\", int[2] dilation=1, int groups=1) -> Tensor") |
| 1748 | |
| 1749 | // aten::conv2d.padding(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, str padding="valid", int[2] dilation=1, int groups=1) -> Tensor |
| 1750 | static C10_NOINLINE c10::TypedOperatorHandle<conv2d_padding::schema> create_conv2d_padding_typed_handle() { |
| 1751 | return c10::Dispatcher::singleton() |
| 1752 | .findSchemaOrThrow(conv2d_padding::name, conv2d_padding::overload_name) |
| 1753 | .typed<conv2d_padding::schema>(); |
| 1754 | } |
| 1755 | |
| 1756 | // aten::conv2d.padding(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, str padding="valid", int[2] dilation=1, int groups=1) -> Tensor |
| 1757 | at::Tensor conv2d_padding::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation, int64_t groups) { |
| 1758 | |
| 1759 | static auto op = create_conv2d_padding_typed_handle(); |
| 1760 | return op.call(input, weight, bias, stride, padding, dilation, groups); |
| 1761 | } |
| 1762 | |
| 1763 | // aten::conv2d.padding(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, str padding="valid", int[2] dilation=1, int groups=1) -> Tensor |
| 1764 | at::Tensor conv2d_padding::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::string_view padding, at::IntArrayRef dilation, int64_t groups) { |
| 1765 | |
| 1766 | static auto op = create_conv2d_padding_typed_handle(); |
| 1767 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, groups); |
| 1768 | } |
| 1769 | |
| 1770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_copy_from, name, "aten::_copy_from") |
| 1771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_copy_from, overload_name, "") |
| 1772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_copy_from, schema_str, "_copy_from(Tensor self, Tensor dst, bool non_blocking=False) -> Tensor") |
| 1773 | |
| 1774 | // aten::_copy_from(Tensor self, Tensor dst, bool non_blocking=False) -> Tensor |
| 1775 | static C10_NOINLINE c10::TypedOperatorHandle<_copy_from::schema> create__copy_from_typed_handle() { |
| 1776 | return c10::Dispatcher::singleton() |
| 1777 | .findSchemaOrThrow(_copy_from::name, _copy_from::overload_name) |
| 1778 | .typed<_copy_from::schema>(); |
| 1779 | } |
| 1780 | |
| 1781 | // aten::_copy_from(Tensor self, Tensor dst, bool non_blocking=False) -> Tensor |
| 1782 | at::Tensor _copy_from::call(const at::Tensor & self, const at::Tensor & dst, bool non_blocking) { |
| 1783 | |
| 1784 | static auto op = create__copy_from_typed_handle(); |
| 1785 | return op.call(self, dst, non_blocking); |
| 1786 | } |
| 1787 | |
| 1788 | // aten::_copy_from(Tensor self, Tensor dst, bool non_blocking=False) -> Tensor |
| 1789 | at::Tensor _copy_from::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & dst, bool non_blocking) { |
| 1790 | |
| 1791 | static auto op = create__copy_from_typed_handle(); |
| 1792 | return op.redispatch(dispatchKeySet, self, dst, non_blocking); |
| 1793 | } |
| 1794 | |
| 1795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(corrcoef, name, "aten::corrcoef") |
| 1796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(corrcoef, overload_name, "") |
| 1797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(corrcoef, schema_str, "corrcoef(Tensor self) -> Tensor") |
| 1798 | |
| 1799 | // aten::corrcoef(Tensor self) -> Tensor |
| 1800 | static C10_NOINLINE c10::TypedOperatorHandle<corrcoef::schema> create_corrcoef_typed_handle() { |
| 1801 | return c10::Dispatcher::singleton() |
| 1802 | .findSchemaOrThrow(corrcoef::name, corrcoef::overload_name) |
| 1803 | .typed<corrcoef::schema>(); |
| 1804 | } |
| 1805 | |
| 1806 | // aten::corrcoef(Tensor self) -> Tensor |
| 1807 | at::Tensor corrcoef::call(const at::Tensor & self) { |
| 1808 | |
| 1809 | static auto op = create_corrcoef_typed_handle(); |
| 1810 | return op.call(self); |
| 1811 | } |
| 1812 | |
| 1813 | // aten::corrcoef(Tensor self) -> Tensor |
| 1814 | at::Tensor corrcoef::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 1815 | |
| 1816 | static auto op = create_corrcoef_typed_handle(); |
| 1817 | return op.redispatch(dispatchKeySet, self); |
| 1818 | } |
| 1819 | |
| 1820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm, name, "aten::cudnn_batch_norm") |
| 1821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm, overload_name, "") |
| 1822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm, schema_str, "cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor)") |
| 1823 | |
| 1824 | // aten::cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor) |
| 1825 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_batch_norm::schema> create_cudnn_batch_norm_typed_handle() { |
| 1826 | return c10::Dispatcher::singleton() |
| 1827 | .findSchemaOrThrow(cudnn_batch_norm::name, cudnn_batch_norm::overload_name) |
| 1828 | .typed<cudnn_batch_norm::schema>(); |
| 1829 | } |
| 1830 | |
| 1831 | // aten::cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor) |
| 1832 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> cudnn_batch_norm::call(const at::Tensor & input, const 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 exponential_average_factor, double epsilon) { |
| 1833 | |
| 1834 | static auto op = create_cudnn_batch_norm_typed_handle(); |
| 1835 | return op.call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); |
| 1836 | } |
| 1837 | |
| 1838 | // aten::cudnn_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor, Tensor) |
| 1839 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> cudnn_batch_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const 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 exponential_average_factor, double epsilon) { |
| 1840 | |
| 1841 | static auto op = create_cudnn_batch_norm_typed_handle(); |
| 1842 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); |
| 1843 | } |
| 1844 | |
| 1845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mps_convolution_transpose, name, "aten::_mps_convolution_transpose") |
| 1846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mps_convolution_transpose, overload_name, "") |
| 1847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mps_convolution_transpose, schema_str, "_mps_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups) -> Tensor") |
| 1848 | |
| 1849 | // aten::_mps_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups) -> Tensor |
| 1850 | static C10_NOINLINE c10::TypedOperatorHandle<_mps_convolution_transpose::schema> create__mps_convolution_transpose_typed_handle() { |
| 1851 | return c10::Dispatcher::singleton() |
| 1852 | .findSchemaOrThrow(_mps_convolution_transpose::name, _mps_convolution_transpose::overload_name) |
| 1853 | .typed<_mps_convolution_transpose::schema>(); |
| 1854 | } |
| 1855 | |
| 1856 | // aten::_mps_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups) -> Tensor |
| 1857 | at::Tensor _mps_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) { |
| 1858 | |
| 1859 | static auto op = create__mps_convolution_transpose_typed_handle(); |
| 1860 | return op.call(self, weight, padding, output_padding, stride, dilation, groups); |
| 1861 | } |
| 1862 | |
| 1863 | // aten::_mps_convolution_transpose(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups) -> Tensor |
| 1864 | at::Tensor _mps_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) { |
| 1865 | |
| 1866 | static auto op = create__mps_convolution_transpose_typed_handle(); |
| 1867 | return op.redispatch(dispatchKeySet, self, weight, padding, output_padding, stride, dilation, groups); |
| 1868 | } |
| 1869 | |
| 1870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_transpose_backward, name, "aten::mps_convolution_transpose_backward") |
| 1871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_transpose_backward, overload_name, "") |
| 1872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_transpose_backward, schema_str, "mps_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask) -> (Tensor, Tensor)") |
| 1873 | |
| 1874 | // aten::mps_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask) -> (Tensor, Tensor) |
| 1875 | static C10_NOINLINE c10::TypedOperatorHandle<mps_convolution_transpose_backward::schema> create_mps_convolution_transpose_backward_typed_handle() { |
| 1876 | return c10::Dispatcher::singleton() |
| 1877 | .findSchemaOrThrow(mps_convolution_transpose_backward::name, mps_convolution_transpose_backward::overload_name) |
| 1878 | .typed<mps_convolution_transpose_backward::schema>(); |
| 1879 | } |
| 1880 | |
| 1881 | // aten::mps_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask) -> (Tensor, Tensor) |
| 1882 | ::std::tuple<at::Tensor,at::Tensor> mps_convolution_transpose_backward::call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,2> output_mask) { |
| 1883 | |
| 1884 | static auto op = create_mps_convolution_transpose_backward_typed_handle(); |
| 1885 | return op.call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask); |
| 1886 | } |
| 1887 | |
| 1888 | // aten::mps_convolution_transpose_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask) -> (Tensor, Tensor) |
| 1889 | ::std::tuple<at::Tensor,at::Tensor> mps_convolution_transpose_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,2> output_mask) { |
| 1890 | |
| 1891 | static auto op = create_mps_convolution_transpose_backward_typed_handle(); |
| 1892 | return op.redispatch(dispatchKeySet, self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask); |
| 1893 | } |
| 1894 | |
| 1895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummaxmin_backward, name, "aten::cummaxmin_backward") |
| 1896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummaxmin_backward, overload_name, "") |
| 1897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummaxmin_backward, schema_str, "cummaxmin_backward(Tensor grad, Tensor input, Tensor indices, int dim) -> Tensor") |
| 1898 | |
| 1899 | // aten::cummaxmin_backward(Tensor grad, Tensor input, Tensor indices, int dim) -> Tensor |
| 1900 | static C10_NOINLINE c10::TypedOperatorHandle<cummaxmin_backward::schema> create_cummaxmin_backward_typed_handle() { |
| 1901 | return c10::Dispatcher::singleton() |
| 1902 | .findSchemaOrThrow(cummaxmin_backward::name, cummaxmin_backward::overload_name) |
| 1903 | .typed<cummaxmin_backward::schema>(); |
| 1904 | } |
| 1905 | |
| 1906 | // aten::cummaxmin_backward(Tensor grad, Tensor input, Tensor indices, int dim) -> Tensor |
| 1907 | at::Tensor cummaxmin_backward::call(const at::Tensor & grad, const at::Tensor & input, const at::Tensor & indices, int64_t dim) { |
| 1908 | |
| 1909 | static auto op = create_cummaxmin_backward_typed_handle(); |
| 1910 | return op.call(grad, input, indices, dim); |
| 1911 | } |
| 1912 | |
| 1913 | // aten::cummaxmin_backward(Tensor grad, Tensor input, Tensor indices, int dim) -> Tensor |
| 1914 | at::Tensor cummaxmin_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & input, const at::Tensor & indices, int64_t dim) { |
| 1915 | |
| 1916 | static auto op = create_cummaxmin_backward_typed_handle(); |
| 1917 | return op.redispatch(dispatchKeySet, grad, input, indices, dim); |
| 1918 | } |
| 1919 | |
| 1920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumprod_backward, name, "aten::cumprod_backward") |
| 1921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumprod_backward, overload_name, "") |
| 1922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cumprod_backward, schema_str, "cumprod_backward(Tensor grad, Tensor input, int dim, Tensor output) -> Tensor") |
| 1923 | |
| 1924 | // aten::cumprod_backward(Tensor grad, Tensor input, int dim, Tensor output) -> Tensor |
| 1925 | static C10_NOINLINE c10::TypedOperatorHandle<cumprod_backward::schema> create_cumprod_backward_typed_handle() { |
| 1926 | return c10::Dispatcher::singleton() |
| 1927 | .findSchemaOrThrow(cumprod_backward::name, cumprod_backward::overload_name) |
| 1928 | .typed<cumprod_backward::schema>(); |
| 1929 | } |
| 1930 | |
| 1931 | // aten::cumprod_backward(Tensor grad, Tensor input, int dim, Tensor output) -> Tensor |
| 1932 | at::Tensor cumprod_backward::call(const at::Tensor & grad, const at::Tensor & input, int64_t dim, const at::Tensor & output) { |
| 1933 | |
| 1934 | static auto op = create_cumprod_backward_typed_handle(); |
| 1935 | return op.call(grad, input, dim, output); |
| 1936 | } |
| 1937 | |
| 1938 | // aten::cumprod_backward(Tensor grad, Tensor input, int dim, Tensor output) -> Tensor |
| 1939 | at::Tensor cumprod_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & input, int64_t dim, const at::Tensor & output) { |
| 1940 | |
| 1941 | static auto op = create_cumprod_backward_typed_handle(); |
| 1942 | return op.redispatch(dispatchKeySet, grad, input, dim, output); |
| 1943 | } |
| 1944 | |
| 1945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_diagonal_, name, "aten::fill_diagonal_") |
| 1946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_diagonal_, overload_name, "") |
| 1947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fill_diagonal_, schema_str, "fill_diagonal_(Tensor(a!) self, Scalar fill_value, bool wrap=False) -> Tensor(a!)") |
| 1948 | |
| 1949 | // aten::fill_diagonal_(Tensor(a!) self, Scalar fill_value, bool wrap=False) -> Tensor(a!) |
| 1950 | static C10_NOINLINE c10::TypedOperatorHandle<fill_diagonal_::schema> create_fill_diagonal__typed_handle() { |
| 1951 | return c10::Dispatcher::singleton() |
| 1952 | .findSchemaOrThrow(fill_diagonal_::name, fill_diagonal_::overload_name) |
| 1953 | .typed<fill_diagonal_::schema>(); |
| 1954 | } |
| 1955 | |
| 1956 | // aten::fill_diagonal_(Tensor(a!) self, Scalar fill_value, bool wrap=False) -> Tensor(a!) |
| 1957 | at::Tensor & fill_diagonal_::call(at::Tensor & self, const at::Scalar & fill_value, bool wrap) { |
| 1958 | |
| 1959 | static auto op = create_fill_diagonal__typed_handle(); |
| 1960 | return op.call(self, fill_value, wrap); |
| 1961 | } |
| 1962 | |
| 1963 | // aten::fill_diagonal_(Tensor(a!) self, Scalar fill_value, bool wrap=False) -> Tensor(a!) |
| 1964 | at::Tensor & fill_diagonal_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & fill_value, bool wrap) { |
| 1965 | |
| 1966 | static auto op = create_fill_diagonal__typed_handle(); |
| 1967 | return op.redispatch(dispatchKeySet, self, fill_value, wrap); |
| 1968 | } |
| 1969 | |
| 1970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding, name, "aten::embedding") |
| 1971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding, overload_name, "") |
| 1972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding, schema_str, "embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor") |
| 1973 | |
| 1974 | // aten::embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor |
| 1975 | static C10_NOINLINE c10::TypedOperatorHandle<embedding::schema> create_embedding_typed_handle() { |
| 1976 | return c10::Dispatcher::singleton() |
| 1977 | .findSchemaOrThrow(embedding::name, embedding::overload_name) |
| 1978 | .typed<embedding::schema>(); |
| 1979 | } |
| 1980 | |
| 1981 | // aten::embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor |
| 1982 | at::Tensor embedding::call(const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse) { |
| 1983 | |
| 1984 | static auto op = create_embedding_typed_handle(); |
| 1985 | return op.call(weight, indices, padding_idx, scale_grad_by_freq, sparse); |
| 1986 | } |
| 1987 | |
| 1988 | // aten::embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor |
| 1989 | at::Tensor embedding::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse) { |
| 1990 | |
| 1991 | static auto op = create_embedding_typed_handle(); |
| 1992 | return op.redispatch(dispatchKeySet, weight, indices, padding_idx, scale_grad_by_freq, sparse); |
| 1993 | } |
| 1994 | |
| 1995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_rowwise_prune, name, "aten::_rowwise_prune") |
| 1996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_rowwise_prune, overload_name, "") |
| 1997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_rowwise_prune, schema_str, "_rowwise_prune(Tensor weight, Tensor mask, ScalarType compressed_indices_dtype) -> (Tensor, Tensor)") |
| 1998 | |
| 1999 | // aten::_rowwise_prune(Tensor weight, Tensor mask, ScalarType compressed_indices_dtype) -> (Tensor, Tensor) |
| 2000 | static C10_NOINLINE c10::TypedOperatorHandle<_rowwise_prune::schema> create__rowwise_prune_typed_handle() { |
| 2001 | return c10::Dispatcher::singleton() |
| 2002 | .findSchemaOrThrow(_rowwise_prune::name, _rowwise_prune::overload_name) |
| 2003 | .typed<_rowwise_prune::schema>(); |
| 2004 | } |
| 2005 | |
| 2006 | // aten::_rowwise_prune(Tensor weight, Tensor mask, ScalarType compressed_indices_dtype) -> (Tensor, Tensor) |
| 2007 | ::std::tuple<at::Tensor,at::Tensor> _rowwise_prune::call(const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype) { |
| 2008 | |
| 2009 | static auto op = create__rowwise_prune_typed_handle(); |
| 2010 | return op.call(weight, mask, compressed_indices_dtype); |
| 2011 | } |
| 2012 | |
| 2013 | // aten::_rowwise_prune(Tensor weight, Tensor mask, ScalarType compressed_indices_dtype) -> (Tensor, Tensor) |
| 2014 | ::std::tuple<at::Tensor,at::Tensor> _rowwise_prune::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & mask, at::ScalarType compressed_indices_dtype) { |
| 2015 | |
| 2016 | static auto op = create__rowwise_prune_typed_handle(); |
| 2017 | return op.redispatch(dispatchKeySet, weight, mask, compressed_indices_dtype); |
| 2018 | } |
| 2019 | |
| 2020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_stack, name, "aten::row_stack") |
| 2021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_stack, overload_name, "") |
| 2022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_stack, schema_str, "row_stack(Tensor[] tensors) -> Tensor") |
| 2023 | |
| 2024 | // aten::row_stack(Tensor[] tensors) -> Tensor |
| 2025 | static C10_NOINLINE c10::TypedOperatorHandle<row_stack::schema> create_row_stack_typed_handle() { |
| 2026 | return c10::Dispatcher::singleton() |
| 2027 | .findSchemaOrThrow(row_stack::name, row_stack::overload_name) |
| 2028 | .typed<row_stack::schema>(); |
| 2029 | } |
| 2030 | |
| 2031 | // aten::row_stack(Tensor[] tensors) -> Tensor |
| 2032 | at::Tensor row_stack::call(at::TensorList tensors) { |
| 2033 | |
| 2034 | static auto op = create_row_stack_typed_handle(); |
| 2035 | return op.call(tensors); |
| 2036 | } |
| 2037 | |
| 2038 | // aten::row_stack(Tensor[] tensors) -> Tensor |
| 2039 | at::Tensor row_stack::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 2040 | |
| 2041 | static auto op = create_row_stack_typed_handle(); |
| 2042 | return op.redispatch(dispatchKeySet, tensors); |
| 2043 | } |
| 2044 | |
| 2045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_stack_out, name, "aten::row_stack") |
| 2046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_stack_out, overload_name, "out") |
| 2047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(row_stack_out, schema_str, "row_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)") |
| 2048 | |
| 2049 | // aten::row_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 2050 | static C10_NOINLINE c10::TypedOperatorHandle<row_stack_out::schema> create_row_stack_out_typed_handle() { |
| 2051 | return c10::Dispatcher::singleton() |
| 2052 | .findSchemaOrThrow(row_stack_out::name, row_stack_out::overload_name) |
| 2053 | .typed<row_stack_out::schema>(); |
| 2054 | } |
| 2055 | |
| 2056 | // aten::row_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 2057 | at::Tensor & row_stack_out::call(at::TensorList tensors, at::Tensor & out) { |
| 2058 | |
| 2059 | static auto op = create_row_stack_out_typed_handle(); |
| 2060 | return op.call(tensors, out); |
| 2061 | } |
| 2062 | |
| 2063 | // aten::row_stack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 2064 | at::Tensor & row_stack_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out) { |
| 2065 | |
| 2066 | static auto op = create_row_stack_out_typed_handle(); |
| 2067 | return op.redispatch(dispatchKeySet, tensors, out); |
| 2068 | } |
| 2069 | |
| 2070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_backward, name, "aten::_embedding_bag_backward") |
| 2071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_backward, overload_name, "") |
| 2072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_backward, schema_str, "_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor") |
| 2073 | |
| 2074 | // aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2075 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag_backward::schema> create__embedding_bag_backward_typed_handle() { |
| 2076 | return c10::Dispatcher::singleton() |
| 2077 | .findSchemaOrThrow(_embedding_bag_backward::name, _embedding_bag_backward::overload_name) |
| 2078 | .typed<_embedding_bag_backward::schema>(); |
| 2079 | } |
| 2080 | |
| 2081 | // aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2082 | at::Tensor _embedding_bag_backward::call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx) { |
| 2083 | |
| 2084 | static auto op = create__embedding_bag_backward_typed_handle(); |
| 2085 | return op.call(grad, indices, offsets, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, sparse, per_sample_weights, padding_idx); |
| 2086 | } |
| 2087 | |
| 2088 | // aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2089 | at::Tensor _embedding_bag_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, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, bool sparse, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx) { |
| 2090 | |
| 2091 | static auto op = create__embedding_bag_backward_typed_handle(); |
| 2092 | return op.redispatch(dispatchKeySet, grad, indices, offsets, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, sparse, per_sample_weights, padding_idx); |
| 2093 | } |
| 2094 | |
| 2095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_dense_backward, name, "aten::_embedding_bag_dense_backward") |
| 2096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_dense_backward, overload_name, "") |
| 2097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_dense_backward, schema_str, "_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor") |
| 2098 | |
| 2099 | // aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2100 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag_dense_backward::schema> create__embedding_bag_dense_backward_typed_handle() { |
| 2101 | return c10::Dispatcher::singleton() |
| 2102 | .findSchemaOrThrow(_embedding_bag_dense_backward::name, _embedding_bag_dense_backward::overload_name) |
| 2103 | .typed<_embedding_bag_dense_backward::schema>(); |
| 2104 | } |
| 2105 | |
| 2106 | // aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2107 | at::Tensor _embedding_bag_dense_backward::call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx) { |
| 2108 | |
| 2109 | static auto op = create__embedding_bag_dense_backward_typed_handle(); |
| 2110 | return op.call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); |
| 2111 | } |
| 2112 | |
| 2113 | // aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor |
| 2114 | at::Tensor _embedding_bag_dense_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx) { |
| 2115 | |
| 2116 | static auto op = create__embedding_bag_dense_backward_typed_handle(); |
| 2117 | return op.redispatch(dispatchKeySet, grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx); |
| 2118 | } |
| 2119 | |
| 2120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize_, name, "aten::resize_") |
| 2121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize_, overload_name, "") |
| 2122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize_, schema_str, "resize_(Tensor(a!) self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor(a!)") |
| 2123 | |
| 2124 | // aten::resize_(Tensor(a!) self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor(a!) |
| 2125 | static C10_NOINLINE c10::TypedOperatorHandle<resize_::schema> create_resize__typed_handle() { |
| 2126 | return c10::Dispatcher::singleton() |
| 2127 | .findSchemaOrThrow(resize_::name, resize_::overload_name) |
| 2128 | .typed<resize_::schema>(); |
| 2129 | } |
| 2130 | |
| 2131 | // aten::resize_(Tensor(a!) self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor(a!) |
| 2132 | const at::Tensor & resize_::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format) { |
| 2133 | |
| 2134 | static auto op = create_resize__typed_handle(); |
| 2135 | return op.call(self, size, memory_format); |
| 2136 | } |
| 2137 | |
| 2138 | // aten::resize_(Tensor(a!) self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor(a!) |
| 2139 | const at::Tensor & resize_::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format) { |
| 2140 | |
| 2141 | static auto op = create_resize__typed_handle(); |
| 2142 | return op.redispatch(dispatchKeySet, self, size, memory_format); |
| 2143 | } |
| 2144 | |
| 2145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc, name, "aten::erfc") |
| 2146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc, overload_name, "") |
| 2147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc, schema_str, "erfc(Tensor self) -> Tensor") |
| 2148 | |
| 2149 | // aten::erfc(Tensor self) -> Tensor |
| 2150 | static C10_NOINLINE c10::TypedOperatorHandle<erfc::schema> create_erfc_typed_handle() { |
| 2151 | return c10::Dispatcher::singleton() |
| 2152 | .findSchemaOrThrow(erfc::name, erfc::overload_name) |
| 2153 | .typed<erfc::schema>(); |
| 2154 | } |
| 2155 | |
| 2156 | // aten::erfc(Tensor self) -> Tensor |
| 2157 | at::Tensor erfc::call(const at::Tensor & self) { |
| 2158 | |
| 2159 | static auto op = create_erfc_typed_handle(); |
| 2160 | return op.call(self); |
| 2161 | } |
| 2162 | |
| 2163 | // aten::erfc(Tensor self) -> Tensor |
| 2164 | at::Tensor erfc::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 2165 | |
| 2166 | static auto op = create_erfc_typed_handle(); |
| 2167 | return op.redispatch(dispatchKeySet, self); |
| 2168 | } |
| 2169 | |
| 2170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc_, name, "aten::erfc_") |
| 2171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc_, overload_name, "") |
| 2172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc_, schema_str, "erfc_(Tensor(a!) self) -> Tensor(a!)") |
| 2173 | |
| 2174 | // aten::erfc_(Tensor(a!) self) -> Tensor(a!) |
| 2175 | static C10_NOINLINE c10::TypedOperatorHandle<erfc_::schema> create_erfc__typed_handle() { |
| 2176 | return c10::Dispatcher::singleton() |
| 2177 | .findSchemaOrThrow(erfc_::name, erfc_::overload_name) |
| 2178 | .typed<erfc_::schema>(); |
| 2179 | } |
| 2180 | |
| 2181 | // aten::erfc_(Tensor(a!) self) -> Tensor(a!) |
| 2182 | at::Tensor & erfc_::call(at::Tensor & self) { |
| 2183 | |
| 2184 | static auto op = create_erfc__typed_handle(); |
| 2185 | return op.call(self); |
| 2186 | } |
| 2187 | |
| 2188 | // aten::erfc_(Tensor(a!) self) -> Tensor(a!) |
| 2189 | at::Tensor & erfc_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 2190 | |
| 2191 | static auto op = create_erfc__typed_handle(); |
| 2192 | return op.redispatch(dispatchKeySet, self); |
| 2193 | } |
| 2194 | |
| 2195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc_out, name, "aten::erfc") |
| 2196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc_out, overload_name, "out") |
| 2197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfc_out, schema_str, "erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 2198 | |
| 2199 | // aten::erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2200 | static C10_NOINLINE c10::TypedOperatorHandle<erfc_out::schema> create_erfc_out_typed_handle() { |
| 2201 | return c10::Dispatcher::singleton() |
| 2202 | .findSchemaOrThrow(erfc_out::name, erfc_out::overload_name) |
| 2203 | .typed<erfc_out::schema>(); |
| 2204 | } |
| 2205 | |
| 2206 | // aten::erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2207 | at::Tensor & erfc_out::call(const at::Tensor & self, at::Tensor & out) { |
| 2208 | |
| 2209 | static auto op = create_erfc_out_typed_handle(); |
| 2210 | return op.call(self, out); |
| 2211 | } |
| 2212 | |
| 2213 | // aten::erfc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 2214 | at::Tensor & erfc_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 2215 | |
| 2216 | static auto op = create_erfc_out_typed_handle(); |
| 2217 | return op.redispatch(dispatchKeySet, self, out); |
| 2218 | } |
| 2219 | |
| 2220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide, name, "aten::floor_divide") |
| 2221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide, overload_name, "") |
| 2222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide, schema_str, "floor_divide(Tensor self, Tensor other) -> Tensor") |
| 2223 | |
| 2224 | // aten::floor_divide(Tensor self, Tensor other) -> Tensor |
| 2225 | static C10_NOINLINE c10::TypedOperatorHandle<floor_divide::schema> create_floor_divide_typed_handle() { |
| 2226 | return c10::Dispatcher::singleton() |
| 2227 | .findSchemaOrThrow(floor_divide::name, floor_divide::overload_name) |
| 2228 | .typed<floor_divide::schema>(); |
| 2229 | } |
| 2230 | |
| 2231 | // aten::floor_divide(Tensor self, Tensor other) -> Tensor |
| 2232 | at::Tensor floor_divide::call(const at::Tensor & self, const at::Tensor & other) { |
| 2233 | |
| 2234 | static auto op = create_floor_divide_typed_handle(); |
| 2235 | return op.call(self, other); |
| 2236 | } |
| 2237 | |
| 2238 | // aten::floor_divide(Tensor self, Tensor other) -> Tensor |
| 2239 | at::Tensor floor_divide::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 2240 | |
| 2241 | static auto op = create_floor_divide_typed_handle(); |
| 2242 | return op.redispatch(dispatchKeySet, self, other); |
| 2243 | } |
| 2244 | |
| 2245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide__Tensor, name, "aten::floor_divide_") |
| 2246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide__Tensor, overload_name, "Tensor") |
| 2247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide__Tensor, schema_str, "floor_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 2248 | |
| 2249 | // aten::floor_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 2250 | static C10_NOINLINE c10::TypedOperatorHandle<floor_divide__Tensor::schema> create_floor_divide__Tensor_typed_handle() { |
| 2251 | return c10::Dispatcher::singleton() |
| 2252 | .findSchemaOrThrow(floor_divide__Tensor::name, floor_divide__Tensor::overload_name) |
| 2253 | .typed<floor_divide__Tensor::schema>(); |
| 2254 | } |
| 2255 | |
| 2256 | // aten::floor_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 2257 | at::Tensor & floor_divide__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 2258 | |
| 2259 | static auto op = create_floor_divide__Tensor_typed_handle(); |
| 2260 | return op.call(self, other); |
| 2261 | } |
| 2262 | |
| 2263 | // aten::floor_divide_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 2264 | at::Tensor & floor_divide__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 2265 | |
| 2266 | static auto op = create_floor_divide__Tensor_typed_handle(); |
| 2267 | return op.redispatch(dispatchKeySet, self, other); |
| 2268 | } |
| 2269 | |
| 2270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide_out, name, "aten::floor_divide") |
| 2271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide_out, overload_name, "out") |
| 2272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide_out, schema_str, "floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 2273 | |
| 2274 | // aten::floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2275 | static C10_NOINLINE c10::TypedOperatorHandle<floor_divide_out::schema> create_floor_divide_out_typed_handle() { |
| 2276 | return c10::Dispatcher::singleton() |
| 2277 | .findSchemaOrThrow(floor_divide_out::name, floor_divide_out::overload_name) |
| 2278 | .typed<floor_divide_out::schema>(); |
| 2279 | } |
| 2280 | |
| 2281 | // aten::floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2282 | at::Tensor & floor_divide_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2283 | |
| 2284 | static auto op = create_floor_divide_out_typed_handle(); |
| 2285 | return op.call(self, other, out); |
| 2286 | } |
| 2287 | |
| 2288 | // aten::floor_divide.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2289 | at::Tensor & floor_divide_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2290 | |
| 2291 | static auto op = create_floor_divide_out_typed_handle(); |
| 2292 | return op.redispatch(dispatchKeySet, self, other, out); |
| 2293 | } |
| 2294 | |
| 2295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide_Scalar, name, "aten::floor_divide") |
| 2296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide_Scalar, overload_name, "Scalar") |
| 2297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide_Scalar, schema_str, "floor_divide.Scalar(Tensor self, Scalar other) -> Tensor") |
| 2298 | |
| 2299 | // aten::floor_divide.Scalar(Tensor self, Scalar other) -> Tensor |
| 2300 | static C10_NOINLINE c10::TypedOperatorHandle<floor_divide_Scalar::schema> create_floor_divide_Scalar_typed_handle() { |
| 2301 | return c10::Dispatcher::singleton() |
| 2302 | .findSchemaOrThrow(floor_divide_Scalar::name, floor_divide_Scalar::overload_name) |
| 2303 | .typed<floor_divide_Scalar::schema>(); |
| 2304 | } |
| 2305 | |
| 2306 | // aten::floor_divide.Scalar(Tensor self, Scalar other) -> Tensor |
| 2307 | at::Tensor floor_divide_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 2308 | |
| 2309 | static auto op = create_floor_divide_Scalar_typed_handle(); |
| 2310 | return op.call(self, other); |
| 2311 | } |
| 2312 | |
| 2313 | // aten::floor_divide.Scalar(Tensor self, Scalar other) -> Tensor |
| 2314 | at::Tensor floor_divide_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 2315 | |
| 2316 | static auto op = create_floor_divide_Scalar_typed_handle(); |
| 2317 | return op.redispatch(dispatchKeySet, self, other); |
| 2318 | } |
| 2319 | |
| 2320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide__Scalar, name, "aten::floor_divide_") |
| 2321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide__Scalar, overload_name, "Scalar") |
| 2322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(floor_divide__Scalar, schema_str, "floor_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 2323 | |
| 2324 | // aten::floor_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 2325 | static C10_NOINLINE c10::TypedOperatorHandle<floor_divide__Scalar::schema> create_floor_divide__Scalar_typed_handle() { |
| 2326 | return c10::Dispatcher::singleton() |
| 2327 | .findSchemaOrThrow(floor_divide__Scalar::name, floor_divide__Scalar::overload_name) |
| 2328 | .typed<floor_divide__Scalar::schema>(); |
| 2329 | } |
| 2330 | |
| 2331 | // aten::floor_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 2332 | at::Tensor & floor_divide__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 2333 | |
| 2334 | static auto op = create_floor_divide__Scalar_typed_handle(); |
| 2335 | return op.call(self, other); |
| 2336 | } |
| 2337 | |
| 2338 | // aten::floor_divide_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 2339 | at::Tensor & floor_divide__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 2340 | |
| 2341 | static auto op = create_floor_divide__Scalar_typed_handle(); |
| 2342 | return op.redispatch(dispatchKeySet, self, other); |
| 2343 | } |
| 2344 | |
| 2345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_names, name, "aten::full") |
| 2346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_names, overload_name, "names") |
| 2347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_names, schema_str, "full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 2348 | |
| 2349 | // aten::full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2350 | static C10_NOINLINE c10::TypedOperatorHandle<full_names::schema> create_full_names_typed_handle() { |
| 2351 | return c10::Dispatcher::singleton() |
| 2352 | .findSchemaOrThrow(full_names::name, full_names::overload_name) |
| 2353 | .typed<full_names::schema>(); |
| 2354 | } |
| 2355 | |
| 2356 | // aten::full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2357 | at::Tensor full_names::call(at::IntArrayRef size, const at::Scalar & fill_value, 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) { |
| 2358 | |
| 2359 | static auto op = create_full_names_typed_handle(); |
| 2360 | return op.call(size, fill_value, names, dtype, layout, device, pin_memory); |
| 2361 | } |
| 2362 | |
| 2363 | // aten::full.names(int[] size, Scalar fill_value, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2364 | at::Tensor full_names::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Scalar & fill_value, 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) { |
| 2365 | |
| 2366 | static auto op = create_full_names_typed_handle(); |
| 2367 | return op.redispatch(dispatchKeySet, size, fill_value, names, dtype, layout, device, pin_memory); |
| 2368 | } |
| 2369 | |
| 2370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full, name, "aten::full") |
| 2371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full, overload_name, "") |
| 2372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full, schema_str, "full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 2373 | |
| 2374 | // aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2375 | static C10_NOINLINE c10::TypedOperatorHandle<full::schema> create_full_typed_handle() { |
| 2376 | return c10::Dispatcher::singleton() |
| 2377 | .findSchemaOrThrow(full::name, full::overload_name) |
| 2378 | .typed<full::schema>(); |
| 2379 | } |
| 2380 | |
| 2381 | // aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2382 | at::Tensor full::call(c10::SymIntArrayRef size, const at::Scalar & fill_value, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 2383 | |
| 2384 | static auto op = create_full_typed_handle(); |
| 2385 | return op.call(size, fill_value, dtype, layout, device, pin_memory); |
| 2386 | } |
| 2387 | |
| 2388 | // aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2389 | at::Tensor full::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Scalar & fill_value, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 2390 | |
| 2391 | static auto op = create_full_typed_handle(); |
| 2392 | return op.redispatch(dispatchKeySet, size, fill_value, dtype, layout, device, pin_memory); |
| 2393 | } |
| 2394 | |
| 2395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_out, name, "aten::full") |
| 2396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_out, overload_name, "out") |
| 2397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_out, schema_str, "full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)") |
| 2398 | |
| 2399 | // aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) |
| 2400 | static C10_NOINLINE c10::TypedOperatorHandle<full_out::schema> create_full_out_typed_handle() { |
| 2401 | return c10::Dispatcher::singleton() |
| 2402 | .findSchemaOrThrow(full_out::name, full_out::overload_name) |
| 2403 | .typed<full_out::schema>(); |
| 2404 | } |
| 2405 | |
| 2406 | // aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) |
| 2407 | at::Tensor & full_out::call(c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { |
| 2408 | |
| 2409 | static auto op = create_full_out_typed_handle(); |
| 2410 | return op.call(size, fill_value, out); |
| 2411 | } |
| 2412 | |
| 2413 | // aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) |
| 2414 | at::Tensor & full_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { |
| 2415 | |
| 2416 | static auto op = create_full_out_typed_handle(); |
| 2417 | return op.redispatch(dispatchKeySet, size, fill_value, out); |
| 2418 | } |
| 2419 | |
| 2420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_like, name, "aten::full_like") |
| 2421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_like, overload_name, "") |
| 2422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_like, schema_str, "full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor") |
| 2423 | |
| 2424 | // aten::full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
| 2425 | static C10_NOINLINE c10::TypedOperatorHandle<full_like::schema> create_full_like_typed_handle() { |
| 2426 | return c10::Dispatcher::singleton() |
| 2427 | .findSchemaOrThrow(full_like::name, full_like::overload_name) |
| 2428 | .typed<full_like::schema>(); |
| 2429 | } |
| 2430 | |
| 2431 | // aten::full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
| 2432 | at::Tensor full_like::call(const at::Tensor & self, const at::Scalar & fill_value, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
| 2433 | |
| 2434 | static auto op = create_full_like_typed_handle(); |
| 2435 | return op.call(self, fill_value, dtype, layout, device, pin_memory, memory_format); |
| 2436 | } |
| 2437 | |
| 2438 | // aten::full_like(Tensor self, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
| 2439 | at::Tensor full_like::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & fill_value, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
| 2440 | |
| 2441 | static auto op = create_full_like_typed_handle(); |
| 2442 | return op.redispatch(dispatchKeySet, self, fill_value, dtype, layout, device, pin_memory, memory_format); |
| 2443 | } |
| 2444 | |
| 2445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d, name, "aten::grid_sampler_2d") |
| 2446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d, overload_name, "") |
| 2447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d, schema_str, "grid_sampler_2d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor") |
| 2448 | |
| 2449 | // aten::grid_sampler_2d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor |
| 2450 | static C10_NOINLINE c10::TypedOperatorHandle<grid_sampler_2d::schema> create_grid_sampler_2d_typed_handle() { |
| 2451 | return c10::Dispatcher::singleton() |
| 2452 | .findSchemaOrThrow(grid_sampler_2d::name, grid_sampler_2d::overload_name) |
| 2453 | .typed<grid_sampler_2d::schema>(); |
| 2454 | } |
| 2455 | |
| 2456 | // aten::grid_sampler_2d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor |
| 2457 | at::Tensor grid_sampler_2d::call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { |
| 2458 | |
| 2459 | static auto op = create_grid_sampler_2d_typed_handle(); |
| 2460 | return op.call(input, grid, interpolation_mode, padding_mode, align_corners); |
| 2461 | } |
| 2462 | |
| 2463 | // aten::grid_sampler_2d(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> Tensor |
| 2464 | at::Tensor grid_sampler_2d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners) { |
| 2465 | |
| 2466 | static auto op = create_grid_sampler_2d_typed_handle(); |
| 2467 | return op.redispatch(dispatchKeySet, input, grid, interpolation_mode, padding_mode, align_corners); |
| 2468 | } |
| 2469 | |
| 2470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_grid_sampler_2d_cpu_fallback_backward, name, "aten::_grid_sampler_2d_cpu_fallback_backward") |
| 2471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_grid_sampler_2d_cpu_fallback_backward, overload_name, "") |
| 2472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_grid_sampler_2d_cpu_fallback_backward, schema_str, "_grid_sampler_2d_cpu_fallback_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> (Tensor, Tensor)") |
| 2473 | |
| 2474 | // aten::_grid_sampler_2d_cpu_fallback_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> (Tensor, Tensor) |
| 2475 | static C10_NOINLINE c10::TypedOperatorHandle<_grid_sampler_2d_cpu_fallback_backward::schema> create__grid_sampler_2d_cpu_fallback_backward_typed_handle() { |
| 2476 | return c10::Dispatcher::singleton() |
| 2477 | .findSchemaOrThrow(_grid_sampler_2d_cpu_fallback_backward::name, _grid_sampler_2d_cpu_fallback_backward::overload_name) |
| 2478 | .typed<_grid_sampler_2d_cpu_fallback_backward::schema>(); |
| 2479 | } |
| 2480 | |
| 2481 | // aten::_grid_sampler_2d_cpu_fallback_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> (Tensor, Tensor) |
| 2482 | ::std::tuple<at::Tensor,at::Tensor> _grid_sampler_2d_cpu_fallback_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) { |
| 2483 | |
| 2484 | static auto op = create__grid_sampler_2d_cpu_fallback_backward_typed_handle(); |
| 2485 | return op.call(grad_output, input, grid, interpolation_mode, padding_mode, align_corners); |
| 2486 | } |
| 2487 | |
| 2488 | // aten::_grid_sampler_2d_cpu_fallback_backward(Tensor grad_output, Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners) -> (Tensor, Tensor) |
| 2489 | ::std::tuple<at::Tensor,at::Tensor> _grid_sampler_2d_cpu_fallback_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) { |
| 2490 | |
| 2491 | static auto op = create__grid_sampler_2d_cpu_fallback_backward_typed_handle(); |
| 2492 | return op.redispatch(dispatchKeySet, grad_output, input, grid, interpolation_mode, padding_mode, align_corners); |
| 2493 | } |
| 2494 | |
| 2495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window, name, "aten::kaiser_window") |
| 2496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window, overload_name, "") |
| 2497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window, schema_str, "kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 2498 | |
| 2499 | // aten::kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2500 | static C10_NOINLINE c10::TypedOperatorHandle<kaiser_window::schema> create_kaiser_window_typed_handle() { |
| 2501 | return c10::Dispatcher::singleton() |
| 2502 | .findSchemaOrThrow(kaiser_window::name, kaiser_window::overload_name) |
| 2503 | .typed<kaiser_window::schema>(); |
| 2504 | } |
| 2505 | |
| 2506 | // aten::kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2507 | at::Tensor kaiser_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) { |
| 2508 | |
| 2509 | static auto op = create_kaiser_window_typed_handle(); |
| 2510 | return op.call(window_length, dtype, layout, device, pin_memory); |
| 2511 | } |
| 2512 | |
| 2513 | // aten::kaiser_window(int window_length, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2514 | at::Tensor kaiser_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) { |
| 2515 | |
| 2516 | static auto op = create_kaiser_window_typed_handle(); |
| 2517 | return op.redispatch(dispatchKeySet, window_length, dtype, layout, device, pin_memory); |
| 2518 | } |
| 2519 | |
| 2520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_periodic, name, "aten::kaiser_window") |
| 2521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_periodic, overload_name, "periodic") |
| 2522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_periodic, schema_str, "kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 2523 | |
| 2524 | // aten::kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2525 | static C10_NOINLINE c10::TypedOperatorHandle<kaiser_window_periodic::schema> create_kaiser_window_periodic_typed_handle() { |
| 2526 | return c10::Dispatcher::singleton() |
| 2527 | .findSchemaOrThrow(kaiser_window_periodic::name, kaiser_window_periodic::overload_name) |
| 2528 | .typed<kaiser_window_periodic::schema>(); |
| 2529 | } |
| 2530 | |
| 2531 | // aten::kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2532 | at::Tensor kaiser_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) { |
| 2533 | |
| 2534 | static auto op = create_kaiser_window_periodic_typed_handle(); |
| 2535 | return op.call(window_length, periodic, dtype, layout, device, pin_memory); |
| 2536 | } |
| 2537 | |
| 2538 | // aten::kaiser_window.periodic(int window_length, bool periodic, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2539 | at::Tensor kaiser_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) { |
| 2540 | |
| 2541 | static auto op = create_kaiser_window_periodic_typed_handle(); |
| 2542 | return op.redispatch(dispatchKeySet, window_length, periodic, dtype, layout, device, pin_memory); |
| 2543 | } |
| 2544 | |
| 2545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_beta, name, "aten::kaiser_window") |
| 2546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_beta, overload_name, "beta") |
| 2547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_beta, schema_str, "kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 2548 | |
| 2549 | // aten::kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2550 | static C10_NOINLINE c10::TypedOperatorHandle<kaiser_window_beta::schema> create_kaiser_window_beta_typed_handle() { |
| 2551 | return c10::Dispatcher::singleton() |
| 2552 | .findSchemaOrThrow(kaiser_window_beta::name, kaiser_window_beta::overload_name) |
| 2553 | .typed<kaiser_window_beta::schema>(); |
| 2554 | } |
| 2555 | |
| 2556 | // aten::kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2557 | at::Tensor kaiser_window_beta::call(int64_t window_length, bool periodic, double beta, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 2558 | |
| 2559 | static auto op = create_kaiser_window_beta_typed_handle(); |
| 2560 | return op.call(window_length, periodic, beta, dtype, layout, device, pin_memory); |
| 2561 | } |
| 2562 | |
| 2563 | // aten::kaiser_window.beta(int window_length, bool periodic, float beta, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 2564 | at::Tensor kaiser_window_beta::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double beta, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 2565 | |
| 2566 | static auto op = create_kaiser_window_beta_typed_handle(); |
| 2567 | return op.redispatch(dispatchKeySet, window_length, periodic, beta, dtype, layout, device, pin_memory); |
| 2568 | } |
| 2569 | |
| 2570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fft_c2r, name, "aten::_fft_c2r") |
| 2571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fft_c2r, overload_name, "") |
| 2572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fft_c2r, schema_str, "_fft_c2r(Tensor self, int[] dim, int normalization, int last_dim_size) -> Tensor") |
| 2573 | |
| 2574 | // aten::_fft_c2r(Tensor self, int[] dim, int normalization, int last_dim_size) -> Tensor |
| 2575 | static C10_NOINLINE c10::TypedOperatorHandle<_fft_c2r::schema> create__fft_c2r_typed_handle() { |
| 2576 | return c10::Dispatcher::singleton() |
| 2577 | .findSchemaOrThrow(_fft_c2r::name, _fft_c2r::overload_name) |
| 2578 | .typed<_fft_c2r::schema>(); |
| 2579 | } |
| 2580 | |
| 2581 | // aten::_fft_c2r(Tensor self, int[] dim, int normalization, int last_dim_size) -> Tensor |
| 2582 | at::Tensor _fft_c2r::call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { |
| 2583 | |
| 2584 | static auto op = create__fft_c2r_typed_handle(); |
| 2585 | return op.call(self, dim, normalization, last_dim_size); |
| 2586 | } |
| 2587 | |
| 2588 | // aten::_fft_c2r(Tensor self, int[] dim, int normalization, int last_dim_size) -> Tensor |
| 2589 | at::Tensor _fft_c2r::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size) { |
| 2590 | |
| 2591 | static auto op = create__fft_c2r_typed_handle(); |
| 2592 | return op.redispatch(dispatchKeySet, self, dim, normalization, last_dim_size); |
| 2593 | } |
| 2594 | |
| 2595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fft_c2r_out, name, "aten::_fft_c2r") |
| 2596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fft_c2r_out, overload_name, "out") |
| 2597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fft_c2r_out, schema_str, "_fft_c2r.out(Tensor self, int[] dim, int normalization, int last_dim_size, *, Tensor(a!) out) -> Tensor(a!)") |
| 2598 | |
| 2599 | // aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, int last_dim_size, *, Tensor(a!) out) -> Tensor(a!) |
| 2600 | static C10_NOINLINE c10::TypedOperatorHandle<_fft_c2r_out::schema> create__fft_c2r_out_typed_handle() { |
| 2601 | return c10::Dispatcher::singleton() |
| 2602 | .findSchemaOrThrow(_fft_c2r_out::name, _fft_c2r_out::overload_name) |
| 2603 | .typed<_fft_c2r_out::schema>(); |
| 2604 | } |
| 2605 | |
| 2606 | // aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, int last_dim_size, *, Tensor(a!) out) -> Tensor(a!) |
| 2607 | at::Tensor & _fft_c2r_out::call(const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { |
| 2608 | |
| 2609 | static auto op = create__fft_c2r_out_typed_handle(); |
| 2610 | return op.call(self, dim, normalization, last_dim_size, out); |
| 2611 | } |
| 2612 | |
| 2613 | // aten::_fft_c2r.out(Tensor self, int[] dim, int normalization, int last_dim_size, *, Tensor(a!) out) -> Tensor(a!) |
| 2614 | at::Tensor & _fft_c2r_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t normalization, int64_t last_dim_size, at::Tensor & out) { |
| 2615 | |
| 2616 | static auto op = create__fft_c2r_out_typed_handle(); |
| 2617 | return op.redispatch(dispatchKeySet, self, dim, normalization, last_dim_size, out); |
| 2618 | } |
| 2619 | |
| 2620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cufft_set_plan_cache_max_size, name, "aten::_cufft_set_plan_cache_max_size") |
| 2621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cufft_set_plan_cache_max_size, overload_name, "") |
| 2622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cufft_set_plan_cache_max_size, schema_str, "_cufft_set_plan_cache_max_size(int device_index, int max_size) -> ()") |
| 2623 | |
| 2624 | // aten::_cufft_set_plan_cache_max_size(int device_index, int max_size) -> () |
| 2625 | static C10_NOINLINE c10::TypedOperatorHandle<_cufft_set_plan_cache_max_size::schema> create__cufft_set_plan_cache_max_size_typed_handle() { |
| 2626 | return c10::Dispatcher::singleton() |
| 2627 | .findSchemaOrThrow(_cufft_set_plan_cache_max_size::name, _cufft_set_plan_cache_max_size::overload_name) |
| 2628 | .typed<_cufft_set_plan_cache_max_size::schema>(); |
| 2629 | } |
| 2630 | |
| 2631 | // aten::_cufft_set_plan_cache_max_size(int device_index, int max_size) -> () |
| 2632 | void _cufft_set_plan_cache_max_size::call(int64_t device_index, int64_t max_size) { |
| 2633 | |
| 2634 | static auto op = create__cufft_set_plan_cache_max_size_typed_handle(); |
| 2635 | return op.call(device_index, max_size); |
| 2636 | } |
| 2637 | |
| 2638 | // aten::_cufft_set_plan_cache_max_size(int device_index, int max_size) -> () |
| 2639 | void _cufft_set_plan_cache_max_size::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t device_index, int64_t max_size) { |
| 2640 | |
| 2641 | static auto op = create__cufft_set_plan_cache_max_size_typed_handle(); |
| 2642 | return op.redispatch(dispatchKeySet, device_index, max_size); |
| 2643 | } |
| 2644 | |
| 2645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put_, name, "aten::index_put_") |
| 2646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put_, overload_name, "") |
| 2647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put_, schema_str, "index_put_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor(a!)") |
| 2648 | |
| 2649 | // aten::index_put_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor(a!) |
| 2650 | static C10_NOINLINE c10::TypedOperatorHandle<index_put_::schema> create_index_put__typed_handle() { |
| 2651 | return c10::Dispatcher::singleton() |
| 2652 | .findSchemaOrThrow(index_put_::name, index_put_::overload_name) |
| 2653 | .typed<index_put_::schema>(); |
| 2654 | } |
| 2655 | |
| 2656 | // aten::index_put_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor(a!) |
| 2657 | at::Tensor & index_put_::call(at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate) { |
| 2658 | |
| 2659 | static auto op = create_index_put__typed_handle(); |
| 2660 | return op.call(self, indices, values, accumulate); |
| 2661 | } |
| 2662 | |
| 2663 | // aten::index_put_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor(a!) |
| 2664 | at::Tensor & index_put_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate) { |
| 2665 | |
| 2666 | static auto op = create_index_put__typed_handle(); |
| 2667 | return op.redispatch(dispatchKeySet, self, indices, values, accumulate); |
| 2668 | } |
| 2669 | |
| 2670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put, name, "aten::index_put") |
| 2671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put, overload_name, "") |
| 2672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put, schema_str, "index_put(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor") |
| 2673 | |
| 2674 | // aten::index_put(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor |
| 2675 | static C10_NOINLINE c10::TypedOperatorHandle<index_put::schema> create_index_put_typed_handle() { |
| 2676 | return c10::Dispatcher::singleton() |
| 2677 | .findSchemaOrThrow(index_put::name, index_put::overload_name) |
| 2678 | .typed<index_put::schema>(); |
| 2679 | } |
| 2680 | |
| 2681 | // aten::index_put(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor |
| 2682 | at::Tensor index_put::call(const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate) { |
| 2683 | |
| 2684 | static auto op = create_index_put_typed_handle(); |
| 2685 | return op.call(self, indices, values, accumulate); |
| 2686 | } |
| 2687 | |
| 2688 | // aten::index_put(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor |
| 2689 | at::Tensor index_put::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate) { |
| 2690 | |
| 2691 | static auto op = create_index_put_typed_handle(); |
| 2692 | return op.redispatch(dispatchKeySet, self, indices, values, accumulate); |
| 2693 | } |
| 2694 | |
| 2695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(instance_norm, name, "aten::instance_norm") |
| 2696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(instance_norm, overload_name, "") |
| 2697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(instance_norm, schema_str, "instance_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool use_input_stats, float momentum, float eps, bool cudnn_enabled) -> Tensor") |
| 2698 | |
| 2699 | // aten::instance_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool use_input_stats, float momentum, float eps, bool cudnn_enabled) -> Tensor |
| 2700 | static C10_NOINLINE c10::TypedOperatorHandle<instance_norm::schema> create_instance_norm_typed_handle() { |
| 2701 | return c10::Dispatcher::singleton() |
| 2702 | .findSchemaOrThrow(instance_norm::name, instance_norm::overload_name) |
| 2703 | .typed<instance_norm::schema>(); |
| 2704 | } |
| 2705 | |
| 2706 | // aten::instance_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool use_input_stats, float momentum, float eps, bool cudnn_enabled) -> Tensor |
| 2707 | at::Tensor instance_norm::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 use_input_stats, double momentum, double eps, bool cudnn_enabled) { |
| 2708 | |
| 2709 | static auto op = create_instance_norm_typed_handle(); |
| 2710 | return op.call(input, weight, bias, running_mean, running_var, use_input_stats, momentum, eps, cudnn_enabled); |
| 2711 | } |
| 2712 | |
| 2713 | // aten::instance_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool use_input_stats, float momentum, float eps, bool cudnn_enabled) -> Tensor |
| 2714 | at::Tensor instance_norm::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 use_input_stats, double momentum, double eps, bool cudnn_enabled) { |
| 2715 | |
| 2716 | static auto op = create_instance_norm_typed_handle(); |
| 2717 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, use_input_stats, momentum, eps, cudnn_enabled); |
| 2718 | } |
| 2719 | |
| 2720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isclose, name, "aten::isclose") |
| 2721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isclose, overload_name, "") |
| 2722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isclose, schema_str, "isclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> Tensor") |
| 2723 | |
| 2724 | // aten::isclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> Tensor |
| 2725 | static C10_NOINLINE c10::TypedOperatorHandle<isclose::schema> create_isclose_typed_handle() { |
| 2726 | return c10::Dispatcher::singleton() |
| 2727 | .findSchemaOrThrow(isclose::name, isclose::overload_name) |
| 2728 | .typed<isclose::schema>(); |
| 2729 | } |
| 2730 | |
| 2731 | // aten::isclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> Tensor |
| 2732 | at::Tensor isclose::call(const at::Tensor & self, const at::Tensor & other, double rtol, double atol, bool equal_nan) { |
| 2733 | |
| 2734 | static auto op = create_isclose_typed_handle(); |
| 2735 | return op.call(self, other, rtol, atol, equal_nan); |
| 2736 | } |
| 2737 | |
| 2738 | // aten::isclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> Tensor |
| 2739 | at::Tensor isclose::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, double rtol, double atol, bool equal_nan) { |
| 2740 | |
| 2741 | static auto op = create_isclose_typed_handle(); |
| 2742 | return op.redispatch(dispatchKeySet, self, other, rtol, atol, equal_nan); |
| 2743 | } |
| 2744 | |
| 2745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_floating_point, name, "aten::is_floating_point") |
| 2746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_floating_point, overload_name, "") |
| 2747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_floating_point, schema_str, "is_floating_point(Tensor self) -> bool") |
| 2748 | |
| 2749 | // aten::is_floating_point(Tensor self) -> bool |
| 2750 | static C10_NOINLINE c10::TypedOperatorHandle<is_floating_point::schema> create_is_floating_point_typed_handle() { |
| 2751 | return c10::Dispatcher::singleton() |
| 2752 | .findSchemaOrThrow(is_floating_point::name, is_floating_point::overload_name) |
| 2753 | .typed<is_floating_point::schema>(); |
| 2754 | } |
| 2755 | |
| 2756 | // aten::is_floating_point(Tensor self) -> bool |
| 2757 | bool is_floating_point::call(const at::Tensor & self) { |
| 2758 | |
| 2759 | static auto op = create_is_floating_point_typed_handle(); |
| 2760 | return op.call(self); |
| 2761 | } |
| 2762 | |
| 2763 | // aten::is_floating_point(Tensor self) -> bool |
| 2764 | bool is_floating_point::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 2765 | |
| 2766 | static auto op = create_is_floating_point_typed_handle(); |
| 2767 | return op.redispatch(dispatchKeySet, self); |
| 2768 | } |
| 2769 | |
| 2770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_complex, name, "aten::is_complex") |
| 2771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_complex, overload_name, "") |
| 2772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_complex, schema_str, "is_complex(Tensor self) -> bool") |
| 2773 | |
| 2774 | // aten::is_complex(Tensor self) -> bool |
| 2775 | static C10_NOINLINE c10::TypedOperatorHandle<is_complex::schema> create_is_complex_typed_handle() { |
| 2776 | return c10::Dispatcher::singleton() |
| 2777 | .findSchemaOrThrow(is_complex::name, is_complex::overload_name) |
| 2778 | .typed<is_complex::schema>(); |
| 2779 | } |
| 2780 | |
| 2781 | // aten::is_complex(Tensor self) -> bool |
| 2782 | bool is_complex::call(const at::Tensor & self) { |
| 2783 | |
| 2784 | static auto op = create_is_complex_typed_handle(); |
| 2785 | return op.call(self); |
| 2786 | } |
| 2787 | |
| 2788 | // aten::is_complex(Tensor self) -> bool |
| 2789 | bool is_complex::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 2790 | |
| 2791 | static auto op = create_is_complex_typed_handle(); |
| 2792 | return op.redispatch(dispatchKeySet, self); |
| 2793 | } |
| 2794 | |
| 2795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_same_size, name, "aten::is_same_size") |
| 2796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_same_size, overload_name, "") |
| 2797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_same_size, schema_str, "is_same_size(Tensor self, Tensor other) -> bool") |
| 2798 | |
| 2799 | // aten::is_same_size(Tensor self, Tensor other) -> bool |
| 2800 | static C10_NOINLINE c10::TypedOperatorHandle<is_same_size::schema> create_is_same_size_typed_handle() { |
| 2801 | return c10::Dispatcher::singleton() |
| 2802 | .findSchemaOrThrow(is_same_size::name, is_same_size::overload_name) |
| 2803 | .typed<is_same_size::schema>(); |
| 2804 | } |
| 2805 | |
| 2806 | // aten::is_same_size(Tensor self, Tensor other) -> bool |
| 2807 | bool is_same_size::call(const at::Tensor & self, const at::Tensor & other) { |
| 2808 | |
| 2809 | static auto op = create_is_same_size_typed_handle(); |
| 2810 | return op.call(self, other); |
| 2811 | } |
| 2812 | |
| 2813 | // aten::is_same_size(Tensor self, Tensor other) -> bool |
| 2814 | bool is_same_size::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 2815 | |
| 2816 | static auto op = create_is_same_size_typed_handle(); |
| 2817 | return op.redispatch(dispatchKeySet, self, other); |
| 2818 | } |
| 2819 | |
| 2820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kl_div, name, "aten::kl_div") |
| 2821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kl_div, overload_name, "") |
| 2822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kl_div, schema_str, "kl_div(Tensor self, Tensor target, int reduction=Mean, *, bool log_target=False) -> Tensor") |
| 2823 | |
| 2824 | // aten::kl_div(Tensor self, Tensor target, int reduction=Mean, *, bool log_target=False) -> Tensor |
| 2825 | static C10_NOINLINE c10::TypedOperatorHandle<kl_div::schema> create_kl_div_typed_handle() { |
| 2826 | return c10::Dispatcher::singleton() |
| 2827 | .findSchemaOrThrow(kl_div::name, kl_div::overload_name) |
| 2828 | .typed<kl_div::schema>(); |
| 2829 | } |
| 2830 | |
| 2831 | // aten::kl_div(Tensor self, Tensor target, int reduction=Mean, *, bool log_target=False) -> Tensor |
| 2832 | at::Tensor kl_div::call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, bool log_target) { |
| 2833 | |
| 2834 | static auto op = create_kl_div_typed_handle(); |
| 2835 | return op.call(self, target, reduction, log_target); |
| 2836 | } |
| 2837 | |
| 2838 | // aten::kl_div(Tensor self, Tensor target, int reduction=Mean, *, bool log_target=False) -> Tensor |
| 2839 | at::Tensor kl_div::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, bool log_target) { |
| 2840 | |
| 2841 | static auto op = create_kl_div_typed_handle(); |
| 2842 | return op.redispatch(dispatchKeySet, self, target, reduction, log_target); |
| 2843 | } |
| 2844 | |
| 2845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_gemm_matrix_fp16, name, "aten::fbgemm_pack_gemm_matrix_fp16") |
| 2846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_gemm_matrix_fp16, overload_name, "") |
| 2847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_gemm_matrix_fp16, schema_str, "fbgemm_pack_gemm_matrix_fp16(Tensor input) -> Tensor") |
| 2848 | |
| 2849 | // aten::fbgemm_pack_gemm_matrix_fp16(Tensor input) -> Tensor |
| 2850 | static C10_NOINLINE c10::TypedOperatorHandle<fbgemm_pack_gemm_matrix_fp16::schema> create_fbgemm_pack_gemm_matrix_fp16_typed_handle() { |
| 2851 | return c10::Dispatcher::singleton() |
| 2852 | .findSchemaOrThrow(fbgemm_pack_gemm_matrix_fp16::name, fbgemm_pack_gemm_matrix_fp16::overload_name) |
| 2853 | .typed<fbgemm_pack_gemm_matrix_fp16::schema>(); |
| 2854 | } |
| 2855 | |
| 2856 | // aten::fbgemm_pack_gemm_matrix_fp16(Tensor input) -> Tensor |
| 2857 | at::Tensor fbgemm_pack_gemm_matrix_fp16::call(const at::Tensor & input) { |
| 2858 | |
| 2859 | static auto op = create_fbgemm_pack_gemm_matrix_fp16_typed_handle(); |
| 2860 | return op.call(input); |
| 2861 | } |
| 2862 | |
| 2863 | // aten::fbgemm_pack_gemm_matrix_fp16(Tensor input) -> Tensor |
| 2864 | at::Tensor fbgemm_pack_gemm_matrix_fp16::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input) { |
| 2865 | |
| 2866 | static auto op = create_fbgemm_pack_gemm_matrix_fp16_typed_handle(); |
| 2867 | return op.redispatch(dispatchKeySet, input); |
| 2868 | } |
| 2869 | |
| 2870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(margin_ranking_loss, name, "aten::margin_ranking_loss") |
| 2871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(margin_ranking_loss, overload_name, "") |
| 2872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(margin_ranking_loss, schema_str, "margin_ranking_loss(Tensor input1, Tensor input2, Tensor target, float margin=0.0, int reduction=Mean) -> Tensor") |
| 2873 | |
| 2874 | // aten::margin_ranking_loss(Tensor input1, Tensor input2, Tensor target, float margin=0.0, int reduction=Mean) -> Tensor |
| 2875 | static C10_NOINLINE c10::TypedOperatorHandle<margin_ranking_loss::schema> create_margin_ranking_loss_typed_handle() { |
| 2876 | return c10::Dispatcher::singleton() |
| 2877 | .findSchemaOrThrow(margin_ranking_loss::name, margin_ranking_loss::overload_name) |
| 2878 | .typed<margin_ranking_loss::schema>(); |
| 2879 | } |
| 2880 | |
| 2881 | // aten::margin_ranking_loss(Tensor input1, Tensor input2, Tensor target, float margin=0.0, int reduction=Mean) -> Tensor |
| 2882 | at::Tensor margin_ranking_loss::call(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin, int64_t reduction) { |
| 2883 | |
| 2884 | static auto op = create_margin_ranking_loss_typed_handle(); |
| 2885 | return op.call(input1, input2, target, margin, reduction); |
| 2886 | } |
| 2887 | |
| 2888 | // aten::margin_ranking_loss(Tensor input1, Tensor input2, Tensor target, float margin=0.0, int reduction=Mean) -> Tensor |
| 2889 | at::Tensor margin_ranking_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & target, double margin, int64_t reduction) { |
| 2890 | |
| 2891 | static auto op = create_margin_ranking_loss_typed_handle(); |
| 2892 | return op.redispatch(dispatchKeySet, input1, input2, target, margin, reduction); |
| 2893 | } |
| 2894 | |
| 2895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul, name, "aten::matmul") |
| 2896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul, overload_name, "") |
| 2897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul, schema_str, "matmul(Tensor self, Tensor other) -> Tensor") |
| 2898 | |
| 2899 | // aten::matmul(Tensor self, Tensor other) -> Tensor |
| 2900 | static C10_NOINLINE c10::TypedOperatorHandle<matmul::schema> create_matmul_typed_handle() { |
| 2901 | return c10::Dispatcher::singleton() |
| 2902 | .findSchemaOrThrow(matmul::name, matmul::overload_name) |
| 2903 | .typed<matmul::schema>(); |
| 2904 | } |
| 2905 | |
| 2906 | // aten::matmul(Tensor self, Tensor other) -> Tensor |
| 2907 | at::Tensor matmul::call(const at::Tensor & self, const at::Tensor & other) { |
| 2908 | |
| 2909 | static auto op = create_matmul_typed_handle(); |
| 2910 | return op.call(self, other); |
| 2911 | } |
| 2912 | |
| 2913 | // aten::matmul(Tensor self, Tensor other) -> Tensor |
| 2914 | at::Tensor matmul::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 2915 | |
| 2916 | static auto op = create_matmul_typed_handle(); |
| 2917 | return op.redispatch(dispatchKeySet, self, other); |
| 2918 | } |
| 2919 | |
| 2920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_backward, name, "aten::matmul_backward") |
| 2921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_backward, overload_name, "") |
| 2922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_backward, schema_str, "matmul_backward(Tensor grad, Tensor self, Tensor other, bool[2] mask) -> (Tensor, Tensor)") |
| 2923 | |
| 2924 | // aten::matmul_backward(Tensor grad, Tensor self, Tensor other, bool[2] mask) -> (Tensor, Tensor) |
| 2925 | static C10_NOINLINE c10::TypedOperatorHandle<matmul_backward::schema> create_matmul_backward_typed_handle() { |
| 2926 | return c10::Dispatcher::singleton() |
| 2927 | .findSchemaOrThrow(matmul_backward::name, matmul_backward::overload_name) |
| 2928 | .typed<matmul_backward::schema>(); |
| 2929 | } |
| 2930 | |
| 2931 | // aten::matmul_backward(Tensor grad, Tensor self, Tensor other, bool[2] mask) -> (Tensor, Tensor) |
| 2932 | ::std::tuple<at::Tensor,at::Tensor> matmul_backward::call(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array<bool,2> mask) { |
| 2933 | |
| 2934 | static auto op = create_matmul_backward_typed_handle(); |
| 2935 | return op.call(grad, self, other, mask); |
| 2936 | } |
| 2937 | |
| 2938 | // aten::matmul_backward(Tensor grad, Tensor self, Tensor other, bool[2] mask) -> (Tensor, Tensor) |
| 2939 | ::std::tuple<at::Tensor,at::Tensor> matmul_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array<bool,2> mask) { |
| 2940 | |
| 2941 | static auto op = create_matmul_backward_typed_handle(); |
| 2942 | return op.redispatch(dispatchKeySet, grad, self, other, mask); |
| 2943 | } |
| 2944 | |
| 2945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_out, name, "aten::matmul") |
| 2946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_out, overload_name, "out") |
| 2947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_out, schema_str, "matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 2948 | |
| 2949 | // aten::matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2950 | static C10_NOINLINE c10::TypedOperatorHandle<matmul_out::schema> create_matmul_out_typed_handle() { |
| 2951 | return c10::Dispatcher::singleton() |
| 2952 | .findSchemaOrThrow(matmul_out::name, matmul_out::overload_name) |
| 2953 | .typed<matmul_out::schema>(); |
| 2954 | } |
| 2955 | |
| 2956 | // aten::matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2957 | at::Tensor & matmul_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2958 | |
| 2959 | static auto op = create_matmul_out_typed_handle(); |
| 2960 | return op.call(self, other, out); |
| 2961 | } |
| 2962 | |
| 2963 | // aten::matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 2964 | at::Tensor & matmul_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 2965 | |
| 2966 | static auto op = create_matmul_out_typed_handle(); |
| 2967 | return op.redispatch(dispatchKeySet, self, other, out); |
| 2968 | } |
| 2969 | |
| 2970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_exp, name, "aten::matrix_exp") |
| 2971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_exp, overload_name, "") |
| 2972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_exp, schema_str, "matrix_exp(Tensor self) -> Tensor") |
| 2973 | |
| 2974 | // aten::matrix_exp(Tensor self) -> Tensor |
| 2975 | static C10_NOINLINE c10::TypedOperatorHandle<matrix_exp::schema> create_matrix_exp_typed_handle() { |
| 2976 | return c10::Dispatcher::singleton() |
| 2977 | .findSchemaOrThrow(matrix_exp::name, matrix_exp::overload_name) |
| 2978 | .typed<matrix_exp::schema>(); |
| 2979 | } |
| 2980 | |
| 2981 | // aten::matrix_exp(Tensor self) -> Tensor |
| 2982 | at::Tensor matrix_exp::call(const at::Tensor & self) { |
| 2983 | |
| 2984 | static auto op = create_matrix_exp_typed_handle(); |
| 2985 | return op.call(self); |
| 2986 | } |
| 2987 | |
| 2988 | // aten::matrix_exp(Tensor self) -> Tensor |
| 2989 | at::Tensor matrix_exp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 2990 | |
| 2991 | static auto op = create_matrix_exp_typed_handle(); |
| 2992 | return op.redispatch(dispatchKeySet, self); |
| 2993 | } |
| 2994 | |
| 2995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_compute_linear_combination, name, "aten::_compute_linear_combination") |
| 2996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_compute_linear_combination, overload_name, "") |
| 2997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_compute_linear_combination, schema_str, "_compute_linear_combination(Tensor input, Tensor coefficients) -> Tensor") |
| 2998 | |
| 2999 | // aten::_compute_linear_combination(Tensor input, Tensor coefficients) -> Tensor |
| 3000 | static C10_NOINLINE c10::TypedOperatorHandle<_compute_linear_combination::schema> create__compute_linear_combination_typed_handle() { |
| 3001 | return c10::Dispatcher::singleton() |
| 3002 | .findSchemaOrThrow(_compute_linear_combination::name, _compute_linear_combination::overload_name) |
| 3003 | .typed<_compute_linear_combination::schema>(); |
| 3004 | } |
| 3005 | |
| 3006 | // aten::_compute_linear_combination(Tensor input, Tensor coefficients) -> Tensor |
| 3007 | at::Tensor _compute_linear_combination::call(const at::Tensor & input, const at::Tensor & coefficients) { |
| 3008 | |
| 3009 | static auto op = create__compute_linear_combination_typed_handle(); |
| 3010 | return op.call(input, coefficients); |
| 3011 | } |
| 3012 | |
| 3013 | // aten::_compute_linear_combination(Tensor input, Tensor coefficients) -> Tensor |
| 3014 | at::Tensor _compute_linear_combination::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & coefficients) { |
| 3015 | |
| 3016 | static auto op = create__compute_linear_combination_typed_handle(); |
| 3017 | return op.redispatch(dispatchKeySet, input, coefficients); |
| 3018 | } |
| 3019 | |
| 3020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_compute_linear_combination_out, name, "aten::_compute_linear_combination") |
| 3021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_compute_linear_combination_out, overload_name, "out") |
| 3022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_compute_linear_combination_out, schema_str, "_compute_linear_combination.out(Tensor input, Tensor coefficients, *, Tensor(a!) out) -> Tensor(a!)") |
| 3023 | |
| 3024 | // aten::_compute_linear_combination.out(Tensor input, Tensor coefficients, *, Tensor(a!) out) -> Tensor(a!) |
| 3025 | static C10_NOINLINE c10::TypedOperatorHandle<_compute_linear_combination_out::schema> create__compute_linear_combination_out_typed_handle() { |
| 3026 | return c10::Dispatcher::singleton() |
| 3027 | .findSchemaOrThrow(_compute_linear_combination_out::name, _compute_linear_combination_out::overload_name) |
| 3028 | .typed<_compute_linear_combination_out::schema>(); |
| 3029 | } |
| 3030 | |
| 3031 | // aten::_compute_linear_combination.out(Tensor input, Tensor coefficients, *, Tensor(a!) out) -> Tensor(a!) |
| 3032 | at::Tensor & _compute_linear_combination_out::call(const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out) { |
| 3033 | |
| 3034 | static auto op = create__compute_linear_combination_out_typed_handle(); |
| 3035 | return op.call(input, coefficients, out); |
| 3036 | } |
| 3037 | |
| 3038 | // aten::_compute_linear_combination.out(Tensor input, Tensor coefficients, *, Tensor(a!) out) -> Tensor(a!) |
| 3039 | at::Tensor & _compute_linear_combination_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & coefficients, at::Tensor & out) { |
| 3040 | |
| 3041 | static auto op = create__compute_linear_combination_out_typed_handle(); |
| 3042 | return op.redispatch(dispatchKeySet, input, coefficients, out); |
| 3043 | } |
| 3044 | |
| 3045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool2d_backward, name, "aten::mkldnn_max_pool2d_backward") |
| 3046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool2d_backward, overload_name, "") |
| 3047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool2d_backward, schema_str, "mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor") |
| 3048 | |
| 3049 | // aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor |
| 3050 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_max_pool2d_backward::schema> create_mkldnn_max_pool2d_backward_typed_handle() { |
| 3051 | return c10::Dispatcher::singleton() |
| 3052 | .findSchemaOrThrow(mkldnn_max_pool2d_backward::name, mkldnn_max_pool2d_backward::overload_name) |
| 3053 | .typed<mkldnn_max_pool2d_backward::schema>(); |
| 3054 | } |
| 3055 | |
| 3056 | // aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor |
| 3057 | at::Tensor mkldnn_max_pool2d_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) { |
| 3058 | |
| 3059 | static auto op = create_mkldnn_max_pool2d_backward_typed_handle(); |
| 3060 | return op.call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode); |
| 3061 | } |
| 3062 | |
| 3063 | // aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor |
| 3064 | at::Tensor mkldnn_max_pool2d_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) { |
| 3065 | |
| 3066 | static auto op = create_mkldnn_max_pool2d_backward_typed_handle(); |
| 3067 | return op.redispatch(dispatchKeySet, grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode); |
| 3068 | } |
| 3069 | |
| 3070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d, name, "aten::max_pool3d") |
| 3071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d, overload_name, "") |
| 3072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d, schema_str, "max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor") |
| 3073 | |
| 3074 | // aten::max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
| 3075 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool3d::schema> create_max_pool3d_typed_handle() { |
| 3076 | return c10::Dispatcher::singleton() |
| 3077 | .findSchemaOrThrow(max_pool3d::name, max_pool3d::overload_name) |
| 3078 | .typed<max_pool3d::schema>(); |
| 3079 | } |
| 3080 | |
| 3081 | // aten::max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
| 3082 | at::Tensor max_pool3d::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 3083 | |
| 3084 | static auto op = create_max_pool3d_typed_handle(); |
| 3085 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode); |
| 3086 | } |
| 3087 | |
| 3088 | // aten::max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
| 3089 | at::Tensor max_pool3d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 3090 | |
| 3091 | static auto op = create_max_pool3d_typed_handle(); |
| 3092 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode); |
| 3093 | } |
| 3094 | |
| 3095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median, name, "aten::median") |
| 3096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median, overload_name, "") |
| 3097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median, schema_str, "median(Tensor self) -> Tensor") |
| 3098 | |
| 3099 | // aten::median(Tensor self) -> Tensor |
| 3100 | static C10_NOINLINE c10::TypedOperatorHandle<median::schema> create_median_typed_handle() { |
| 3101 | return c10::Dispatcher::singleton() |
| 3102 | .findSchemaOrThrow(median::name, median::overload_name) |
| 3103 | .typed<median::schema>(); |
| 3104 | } |
| 3105 | |
| 3106 | // aten::median(Tensor self) -> Tensor |
| 3107 | at::Tensor median::call(const at::Tensor & self) { |
| 3108 | |
| 3109 | static auto op = create_median_typed_handle(); |
| 3110 | return op.call(self); |
| 3111 | } |
| 3112 | |
| 3113 | // aten::median(Tensor self) -> Tensor |
| 3114 | at::Tensor median::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3115 | |
| 3116 | static auto op = create_median_typed_handle(); |
| 3117 | return op.redispatch(dispatchKeySet, self); |
| 3118 | } |
| 3119 | |
| 3120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_dim, name, "aten::median") |
| 3121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_dim, overload_name, "dim") |
| 3122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_dim, schema_str, "median.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 3123 | |
| 3124 | // aten::median.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3125 | static C10_NOINLINE c10::TypedOperatorHandle<median_dim::schema> create_median_dim_typed_handle() { |
| 3126 | return c10::Dispatcher::singleton() |
| 3127 | .findSchemaOrThrow(median_dim::name, median_dim::overload_name) |
| 3128 | .typed<median_dim::schema>(); |
| 3129 | } |
| 3130 | |
| 3131 | // aten::median.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3132 | ::std::tuple<at::Tensor,at::Tensor> median_dim::call(const at::Tensor & self, int64_t dim, bool keepdim) { |
| 3133 | |
| 3134 | static auto op = create_median_dim_typed_handle(); |
| 3135 | return op.call(self, dim, keepdim); |
| 3136 | } |
| 3137 | |
| 3138 | // aten::median.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3139 | ::std::tuple<at::Tensor,at::Tensor> median_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim) { |
| 3140 | |
| 3141 | static auto op = create_median_dim_typed_handle(); |
| 3142 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 3143 | } |
| 3144 | |
| 3145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_dim_values, name, "aten::median") |
| 3146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_dim_values, overload_name, "dim_values") |
| 3147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_dim_values, schema_str, "median.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 3148 | |
| 3149 | // aten::median.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3150 | static C10_NOINLINE c10::TypedOperatorHandle<median_dim_values::schema> create_median_dim_values_typed_handle() { |
| 3151 | return c10::Dispatcher::singleton() |
| 3152 | .findSchemaOrThrow(median_dim_values::name, median_dim_values::overload_name) |
| 3153 | .typed<median_dim_values::schema>(); |
| 3154 | } |
| 3155 | |
| 3156 | // aten::median.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3157 | ::std::tuple<at::Tensor &,at::Tensor &> median_dim_values::call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3158 | |
| 3159 | static auto op = create_median_dim_values_typed_handle(); |
| 3160 | return op.call(self, dim, keepdim, values, indices); |
| 3161 | } |
| 3162 | |
| 3163 | // aten::median.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3164 | ::std::tuple<at::Tensor &,at::Tensor &> median_dim_values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3165 | |
| 3166 | static auto op = create_median_dim_values_typed_handle(); |
| 3167 | return op.redispatch(dispatchKeySet, self, dim, keepdim, values, indices); |
| 3168 | } |
| 3169 | |
| 3170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_names_dim, name, "aten::median") |
| 3171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_names_dim, overload_name, "names_dim") |
| 3172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_names_dim, schema_str, "median.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 3173 | |
| 3174 | // aten::median.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3175 | static C10_NOINLINE c10::TypedOperatorHandle<median_names_dim::schema> create_median_names_dim_typed_handle() { |
| 3176 | return c10::Dispatcher::singleton() |
| 3177 | .findSchemaOrThrow(median_names_dim::name, median_names_dim::overload_name) |
| 3178 | .typed<median_names_dim::schema>(); |
| 3179 | } |
| 3180 | |
| 3181 | // aten::median.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3182 | ::std::tuple<at::Tensor,at::Tensor> median_names_dim::call(const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 3183 | |
| 3184 | static auto op = create_median_names_dim_typed_handle(); |
| 3185 | return op.call(self, dim, keepdim); |
| 3186 | } |
| 3187 | |
| 3188 | // aten::median.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3189 | ::std::tuple<at::Tensor,at::Tensor> median_names_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 3190 | |
| 3191 | static auto op = create_median_names_dim_typed_handle(); |
| 3192 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 3193 | } |
| 3194 | |
| 3195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_names_dim_values, name, "aten::median") |
| 3196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_names_dim_values, overload_name, "names_dim_values") |
| 3197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_names_dim_values, schema_str, "median.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 3198 | |
| 3199 | // aten::median.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3200 | static C10_NOINLINE c10::TypedOperatorHandle<median_names_dim_values::schema> create_median_names_dim_values_typed_handle() { |
| 3201 | return c10::Dispatcher::singleton() |
| 3202 | .findSchemaOrThrow(median_names_dim_values::name, median_names_dim_values::overload_name) |
| 3203 | .typed<median_names_dim_values::schema>(); |
| 3204 | } |
| 3205 | |
| 3206 | // aten::median.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3207 | ::std::tuple<at::Tensor &,at::Tensor &> median_names_dim_values::call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3208 | |
| 3209 | static auto op = create_median_names_dim_values_typed_handle(); |
| 3210 | return op.call(self, dim, keepdim, values, indices); |
| 3211 | } |
| 3212 | |
| 3213 | // aten::median.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3214 | ::std::tuple<at::Tensor &,at::Tensor &> median_names_dim_values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3215 | |
| 3216 | static auto op = create_median_names_dim_values_typed_handle(); |
| 3217 | return op.redispatch(dispatchKeySet, self, dim, keepdim, values, indices); |
| 3218 | } |
| 3219 | |
| 3220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian, name, "aten::nanmedian") |
| 3221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian, overload_name, "") |
| 3222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian, schema_str, "nanmedian(Tensor self) -> Tensor") |
| 3223 | |
| 3224 | // aten::nanmedian(Tensor self) -> Tensor |
| 3225 | static C10_NOINLINE c10::TypedOperatorHandle<nanmedian::schema> create_nanmedian_typed_handle() { |
| 3226 | return c10::Dispatcher::singleton() |
| 3227 | .findSchemaOrThrow(nanmedian::name, nanmedian::overload_name) |
| 3228 | .typed<nanmedian::schema>(); |
| 3229 | } |
| 3230 | |
| 3231 | // aten::nanmedian(Tensor self) -> Tensor |
| 3232 | at::Tensor nanmedian::call(const at::Tensor & self) { |
| 3233 | |
| 3234 | static auto op = create_nanmedian_typed_handle(); |
| 3235 | return op.call(self); |
| 3236 | } |
| 3237 | |
| 3238 | // aten::nanmedian(Tensor self) -> Tensor |
| 3239 | at::Tensor nanmedian::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3240 | |
| 3241 | static auto op = create_nanmedian_typed_handle(); |
| 3242 | return op.redispatch(dispatchKeySet, self); |
| 3243 | } |
| 3244 | |
| 3245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_dim, name, "aten::nanmedian") |
| 3246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_dim, overload_name, "dim") |
| 3247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_dim, schema_str, "nanmedian.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 3248 | |
| 3249 | // aten::nanmedian.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3250 | static C10_NOINLINE c10::TypedOperatorHandle<nanmedian_dim::schema> create_nanmedian_dim_typed_handle() { |
| 3251 | return c10::Dispatcher::singleton() |
| 3252 | .findSchemaOrThrow(nanmedian_dim::name, nanmedian_dim::overload_name) |
| 3253 | .typed<nanmedian_dim::schema>(); |
| 3254 | } |
| 3255 | |
| 3256 | // aten::nanmedian.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3257 | ::std::tuple<at::Tensor,at::Tensor> nanmedian_dim::call(const at::Tensor & self, int64_t dim, bool keepdim) { |
| 3258 | |
| 3259 | static auto op = create_nanmedian_dim_typed_handle(); |
| 3260 | return op.call(self, dim, keepdim); |
| 3261 | } |
| 3262 | |
| 3263 | // aten::nanmedian.dim(Tensor self, int dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3264 | ::std::tuple<at::Tensor,at::Tensor> nanmedian_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim) { |
| 3265 | |
| 3266 | static auto op = create_nanmedian_dim_typed_handle(); |
| 3267 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 3268 | } |
| 3269 | |
| 3270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_dim_values, name, "aten::nanmedian") |
| 3271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_dim_values, overload_name, "dim_values") |
| 3272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_dim_values, schema_str, "nanmedian.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 3273 | |
| 3274 | // aten::nanmedian.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3275 | static C10_NOINLINE c10::TypedOperatorHandle<nanmedian_dim_values::schema> create_nanmedian_dim_values_typed_handle() { |
| 3276 | return c10::Dispatcher::singleton() |
| 3277 | .findSchemaOrThrow(nanmedian_dim_values::name, nanmedian_dim_values::overload_name) |
| 3278 | .typed<nanmedian_dim_values::schema>(); |
| 3279 | } |
| 3280 | |
| 3281 | // aten::nanmedian.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3282 | ::std::tuple<at::Tensor &,at::Tensor &> nanmedian_dim_values::call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3283 | |
| 3284 | static auto op = create_nanmedian_dim_values_typed_handle(); |
| 3285 | return op.call(self, dim, keepdim, values, indices); |
| 3286 | } |
| 3287 | |
| 3288 | // aten::nanmedian.dim_values(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3289 | ::std::tuple<at::Tensor &,at::Tensor &> nanmedian_dim_values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3290 | |
| 3291 | static auto op = create_nanmedian_dim_values_typed_handle(); |
| 3292 | return op.redispatch(dispatchKeySet, self, dim, keepdim, values, indices); |
| 3293 | } |
| 3294 | |
| 3295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_names_dim, name, "aten::nanmedian") |
| 3296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_names_dim, overload_name, "names_dim") |
| 3297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_names_dim, schema_str, "nanmedian.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)") |
| 3298 | |
| 3299 | // aten::nanmedian.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3300 | static C10_NOINLINE c10::TypedOperatorHandle<nanmedian_names_dim::schema> create_nanmedian_names_dim_typed_handle() { |
| 3301 | return c10::Dispatcher::singleton() |
| 3302 | .findSchemaOrThrow(nanmedian_names_dim::name, nanmedian_names_dim::overload_name) |
| 3303 | .typed<nanmedian_names_dim::schema>(); |
| 3304 | } |
| 3305 | |
| 3306 | // aten::nanmedian.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3307 | ::std::tuple<at::Tensor,at::Tensor> nanmedian_names_dim::call(const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 3308 | |
| 3309 | static auto op = create_nanmedian_names_dim_typed_handle(); |
| 3310 | return op.call(self, dim, keepdim); |
| 3311 | } |
| 3312 | |
| 3313 | // aten::nanmedian.names_dim(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) |
| 3314 | ::std::tuple<at::Tensor,at::Tensor> nanmedian_names_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim) { |
| 3315 | |
| 3316 | static auto op = create_nanmedian_names_dim_typed_handle(); |
| 3317 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
| 3318 | } |
| 3319 | |
| 3320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_names_dim_values, name, "aten::nanmedian") |
| 3321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_names_dim_values, overload_name, "names_dim_values") |
| 3322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_names_dim_values, schema_str, "nanmedian.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)") |
| 3323 | |
| 3324 | // aten::nanmedian.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3325 | static C10_NOINLINE c10::TypedOperatorHandle<nanmedian_names_dim_values::schema> create_nanmedian_names_dim_values_typed_handle() { |
| 3326 | return c10::Dispatcher::singleton() |
| 3327 | .findSchemaOrThrow(nanmedian_names_dim_values::name, nanmedian_names_dim_values::overload_name) |
| 3328 | .typed<nanmedian_names_dim_values::schema>(); |
| 3329 | } |
| 3330 | |
| 3331 | // aten::nanmedian.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3332 | ::std::tuple<at::Tensor &,at::Tensor &> nanmedian_names_dim_values::call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3333 | |
| 3334 | static auto op = create_nanmedian_names_dim_values_typed_handle(); |
| 3335 | return op.call(self, dim, keepdim, values, indices); |
| 3336 | } |
| 3337 | |
| 3338 | // aten::nanmedian.names_dim_values(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
| 3339 | ::std::tuple<at::Tensor &,at::Tensor &> nanmedian_names_dim_values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & values, at::Tensor & indices) { |
| 3340 | |
| 3341 | static auto op = create_nanmedian_names_dim_values_typed_handle(); |
| 3342 | return op.redispatch(dispatchKeySet, self, dim, keepdim, values, indices); |
| 3343 | } |
| 3344 | |
| 3345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm, name, "aten::miopen_batch_norm") |
| 3346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm, overload_name, "") |
| 3347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm, schema_str, "miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor)") |
| 3348 | |
| 3349 | // aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) |
| 3350 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_batch_norm::schema> create_miopen_batch_norm_typed_handle() { |
| 3351 | return c10::Dispatcher::singleton() |
| 3352 | .findSchemaOrThrow(miopen_batch_norm::name, miopen_batch_norm::overload_name) |
| 3353 | .typed<miopen_batch_norm::schema>(); |
| 3354 | } |
| 3355 | |
| 3356 | // aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) |
| 3357 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> miopen_batch_norm::call(const at::Tensor & input, const 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 exponential_average_factor, double epsilon) { |
| 3358 | |
| 3359 | static auto op = create_miopen_batch_norm_typed_handle(); |
| 3360 | return op.call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); |
| 3361 | } |
| 3362 | |
| 3363 | // aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) |
| 3364 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> miopen_batch_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const 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 exponential_average_factor, double epsilon) { |
| 3365 | |
| 3366 | static auto op = create_miopen_batch_norm_typed_handle(); |
| 3367 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); |
| 3368 | } |
| 3369 | |
| 3370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_transpose, name, "aten::miopen_convolution_transpose") |
| 3371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_transpose, overload_name, "") |
| 3372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_transpose, schema_str, "miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor") |
| 3373 | |
| 3374 | // aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor |
| 3375 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_convolution_transpose::schema> create_miopen_convolution_transpose_typed_handle() { |
| 3376 | return c10::Dispatcher::singleton() |
| 3377 | .findSchemaOrThrow(miopen_convolution_transpose::name, miopen_convolution_transpose::overload_name) |
| 3378 | .typed<miopen_convolution_transpose::schema>(); |
| 3379 | } |
| 3380 | |
| 3381 | // aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor |
| 3382 | at::Tensor miopen_convolution_transpose::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { |
| 3383 | |
| 3384 | static auto op = create_miopen_convolution_transpose_typed_handle(); |
| 3385 | return op.call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic); |
| 3386 | } |
| 3387 | |
| 3388 | // aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor |
| 3389 | at::Tensor miopen_convolution_transpose::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { |
| 3390 | |
| 3391 | static auto op = create_miopen_convolution_transpose_typed_handle(); |
| 3392 | return op.redispatch(dispatchKeySet, self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic); |
| 3393 | } |
| 3394 | |
| 3395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_add_relu, name, "aten::miopen_convolution_add_relu") |
| 3396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_add_relu, overload_name, "") |
| 3397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_add_relu, schema_str, "miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor") |
| 3398 | |
| 3399 | // aten::miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
| 3400 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_convolution_add_relu::schema> create_miopen_convolution_add_relu_typed_handle() { |
| 3401 | return c10::Dispatcher::singleton() |
| 3402 | .findSchemaOrThrow(miopen_convolution_add_relu::name, miopen_convolution_add_relu::overload_name) |
| 3403 | .typed<miopen_convolution_add_relu::schema>(); |
| 3404 | } |
| 3405 | |
| 3406 | // aten::miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
| 3407 | at::Tensor miopen_convolution_add_relu::call(const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const c10::optional<at::Scalar> & alpha, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { |
| 3408 | |
| 3409 | static auto op = create_miopen_convolution_add_relu_typed_handle(); |
| 3410 | return op.call(self, weight, z, alpha, bias, stride, padding, dilation, groups); |
| 3411 | } |
| 3412 | |
| 3413 | // aten::miopen_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
| 3414 | at::Tensor miopen_convolution_add_relu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const at::Tensor & z, const c10::optional<at::Scalar> & alpha, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, int64_t groups) { |
| 3415 | |
| 3416 | static auto op = create_miopen_convolution_add_relu_typed_handle(); |
| 3417 | return op.redispatch(dispatchKeySet, self, weight, z, alpha, bias, stride, padding, dilation, groups); |
| 3418 | } |
| 3419 | |
| 3420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_backward, name, "aten::miopen_rnn_backward") |
| 3421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_backward, overload_name, "") |
| 3422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_backward, schema_str, "miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[])") |
| 3423 | |
| 3424 | // aten::miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) |
| 3425 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_rnn_backward::schema> create_miopen_rnn_backward_typed_handle() { |
| 3426 | return c10::Dispatcher::singleton() |
| 3427 | .findSchemaOrThrow(miopen_rnn_backward::name, miopen_rnn_backward::overload_name) |
| 3428 | .typed<miopen_rnn_backward::schema>(); |
| 3429 | } |
| 3430 | |
| 3431 | // aten::miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) |
| 3432 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,::std::vector<at::Tensor>> miopen_rnn_backward::call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, const at::Tensor & output, const c10::optional<at::Tensor> & grad_output, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state, const at::Tensor & reserve, ::std::array<bool,4> output_mask) { |
| 3433 | |
| 3434 | static auto op = create_miopen_rnn_backward_typed_handle(); |
| 3435 | return op.call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); |
| 3436 | } |
| 3437 | |
| 3438 | // aten::miopen_rnn_backward(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask) -> (Tensor, Tensor, Tensor, Tensor[]) |
| 3439 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,::std::vector<at::Tensor>> miopen_rnn_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, const at::Tensor & output, const c10::optional<at::Tensor> & grad_output, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state, const at::Tensor & reserve, ::std::array<bool,4> output_mask) { |
| 3440 | |
| 3441 | static auto op = create_miopen_rnn_backward_typed_handle(); |
| 3442 | return op.redispatch(dispatchKeySet, input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); |
| 3443 | } |
| 3444 | |
| 3445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_Tensor, name, "aten::multiply") |
| 3446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_Tensor, overload_name, "Tensor") |
| 3447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_Tensor, schema_str, "multiply.Tensor(Tensor self, Tensor other) -> Tensor") |
| 3448 | |
| 3449 | // aten::multiply.Tensor(Tensor self, Tensor other) -> Tensor |
| 3450 | static C10_NOINLINE c10::TypedOperatorHandle<multiply_Tensor::schema> create_multiply_Tensor_typed_handle() { |
| 3451 | return c10::Dispatcher::singleton() |
| 3452 | .findSchemaOrThrow(multiply_Tensor::name, multiply_Tensor::overload_name) |
| 3453 | .typed<multiply_Tensor::schema>(); |
| 3454 | } |
| 3455 | |
| 3456 | // aten::multiply.Tensor(Tensor self, Tensor other) -> Tensor |
| 3457 | at::Tensor multiply_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 3458 | |
| 3459 | static auto op = create_multiply_Tensor_typed_handle(); |
| 3460 | return op.call(self, other); |
| 3461 | } |
| 3462 | |
| 3463 | // aten::multiply.Tensor(Tensor self, Tensor other) -> Tensor |
| 3464 | at::Tensor multiply_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 3465 | |
| 3466 | static auto op = create_multiply_Tensor_typed_handle(); |
| 3467 | return op.redispatch(dispatchKeySet, self, other); |
| 3468 | } |
| 3469 | |
| 3470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply__Tensor, name, "aten::multiply_") |
| 3471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply__Tensor, overload_name, "Tensor") |
| 3472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply__Tensor, schema_str, "multiply_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 3473 | |
| 3474 | // aten::multiply_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 3475 | static C10_NOINLINE c10::TypedOperatorHandle<multiply__Tensor::schema> create_multiply__Tensor_typed_handle() { |
| 3476 | return c10::Dispatcher::singleton() |
| 3477 | .findSchemaOrThrow(multiply__Tensor::name, multiply__Tensor::overload_name) |
| 3478 | .typed<multiply__Tensor::schema>(); |
| 3479 | } |
| 3480 | |
| 3481 | // aten::multiply_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 3482 | at::Tensor & multiply__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 3483 | |
| 3484 | static auto op = create_multiply__Tensor_typed_handle(); |
| 3485 | return op.call(self, other); |
| 3486 | } |
| 3487 | |
| 3488 | // aten::multiply_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 3489 | at::Tensor & multiply__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 3490 | |
| 3491 | static auto op = create_multiply__Tensor_typed_handle(); |
| 3492 | return op.redispatch(dispatchKeySet, self, other); |
| 3493 | } |
| 3494 | |
| 3495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_out, name, "aten::multiply") |
| 3496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_out, overload_name, "out") |
| 3497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_out, schema_str, "multiply.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 3498 | |
| 3499 | // aten::multiply.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3500 | static C10_NOINLINE c10::TypedOperatorHandle<multiply_out::schema> create_multiply_out_typed_handle() { |
| 3501 | return c10::Dispatcher::singleton() |
| 3502 | .findSchemaOrThrow(multiply_out::name, multiply_out::overload_name) |
| 3503 | .typed<multiply_out::schema>(); |
| 3504 | } |
| 3505 | |
| 3506 | // aten::multiply.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3507 | at::Tensor & multiply_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3508 | |
| 3509 | static auto op = create_multiply_out_typed_handle(); |
| 3510 | return op.call(self, other, out); |
| 3511 | } |
| 3512 | |
| 3513 | // aten::multiply.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 3514 | at::Tensor & multiply_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 3515 | |
| 3516 | static auto op = create_multiply_out_typed_handle(); |
| 3517 | return op.redispatch(dispatchKeySet, self, other, out); |
| 3518 | } |
| 3519 | |
| 3520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_Scalar, name, "aten::multiply") |
| 3521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_Scalar, overload_name, "Scalar") |
| 3522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply_Scalar, schema_str, "multiply.Scalar(Tensor self, Scalar other) -> Tensor") |
| 3523 | |
| 3524 | // aten::multiply.Scalar(Tensor self, Scalar other) -> Tensor |
| 3525 | static C10_NOINLINE c10::TypedOperatorHandle<multiply_Scalar::schema> create_multiply_Scalar_typed_handle() { |
| 3526 | return c10::Dispatcher::singleton() |
| 3527 | .findSchemaOrThrow(multiply_Scalar::name, multiply_Scalar::overload_name) |
| 3528 | .typed<multiply_Scalar::schema>(); |
| 3529 | } |
| 3530 | |
| 3531 | // aten::multiply.Scalar(Tensor self, Scalar other) -> Tensor |
| 3532 | at::Tensor multiply_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 3533 | |
| 3534 | static auto op = create_multiply_Scalar_typed_handle(); |
| 3535 | return op.call(self, other); |
| 3536 | } |
| 3537 | |
| 3538 | // aten::multiply.Scalar(Tensor self, Scalar other) -> Tensor |
| 3539 | at::Tensor multiply_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 3540 | |
| 3541 | static auto op = create_multiply_Scalar_typed_handle(); |
| 3542 | return op.redispatch(dispatchKeySet, self, other); |
| 3543 | } |
| 3544 | |
| 3545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply__Scalar, name, "aten::multiply_") |
| 3546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply__Scalar, overload_name, "Scalar") |
| 3547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multiply__Scalar, schema_str, "multiply_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 3548 | |
| 3549 | // aten::multiply_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 3550 | static C10_NOINLINE c10::TypedOperatorHandle<multiply__Scalar::schema> create_multiply__Scalar_typed_handle() { |
| 3551 | return c10::Dispatcher::singleton() |
| 3552 | .findSchemaOrThrow(multiply__Scalar::name, multiply__Scalar::overload_name) |
| 3553 | .typed<multiply__Scalar::schema>(); |
| 3554 | } |
| 3555 | |
| 3556 | // aten::multiply_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 3557 | at::Tensor & multiply__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 3558 | |
| 3559 | static auto op = create_multiply__Scalar_typed_handle(); |
| 3560 | return op.call(self, other); |
| 3561 | } |
| 3562 | |
| 3563 | // aten::multiply_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 3564 | at::Tensor & multiply__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 3565 | |
| 3566 | static auto op = create_multiply__Scalar_typed_handle(); |
| 3567 | return op.redispatch(dispatchKeySet, self, other); |
| 3568 | } |
| 3569 | |
| 3570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_elemt, name, "aten::batch_norm_elemt") |
| 3571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_elemt, overload_name, "") |
| 3572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_elemt, schema_str, "batch_norm_elemt(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps) -> Tensor") |
| 3573 | |
| 3574 | // aten::batch_norm_elemt(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps) -> Tensor |
| 3575 | static C10_NOINLINE c10::TypedOperatorHandle<batch_norm_elemt::schema> create_batch_norm_elemt_typed_handle() { |
| 3576 | return c10::Dispatcher::singleton() |
| 3577 | .findSchemaOrThrow(batch_norm_elemt::name, batch_norm_elemt::overload_name) |
| 3578 | .typed<batch_norm_elemt::schema>(); |
| 3579 | } |
| 3580 | |
| 3581 | // aten::batch_norm_elemt(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps) -> Tensor |
| 3582 | at::Tensor batch_norm_elemt::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps) { |
| 3583 | |
| 3584 | static auto op = create_batch_norm_elemt_typed_handle(); |
| 3585 | return op.call(input, weight, bias, mean, invstd, eps); |
| 3586 | } |
| 3587 | |
| 3588 | // aten::batch_norm_elemt(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps) -> Tensor |
| 3589 | at::Tensor batch_norm_elemt::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps) { |
| 3590 | |
| 3591 | static auto op = create_batch_norm_elemt_typed_handle(); |
| 3592 | return op.redispatch(dispatchKeySet, input, weight, bias, mean, invstd, eps); |
| 3593 | } |
| 3594 | |
| 3595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_elemt_out, name, "aten::batch_norm_elemt") |
| 3596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_elemt_out, overload_name, "out") |
| 3597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_elemt_out, schema_str, "batch_norm_elemt.out(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps, *, Tensor(a!) out) -> Tensor(a!)") |
| 3598 | |
| 3599 | // aten::batch_norm_elemt.out(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps, *, Tensor(a!) out) -> Tensor(a!) |
| 3600 | static C10_NOINLINE c10::TypedOperatorHandle<batch_norm_elemt_out::schema> create_batch_norm_elemt_out_typed_handle() { |
| 3601 | return c10::Dispatcher::singleton() |
| 3602 | .findSchemaOrThrow(batch_norm_elemt_out::name, batch_norm_elemt_out::overload_name) |
| 3603 | .typed<batch_norm_elemt_out::schema>(); |
| 3604 | } |
| 3605 | |
| 3606 | // aten::batch_norm_elemt.out(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps, *, Tensor(a!) out) -> Tensor(a!) |
| 3607 | at::Tensor & batch_norm_elemt_out::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps, at::Tensor & out) { |
| 3608 | |
| 3609 | static auto op = create_batch_norm_elemt_out_typed_handle(); |
| 3610 | return op.call(input, weight, bias, mean, invstd, eps, out); |
| 3611 | } |
| 3612 | |
| 3613 | // aten::batch_norm_elemt.out(Tensor input, Tensor? weight, Tensor? bias, Tensor mean, Tensor invstd, float eps, *, Tensor(a!) out) -> Tensor(a!) |
| 3614 | at::Tensor & batch_norm_elemt_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & mean, const at::Tensor & invstd, double eps, at::Tensor & out) { |
| 3615 | |
| 3616 | static auto op = create_batch_norm_elemt_out_typed_handle(); |
| 3617 | return op.redispatch(dispatchKeySet, input, weight, bias, mean, invstd, eps, out); |
| 3618 | } |
| 3619 | |
| 3620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cdist, name, "aten::cdist") |
| 3621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cdist, overload_name, "") |
| 3622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cdist, schema_str, "cdist(Tensor x1, Tensor x2, float p=2, int? compute_mode=None) -> Tensor") |
| 3623 | |
| 3624 | // aten::cdist(Tensor x1, Tensor x2, float p=2, int? compute_mode=None) -> Tensor |
| 3625 | static C10_NOINLINE c10::TypedOperatorHandle<cdist::schema> create_cdist_typed_handle() { |
| 3626 | return c10::Dispatcher::singleton() |
| 3627 | .findSchemaOrThrow(cdist::name, cdist::overload_name) |
| 3628 | .typed<cdist::schema>(); |
| 3629 | } |
| 3630 | |
| 3631 | // aten::cdist(Tensor x1, Tensor x2, float p=2, int? compute_mode=None) -> Tensor |
| 3632 | at::Tensor cdist::call(const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional<int64_t> compute_mode) { |
| 3633 | |
| 3634 | static auto op = create_cdist_typed_handle(); |
| 3635 | return op.call(x1, x2, p, compute_mode); |
| 3636 | } |
| 3637 | |
| 3638 | // aten::cdist(Tensor x1, Tensor x2, float p=2, int? compute_mode=None) -> Tensor |
| 3639 | at::Tensor cdist::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, double p, c10::optional<int64_t> compute_mode) { |
| 3640 | |
| 3641 | static auto op = create_cdist_typed_handle(); |
| 3642 | return op.redispatch(dispatchKeySet, x1, x2, p, compute_mode); |
| 3643 | } |
| 3644 | |
| 3645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mT, name, "aten::mT") |
| 3646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mT, overload_name, "") |
| 3647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mT, schema_str, "mT(Tensor(a) self) -> Tensor(a)") |
| 3648 | |
| 3649 | // aten::mT(Tensor(a) self) -> Tensor(a) |
| 3650 | static C10_NOINLINE c10::TypedOperatorHandle<mT::schema> create_mT_typed_handle() { |
| 3651 | return c10::Dispatcher::singleton() |
| 3652 | .findSchemaOrThrow(mT::name, mT::overload_name) |
| 3653 | .typed<mT::schema>(); |
| 3654 | } |
| 3655 | |
| 3656 | // aten::mT(Tensor(a) self) -> Tensor(a) |
| 3657 | at::Tensor mT::call(const at::Tensor & self) { |
| 3658 | |
| 3659 | static auto op = create_mT_typed_handle(); |
| 3660 | return op.call(self); |
| 3661 | } |
| 3662 | |
| 3663 | // aten::mT(Tensor(a) self) -> Tensor(a) |
| 3664 | at::Tensor mT::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3665 | |
| 3666 | static auto op = create_mT_typed_handle(); |
| 3667 | return op.redispatch(dispatchKeySet, self); |
| 3668 | } |
| 3669 | |
| 3670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(adjoint, name, "aten::adjoint") |
| 3671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(adjoint, overload_name, "") |
| 3672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(adjoint, schema_str, "adjoint(Tensor(a) self) -> Tensor(a)") |
| 3673 | |
| 3674 | // aten::adjoint(Tensor(a) self) -> Tensor(a) |
| 3675 | static C10_NOINLINE c10::TypedOperatorHandle<adjoint::schema> create_adjoint_typed_handle() { |
| 3676 | return c10::Dispatcher::singleton() |
| 3677 | .findSchemaOrThrow(adjoint::name, adjoint::overload_name) |
| 3678 | .typed<adjoint::schema>(); |
| 3679 | } |
| 3680 | |
| 3681 | // aten::adjoint(Tensor(a) self) -> Tensor(a) |
| 3682 | at::Tensor adjoint::call(const at::Tensor & self) { |
| 3683 | |
| 3684 | static auto op = create_adjoint_typed_handle(); |
| 3685 | return op.call(self); |
| 3686 | } |
| 3687 | |
| 3688 | // aten::adjoint(Tensor(a) self) -> Tensor(a) |
| 3689 | at::Tensor adjoint::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3690 | |
| 3691 | static auto op = create_adjoint_typed_handle(); |
| 3692 | return op.redispatch(dispatchKeySet, self); |
| 3693 | } |
| 3694 | |
| 3695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(channel_shuffle, name, "aten::channel_shuffle") |
| 3696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(channel_shuffle, overload_name, "") |
| 3697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(channel_shuffle, schema_str, "channel_shuffle(Tensor self, int groups) -> Tensor") |
| 3698 | |
| 3699 | // aten::channel_shuffle(Tensor self, int groups) -> Tensor |
| 3700 | static C10_NOINLINE c10::TypedOperatorHandle<channel_shuffle::schema> create_channel_shuffle_typed_handle() { |
| 3701 | return c10::Dispatcher::singleton() |
| 3702 | .findSchemaOrThrow(channel_shuffle::name, channel_shuffle::overload_name) |
| 3703 | .typed<channel_shuffle::schema>(); |
| 3704 | } |
| 3705 | |
| 3706 | // aten::channel_shuffle(Tensor self, int groups) -> Tensor |
| 3707 | at::Tensor channel_shuffle::call(const at::Tensor & self, int64_t groups) { |
| 3708 | |
| 3709 | static auto op = create_channel_shuffle_typed_handle(); |
| 3710 | return op.call(self, groups); |
| 3711 | } |
| 3712 | |
| 3713 | // aten::channel_shuffle(Tensor self, int groups) -> Tensor |
| 3714 | at::Tensor channel_shuffle::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t groups) { |
| 3715 | |
| 3716 | static auto op = create_channel_shuffle_typed_handle(); |
| 3717 | return op.redispatch(dispatchKeySet, self, groups); |
| 3718 | } |
| 3719 | |
| 3720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson_nll_loss, name, "aten::poisson_nll_loss") |
| 3721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson_nll_loss, overload_name, "") |
| 3722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson_nll_loss, schema_str, "poisson_nll_loss(Tensor input, Tensor target, bool log_input, bool full, float eps, int reduction) -> Tensor") |
| 3723 | |
| 3724 | // aten::poisson_nll_loss(Tensor input, Tensor target, bool log_input, bool full, float eps, int reduction) -> Tensor |
| 3725 | static C10_NOINLINE c10::TypedOperatorHandle<poisson_nll_loss::schema> create_poisson_nll_loss_typed_handle() { |
| 3726 | return c10::Dispatcher::singleton() |
| 3727 | .findSchemaOrThrow(poisson_nll_loss::name, poisson_nll_loss::overload_name) |
| 3728 | .typed<poisson_nll_loss::schema>(); |
| 3729 | } |
| 3730 | |
| 3731 | // aten::poisson_nll_loss(Tensor input, Tensor target, bool log_input, bool full, float eps, int reduction) -> Tensor |
| 3732 | at::Tensor poisson_nll_loss::call(const at::Tensor & input, const at::Tensor & target, bool log_input, bool full, double eps, int64_t reduction) { |
| 3733 | |
| 3734 | static auto op = create_poisson_nll_loss_typed_handle(); |
| 3735 | return op.call(input, target, log_input, full, eps, reduction); |
| 3736 | } |
| 3737 | |
| 3738 | // aten::poisson_nll_loss(Tensor input, Tensor target, bool log_input, bool full, float eps, int reduction) -> Tensor |
| 3739 | at::Tensor poisson_nll_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & target, bool log_input, bool full, double eps, int64_t reduction) { |
| 3740 | |
| 3741 | static auto op = create_poisson_nll_loss_typed_handle(); |
| 3742 | return op.redispatch(dispatchKeySet, input, target, log_input, full, eps, reduction); |
| 3743 | } |
| 3744 | |
| 3745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad, name, "aten::deg2rad") |
| 3746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad, overload_name, "") |
| 3747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad, schema_str, "deg2rad(Tensor self) -> Tensor") |
| 3748 | |
| 3749 | // aten::deg2rad(Tensor self) -> Tensor |
| 3750 | static C10_NOINLINE c10::TypedOperatorHandle<deg2rad::schema> create_deg2rad_typed_handle() { |
| 3751 | return c10::Dispatcher::singleton() |
| 3752 | .findSchemaOrThrow(deg2rad::name, deg2rad::overload_name) |
| 3753 | .typed<deg2rad::schema>(); |
| 3754 | } |
| 3755 | |
| 3756 | // aten::deg2rad(Tensor self) -> Tensor |
| 3757 | at::Tensor deg2rad::call(const at::Tensor & self) { |
| 3758 | |
| 3759 | static auto op = create_deg2rad_typed_handle(); |
| 3760 | return op.call(self); |
| 3761 | } |
| 3762 | |
| 3763 | // aten::deg2rad(Tensor self) -> Tensor |
| 3764 | at::Tensor deg2rad::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3765 | |
| 3766 | static auto op = create_deg2rad_typed_handle(); |
| 3767 | return op.redispatch(dispatchKeySet, self); |
| 3768 | } |
| 3769 | |
| 3770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad_, name, "aten::deg2rad_") |
| 3771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad_, overload_name, "") |
| 3772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad_, schema_str, "deg2rad_(Tensor(a!) self) -> Tensor(a!)") |
| 3773 | |
| 3774 | // aten::deg2rad_(Tensor(a!) self) -> Tensor(a!) |
| 3775 | static C10_NOINLINE c10::TypedOperatorHandle<deg2rad_::schema> create_deg2rad__typed_handle() { |
| 3776 | return c10::Dispatcher::singleton() |
| 3777 | .findSchemaOrThrow(deg2rad_::name, deg2rad_::overload_name) |
| 3778 | .typed<deg2rad_::schema>(); |
| 3779 | } |
| 3780 | |
| 3781 | // aten::deg2rad_(Tensor(a!) self) -> Tensor(a!) |
| 3782 | at::Tensor & deg2rad_::call(at::Tensor & self) { |
| 3783 | |
| 3784 | static auto op = create_deg2rad__typed_handle(); |
| 3785 | return op.call(self); |
| 3786 | } |
| 3787 | |
| 3788 | // aten::deg2rad_(Tensor(a!) self) -> Tensor(a!) |
| 3789 | at::Tensor & deg2rad_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 3790 | |
| 3791 | static auto op = create_deg2rad__typed_handle(); |
| 3792 | return op.redispatch(dispatchKeySet, self); |
| 3793 | } |
| 3794 | |
| 3795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad_out, name, "aten::deg2rad") |
| 3796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad_out, overload_name, "out") |
| 3797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(deg2rad_out, schema_str, "deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 3798 | |
| 3799 | // aten::deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3800 | static C10_NOINLINE c10::TypedOperatorHandle<deg2rad_out::schema> create_deg2rad_out_typed_handle() { |
| 3801 | return c10::Dispatcher::singleton() |
| 3802 | .findSchemaOrThrow(deg2rad_out::name, deg2rad_out::overload_name) |
| 3803 | .typed<deg2rad_out::schema>(); |
| 3804 | } |
| 3805 | |
| 3806 | // aten::deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3807 | at::Tensor & deg2rad_out::call(const at::Tensor & self, at::Tensor & out) { |
| 3808 | |
| 3809 | static auto op = create_deg2rad_out_typed_handle(); |
| 3810 | return op.call(self, out); |
| 3811 | } |
| 3812 | |
| 3813 | // aten::deg2rad.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3814 | at::Tensor & deg2rad_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 3815 | |
| 3816 | static auto op = create_deg2rad_out_typed_handle(); |
| 3817 | return op.redispatch(dispatchKeySet, self, out); |
| 3818 | } |
| 3819 | |
| 3820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm, name, "aten::randperm") |
| 3821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm, overload_name, "") |
| 3822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm, schema_str, "randperm(int n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 3823 | |
| 3824 | // aten::randperm(int n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3825 | static C10_NOINLINE c10::TypedOperatorHandle<randperm::schema> create_randperm_typed_handle() { |
| 3826 | return c10::Dispatcher::singleton() |
| 3827 | .findSchemaOrThrow(randperm::name, randperm::overload_name) |
| 3828 | .typed<randperm::schema>(); |
| 3829 | } |
| 3830 | |
| 3831 | // aten::randperm(int n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3832 | at::Tensor randperm::call(int64_t n, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 3833 | |
| 3834 | static auto op = create_randperm_typed_handle(); |
| 3835 | return op.call(n, dtype, layout, device, pin_memory); |
| 3836 | } |
| 3837 | |
| 3838 | // aten::randperm(int n, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3839 | at::Tensor randperm::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 3840 | |
| 3841 | static auto op = create_randperm_typed_handle(); |
| 3842 | return op.redispatch(dispatchKeySet, n, dtype, layout, device, pin_memory); |
| 3843 | } |
| 3844 | |
| 3845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_generator, name, "aten::randperm") |
| 3846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_generator, overload_name, "generator") |
| 3847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_generator, schema_str, "randperm.generator(int n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 3848 | |
| 3849 | // aten::randperm.generator(int n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3850 | static C10_NOINLINE c10::TypedOperatorHandle<randperm_generator::schema> create_randperm_generator_typed_handle() { |
| 3851 | return c10::Dispatcher::singleton() |
| 3852 | .findSchemaOrThrow(randperm_generator::name, randperm_generator::overload_name) |
| 3853 | .typed<randperm_generator::schema>(); |
| 3854 | } |
| 3855 | |
| 3856 | // aten::randperm.generator(int n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3857 | at::Tensor randperm_generator::call(int64_t n, 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) { |
| 3858 | |
| 3859 | static auto op = create_randperm_generator_typed_handle(); |
| 3860 | return op.call(n, generator, dtype, layout, device, pin_memory); |
| 3861 | } |
| 3862 | |
| 3863 | // aten::randperm.generator(int n, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 3864 | at::Tensor randperm_generator::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, 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) { |
| 3865 | |
| 3866 | static auto op = create_randperm_generator_typed_handle(); |
| 3867 | return op.redispatch(dispatchKeySet, n, generator, dtype, layout, device, pin_memory); |
| 3868 | } |
| 3869 | |
| 3870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_out, name, "aten::randperm") |
| 3871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_out, overload_name, "out") |
| 3872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_out, schema_str, "randperm.out(int n, *, Tensor(a!) out) -> Tensor(a!)") |
| 3873 | |
| 3874 | // aten::randperm.out(int n, *, Tensor(a!) out) -> Tensor(a!) |
| 3875 | static C10_NOINLINE c10::TypedOperatorHandle<randperm_out::schema> create_randperm_out_typed_handle() { |
| 3876 | return c10::Dispatcher::singleton() |
| 3877 | .findSchemaOrThrow(randperm_out::name, randperm_out::overload_name) |
| 3878 | .typed<randperm_out::schema>(); |
| 3879 | } |
| 3880 | |
| 3881 | // aten::randperm.out(int n, *, Tensor(a!) out) -> Tensor(a!) |
| 3882 | at::Tensor & randperm_out::call(int64_t n, at::Tensor & out) { |
| 3883 | |
| 3884 | static auto op = create_randperm_out_typed_handle(); |
| 3885 | return op.call(n, out); |
| 3886 | } |
| 3887 | |
| 3888 | // aten::randperm.out(int n, *, Tensor(a!) out) -> Tensor(a!) |
| 3889 | at::Tensor & randperm_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, at::Tensor & out) { |
| 3890 | |
| 3891 | static auto op = create_randperm_out_typed_handle(); |
| 3892 | return op.redispatch(dispatchKeySet, n, out); |
| 3893 | } |
| 3894 | |
| 3895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_generator_out, name, "aten::randperm") |
| 3896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_generator_out, overload_name, "generator_out") |
| 3897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randperm_generator_out, schema_str, "randperm.generator_out(int n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)") |
| 3898 | |
| 3899 | // aten::randperm.generator_out(int n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
| 3900 | static C10_NOINLINE c10::TypedOperatorHandle<randperm_generator_out::schema> create_randperm_generator_out_typed_handle() { |
| 3901 | return c10::Dispatcher::singleton() |
| 3902 | .findSchemaOrThrow(randperm_generator_out::name, randperm_generator_out::overload_name) |
| 3903 | .typed<randperm_generator_out::schema>(); |
| 3904 | } |
| 3905 | |
| 3906 | // aten::randperm.generator_out(int n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
| 3907 | at::Tensor & randperm_generator_out::call(int64_t n, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 3908 | |
| 3909 | static auto op = create_randperm_generator_out_typed_handle(); |
| 3910 | return op.call(n, generator, out); |
| 3911 | } |
| 3912 | |
| 3913 | // aten::randperm.generator_out(int n, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
| 3914 | at::Tensor & randperm_generator_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 3915 | |
| 3916 | static auto op = create_randperm_generator_out_typed_handle(); |
| 3917 | return op.redispatch(dispatchKeySet, n, generator, out); |
| 3918 | } |
| 3919 | |
| 3920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative, name, "aten::negative") |
| 3921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative, overload_name, "") |
| 3922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative, schema_str, "negative(Tensor self) -> Tensor") |
| 3923 | |
| 3924 | // aten::negative(Tensor self) -> Tensor |
| 3925 | static C10_NOINLINE c10::TypedOperatorHandle<negative::schema> create_negative_typed_handle() { |
| 3926 | return c10::Dispatcher::singleton() |
| 3927 | .findSchemaOrThrow(negative::name, negative::overload_name) |
| 3928 | .typed<negative::schema>(); |
| 3929 | } |
| 3930 | |
| 3931 | // aten::negative(Tensor self) -> Tensor |
| 3932 | at::Tensor negative::call(const at::Tensor & self) { |
| 3933 | |
| 3934 | static auto op = create_negative_typed_handle(); |
| 3935 | return op.call(self); |
| 3936 | } |
| 3937 | |
| 3938 | // aten::negative(Tensor self) -> Tensor |
| 3939 | at::Tensor negative::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 3940 | |
| 3941 | static auto op = create_negative_typed_handle(); |
| 3942 | return op.redispatch(dispatchKeySet, self); |
| 3943 | } |
| 3944 | |
| 3945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative_, name, "aten::negative_") |
| 3946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative_, overload_name, "") |
| 3947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative_, schema_str, "negative_(Tensor(a!) self) -> Tensor(a!)") |
| 3948 | |
| 3949 | // aten::negative_(Tensor(a!) self) -> Tensor(a!) |
| 3950 | static C10_NOINLINE c10::TypedOperatorHandle<negative_::schema> create_negative__typed_handle() { |
| 3951 | return c10::Dispatcher::singleton() |
| 3952 | .findSchemaOrThrow(negative_::name, negative_::overload_name) |
| 3953 | .typed<negative_::schema>(); |
| 3954 | } |
| 3955 | |
| 3956 | // aten::negative_(Tensor(a!) self) -> Tensor(a!) |
| 3957 | at::Tensor & negative_::call(at::Tensor & self) { |
| 3958 | |
| 3959 | static auto op = create_negative__typed_handle(); |
| 3960 | return op.call(self); |
| 3961 | } |
| 3962 | |
| 3963 | // aten::negative_(Tensor(a!) self) -> Tensor(a!) |
| 3964 | at::Tensor & negative_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 3965 | |
| 3966 | static auto op = create_negative__typed_handle(); |
| 3967 | return op.redispatch(dispatchKeySet, self); |
| 3968 | } |
| 3969 | |
| 3970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative_out, name, "aten::negative") |
| 3971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative_out, overload_name, "out") |
| 3972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(negative_out, schema_str, "negative.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 3973 | |
| 3974 | // aten::negative.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3975 | static C10_NOINLINE c10::TypedOperatorHandle<negative_out::schema> create_negative_out_typed_handle() { |
| 3976 | return c10::Dispatcher::singleton() |
| 3977 | .findSchemaOrThrow(negative_out::name, negative_out::overload_name) |
| 3978 | .typed<negative_out::schema>(); |
| 3979 | } |
| 3980 | |
| 3981 | // aten::negative.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3982 | at::Tensor & negative_out::call(const at::Tensor & self, at::Tensor & out) { |
| 3983 | |
| 3984 | static auto op = create_negative_out_typed_handle(); |
| 3985 | return op.call(self, out); |
| 3986 | } |
| 3987 | |
| 3988 | // aten::negative.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 3989 | at::Tensor & negative_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 3990 | |
| 3991 | static auto op = create_negative_out_typed_handle(); |
| 3992 | return op.redispatch(dispatchKeySet, self, out); |
| 3993 | } |
| 3994 | |
| 3995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_reshape_copy, name, "aten::_reshape_copy") |
| 3996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_reshape_copy, overload_name, "") |
| 3997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_reshape_copy, schema_str, "_reshape_copy(Tensor self, SymInt[] size) -> Tensor") |
| 3998 | |
| 3999 | // aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor |
| 4000 | static C10_NOINLINE c10::TypedOperatorHandle<_reshape_copy::schema> create__reshape_copy_typed_handle() { |
| 4001 | return c10::Dispatcher::singleton() |
| 4002 | .findSchemaOrThrow(_reshape_copy::name, _reshape_copy::overload_name) |
| 4003 | .typed<_reshape_copy::schema>(); |
| 4004 | } |
| 4005 | |
| 4006 | // aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor |
| 4007 | at::Tensor _reshape_copy::call(const at::Tensor & self, c10::SymIntArrayRef size) { |
| 4008 | |
| 4009 | static auto op = create__reshape_copy_typed_handle(); |
| 4010 | return op.call(self, size); |
| 4011 | } |
| 4012 | |
| 4013 | // aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor |
| 4014 | at::Tensor _reshape_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size) { |
| 4015 | |
| 4016 | static auto op = create__reshape_copy_typed_handle(); |
| 4017 | return op.redispatch(dispatchKeySet, self, size); |
| 4018 | } |
| 4019 | |
| 4020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu, name, "aten::relu") |
| 4021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu, overload_name, "") |
| 4022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu, schema_str, "relu(Tensor self) -> Tensor") |
| 4023 | |
| 4024 | // aten::relu(Tensor self) -> Tensor |
| 4025 | static C10_NOINLINE c10::TypedOperatorHandle<relu::schema> create_relu_typed_handle() { |
| 4026 | return c10::Dispatcher::singleton() |
| 4027 | .findSchemaOrThrow(relu::name, relu::overload_name) |
| 4028 | .typed<relu::schema>(); |
| 4029 | } |
| 4030 | |
| 4031 | // aten::relu(Tensor self) -> Tensor |
| 4032 | at::Tensor relu::call(const at::Tensor & self) { |
| 4033 | |
| 4034 | static auto op = create_relu_typed_handle(); |
| 4035 | return op.call(self); |
| 4036 | } |
| 4037 | |
| 4038 | // aten::relu(Tensor self) -> Tensor |
| 4039 | at::Tensor relu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 4040 | |
| 4041 | static auto op = create_relu_typed_handle(); |
| 4042 | return op.redispatch(dispatchKeySet, self); |
| 4043 | } |
| 4044 | |
| 4045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu_, name, "aten::relu_") |
| 4046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu_, overload_name, "") |
| 4047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu_, schema_str, "relu_(Tensor(a!) self) -> Tensor(a!)") |
| 4048 | |
| 4049 | // aten::relu_(Tensor(a!) self) -> Tensor(a!) |
| 4050 | static C10_NOINLINE c10::TypedOperatorHandle<relu_::schema> create_relu__typed_handle() { |
| 4051 | return c10::Dispatcher::singleton() |
| 4052 | .findSchemaOrThrow(relu_::name, relu_::overload_name) |
| 4053 | .typed<relu_::schema>(); |
| 4054 | } |
| 4055 | |
| 4056 | // aten::relu_(Tensor(a!) self) -> Tensor(a!) |
| 4057 | at::Tensor & relu_::call(at::Tensor & self) { |
| 4058 | |
| 4059 | static auto op = create_relu__typed_handle(); |
| 4060 | return op.call(self); |
| 4061 | } |
| 4062 | |
| 4063 | // aten::relu_(Tensor(a!) self) -> Tensor(a!) |
| 4064 | at::Tensor & relu_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 4065 | |
| 4066 | static auto op = create_relu__typed_handle(); |
| 4067 | return op.redispatch(dispatchKeySet, self); |
| 4068 | } |
| 4069 | |
| 4070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(infinitely_differentiable_gelu_backward, name, "aten::infinitely_differentiable_gelu_backward") |
| 4071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(infinitely_differentiable_gelu_backward, overload_name, "") |
| 4072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(infinitely_differentiable_gelu_backward, schema_str, "infinitely_differentiable_gelu_backward(Tensor grad, Tensor self) -> Tensor") |
| 4073 | |
| 4074 | // aten::infinitely_differentiable_gelu_backward(Tensor grad, Tensor self) -> Tensor |
| 4075 | static C10_NOINLINE c10::TypedOperatorHandle<infinitely_differentiable_gelu_backward::schema> create_infinitely_differentiable_gelu_backward_typed_handle() { |
| 4076 | return c10::Dispatcher::singleton() |
| 4077 | .findSchemaOrThrow(infinitely_differentiable_gelu_backward::name, infinitely_differentiable_gelu_backward::overload_name) |
| 4078 | .typed<infinitely_differentiable_gelu_backward::schema>(); |
| 4079 | } |
| 4080 | |
| 4081 | // aten::infinitely_differentiable_gelu_backward(Tensor grad, Tensor self) -> Tensor |
| 4082 | at::Tensor infinitely_differentiable_gelu_backward::call(const at::Tensor & grad, const at::Tensor & self) { |
| 4083 | |
| 4084 | static auto op = create_infinitely_differentiable_gelu_backward_typed_handle(); |
| 4085 | return op.call(grad, self); |
| 4086 | } |
| 4087 | |
| 4088 | // aten::infinitely_differentiable_gelu_backward(Tensor grad, Tensor self) -> Tensor |
| 4089 | at::Tensor infinitely_differentiable_gelu_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self) { |
| 4090 | |
| 4091 | static auto op = create_infinitely_differentiable_gelu_backward_typed_handle(); |
| 4092 | return op.redispatch(dispatchKeySet, grad, self); |
| 4093 | } |
| 4094 | |
| 4095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardshrink_backward_grad_input, name, "aten::hardshrink_backward") |
| 4096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardshrink_backward_grad_input, overload_name, "grad_input") |
| 4097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardshrink_backward_grad_input, schema_str, "hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 4098 | |
| 4099 | // aten::hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 4100 | static C10_NOINLINE c10::TypedOperatorHandle<hardshrink_backward_grad_input::schema> create_hardshrink_backward_grad_input_typed_handle() { |
| 4101 | return c10::Dispatcher::singleton() |
| 4102 | .findSchemaOrThrow(hardshrink_backward_grad_input::name, hardshrink_backward_grad_input::overload_name) |
| 4103 | .typed<hardshrink_backward_grad_input::schema>(); |
| 4104 | } |
| 4105 | |
| 4106 | // aten::hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 4107 | at::Tensor & hardshrink_backward_grad_input::call(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input) { |
| 4108 | |
| 4109 | static auto op = create_hardshrink_backward_grad_input_typed_handle(); |
| 4110 | return op.call(grad_out, self, lambd, grad_input); |
| 4111 | } |
| 4112 | |
| 4113 | // aten::hardshrink_backward.grad_input(Tensor grad_out, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 4114 | at::Tensor & hardshrink_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input) { |
| 4115 | |
| 4116 | static auto op = create_hardshrink_backward_grad_input_typed_handle(); |
| 4117 | return op.redispatch(dispatchKeySet, grad_out, self, lambd, grad_input); |
| 4118 | } |
| 4119 | |
| 4120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardshrink_backward, name, "aten::hardshrink_backward") |
| 4121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardshrink_backward, overload_name, "") |
| 4122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardshrink_backward, schema_str, "hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor") |
| 4123 | |
| 4124 | // aten::hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor |
| 4125 | static C10_NOINLINE c10::TypedOperatorHandle<hardshrink_backward::schema> create_hardshrink_backward_typed_handle() { |
| 4126 | return c10::Dispatcher::singleton() |
| 4127 | .findSchemaOrThrow(hardshrink_backward::name, hardshrink_backward::overload_name) |
| 4128 | .typed<hardshrink_backward::schema>(); |
| 4129 | } |
| 4130 | |
| 4131 | // aten::hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor |
| 4132 | at::Tensor hardshrink_backward::call(const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd) { |
| 4133 | |
| 4134 | static auto op = create_hardshrink_backward_typed_handle(); |
| 4135 | return op.call(grad_out, self, lambd); |
| 4136 | } |
| 4137 | |
| 4138 | // aten::hardshrink_backward(Tensor grad_out, Tensor self, Scalar lambd) -> Tensor |
| 4139 | at::Tensor hardshrink_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & self, const at::Scalar & lambd) { |
| 4140 | |
| 4141 | static auto op = create_hardshrink_backward_typed_handle(); |
| 4142 | return op.redispatch(dispatchKeySet, grad_out, self, lambd); |
| 4143 | } |
| 4144 | |
| 4145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc, name, "aten::sinc") |
| 4146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc, overload_name, "") |
| 4147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc, schema_str, "sinc(Tensor self) -> Tensor") |
| 4148 | |
| 4149 | // aten::sinc(Tensor self) -> Tensor |
| 4150 | static C10_NOINLINE c10::TypedOperatorHandle<sinc::schema> create_sinc_typed_handle() { |
| 4151 | return c10::Dispatcher::singleton() |
| 4152 | .findSchemaOrThrow(sinc::name, sinc::overload_name) |
| 4153 | .typed<sinc::schema>(); |
| 4154 | } |
| 4155 | |
| 4156 | // aten::sinc(Tensor self) -> Tensor |
| 4157 | at::Tensor sinc::call(const at::Tensor & self) { |
| 4158 | |
| 4159 | static auto op = create_sinc_typed_handle(); |
| 4160 | return op.call(self); |
| 4161 | } |
| 4162 | |
| 4163 | // aten::sinc(Tensor self) -> Tensor |
| 4164 | at::Tensor sinc::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 4165 | |
| 4166 | static auto op = create_sinc_typed_handle(); |
| 4167 | return op.redispatch(dispatchKeySet, self); |
| 4168 | } |
| 4169 | |
| 4170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc_, name, "aten::sinc_") |
| 4171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc_, overload_name, "") |
| 4172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc_, schema_str, "sinc_(Tensor(a!) self) -> Tensor(a!)") |
| 4173 | |
| 4174 | // aten::sinc_(Tensor(a!) self) -> Tensor(a!) |
| 4175 | static C10_NOINLINE c10::TypedOperatorHandle<sinc_::schema> create_sinc__typed_handle() { |
| 4176 | return c10::Dispatcher::singleton() |
| 4177 | .findSchemaOrThrow(sinc_::name, sinc_::overload_name) |
| 4178 | .typed<sinc_::schema>(); |
| 4179 | } |
| 4180 | |
| 4181 | // aten::sinc_(Tensor(a!) self) -> Tensor(a!) |
| 4182 | at::Tensor & sinc_::call(at::Tensor & self) { |
| 4183 | |
| 4184 | static auto op = create_sinc__typed_handle(); |
| 4185 | return op.call(self); |
| 4186 | } |
| 4187 | |
| 4188 | // aten::sinc_(Tensor(a!) self) -> Tensor(a!) |
| 4189 | at::Tensor & sinc_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 4190 | |
| 4191 | static auto op = create_sinc__typed_handle(); |
| 4192 | return op.redispatch(dispatchKeySet, self); |
| 4193 | } |
| 4194 | |
| 4195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc_out, name, "aten::sinc") |
| 4196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc_out, overload_name, "out") |
| 4197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sinc_out, schema_str, "sinc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 4198 | |
| 4199 | // aten::sinc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 4200 | static C10_NOINLINE c10::TypedOperatorHandle<sinc_out::schema> create_sinc_out_typed_handle() { |
| 4201 | return c10::Dispatcher::singleton() |
| 4202 | .findSchemaOrThrow(sinc_out::name, sinc_out::overload_name) |
| 4203 | .typed<sinc_out::schema>(); |
| 4204 | } |
| 4205 | |
| 4206 | // aten::sinc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 4207 | at::Tensor & sinc_out::call(const at::Tensor & self, at::Tensor & out) { |
| 4208 | |
| 4209 | static auto op = create_sinc_out_typed_handle(); |
| 4210 | return op.call(self, out); |
| 4211 | } |
| 4212 | |
| 4213 | // aten::sinc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 4214 | at::Tensor & sinc_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 4215 | |
| 4216 | static auto op = create_sinc_out_typed_handle(); |
| 4217 | return op.redispatch(dispatchKeySet, self, out); |
| 4218 | } |
| 4219 | |
| 4220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_Tensor, name, "aten::slice") |
| 4221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_Tensor, overload_name, "Tensor") |
| 4222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_Tensor, schema_str, "slice.Tensor(Tensor(a) self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor(a)") |
| 4223 | |
| 4224 | // aten::slice.Tensor(Tensor(a) self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor(a) |
| 4225 | static C10_NOINLINE c10::TypedOperatorHandle<slice_Tensor::schema> create_slice_Tensor_typed_handle() { |
| 4226 | return c10::Dispatcher::singleton() |
| 4227 | .findSchemaOrThrow(slice_Tensor::name, slice_Tensor::overload_name) |
| 4228 | .typed<slice_Tensor::schema>(); |
| 4229 | } |
| 4230 | |
| 4231 | // aten::slice.Tensor(Tensor(a) self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor(a) |
| 4232 | at::Tensor slice_Tensor::call(const at::Tensor & self, int64_t dim, c10::optional<c10::SymInt> start, c10::optional<c10::SymInt> end, c10::SymInt step) { |
| 4233 | |
| 4234 | static auto op = create_slice_Tensor_typed_handle(); |
| 4235 | return op.call(self, dim, start, end, step); |
| 4236 | } |
| 4237 | |
| 4238 | // aten::slice.Tensor(Tensor(a) self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor(a) |
| 4239 | at::Tensor slice_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<c10::SymInt> start, c10::optional<c10::SymInt> end, c10::SymInt step) { |
| 4240 | |
| 4241 | static auto op = create_slice_Tensor_typed_handle(); |
| 4242 | return op.redispatch(dispatchKeySet, self, dim, start, end, step); |
| 4243 | } |
| 4244 | |
| 4245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_scatter, name, "aten::select_scatter") |
| 4246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_scatter, overload_name, "") |
| 4247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_scatter, schema_str, "select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor") |
| 4248 | |
| 4249 | // aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor |
| 4250 | static C10_NOINLINE c10::TypedOperatorHandle<select_scatter::schema> create_select_scatter_typed_handle() { |
| 4251 | return c10::Dispatcher::singleton() |
| 4252 | .findSchemaOrThrow(select_scatter::name, select_scatter::overload_name) |
| 4253 | .typed<select_scatter::schema>(); |
| 4254 | } |
| 4255 | |
| 4256 | // aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor |
| 4257 | at::Tensor select_scatter::call(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index) { |
| 4258 | |
| 4259 | static auto op = create_select_scatter_typed_handle(); |
| 4260 | return op.call(self, src, dim, index); |
| 4261 | } |
| 4262 | |
| 4263 | // aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor |
| 4264 | at::Tensor select_scatter::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index) { |
| 4265 | |
| 4266 | static auto op = create_select_scatter_typed_handle(); |
| 4267 | return op.redispatch(dispatchKeySet, self, src, dim, index); |
| 4268 | } |
| 4269 | |
| 4270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smm, name, "aten::smm") |
| 4271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smm, overload_name, "") |
| 4272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smm, schema_str, "smm(Tensor self, Tensor mat2) -> Tensor") |
| 4273 | |
| 4274 | // aten::smm(Tensor self, Tensor mat2) -> Tensor |
| 4275 | static C10_NOINLINE c10::TypedOperatorHandle<smm::schema> create_smm_typed_handle() { |
| 4276 | return c10::Dispatcher::singleton() |
| 4277 | .findSchemaOrThrow(smm::name, smm::overload_name) |
| 4278 | .typed<smm::schema>(); |
| 4279 | } |
| 4280 | |
| 4281 | // aten::smm(Tensor self, Tensor mat2) -> Tensor |
| 4282 | at::Tensor smm::call(const at::Tensor & self, const at::Tensor & mat2) { |
| 4283 | |
| 4284 | static auto op = create_smm_typed_handle(); |
| 4285 | return op.call(self, mat2); |
| 4286 | } |
| 4287 | |
| 4288 | // aten::smm(Tensor self, Tensor mat2) -> Tensor |
| 4289 | at::Tensor smm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat2) { |
| 4290 | |
| 4291 | static auto op = create_smm_typed_handle(); |
| 4292 | return op.redispatch(dispatchKeySet, self, mat2); |
| 4293 | } |
| 4294 | |
| 4295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_split_with_sizes, name, "aten::unsafe_split_with_sizes") |
| 4296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_split_with_sizes, overload_name, "") |
| 4297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_split_with_sizes, schema_str, "unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]") |
| 4298 | |
| 4299 | // aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] |
| 4300 | static C10_NOINLINE c10::TypedOperatorHandle<unsafe_split_with_sizes::schema> create_unsafe_split_with_sizes_typed_handle() { |
| 4301 | return c10::Dispatcher::singleton() |
| 4302 | .findSchemaOrThrow(unsafe_split_with_sizes::name, unsafe_split_with_sizes::overload_name) |
| 4303 | .typed<unsafe_split_with_sizes::schema>(); |
| 4304 | } |
| 4305 | |
| 4306 | // aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] |
| 4307 | ::std::vector<at::Tensor> unsafe_split_with_sizes::call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim) { |
| 4308 | |
| 4309 | static auto op = create_unsafe_split_with_sizes_typed_handle(); |
| 4310 | return op.call(self, split_sizes, dim); |
| 4311 | } |
| 4312 | |
| 4313 | // aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] |
| 4314 | ::std::vector<at::Tensor> unsafe_split_with_sizes::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim) { |
| 4315 | |
| 4316 | static auto op = create_unsafe_split_with_sizes_typed_handle(); |
| 4317 | return op.redispatch(dispatchKeySet, self, split_sizes, dim); |
| 4318 | } |
| 4319 | |
| 4320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dstack, name, "aten::dstack") |
| 4321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dstack, overload_name, "") |
| 4322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dstack, schema_str, "dstack(Tensor[] tensors) -> Tensor") |
| 4323 | |
| 4324 | // aten::dstack(Tensor[] tensors) -> Tensor |
| 4325 | static C10_NOINLINE c10::TypedOperatorHandle<dstack::schema> create_dstack_typed_handle() { |
| 4326 | return c10::Dispatcher::singleton() |
| 4327 | .findSchemaOrThrow(dstack::name, dstack::overload_name) |
| 4328 | .typed<dstack::schema>(); |
| 4329 | } |
| 4330 | |
| 4331 | // aten::dstack(Tensor[] tensors) -> Tensor |
| 4332 | at::Tensor dstack::call(at::TensorList tensors) { |
| 4333 | |
| 4334 | static auto op = create_dstack_typed_handle(); |
| 4335 | return op.call(tensors); |
| 4336 | } |
| 4337 | |
| 4338 | // aten::dstack(Tensor[] tensors) -> Tensor |
| 4339 | at::Tensor dstack::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
| 4340 | |
| 4341 | static auto op = create_dstack_typed_handle(); |
| 4342 | return op.redispatch(dispatchKeySet, tensors); |
| 4343 | } |
| 4344 | |
| 4345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dstack_out, name, "aten::dstack") |
| 4346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dstack_out, overload_name, "out") |
| 4347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dstack_out, schema_str, "dstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)") |
| 4348 | |
| 4349 | // aten::dstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 4350 | static C10_NOINLINE c10::TypedOperatorHandle<dstack_out::schema> create_dstack_out_typed_handle() { |
| 4351 | return c10::Dispatcher::singleton() |
| 4352 | .findSchemaOrThrow(dstack_out::name, dstack_out::overload_name) |
| 4353 | .typed<dstack_out::schema>(); |
| 4354 | } |
| 4355 | |
| 4356 | // aten::dstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 4357 | at::Tensor & dstack_out::call(at::TensorList tensors, at::Tensor & out) { |
| 4358 | |
| 4359 | static auto op = create_dstack_out_typed_handle(); |
| 4360 | return op.call(tensors, out); |
| 4361 | } |
| 4362 | |
| 4363 | // aten::dstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
| 4364 | at::Tensor & dstack_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out) { |
| 4365 | |
| 4366 | static auto op = create_dstack_out_typed_handle(); |
| 4367 | return op.redispatch(dispatchKeySet, tensors, out); |
| 4368 | } |
| 4369 | |
| 4370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod, name, "aten::prod") |
| 4371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod, overload_name, "") |
| 4372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod, schema_str, "prod(Tensor self, *, ScalarType? dtype=None) -> Tensor") |
| 4373 | |
| 4374 | // aten::prod(Tensor self, *, ScalarType? dtype=None) -> Tensor |
| 4375 | static C10_NOINLINE c10::TypedOperatorHandle<prod::schema> create_prod_typed_handle() { |
| 4376 | return c10::Dispatcher::singleton() |
| 4377 | .findSchemaOrThrow(prod::name, prod::overload_name) |
| 4378 | .typed<prod::schema>(); |
| 4379 | } |
| 4380 | |
| 4381 | // aten::prod(Tensor self, *, ScalarType? dtype=None) -> Tensor |
| 4382 | at::Tensor prod::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
| 4383 | |
| 4384 | static auto op = create_prod_typed_handle(); |
| 4385 | return op.call(self, dtype); |
| 4386 | } |
| 4387 | |
| 4388 | // aten::prod(Tensor self, *, ScalarType? dtype=None) -> Tensor |
| 4389 | at::Tensor prod::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
| 4390 | |
| 4391 | static auto op = create_prod_typed_handle(); |
| 4392 | return op.redispatch(dispatchKeySet, self, dtype); |
| 4393 | } |
| 4394 | |
| 4395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_dim_int, name, "aten::prod") |
| 4396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_dim_int, overload_name, "dim_int") |
| 4397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_dim_int, schema_str, "prod.dim_int(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor") |
| 4398 | |
| 4399 | // aten::prod.dim_int(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 4400 | static C10_NOINLINE c10::TypedOperatorHandle<prod_dim_int::schema> create_prod_dim_int_typed_handle() { |
| 4401 | return c10::Dispatcher::singleton() |
| 4402 | .findSchemaOrThrow(prod_dim_int::name, prod_dim_int::overload_name) |
| 4403 | .typed<prod_dim_int::schema>(); |
| 4404 | } |
| 4405 | |
| 4406 | // aten::prod.dim_int(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 4407 | at::Tensor prod_dim_int::call(const at::Tensor & self, int64_t dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 4408 | |
| 4409 | static auto op = create_prod_dim_int_typed_handle(); |
| 4410 | return op.call(self, dim, keepdim, dtype); |
| 4411 | } |
| 4412 | |
| 4413 | // aten::prod.dim_int(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 4414 | at::Tensor prod_dim_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 4415 | |
| 4416 | static auto op = create_prod_dim_int_typed_handle(); |
| 4417 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype); |
| 4418 | } |
| 4419 | |
| 4420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_int_out, name, "aten::prod") |
| 4421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_int_out, overload_name, "int_out") |
| 4422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_int_out, schema_str, "prod.int_out(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") |
| 4423 | |
| 4424 | // aten::prod.int_out(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 4425 | static C10_NOINLINE c10::TypedOperatorHandle<prod_int_out::schema> create_prod_int_out_typed_handle() { |
| 4426 | return c10::Dispatcher::singleton() |
| 4427 | .findSchemaOrThrow(prod_int_out::name, prod_int_out::overload_name) |
| 4428 | .typed<prod_int_out::schema>(); |
| 4429 | } |
| 4430 | |
| 4431 | // aten::prod.int_out(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 4432 | at::Tensor & prod_int_out::call(const at::Tensor & self, int64_t dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 4433 | |
| 4434 | static auto op = create_prod_int_out_typed_handle(); |
| 4435 | return op.call(self, dim, keepdim, dtype, out); |
| 4436 | } |
| 4437 | |
| 4438 | // aten::prod.int_out(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 4439 | at::Tensor & prod_int_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 4440 | |
| 4441 | static auto op = create_prod_int_out_typed_handle(); |
| 4442 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype, out); |
| 4443 | } |
| 4444 | |
| 4445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_dim_Dimname, name, "aten::prod") |
| 4446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_dim_Dimname, overload_name, "dim_Dimname") |
| 4447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_dim_Dimname, schema_str, "prod.dim_Dimname(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor") |
| 4448 | |
| 4449 | // aten::prod.dim_Dimname(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 4450 | static C10_NOINLINE c10::TypedOperatorHandle<prod_dim_Dimname::schema> create_prod_dim_Dimname_typed_handle() { |
| 4451 | return c10::Dispatcher::singleton() |
| 4452 | .findSchemaOrThrow(prod_dim_Dimname::name, prod_dim_Dimname::overload_name) |
| 4453 | .typed<prod_dim_Dimname::schema>(); |
| 4454 | } |
| 4455 | |
| 4456 | // aten::prod.dim_Dimname(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 4457 | at::Tensor prod_dim_Dimname::call(const at::Tensor & self, at::Dimname dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 4458 | |
| 4459 | static auto op = create_prod_dim_Dimname_typed_handle(); |
| 4460 | return op.call(self, dim, keepdim, dtype); |
| 4461 | } |
| 4462 | |
| 4463 | // aten::prod.dim_Dimname(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
| 4464 | at::Tensor prod_dim_Dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
| 4465 | |
| 4466 | static auto op = create_prod_dim_Dimname_typed_handle(); |
| 4467 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype); |
| 4468 | } |
| 4469 | |
| 4470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_Dimname_out, name, "aten::prod") |
| 4471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_Dimname_out, overload_name, "Dimname_out") |
| 4472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_Dimname_out, schema_str, "prod.Dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") |
| 4473 | |
| 4474 | // aten::prod.Dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 4475 | static C10_NOINLINE c10::TypedOperatorHandle<prod_Dimname_out::schema> create_prod_Dimname_out_typed_handle() { |
| 4476 | return c10::Dispatcher::singleton() |
| 4477 | .findSchemaOrThrow(prod_Dimname_out::name, prod_Dimname_out::overload_name) |
| 4478 | .typed<prod_Dimname_out::schema>(); |
| 4479 | } |
| 4480 | |
| 4481 | // aten::prod.Dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 4482 | at::Tensor & prod_Dimname_out::call(const at::Tensor & self, at::Dimname dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 4483 | |
| 4484 | static auto op = create_prod_Dimname_out_typed_handle(); |
| 4485 | return op.call(self, dim, keepdim, dtype, out); |
| 4486 | } |
| 4487 | |
| 4488 | // aten::prod.Dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 4489 | at::Tensor & prod_Dimname_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 4490 | |
| 4491 | static auto op = create_prod_Dimname_out_typed_handle(); |
| 4492 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype, out); |
| 4493 | } |
| 4494 | |
| 4495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan, name, "aten::tan") |
| 4496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan, overload_name, "") |
| 4497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan, schema_str, "tan(Tensor self) -> Tensor") |
| 4498 | |
| 4499 | // aten::tan(Tensor self) -> Tensor |
| 4500 | static C10_NOINLINE c10::TypedOperatorHandle<tan::schema> create_tan_typed_handle() { |
| 4501 | return c10::Dispatcher::singleton() |
| 4502 | .findSchemaOrThrow(tan::name, tan::overload_name) |
| 4503 | .typed<tan::schema>(); |
| 4504 | } |
| 4505 | |
| 4506 | // aten::tan(Tensor self) -> Tensor |
| 4507 | at::Tensor tan::call(const at::Tensor & self) { |
| 4508 | |
| 4509 | static auto op = create_tan_typed_handle(); |
| 4510 | return op.call(self); |
| 4511 | } |
| 4512 | |
| 4513 | // aten::tan(Tensor self) -> Tensor |
| 4514 | at::Tensor tan::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 4515 | |
| 4516 | static auto op = create_tan_typed_handle(); |
| 4517 | return op.redispatch(dispatchKeySet, self); |
| 4518 | } |
| 4519 | |
| 4520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan_, name, "aten::tan_") |
| 4521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan_, overload_name, "") |
| 4522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan_, schema_str, "tan_(Tensor(a!) self) -> Tensor(a!)") |
| 4523 | |
| 4524 | // aten::tan_(Tensor(a!) self) -> Tensor(a!) |
| 4525 | static C10_NOINLINE c10::TypedOperatorHandle<tan_::schema> create_tan__typed_handle() { |
| 4526 | return c10::Dispatcher::singleton() |
| 4527 | .findSchemaOrThrow(tan_::name, tan_::overload_name) |
| 4528 | .typed<tan_::schema>(); |
| 4529 | } |
| 4530 | |
| 4531 | // aten::tan_(Tensor(a!) self) -> Tensor(a!) |
| 4532 | at::Tensor & tan_::call(at::Tensor & self) { |
| 4533 | |
| 4534 | static auto op = create_tan__typed_handle(); |
| 4535 | return op.call(self); |
| 4536 | } |
| 4537 | |
| 4538 | // aten::tan_(Tensor(a!) self) -> Tensor(a!) |
| 4539 | at::Tensor & tan_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 4540 | |
| 4541 | static auto op = create_tan__typed_handle(); |
| 4542 | return op.redispatch(dispatchKeySet, self); |
| 4543 | } |
| 4544 | |
| 4545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan_out, name, "aten::tan") |
| 4546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan_out, overload_name, "out") |
| 4547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tan_out, schema_str, "tan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 4548 | |
| 4549 | // aten::tan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 4550 | static C10_NOINLINE c10::TypedOperatorHandle<tan_out::schema> create_tan_out_typed_handle() { |
| 4551 | return c10::Dispatcher::singleton() |
| 4552 | .findSchemaOrThrow(tan_out::name, tan_out::overload_name) |
| 4553 | .typed<tan_out::schema>(); |
| 4554 | } |
| 4555 | |
| 4556 | // aten::tan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 4557 | at::Tensor & tan_out::call(const at::Tensor & self, at::Tensor & out) { |
| 4558 | |
| 4559 | static auto op = create_tan_out_typed_handle(); |
| 4560 | return op.call(self, out); |
| 4561 | } |
| 4562 | |
| 4563 | // aten::tan.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 4564 | at::Tensor & tan_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 4565 | |
| 4566 | static auto op = create_tan_out_typed_handle(); |
| 4567 | return op.redispatch(dispatchKeySet, self, out); |
| 4568 | } |
| 4569 | |
| 4570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapezoid_x, name, "aten::trapezoid") |
| 4571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapezoid_x, overload_name, "x") |
| 4572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapezoid_x, schema_str, "trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor") |
| 4573 | |
| 4574 | // aten::trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor |
| 4575 | static C10_NOINLINE c10::TypedOperatorHandle<trapezoid_x::schema> create_trapezoid_x_typed_handle() { |
| 4576 | return c10::Dispatcher::singleton() |
| 4577 | .findSchemaOrThrow(trapezoid_x::name, trapezoid_x::overload_name) |
| 4578 | .typed<trapezoid_x::schema>(); |
| 4579 | } |
| 4580 | |
| 4581 | // aten::trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor |
| 4582 | at::Tensor trapezoid_x::call(const at::Tensor & y, const at::Tensor & x, int64_t dim) { |
| 4583 | |
| 4584 | static auto op = create_trapezoid_x_typed_handle(); |
| 4585 | return op.call(y, x, dim); |
| 4586 | } |
| 4587 | |
| 4588 | // aten::trapezoid.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor |
| 4589 | at::Tensor trapezoid_x::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Tensor & x, int64_t dim) { |
| 4590 | |
| 4591 | static auto op = create_trapezoid_x_typed_handle(); |
| 4592 | return op.redispatch(dispatchKeySet, y, x, dim); |
| 4593 | } |
| 4594 | |
| 4595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapezoid_dx, name, "aten::trapezoid") |
| 4596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapezoid_dx, overload_name, "dx") |
| 4597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapezoid_dx, schema_str, "trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor") |
| 4598 | |
| 4599 | // aten::trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor |
| 4600 | static C10_NOINLINE c10::TypedOperatorHandle<trapezoid_dx::schema> create_trapezoid_dx_typed_handle() { |
| 4601 | return c10::Dispatcher::singleton() |
| 4602 | .findSchemaOrThrow(trapezoid_dx::name, trapezoid_dx::overload_name) |
| 4603 | .typed<trapezoid_dx::schema>(); |
| 4604 | } |
| 4605 | |
| 4606 | // aten::trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor |
| 4607 | at::Tensor trapezoid_dx::call(const at::Tensor & y, const at::Scalar & dx, int64_t dim) { |
| 4608 | |
| 4609 | static auto op = create_trapezoid_dx_typed_handle(); |
| 4610 | return op.call(y, dx, dim); |
| 4611 | } |
| 4612 | |
| 4613 | // aten::trapezoid.dx(Tensor y, *, Scalar dx=1, int dim=-1) -> Tensor |
| 4614 | at::Tensor trapezoid_dx::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Scalar & dx, int64_t dim) { |
| 4615 | |
| 4616 | static auto op = create_trapezoid_dx_typed_handle(); |
| 4617 | return op.redispatch(dispatchKeySet, y, dx, dim); |
| 4618 | } |
| 4619 | |
| 4620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask, name, "aten::_nested_tensor_from_mask") |
| 4621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask, overload_name, "") |
| 4622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask, schema_str, "_nested_tensor_from_mask(Tensor t, Tensor mask, bool mask_check=True) -> Tensor") |
| 4623 | |
| 4624 | // aten::_nested_tensor_from_mask(Tensor t, Tensor mask, bool mask_check=True) -> Tensor |
| 4625 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_from_mask::schema> create__nested_tensor_from_mask_typed_handle() { |
| 4626 | return c10::Dispatcher::singleton() |
| 4627 | .findSchemaOrThrow(_nested_tensor_from_mask::name, _nested_tensor_from_mask::overload_name) |
| 4628 | .typed<_nested_tensor_from_mask::schema>(); |
| 4629 | } |
| 4630 | |
| 4631 | // aten::_nested_tensor_from_mask(Tensor t, Tensor mask, bool mask_check=True) -> Tensor |
| 4632 | at::Tensor _nested_tensor_from_mask::call(const at::Tensor & t, const at::Tensor & mask, bool mask_check) { |
| 4633 | |
| 4634 | static auto op = create__nested_tensor_from_mask_typed_handle(); |
| 4635 | return op.call(t, mask, mask_check); |
| 4636 | } |
| 4637 | |
| 4638 | // aten::_nested_tensor_from_mask(Tensor t, Tensor mask, bool mask_check=True) -> Tensor |
| 4639 | at::Tensor _nested_tensor_from_mask::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & t, const at::Tensor & mask, bool mask_check) { |
| 4640 | |
| 4641 | static auto op = create__nested_tensor_from_mask_typed_handle(); |
| 4642 | return op.redispatch(dispatchKeySet, t, mask, mask_check); |
| 4643 | } |
| 4644 | |
| 4645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask_left_aligned, name, "aten::_nested_tensor_from_mask_left_aligned") |
| 4646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask_left_aligned, overload_name, "") |
| 4647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask_left_aligned, schema_str, "_nested_tensor_from_mask_left_aligned(Tensor t, Tensor mask) -> bool") |
| 4648 | |
| 4649 | // aten::_nested_tensor_from_mask_left_aligned(Tensor t, Tensor mask) -> bool |
| 4650 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_from_mask_left_aligned::schema> create__nested_tensor_from_mask_left_aligned_typed_handle() { |
| 4651 | return c10::Dispatcher::singleton() |
| 4652 | .findSchemaOrThrow(_nested_tensor_from_mask_left_aligned::name, _nested_tensor_from_mask_left_aligned::overload_name) |
| 4653 | .typed<_nested_tensor_from_mask_left_aligned::schema>(); |
| 4654 | } |
| 4655 | |
| 4656 | // aten::_nested_tensor_from_mask_left_aligned(Tensor t, Tensor mask) -> bool |
| 4657 | bool _nested_tensor_from_mask_left_aligned::call(const at::Tensor & t, const at::Tensor & mask) { |
| 4658 | |
| 4659 | static auto op = create__nested_tensor_from_mask_left_aligned_typed_handle(); |
| 4660 | return op.call(t, mask); |
| 4661 | } |
| 4662 | |
| 4663 | // aten::_nested_tensor_from_mask_left_aligned(Tensor t, Tensor mask) -> bool |
| 4664 | bool _nested_tensor_from_mask_left_aligned::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & t, const at::Tensor & mask) { |
| 4665 | |
| 4666 | static auto op = create__nested_tensor_from_mask_left_aligned_typed_handle(); |
| 4667 | return op.redispatch(dispatchKeySet, t, mask); |
| 4668 | } |
| 4669 | |
| 4670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_size, name, "aten::_nested_tensor_size") |
| 4671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_size, overload_name, "") |
| 4672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_size, schema_str, "_nested_tensor_size(Tensor self) -> Tensor") |
| 4673 | |
| 4674 | // aten::_nested_tensor_size(Tensor self) -> Tensor |
| 4675 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_size::schema> create__nested_tensor_size_typed_handle() { |
| 4676 | return c10::Dispatcher::singleton() |
| 4677 | .findSchemaOrThrow(_nested_tensor_size::name, _nested_tensor_size::overload_name) |
| 4678 | .typed<_nested_tensor_size::schema>(); |
| 4679 | } |
| 4680 | |
| 4681 | // aten::_nested_tensor_size(Tensor self) -> Tensor |
| 4682 | at::Tensor _nested_tensor_size::call(const at::Tensor & self) { |
| 4683 | |
| 4684 | static auto op = create__nested_tensor_size_typed_handle(); |
| 4685 | return op.call(self); |
| 4686 | } |
| 4687 | |
| 4688 | // aten::_nested_tensor_size(Tensor self) -> Tensor |
| 4689 | at::Tensor _nested_tensor_size::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 4690 | |
| 4691 | static auto op = create__nested_tensor_size_typed_handle(); |
| 4692 | return op.redispatch(dispatchKeySet, self); |
| 4693 | } |
| 4694 | |
| 4695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_view_from_buffer_copy, name, "aten::_nested_view_from_buffer_copy") |
| 4696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_view_from_buffer_copy, overload_name, "") |
| 4697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_view_from_buffer_copy, schema_str, "_nested_view_from_buffer_copy(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets) -> Tensor") |
| 4698 | |
| 4699 | // aten::_nested_view_from_buffer_copy(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets) -> Tensor |
| 4700 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_view_from_buffer_copy::schema> create__nested_view_from_buffer_copy_typed_handle() { |
| 4701 | return c10::Dispatcher::singleton() |
| 4702 | .findSchemaOrThrow(_nested_view_from_buffer_copy::name, _nested_view_from_buffer_copy::overload_name) |
| 4703 | .typed<_nested_view_from_buffer_copy::schema>(); |
| 4704 | } |
| 4705 | |
| 4706 | // aten::_nested_view_from_buffer_copy(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets) -> Tensor |
| 4707 | at::Tensor _nested_view_from_buffer_copy::call(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, at::IntArrayRef offsets) { |
| 4708 | |
| 4709 | static auto op = create__nested_view_from_buffer_copy_typed_handle(); |
| 4710 | return op.call(self, nested_size, nested_strides, offsets); |
| 4711 | } |
| 4712 | |
| 4713 | // aten::_nested_view_from_buffer_copy(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets) -> Tensor |
| 4714 | at::Tensor _nested_view_from_buffer_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, at::IntArrayRef offsets) { |
| 4715 | |
| 4716 | static auto op = create__nested_view_from_buffer_copy_typed_handle(); |
| 4717 | return op.redispatch(dispatchKeySet, self, nested_size, nested_strides, offsets); |
| 4718 | } |
| 4719 | |
| 4720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unique_dim_consecutive, name, "aten::unique_dim_consecutive") |
| 4721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unique_dim_consecutive, overload_name, "") |
| 4722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unique_dim_consecutive, schema_str, "unique_dim_consecutive(Tensor self, int dim, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor)") |
| 4723 | |
| 4724 | // aten::unique_dim_consecutive(Tensor self, int dim, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor) |
| 4725 | static C10_NOINLINE c10::TypedOperatorHandle<unique_dim_consecutive::schema> create_unique_dim_consecutive_typed_handle() { |
| 4726 | return c10::Dispatcher::singleton() |
| 4727 | .findSchemaOrThrow(unique_dim_consecutive::name, unique_dim_consecutive::overload_name) |
| 4728 | .typed<unique_dim_consecutive::schema>(); |
| 4729 | } |
| 4730 | |
| 4731 | // aten::unique_dim_consecutive(Tensor self, int dim, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor) |
| 4732 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim_consecutive::call(const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts) { |
| 4733 | |
| 4734 | static auto op = create_unique_dim_consecutive_typed_handle(); |
| 4735 | return op.call(self, dim, return_inverse, return_counts); |
| 4736 | } |
| 4737 | |
| 4738 | // aten::unique_dim_consecutive(Tensor self, int dim, bool return_inverse=False, bool return_counts=False) -> (Tensor, Tensor, Tensor) |
| 4739 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> unique_dim_consecutive::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts) { |
| 4740 | |
| 4741 | static auto op = create_unique_dim_consecutive_typed_handle(); |
| 4742 | return op.redispatch(dispatchKeySet, self, dim, return_inverse, return_counts); |
| 4743 | } |
| 4744 | |
| 4745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unsafe_view, name, "aten::_unsafe_view") |
| 4746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unsafe_view, overload_name, "") |
| 4747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unsafe_view, schema_str, "_unsafe_view(Tensor self, SymInt[] size) -> Tensor") |
| 4748 | |
| 4749 | // aten::_unsafe_view(Tensor self, SymInt[] size) -> Tensor |
| 4750 | static C10_NOINLINE c10::TypedOperatorHandle<_unsafe_view::schema> create__unsafe_view_typed_handle() { |
| 4751 | return c10::Dispatcher::singleton() |
| 4752 | .findSchemaOrThrow(_unsafe_view::name, _unsafe_view::overload_name) |
| 4753 | .typed<_unsafe_view::schema>(); |
| 4754 | } |
| 4755 | |
| 4756 | // aten::_unsafe_view(Tensor self, SymInt[] size) -> Tensor |
| 4757 | at::Tensor _unsafe_view::call(const at::Tensor & self, c10::SymIntArrayRef size) { |
| 4758 | |
| 4759 | static auto op = create__unsafe_view_typed_handle(); |
| 4760 | return op.call(self, size); |
| 4761 | } |
| 4762 | |
| 4763 | // aten::_unsafe_view(Tensor self, SymInt[] size) -> Tensor |
| 4764 | at::Tensor _unsafe_view::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size) { |
| 4765 | |
| 4766 | static auto op = create__unsafe_view_typed_handle(); |
| 4767 | return op.redispatch(dispatchKeySet, self, size); |
| 4768 | } |
| 4769 | |
| 4770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze, name, "aten::unsqueeze") |
| 4771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze, overload_name, "") |
| 4772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze, schema_str, "unsqueeze(Tensor(a) self, int dim) -> Tensor(a)") |
| 4773 | |
| 4774 | // aten::unsqueeze(Tensor(a) self, int dim) -> Tensor(a) |
| 4775 | static C10_NOINLINE c10::TypedOperatorHandle<unsqueeze::schema> create_unsqueeze_typed_handle() { |
| 4776 | return c10::Dispatcher::singleton() |
| 4777 | .findSchemaOrThrow(unsqueeze::name, unsqueeze::overload_name) |
| 4778 | .typed<unsqueeze::schema>(); |
| 4779 | } |
| 4780 | |
| 4781 | // aten::unsqueeze(Tensor(a) self, int dim) -> Tensor(a) |
| 4782 | at::Tensor unsqueeze::call(const at::Tensor & self, int64_t dim) { |
| 4783 | |
| 4784 | static auto op = create_unsqueeze_typed_handle(); |
| 4785 | return op.call(self, dim); |
| 4786 | } |
| 4787 | |
| 4788 | // aten::unsqueeze(Tensor(a) self, int dim) -> Tensor(a) |
| 4789 | at::Tensor unsqueeze::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim) { |
| 4790 | |
| 4791 | static auto op = create_unsqueeze_typed_handle(); |
| 4792 | return op.redispatch(dispatchKeySet, self, dim); |
| 4793 | } |
| 4794 | |
| 4795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_, name, "aten::unsqueeze_") |
| 4796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_, overload_name, "") |
| 4797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsqueeze_, schema_str, "unsqueeze_(Tensor(a!) self, int dim) -> Tensor(a!)") |
| 4798 | |
| 4799 | // aten::unsqueeze_(Tensor(a!) self, int dim) -> Tensor(a!) |
| 4800 | static C10_NOINLINE c10::TypedOperatorHandle<unsqueeze_::schema> create_unsqueeze__typed_handle() { |
| 4801 | return c10::Dispatcher::singleton() |
| 4802 | .findSchemaOrThrow(unsqueeze_::name, unsqueeze_::overload_name) |
| 4803 | .typed<unsqueeze_::schema>(); |
| 4804 | } |
| 4805 | |
| 4806 | // aten::unsqueeze_(Tensor(a!) self, int dim) -> Tensor(a!) |
| 4807 | at::Tensor & unsqueeze_::call(at::Tensor & self, int64_t dim) { |
| 4808 | |
| 4809 | static auto op = create_unsqueeze__typed_handle(); |
| 4810 | return op.call(self, dim); |
| 4811 | } |
| 4812 | |
| 4813 | // aten::unsqueeze_(Tensor(a!) self, int dim) -> Tensor(a!) |
| 4814 | at::Tensor & unsqueeze_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim) { |
| 4815 | |
| 4816 | static auto op = create_unsqueeze__typed_handle(); |
| 4817 | return op.redispatch(dispatchKeySet, self, dim); |
| 4818 | } |
| 4819 | |
| 4820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_efficientzerotensor, name, "aten::_efficientzerotensor") |
| 4821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_efficientzerotensor, overload_name, "") |
| 4822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_efficientzerotensor, schema_str, "_efficientzerotensor(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 4823 | |
| 4824 | // aten::_efficientzerotensor(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 4825 | static C10_NOINLINE c10::TypedOperatorHandle<_efficientzerotensor::schema> create__efficientzerotensor_typed_handle() { |
| 4826 | return c10::Dispatcher::singleton() |
| 4827 | .findSchemaOrThrow(_efficientzerotensor::name, _efficientzerotensor::overload_name) |
| 4828 | .typed<_efficientzerotensor::schema>(); |
| 4829 | } |
| 4830 | |
| 4831 | // aten::_efficientzerotensor(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 4832 | at::Tensor _efficientzerotensor::call(at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 4833 | |
| 4834 | static auto op = create__efficientzerotensor_typed_handle(); |
| 4835 | return op.call(size, dtype, layout, device, pin_memory); |
| 4836 | } |
| 4837 | |
| 4838 | // aten::_efficientzerotensor(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 4839 | at::Tensor _efficientzerotensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 4840 | |
| 4841 | static auto op = create__efficientzerotensor_typed_handle(); |
| 4842 | return op.redispatch(dispatchKeySet, size, dtype, layout, device, pin_memory); |
| 4843 | } |
| 4844 | |
| 4845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson, name, "aten::poisson") |
| 4846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson, overload_name, "") |
| 4847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson, schema_str, "poisson(Tensor self, Generator? generator=None) -> Tensor") |
| 4848 | |
| 4849 | // aten::poisson(Tensor self, Generator? generator=None) -> Tensor |
| 4850 | static C10_NOINLINE c10::TypedOperatorHandle<poisson::schema> create_poisson_typed_handle() { |
| 4851 | return c10::Dispatcher::singleton() |
| 4852 | .findSchemaOrThrow(poisson::name, poisson::overload_name) |
| 4853 | .typed<poisson::schema>(); |
| 4854 | } |
| 4855 | |
| 4856 | // aten::poisson(Tensor self, Generator? generator=None) -> Tensor |
| 4857 | at::Tensor poisson::call(const at::Tensor & self, c10::optional<at::Generator> generator) { |
| 4858 | |
| 4859 | static auto op = create_poisson_typed_handle(); |
| 4860 | return op.call(self, generator); |
| 4861 | } |
| 4862 | |
| 4863 | // aten::poisson(Tensor self, Generator? generator=None) -> Tensor |
| 4864 | at::Tensor poisson::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator) { |
| 4865 | |
| 4866 | static auto op = create_poisson_typed_handle(); |
| 4867 | return op.redispatch(dispatchKeySet, self, generator); |
| 4868 | } |
| 4869 | |
| 4870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_out, name, "aten::sub") |
| 4871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_out, overload_name, "out") |
| 4872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_out, schema_str, "sub.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") |
| 4873 | |
| 4874 | // aten::sub.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 4875 | static C10_NOINLINE c10::TypedOperatorHandle<sub_out::schema> create_sub_out_typed_handle() { |
| 4876 | return c10::Dispatcher::singleton() |
| 4877 | .findSchemaOrThrow(sub_out::name, sub_out::overload_name) |
| 4878 | .typed<sub_out::schema>(); |
| 4879 | } |
| 4880 | |
| 4881 | // aten::sub.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 4882 | at::Tensor & sub_out::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out) { |
| 4883 | |
| 4884 | static auto op = create_sub_out_typed_handle(); |
| 4885 | return op.call(self, other, alpha, out); |
| 4886 | } |
| 4887 | |
| 4888 | // aten::sub.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 4889 | at::Tensor & sub_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out) { |
| 4890 | |
| 4891 | static auto op = create_sub_out_typed_handle(); |
| 4892 | return op.redispatch(dispatchKeySet, self, other, alpha, out); |
| 4893 | } |
| 4894 | |
| 4895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Tensor, name, "aten::sub") |
| 4896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Tensor, overload_name, "Tensor") |
| 4897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Tensor, schema_str, "sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor") |
| 4898 | |
| 4899 | // aten::sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
| 4900 | static C10_NOINLINE c10::TypedOperatorHandle<sub_Tensor::schema> create_sub_Tensor_typed_handle() { |
| 4901 | return c10::Dispatcher::singleton() |
| 4902 | .findSchemaOrThrow(sub_Tensor::name, sub_Tensor::overload_name) |
| 4903 | .typed<sub_Tensor::schema>(); |
| 4904 | } |
| 4905 | |
| 4906 | // aten::sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
| 4907 | at::Tensor sub_Tensor::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 4908 | |
| 4909 | static auto op = create_sub_Tensor_typed_handle(); |
| 4910 | return op.call(self, other, alpha); |
| 4911 | } |
| 4912 | |
| 4913 | // aten::sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
| 4914 | at::Tensor sub_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 4915 | |
| 4916 | static auto op = create_sub_Tensor_typed_handle(); |
| 4917 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 4918 | } |
| 4919 | |
| 4920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub__Tensor, name, "aten::sub_") |
| 4921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub__Tensor, overload_name, "Tensor") |
| 4922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub__Tensor, schema_str, "sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)") |
| 4923 | |
| 4924 | // aten::sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
| 4925 | static C10_NOINLINE c10::TypedOperatorHandle<sub__Tensor::schema> create_sub__Tensor_typed_handle() { |
| 4926 | return c10::Dispatcher::singleton() |
| 4927 | .findSchemaOrThrow(sub__Tensor::name, sub__Tensor::overload_name) |
| 4928 | .typed<sub__Tensor::schema>(); |
| 4929 | } |
| 4930 | |
| 4931 | // aten::sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
| 4932 | at::Tensor & sub__Tensor::call(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 4933 | |
| 4934 | static auto op = create_sub__Tensor_typed_handle(); |
| 4935 | return op.call(self, other, alpha); |
| 4936 | } |
| 4937 | |
| 4938 | // aten::sub_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
| 4939 | at::Tensor & sub__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 4940 | |
| 4941 | static auto op = create_sub__Tensor_typed_handle(); |
| 4942 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 4943 | } |
| 4944 | |
| 4945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Scalar, name, "aten::sub") |
| 4946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Scalar, overload_name, "Scalar") |
| 4947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Scalar, schema_str, "sub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor") |
| 4948 | |
| 4949 | // aten::sub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
| 4950 | static C10_NOINLINE c10::TypedOperatorHandle<sub_Scalar::schema> create_sub_Scalar_typed_handle() { |
| 4951 | return c10::Dispatcher::singleton() |
| 4952 | .findSchemaOrThrow(sub_Scalar::name, sub_Scalar::overload_name) |
| 4953 | .typed<sub_Scalar::schema>(); |
| 4954 | } |
| 4955 | |
| 4956 | // aten::sub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
| 4957 | at::Tensor sub_Scalar::call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 4958 | |
| 4959 | static auto op = create_sub_Scalar_typed_handle(); |
| 4960 | return op.call(self, other, alpha); |
| 4961 | } |
| 4962 | |
| 4963 | // aten::sub.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
| 4964 | at::Tensor sub_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 4965 | |
| 4966 | static auto op = create_sub_Scalar_typed_handle(); |
| 4967 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 4968 | } |
| 4969 | |
| 4970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub__Scalar, name, "aten::sub_") |
| 4971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub__Scalar, overload_name, "Scalar") |
| 4972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub__Scalar, schema_str, "sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)") |
| 4973 | |
| 4974 | // aten::sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
| 4975 | static C10_NOINLINE c10::TypedOperatorHandle<sub__Scalar::schema> create_sub__Scalar_typed_handle() { |
| 4976 | return c10::Dispatcher::singleton() |
| 4977 | .findSchemaOrThrow(sub__Scalar::name, sub__Scalar::overload_name) |
| 4978 | .typed<sub__Scalar::schema>(); |
| 4979 | } |
| 4980 | |
| 4981 | // aten::sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
| 4982 | at::Tensor & sub__Scalar::call(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 4983 | |
| 4984 | static auto op = create_sub__Scalar_typed_handle(); |
| 4985 | return op.call(self, other, alpha); |
| 4986 | } |
| 4987 | |
| 4988 | // aten::sub_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
| 4989 | at::Tensor & sub__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 4990 | |
| 4991 | static auto op = create_sub__Scalar_typed_handle(); |
| 4992 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 4993 | } |
| 4994 | |
| 4995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_out, name, "aten::subtract") |
| 4996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_out, overload_name, "out") |
| 4997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_out, schema_str, "subtract.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") |
| 4998 | |
| 4999 | // aten::subtract.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 5000 | static C10_NOINLINE c10::TypedOperatorHandle<subtract_out::schema> create_subtract_out_typed_handle() { |
| 5001 | return c10::Dispatcher::singleton() |
| 5002 | .findSchemaOrThrow(subtract_out::name, subtract_out::overload_name) |
| 5003 | .typed<subtract_out::schema>(); |
| 5004 | } |
| 5005 | |
| 5006 | // aten::subtract.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 5007 | at::Tensor & subtract_out::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out) { |
| 5008 | |
| 5009 | static auto op = create_subtract_out_typed_handle(); |
| 5010 | return op.call(self, other, alpha, out); |
| 5011 | } |
| 5012 | |
| 5013 | // aten::subtract.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 5014 | at::Tensor & subtract_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out) { |
| 5015 | |
| 5016 | static auto op = create_subtract_out_typed_handle(); |
| 5017 | return op.redispatch(dispatchKeySet, self, other, alpha, out); |
| 5018 | } |
| 5019 | |
| 5020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_Tensor, name, "aten::subtract") |
| 5021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_Tensor, overload_name, "Tensor") |
| 5022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_Tensor, schema_str, "subtract.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor") |
| 5023 | |
| 5024 | // aten::subtract.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
| 5025 | static C10_NOINLINE c10::TypedOperatorHandle<subtract_Tensor::schema> create_subtract_Tensor_typed_handle() { |
| 5026 | return c10::Dispatcher::singleton() |
| 5027 | .findSchemaOrThrow(subtract_Tensor::name, subtract_Tensor::overload_name) |
| 5028 | .typed<subtract_Tensor::schema>(); |
| 5029 | } |
| 5030 | |
| 5031 | // aten::subtract.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
| 5032 | at::Tensor subtract_Tensor::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 5033 | |
| 5034 | static auto op = create_subtract_Tensor_typed_handle(); |
| 5035 | return op.call(self, other, alpha); |
| 5036 | } |
| 5037 | |
| 5038 | // aten::subtract.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
| 5039 | at::Tensor subtract_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 5040 | |
| 5041 | static auto op = create_subtract_Tensor_typed_handle(); |
| 5042 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 5043 | } |
| 5044 | |
| 5045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract__Tensor, name, "aten::subtract_") |
| 5046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract__Tensor, overload_name, "Tensor") |
| 5047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract__Tensor, schema_str, "subtract_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)") |
| 5048 | |
| 5049 | // aten::subtract_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
| 5050 | static C10_NOINLINE c10::TypedOperatorHandle<subtract__Tensor::schema> create_subtract__Tensor_typed_handle() { |
| 5051 | return c10::Dispatcher::singleton() |
| 5052 | .findSchemaOrThrow(subtract__Tensor::name, subtract__Tensor::overload_name) |
| 5053 | .typed<subtract__Tensor::schema>(); |
| 5054 | } |
| 5055 | |
| 5056 | // aten::subtract_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
| 5057 | at::Tensor & subtract__Tensor::call(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 5058 | |
| 5059 | static auto op = create_subtract__Tensor_typed_handle(); |
| 5060 | return op.call(self, other, alpha); |
| 5061 | } |
| 5062 | |
| 5063 | // aten::subtract_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
| 5064 | at::Tensor & subtract__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
| 5065 | |
| 5066 | static auto op = create_subtract__Tensor_typed_handle(); |
| 5067 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 5068 | } |
| 5069 | |
| 5070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_Scalar, name, "aten::subtract") |
| 5071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_Scalar, overload_name, "Scalar") |
| 5072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract_Scalar, schema_str, "subtract.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor") |
| 5073 | |
| 5074 | // aten::subtract.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
| 5075 | static C10_NOINLINE c10::TypedOperatorHandle<subtract_Scalar::schema> create_subtract_Scalar_typed_handle() { |
| 5076 | return c10::Dispatcher::singleton() |
| 5077 | .findSchemaOrThrow(subtract_Scalar::name, subtract_Scalar::overload_name) |
| 5078 | .typed<subtract_Scalar::schema>(); |
| 5079 | } |
| 5080 | |
| 5081 | // aten::subtract.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
| 5082 | at::Tensor subtract_Scalar::call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 5083 | |
| 5084 | static auto op = create_subtract_Scalar_typed_handle(); |
| 5085 | return op.call(self, other, alpha); |
| 5086 | } |
| 5087 | |
| 5088 | // aten::subtract.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
| 5089 | at::Tensor subtract_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 5090 | |
| 5091 | static auto op = create_subtract_Scalar_typed_handle(); |
| 5092 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 5093 | } |
| 5094 | |
| 5095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract__Scalar, name, "aten::subtract_") |
| 5096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract__Scalar, overload_name, "Scalar") |
| 5097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(subtract__Scalar, schema_str, "subtract_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)") |
| 5098 | |
| 5099 | // aten::subtract_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
| 5100 | static C10_NOINLINE c10::TypedOperatorHandle<subtract__Scalar::schema> create_subtract__Scalar_typed_handle() { |
| 5101 | return c10::Dispatcher::singleton() |
| 5102 | .findSchemaOrThrow(subtract__Scalar::name, subtract__Scalar::overload_name) |
| 5103 | .typed<subtract__Scalar::schema>(); |
| 5104 | } |
| 5105 | |
| 5106 | // aten::subtract_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
| 5107 | at::Tensor & subtract__Scalar::call(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 5108 | |
| 5109 | static auto op = create_subtract__Scalar_typed_handle(); |
| 5110 | return op.call(self, other, alpha); |
| 5111 | } |
| 5112 | |
| 5113 | // aten::subtract_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
| 5114 | at::Tensor & subtract__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
| 5115 | |
| 5116 | static auto op = create_subtract__Scalar_typed_handle(); |
| 5117 | return op.redispatch(dispatchKeySet, self, other, alpha); |
| 5118 | } |
| 5119 | |
| 5120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside_out, name, "aten::heaviside") |
| 5121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside_out, overload_name, "out") |
| 5122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside_out, schema_str, "heaviside.out(Tensor self, Tensor values, *, Tensor(a!) out) -> Tensor(a!)") |
| 5123 | |
| 5124 | // aten::heaviside.out(Tensor self, Tensor values, *, Tensor(a!) out) -> Tensor(a!) |
| 5125 | static C10_NOINLINE c10::TypedOperatorHandle<heaviside_out::schema> create_heaviside_out_typed_handle() { |
| 5126 | return c10::Dispatcher::singleton() |
| 5127 | .findSchemaOrThrow(heaviside_out::name, heaviside_out::overload_name) |
| 5128 | .typed<heaviside_out::schema>(); |
| 5129 | } |
| 5130 | |
| 5131 | // aten::heaviside.out(Tensor self, Tensor values, *, Tensor(a!) out) -> Tensor(a!) |
| 5132 | at::Tensor & heaviside_out::call(const at::Tensor & self, const at::Tensor & values, at::Tensor & out) { |
| 5133 | |
| 5134 | static auto op = create_heaviside_out_typed_handle(); |
| 5135 | return op.call(self, values, out); |
| 5136 | } |
| 5137 | |
| 5138 | // aten::heaviside.out(Tensor self, Tensor values, *, Tensor(a!) out) -> Tensor(a!) |
| 5139 | at::Tensor & heaviside_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & values, at::Tensor & out) { |
| 5140 | |
| 5141 | static auto op = create_heaviside_out_typed_handle(); |
| 5142 | return op.redispatch(dispatchKeySet, self, values, out); |
| 5143 | } |
| 5144 | |
| 5145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside, name, "aten::heaviside") |
| 5146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside, overload_name, "") |
| 5147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside, schema_str, "heaviside(Tensor self, Tensor values) -> Tensor") |
| 5148 | |
| 5149 | // aten::heaviside(Tensor self, Tensor values) -> Tensor |
| 5150 | static C10_NOINLINE c10::TypedOperatorHandle<heaviside::schema> create_heaviside_typed_handle() { |
| 5151 | return c10::Dispatcher::singleton() |
| 5152 | .findSchemaOrThrow(heaviside::name, heaviside::overload_name) |
| 5153 | .typed<heaviside::schema>(); |
| 5154 | } |
| 5155 | |
| 5156 | // aten::heaviside(Tensor self, Tensor values) -> Tensor |
| 5157 | at::Tensor heaviside::call(const at::Tensor & self, const at::Tensor & values) { |
| 5158 | |
| 5159 | static auto op = create_heaviside_typed_handle(); |
| 5160 | return op.call(self, values); |
| 5161 | } |
| 5162 | |
| 5163 | // aten::heaviside(Tensor self, Tensor values) -> Tensor |
| 5164 | at::Tensor heaviside::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & values) { |
| 5165 | |
| 5166 | static auto op = create_heaviside_typed_handle(); |
| 5167 | return op.redispatch(dispatchKeySet, self, values); |
| 5168 | } |
| 5169 | |
| 5170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside_, name, "aten::heaviside_") |
| 5171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside_, overload_name, "") |
| 5172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(heaviside_, schema_str, "heaviside_(Tensor(a!) self, Tensor values) -> Tensor(a!)") |
| 5173 | |
| 5174 | // aten::heaviside_(Tensor(a!) self, Tensor values) -> Tensor(a!) |
| 5175 | static C10_NOINLINE c10::TypedOperatorHandle<heaviside_::schema> create_heaviside__typed_handle() { |
| 5176 | return c10::Dispatcher::singleton() |
| 5177 | .findSchemaOrThrow(heaviside_::name, heaviside_::overload_name) |
| 5178 | .typed<heaviside_::schema>(); |
| 5179 | } |
| 5180 | |
| 5181 | // aten::heaviside_(Tensor(a!) self, Tensor values) -> Tensor(a!) |
| 5182 | at::Tensor & heaviside_::call(at::Tensor & self, const at::Tensor & values) { |
| 5183 | |
| 5184 | static auto op = create_heaviside__typed_handle(); |
| 5185 | return op.call(self, values); |
| 5186 | } |
| 5187 | |
| 5188 | // aten::heaviside_(Tensor(a!) self, Tensor values) -> Tensor(a!) |
| 5189 | at::Tensor & heaviside_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & values) { |
| 5190 | |
| 5191 | static auto op = create_heaviside__typed_handle(); |
| 5192 | return op.redispatch(dispatchKeySet, self, values); |
| 5193 | } |
| 5194 | |
| 5195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_addmm_activation_out, name, "aten::_addmm_activation") |
| 5196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_addmm_activation_out, overload_name, "out") |
| 5197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_addmm_activation_out, schema_str, "_addmm_activation.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False, Tensor(a!) out) -> Tensor(a!)") |
| 5198 | |
| 5199 | // aten::_addmm_activation.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False, Tensor(a!) out) -> Tensor(a!) |
| 5200 | static C10_NOINLINE c10::TypedOperatorHandle<_addmm_activation_out::schema> create__addmm_activation_out_typed_handle() { |
| 5201 | return c10::Dispatcher::singleton() |
| 5202 | .findSchemaOrThrow(_addmm_activation_out::name, _addmm_activation_out::overload_name) |
| 5203 | .typed<_addmm_activation_out::schema>(); |
| 5204 | } |
| 5205 | |
| 5206 | // aten::_addmm_activation.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False, Tensor(a!) out) -> Tensor(a!) |
| 5207 | at::Tensor & _addmm_activation_out::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, bool use_gelu, at::Tensor & out) { |
| 5208 | |
| 5209 | static auto op = create__addmm_activation_out_typed_handle(); |
| 5210 | return op.call(self, mat1, mat2, beta, alpha, use_gelu, out); |
| 5211 | } |
| 5212 | |
| 5213 | // aten::_addmm_activation.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False, Tensor(a!) out) -> Tensor(a!) |
| 5214 | at::Tensor & _addmm_activation_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, bool use_gelu, at::Tensor & out) { |
| 5215 | |
| 5216 | static auto op = create__addmm_activation_out_typed_handle(); |
| 5217 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha, use_gelu, out); |
| 5218 | } |
| 5219 | |
| 5220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_addmm_activation, name, "aten::_addmm_activation") |
| 5221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_addmm_activation, overload_name, "") |
| 5222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_addmm_activation, schema_str, "_addmm_activation(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False) -> Tensor") |
| 5223 | |
| 5224 | // aten::_addmm_activation(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False) -> Tensor |
| 5225 | static C10_NOINLINE c10::TypedOperatorHandle<_addmm_activation::schema> create__addmm_activation_typed_handle() { |
| 5226 | return c10::Dispatcher::singleton() |
| 5227 | .findSchemaOrThrow(_addmm_activation::name, _addmm_activation::overload_name) |
| 5228 | .typed<_addmm_activation::schema>(); |
| 5229 | } |
| 5230 | |
| 5231 | // aten::_addmm_activation(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False) -> Tensor |
| 5232 | at::Tensor _addmm_activation::call(const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, bool use_gelu) { |
| 5233 | |
| 5234 | static auto op = create__addmm_activation_typed_handle(); |
| 5235 | return op.call(self, mat1, mat2, beta, alpha, use_gelu); |
| 5236 | } |
| 5237 | |
| 5238 | // aten::_addmm_activation(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, bool use_gelu=False) -> Tensor |
| 5239 | at::Tensor _addmm_activation::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mat1, const at::Tensor & mat2, const at::Scalar & beta, const at::Scalar & alpha, bool use_gelu) { |
| 5240 | |
| 5241 | static auto op = create__addmm_activation_typed_handle(); |
| 5242 | return op.redispatch(dispatchKeySet, self, mat1, mat2, beta, alpha, use_gelu); |
| 5243 | } |
| 5244 | |
| 5245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_compressed_tensor_comp_plain_value_size, name, "aten::sparse_compressed_tensor") |
| 5246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_compressed_tensor_comp_plain_value_size, overload_name, "comp_plain_value_size") |
| 5247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_compressed_tensor_comp_plain_value_size, schema_str, "sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 5248 | |
| 5249 | // aten::sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5250 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_compressed_tensor_comp_plain_value_size::schema> create_sparse_compressed_tensor_comp_plain_value_size_typed_handle() { |
| 5251 | return c10::Dispatcher::singleton() |
| 5252 | .findSchemaOrThrow(sparse_compressed_tensor_comp_plain_value_size::name, sparse_compressed_tensor_comp_plain_value_size::overload_name) |
| 5253 | .typed<sparse_compressed_tensor_comp_plain_value_size::schema>(); |
| 5254 | } |
| 5255 | |
| 5256 | // aten::sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5257 | at::Tensor sparse_compressed_tensor_comp_plain_value_size::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) { |
| 5258 | |
| 5259 | static auto op = create_sparse_compressed_tensor_comp_plain_value_size_typed_handle(); |
| 5260 | return op.call(compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); |
| 5261 | } |
| 5262 | |
| 5263 | // aten::sparse_compressed_tensor.comp_plain_value_size(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5264 | at::Tensor sparse_compressed_tensor_comp_plain_value_size::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) { |
| 5265 | |
| 5266 | static auto op = create_sparse_compressed_tensor_comp_plain_value_size_typed_handle(); |
| 5267 | return op.redispatch(dispatchKeySet, compressed_indices, plain_indices, values, size, dtype, layout, device, pin_memory); |
| 5268 | } |
| 5269 | |
| 5270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsr_tensor_crow_col_value_size, name, "aten::sparse_bsr_tensor") |
| 5271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsr_tensor_crow_col_value_size, overload_name, "crow_col_value_size") |
| 5272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsr_tensor_crow_col_value_size, schema_str, "sparse_bsr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 5273 | |
| 5274 | // aten::sparse_bsr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5275 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_bsr_tensor_crow_col_value_size::schema> create_sparse_bsr_tensor_crow_col_value_size_typed_handle() { |
| 5276 | return c10::Dispatcher::singleton() |
| 5277 | .findSchemaOrThrow(sparse_bsr_tensor_crow_col_value_size::name, sparse_bsr_tensor_crow_col_value_size::overload_name) |
| 5278 | .typed<sparse_bsr_tensor_crow_col_value_size::schema>(); |
| 5279 | } |
| 5280 | |
| 5281 | // aten::sparse_bsr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5282 | at::Tensor sparse_bsr_tensor_crow_col_value_size::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) { |
| 5283 | |
| 5284 | static auto op = create_sparse_bsr_tensor_crow_col_value_size_typed_handle(); |
| 5285 | return op.call(crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); |
| 5286 | } |
| 5287 | |
| 5288 | // aten::sparse_bsr_tensor.crow_col_value_size(Tensor crow_indices, Tensor col_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5289 | at::Tensor sparse_bsr_tensor_crow_col_value_size::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) { |
| 5290 | |
| 5291 | static auto op = create_sparse_bsr_tensor_crow_col_value_size_typed_handle(); |
| 5292 | return op.redispatch(dispatchKeySet, crow_indices, col_indices, values, size, dtype, layout, device, pin_memory); |
| 5293 | } |
| 5294 | |
| 5295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_compressed_tensor_comp_plain_value, name, "aten::sparse_compressed_tensor") |
| 5296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_compressed_tensor_comp_plain_value, overload_name, "comp_plain_value") |
| 5297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_compressed_tensor_comp_plain_value, schema_str, "sparse_compressed_tensor.comp_plain_value(Tensor compressed_indices, Tensor plain_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 5298 | |
| 5299 | // aten::sparse_compressed_tensor.comp_plain_value(Tensor compressed_indices, Tensor plain_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5300 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_compressed_tensor_comp_plain_value::schema> create_sparse_compressed_tensor_comp_plain_value_typed_handle() { |
| 5301 | return c10::Dispatcher::singleton() |
| 5302 | .findSchemaOrThrow(sparse_compressed_tensor_comp_plain_value::name, sparse_compressed_tensor_comp_plain_value::overload_name) |
| 5303 | .typed<sparse_compressed_tensor_comp_plain_value::schema>(); |
| 5304 | } |
| 5305 | |
| 5306 | // aten::sparse_compressed_tensor.comp_plain_value(Tensor compressed_indices, Tensor plain_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5307 | at::Tensor sparse_compressed_tensor_comp_plain_value::call(const at::Tensor & compressed_indices, const at::Tensor & plain_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) { |
| 5308 | |
| 5309 | static auto op = create_sparse_compressed_tensor_comp_plain_value_typed_handle(); |
| 5310 | return op.call(compressed_indices, plain_indices, values, dtype, layout, device, pin_memory); |
| 5311 | } |
| 5312 | |
| 5313 | // aten::sparse_compressed_tensor.comp_plain_value(Tensor compressed_indices, Tensor plain_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5314 | at::Tensor sparse_compressed_tensor_comp_plain_value::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_indices, const at::Tensor & plain_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) { |
| 5315 | |
| 5316 | static auto op = create_sparse_compressed_tensor_comp_plain_value_typed_handle(); |
| 5317 | return op.redispatch(dispatchKeySet, compressed_indices, plain_indices, values, dtype, layout, device, pin_memory); |
| 5318 | } |
| 5319 | |
| 5320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsr_tensor_crow_col_value, name, "aten::sparse_bsr_tensor") |
| 5321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsr_tensor_crow_col_value, overload_name, "crow_col_value") |
| 5322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_bsr_tensor_crow_col_value, schema_str, "sparse_bsr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 5323 | |
| 5324 | // aten::sparse_bsr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5325 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_bsr_tensor_crow_col_value::schema> create_sparse_bsr_tensor_crow_col_value_typed_handle() { |
| 5326 | return c10::Dispatcher::singleton() |
| 5327 | .findSchemaOrThrow(sparse_bsr_tensor_crow_col_value::name, sparse_bsr_tensor_crow_col_value::overload_name) |
| 5328 | .typed<sparse_bsr_tensor_crow_col_value::schema>(); |
| 5329 | } |
| 5330 | |
| 5331 | // aten::sparse_bsr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5332 | at::Tensor sparse_bsr_tensor_crow_col_value::call(const at::Tensor & crow_indices, const at::Tensor & col_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) { |
| 5333 | |
| 5334 | static auto op = create_sparse_bsr_tensor_crow_col_value_typed_handle(); |
| 5335 | return op.call(crow_indices, col_indices, values, dtype, layout, device, pin_memory); |
| 5336 | } |
| 5337 | |
| 5338 | // aten::sparse_bsr_tensor.crow_col_value(Tensor crow_indices, Tensor col_indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5339 | at::Tensor sparse_bsr_tensor_crow_col_value::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & crow_indices, const at::Tensor & col_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) { |
| 5340 | |
| 5341 | static auto op = create_sparse_bsr_tensor_crow_col_value_typed_handle(); |
| 5342 | return op.redispatch(dispatchKeySet, crow_indices, col_indices, values, dtype, layout, device, pin_memory); |
| 5343 | } |
| 5344 | |
| 5345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_size, name, "aten::sparse_coo_tensor") |
| 5346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_size, overload_name, "size") |
| 5347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_size, schema_str, "sparse_coo_tensor.size(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor") |
| 5348 | |
| 5349 | // aten::sparse_coo_tensor.size(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5350 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_coo_tensor_size::schema> create_sparse_coo_tensor_size_typed_handle() { |
| 5351 | return c10::Dispatcher::singleton() |
| 5352 | .findSchemaOrThrow(sparse_coo_tensor_size::name, sparse_coo_tensor_size::overload_name) |
| 5353 | .typed<sparse_coo_tensor_size::schema>(); |
| 5354 | } |
| 5355 | |
| 5356 | // aten::sparse_coo_tensor.size(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5357 | at::Tensor sparse_coo_tensor_size::call(at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5358 | |
| 5359 | static auto op = create_sparse_coo_tensor_size_typed_handle(); |
| 5360 | return op.call(size, dtype, layout, device, pin_memory); |
| 5361 | } |
| 5362 | |
| 5363 | // aten::sparse_coo_tensor.size(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
| 5364 | at::Tensor sparse_coo_tensor_size::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 5365 | |
| 5366 | static auto op = create_sparse_coo_tensor_size_typed_handle(); |
| 5367 | return op.redispatch(dispatchKeySet, size, dtype, layout, device, pin_memory); |
| 5368 | } |
| 5369 | |
| 5370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_indices, name, "aten::sparse_coo_tensor") |
| 5371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_indices, overload_name, "indices") |
| 5372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_indices, schema_str, "sparse_coo_tensor.indices(Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 5373 | |
| 5374 | // aten::sparse_coo_tensor.indices(Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5375 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_coo_tensor_indices::schema> create_sparse_coo_tensor_indices_typed_handle() { |
| 5376 | return c10::Dispatcher::singleton() |
| 5377 | .findSchemaOrThrow(sparse_coo_tensor_indices::name, sparse_coo_tensor_indices::overload_name) |
| 5378 | .typed<sparse_coo_tensor_indices::schema>(); |
| 5379 | } |
| 5380 | |
| 5381 | // aten::sparse_coo_tensor.indices(Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5382 | at::Tensor sparse_coo_tensor_indices::call(const at::Tensor & 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) { |
| 5383 | |
| 5384 | static auto op = create_sparse_coo_tensor_indices_typed_handle(); |
| 5385 | return op.call(indices, values, dtype, layout, device, pin_memory); |
| 5386 | } |
| 5387 | |
| 5388 | // aten::sparse_coo_tensor.indices(Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5389 | at::Tensor sparse_coo_tensor_indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & 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) { |
| 5390 | |
| 5391 | static auto op = create_sparse_coo_tensor_indices_typed_handle(); |
| 5392 | return op.redispatch(dispatchKeySet, indices, values, dtype, layout, device, pin_memory); |
| 5393 | } |
| 5394 | |
| 5395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_indices_size, name, "aten::sparse_coo_tensor") |
| 5396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_indices_size, overload_name, "indices_size") |
| 5397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_indices_size, schema_str, "sparse_coo_tensor.indices_size(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 5398 | |
| 5399 | // aten::sparse_coo_tensor.indices_size(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5400 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_coo_tensor_indices_size::schema> create_sparse_coo_tensor_indices_size_typed_handle() { |
| 5401 | return c10::Dispatcher::singleton() |
| 5402 | .findSchemaOrThrow(sparse_coo_tensor_indices_size::name, sparse_coo_tensor_indices_size::overload_name) |
| 5403 | .typed<sparse_coo_tensor_indices_size::schema>(); |
| 5404 | } |
| 5405 | |
| 5406 | // aten::sparse_coo_tensor.indices_size(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5407 | at::Tensor sparse_coo_tensor_indices_size::call(const at::Tensor & 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) { |
| 5408 | |
| 5409 | static auto op = create_sparse_coo_tensor_indices_size_typed_handle(); |
| 5410 | return op.call(indices, values, size, dtype, layout, device, pin_memory); |
| 5411 | } |
| 5412 | |
| 5413 | // aten::sparse_coo_tensor.indices_size(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 5414 | at::Tensor sparse_coo_tensor_indices_size::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & 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) { |
| 5415 | |
| 5416 | static auto op = create_sparse_coo_tensor_indices_size_typed_handle(); |
| 5417 | return op.redispatch(dispatchKeySet, indices, values, size, dtype, layout, device, pin_memory); |
| 5418 | } |
| 5419 | |
| 5420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_compressed_tensor_args, name, "aten::_validate_sparse_compressed_tensor_args") |
| 5421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_compressed_tensor_args, overload_name, "") |
| 5422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_compressed_tensor_args, schema_str, "_validate_sparse_compressed_tensor_args(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, Layout layout) -> ()") |
| 5423 | |
| 5424 | // aten::_validate_sparse_compressed_tensor_args(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, Layout layout) -> () |
| 5425 | static C10_NOINLINE c10::TypedOperatorHandle<_validate_sparse_compressed_tensor_args::schema> create__validate_sparse_compressed_tensor_args_typed_handle() { |
| 5426 | return c10::Dispatcher::singleton() |
| 5427 | .findSchemaOrThrow(_validate_sparse_compressed_tensor_args::name, _validate_sparse_compressed_tensor_args::overload_name) |
| 5428 | .typed<_validate_sparse_compressed_tensor_args::schema>(); |
| 5429 | } |
| 5430 | |
| 5431 | // aten::_validate_sparse_compressed_tensor_args(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, Layout layout) -> () |
| 5432 | void _validate_sparse_compressed_tensor_args::call(const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::Layout layout) { |
| 5433 | |
| 5434 | static auto op = create__validate_sparse_compressed_tensor_args_typed_handle(); |
| 5435 | return op.call(compressed_indices, plain_indices, values, size, layout); |
| 5436 | } |
| 5437 | |
| 5438 | // aten::_validate_sparse_compressed_tensor_args(Tensor compressed_indices, Tensor plain_indices, Tensor values, int[] size, Layout layout) -> () |
| 5439 | void _validate_sparse_compressed_tensor_args::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & compressed_indices, const at::Tensor & plain_indices, const at::Tensor & values, at::IntArrayRef size, at::Layout layout) { |
| 5440 | |
| 5441 | static auto op = create__validate_sparse_compressed_tensor_args_typed_handle(); |
| 5442 | return op.redispatch(dispatchKeySet, compressed_indices, plain_indices, values, size, layout); |
| 5443 | } |
| 5444 | |
| 5445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear_, name, "aten::sparse_resize_and_clear_") |
| 5446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear_, overload_name, "") |
| 5447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear_, schema_str, "sparse_resize_and_clear_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!)") |
| 5448 | |
| 5449 | // aten::sparse_resize_and_clear_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!) |
| 5450 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_resize_and_clear_::schema> create_sparse_resize_and_clear__typed_handle() { |
| 5451 | return c10::Dispatcher::singleton() |
| 5452 | .findSchemaOrThrow(sparse_resize_and_clear_::name, sparse_resize_and_clear_::overload_name) |
| 5453 | .typed<sparse_resize_and_clear_::schema>(); |
| 5454 | } |
| 5455 | |
| 5456 | // aten::sparse_resize_and_clear_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!) |
| 5457 | const at::Tensor & sparse_resize_and_clear_::call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 5458 | |
| 5459 | static auto op = create_sparse_resize_and_clear__typed_handle(); |
| 5460 | return op.call(self, size, sparse_dim, dense_dim); |
| 5461 | } |
| 5462 | |
| 5463 | // aten::sparse_resize_and_clear_(Tensor(a!) self, int[] size, int sparse_dim, int dense_dim) -> Tensor(a!) |
| 5464 | const at::Tensor & sparse_resize_and_clear_::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 5465 | |
| 5466 | static auto op = create_sparse_resize_and_clear__typed_handle(); |
| 5467 | return op.redispatch(dispatchKeySet, self, size, sparse_dim, dense_dim); |
| 5468 | } |
| 5469 | |
| 5470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_dense, name, "aten::to_dense") |
| 5471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_dense, overload_name, "") |
| 5472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_dense, schema_str, "to_dense(Tensor self, ScalarType? dtype=None) -> Tensor") |
| 5473 | |
| 5474 | // aten::to_dense(Tensor self, ScalarType? dtype=None) -> Tensor |
| 5475 | static C10_NOINLINE c10::TypedOperatorHandle<to_dense::schema> create_to_dense_typed_handle() { |
| 5476 | return c10::Dispatcher::singleton() |
| 5477 | .findSchemaOrThrow(to_dense::name, to_dense::overload_name) |
| 5478 | .typed<to_dense::schema>(); |
| 5479 | } |
| 5480 | |
| 5481 | // aten::to_dense(Tensor self, ScalarType? dtype=None) -> Tensor |
| 5482 | at::Tensor to_dense::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
| 5483 | |
| 5484 | static auto op = create_to_dense_typed_handle(); |
| 5485 | return op.call(self, dtype); |
| 5486 | } |
| 5487 | |
| 5488 | // aten::to_dense(Tensor self, ScalarType? dtype=None) -> Tensor |
| 5489 | at::Tensor to_dense::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
| 5490 | |
| 5491 | static auto op = create_to_dense_typed_handle(); |
| 5492 | return op.redispatch(dispatchKeySet, self, dtype); |
| 5493 | } |
| 5494 | |
| 5495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_dim, name, "aten::sparse_dim") |
| 5496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_dim, overload_name, "") |
| 5497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_dim, schema_str, "sparse_dim(Tensor self) -> int") |
| 5498 | |
| 5499 | // aten::sparse_dim(Tensor self) -> int |
| 5500 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_dim::schema> create_sparse_dim_typed_handle() { |
| 5501 | return c10::Dispatcher::singleton() |
| 5502 | .findSchemaOrThrow(sparse_dim::name, sparse_dim::overload_name) |
| 5503 | .typed<sparse_dim::schema>(); |
| 5504 | } |
| 5505 | |
| 5506 | // aten::sparse_dim(Tensor self) -> int |
| 5507 | int64_t sparse_dim::call(const at::Tensor & self) { |
| 5508 | |
| 5509 | static auto op = create_sparse_dim_typed_handle(); |
| 5510 | return op.call(self); |
| 5511 | } |
| 5512 | |
| 5513 | // aten::sparse_dim(Tensor self) -> int |
| 5514 | int64_t sparse_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5515 | |
| 5516 | static auto op = create_sparse_dim_typed_handle(); |
| 5517 | return op.redispatch(dispatchKeySet, self); |
| 5518 | } |
| 5519 | |
| 5520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_dimI, name, "aten::_dimI") |
| 5521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_dimI, overload_name, "") |
| 5522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_dimI, schema_str, "_dimI(Tensor self) -> int") |
| 5523 | |
| 5524 | // aten::_dimI(Tensor self) -> int |
| 5525 | static C10_NOINLINE c10::TypedOperatorHandle<_dimI::schema> create__dimI_typed_handle() { |
| 5526 | return c10::Dispatcher::singleton() |
| 5527 | .findSchemaOrThrow(_dimI::name, _dimI::overload_name) |
| 5528 | .typed<_dimI::schema>(); |
| 5529 | } |
| 5530 | |
| 5531 | // aten::_dimI(Tensor self) -> int |
| 5532 | int64_t _dimI::call(const at::Tensor & self) { |
| 5533 | |
| 5534 | static auto op = create__dimI_typed_handle(); |
| 5535 | return op.call(self); |
| 5536 | } |
| 5537 | |
| 5538 | // aten::_dimI(Tensor self) -> int |
| 5539 | int64_t _dimI::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5540 | |
| 5541 | static auto op = create__dimI_typed_handle(); |
| 5542 | return op.redispatch(dispatchKeySet, self); |
| 5543 | } |
| 5544 | |
| 5545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nnz, name, "aten::_nnz") |
| 5546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nnz, overload_name, "") |
| 5547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nnz, schema_str, "_nnz(Tensor self) -> int") |
| 5548 | |
| 5549 | // aten::_nnz(Tensor self) -> int |
| 5550 | static C10_NOINLINE c10::TypedOperatorHandle<_nnz::schema> create__nnz_typed_handle() { |
| 5551 | return c10::Dispatcher::singleton() |
| 5552 | .findSchemaOrThrow(_nnz::name, _nnz::overload_name) |
| 5553 | .typed<_nnz::schema>(); |
| 5554 | } |
| 5555 | |
| 5556 | // aten::_nnz(Tensor self) -> int |
| 5557 | int64_t _nnz::call(const at::Tensor & self) { |
| 5558 | |
| 5559 | static auto op = create__nnz_typed_handle(); |
| 5560 | return op.call(self); |
| 5561 | } |
| 5562 | |
| 5563 | // aten::_nnz(Tensor self) -> int |
| 5564 | int64_t _nnz::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5565 | |
| 5566 | static auto op = create__nnz_typed_handle(); |
| 5567 | return op.redispatch(dispatchKeySet, self); |
| 5568 | } |
| 5569 | |
| 5570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ccol_indices, name, "aten::ccol_indices") |
| 5571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ccol_indices, overload_name, "") |
| 5572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ccol_indices, schema_str, "ccol_indices(Tensor(a) self) -> Tensor(a)") |
| 5573 | |
| 5574 | // aten::ccol_indices(Tensor(a) self) -> Tensor(a) |
| 5575 | static C10_NOINLINE c10::TypedOperatorHandle<ccol_indices::schema> create_ccol_indices_typed_handle() { |
| 5576 | return c10::Dispatcher::singleton() |
| 5577 | .findSchemaOrThrow(ccol_indices::name, ccol_indices::overload_name) |
| 5578 | .typed<ccol_indices::schema>(); |
| 5579 | } |
| 5580 | |
| 5581 | // aten::ccol_indices(Tensor(a) self) -> Tensor(a) |
| 5582 | at::Tensor ccol_indices::call(const at::Tensor & self) { |
| 5583 | |
| 5584 | static auto op = create_ccol_indices_typed_handle(); |
| 5585 | return op.call(self); |
| 5586 | } |
| 5587 | |
| 5588 | // aten::ccol_indices(Tensor(a) self) -> Tensor(a) |
| 5589 | at::Tensor ccol_indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5590 | |
| 5591 | static auto op = create_ccol_indices_typed_handle(); |
| 5592 | return op.redispatch(dispatchKeySet, self); |
| 5593 | } |
| 5594 | |
| 5595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_csr, name, "aten::to_sparse_csr") |
| 5596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_csr, overload_name, "") |
| 5597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_csr, schema_str, "to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor") |
| 5598 | |
| 5599 | // aten::to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor |
| 5600 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_csr::schema> create_to_sparse_csr_typed_handle() { |
| 5601 | return c10::Dispatcher::singleton() |
| 5602 | .findSchemaOrThrow(to_sparse_csr::name, to_sparse_csr::overload_name) |
| 5603 | .typed<to_sparse_csr::schema>(); |
| 5604 | } |
| 5605 | |
| 5606 | // aten::to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor |
| 5607 | at::Tensor to_sparse_csr::call(const at::Tensor & self, c10::optional<int64_t> dense_dim) { |
| 5608 | |
| 5609 | static auto op = create_to_sparse_csr_typed_handle(); |
| 5610 | return op.call(self, dense_dim); |
| 5611 | } |
| 5612 | |
| 5613 | // aten::to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor |
| 5614 | at::Tensor to_sparse_csr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dense_dim) { |
| 5615 | |
| 5616 | static auto op = create_to_sparse_csr_typed_handle(); |
| 5617 | return op.redispatch(dispatchKeySet, self, dense_dim); |
| 5618 | } |
| 5619 | |
| 5620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsr, name, "aten::to_sparse_bsr") |
| 5621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsr, overload_name, "") |
| 5622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsr, schema_str, "to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor") |
| 5623 | |
| 5624 | // aten::to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor |
| 5625 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_bsr::schema> create_to_sparse_bsr_typed_handle() { |
| 5626 | return c10::Dispatcher::singleton() |
| 5627 | .findSchemaOrThrow(to_sparse_bsr::name, to_sparse_bsr::overload_name) |
| 5628 | .typed<to_sparse_bsr::schema>(); |
| 5629 | } |
| 5630 | |
| 5631 | // aten::to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor |
| 5632 | at::Tensor to_sparse_bsr::call(const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim) { |
| 5633 | |
| 5634 | static auto op = create_to_sparse_bsr_typed_handle(); |
| 5635 | return op.call(self, blocksize, dense_dim); |
| 5636 | } |
| 5637 | |
| 5638 | // aten::to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor |
| 5639 | at::Tensor to_sparse_bsr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim) { |
| 5640 | |
| 5641 | static auto op = create_to_sparse_bsr_typed_handle(); |
| 5642 | return op.redispatch(dispatchKeySet, self, blocksize, dense_dim); |
| 5643 | } |
| 5644 | |
| 5645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_reorder_conv3d_weight, name, "aten::mkldnn_reorder_conv3d_weight") |
| 5646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_reorder_conv3d_weight, overload_name, "") |
| 5647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_reorder_conv3d_weight, schema_str, "mkldnn_reorder_conv3d_weight(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1) -> Tensor") |
| 5648 | |
| 5649 | // aten::mkldnn_reorder_conv3d_weight(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1) -> Tensor |
| 5650 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_reorder_conv3d_weight::schema> create_mkldnn_reorder_conv3d_weight_typed_handle() { |
| 5651 | return c10::Dispatcher::singleton() |
| 5652 | .findSchemaOrThrow(mkldnn_reorder_conv3d_weight::name, mkldnn_reorder_conv3d_weight::overload_name) |
| 5653 | .typed<mkldnn_reorder_conv3d_weight::schema>(); |
| 5654 | } |
| 5655 | |
| 5656 | // aten::mkldnn_reorder_conv3d_weight(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1) -> Tensor |
| 5657 | at::Tensor mkldnn_reorder_conv3d_weight::call(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { |
| 5658 | |
| 5659 | static auto op = create_mkldnn_reorder_conv3d_weight_typed_handle(); |
| 5660 | return op.call(self, padding, stride, dilation, groups); |
| 5661 | } |
| 5662 | |
| 5663 | // aten::mkldnn_reorder_conv3d_weight(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1) -> Tensor |
| 5664 | at::Tensor mkldnn_reorder_conv3d_weight::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups) { |
| 5665 | |
| 5666 | static auto op = create_mkldnn_reorder_conv3d_weight_typed_handle(); |
| 5667 | return op.redispatch(dispatchKeySet, self, padding, stride, dilation, groups); |
| 5668 | } |
| 5669 | |
| 5670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(q_scale, name, "aten::q_scale") |
| 5671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(q_scale, overload_name, "") |
| 5672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(q_scale, schema_str, "q_scale(Tensor self) -> float") |
| 5673 | |
| 5674 | // aten::q_scale(Tensor self) -> float |
| 5675 | static C10_NOINLINE c10::TypedOperatorHandle<q_scale::schema> create_q_scale_typed_handle() { |
| 5676 | return c10::Dispatcher::singleton() |
| 5677 | .findSchemaOrThrow(q_scale::name, q_scale::overload_name) |
| 5678 | .typed<q_scale::schema>(); |
| 5679 | } |
| 5680 | |
| 5681 | // aten::q_scale(Tensor self) -> float |
| 5682 | double q_scale::call(const at::Tensor & self) { |
| 5683 | |
| 5684 | static auto op = create_q_scale_typed_handle(); |
| 5685 | return op.call(self); |
| 5686 | } |
| 5687 | |
| 5688 | // aten::q_scale(Tensor self) -> float |
| 5689 | double q_scale::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5690 | |
| 5691 | static auto op = create_q_scale_typed_handle(); |
| 5692 | return op.redispatch(dispatchKeySet, self); |
| 5693 | } |
| 5694 | |
| 5695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(q_per_channel_axis, name, "aten::q_per_channel_axis") |
| 5696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(q_per_channel_axis, overload_name, "") |
| 5697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(q_per_channel_axis, schema_str, "q_per_channel_axis(Tensor self) -> int") |
| 5698 | |
| 5699 | // aten::q_per_channel_axis(Tensor self) -> int |
| 5700 | static C10_NOINLINE c10::TypedOperatorHandle<q_per_channel_axis::schema> create_q_per_channel_axis_typed_handle() { |
| 5701 | return c10::Dispatcher::singleton() |
| 5702 | .findSchemaOrThrow(q_per_channel_axis::name, q_per_channel_axis::overload_name) |
| 5703 | .typed<q_per_channel_axis::schema>(); |
| 5704 | } |
| 5705 | |
| 5706 | // aten::q_per_channel_axis(Tensor self) -> int |
| 5707 | int64_t q_per_channel_axis::call(const at::Tensor & self) { |
| 5708 | |
| 5709 | static auto op = create_q_per_channel_axis_typed_handle(); |
| 5710 | return op.call(self); |
| 5711 | } |
| 5712 | |
| 5713 | // aten::q_per_channel_axis(Tensor self) -> int |
| 5714 | int64_t q_per_channel_axis::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 5715 | |
| 5716 | static auto op = create_q_per_channel_axis_typed_handle(); |
| 5717 | return op.redispatch(dispatchKeySet, self); |
| 5718 | } |
| 5719 | |
| 5720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_tensor_quantized_tensor, name, "aten::_make_per_tensor_quantized_tensor") |
| 5721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_tensor_quantized_tensor, overload_name, "") |
| 5722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_tensor_quantized_tensor, schema_str, "_make_per_tensor_quantized_tensor(Tensor self, float scale, int zero_point) -> Tensor") |
| 5723 | |
| 5724 | // aten::_make_per_tensor_quantized_tensor(Tensor self, float scale, int zero_point) -> Tensor |
| 5725 | static C10_NOINLINE c10::TypedOperatorHandle<_make_per_tensor_quantized_tensor::schema> create__make_per_tensor_quantized_tensor_typed_handle() { |
| 5726 | return c10::Dispatcher::singleton() |
| 5727 | .findSchemaOrThrow(_make_per_tensor_quantized_tensor::name, _make_per_tensor_quantized_tensor::overload_name) |
| 5728 | .typed<_make_per_tensor_quantized_tensor::schema>(); |
| 5729 | } |
| 5730 | |
| 5731 | // aten::_make_per_tensor_quantized_tensor(Tensor self, float scale, int zero_point) -> Tensor |
| 5732 | at::Tensor _make_per_tensor_quantized_tensor::call(const at::Tensor & self, double scale, int64_t zero_point) { |
| 5733 | |
| 5734 | static auto op = create__make_per_tensor_quantized_tensor_typed_handle(); |
| 5735 | return op.call(self, scale, zero_point); |
| 5736 | } |
| 5737 | |
| 5738 | // aten::_make_per_tensor_quantized_tensor(Tensor self, float scale, int zero_point) -> Tensor |
| 5739 | at::Tensor _make_per_tensor_quantized_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point) { |
| 5740 | |
| 5741 | static auto op = create__make_per_tensor_quantized_tensor_typed_handle(); |
| 5742 | return op.redispatch(dispatchKeySet, self, scale, zero_point); |
| 5743 | } |
| 5744 | |
| 5745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_channel_quantized_tensor, name, "aten::_make_per_channel_quantized_tensor") |
| 5746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_channel_quantized_tensor, overload_name, "") |
| 5747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_channel_quantized_tensor, schema_str, "_make_per_channel_quantized_tensor(Tensor self, Tensor scale, Tensor zero_point, int axis) -> Tensor") |
| 5748 | |
| 5749 | // aten::_make_per_channel_quantized_tensor(Tensor self, Tensor scale, Tensor zero_point, int axis) -> Tensor |
| 5750 | static C10_NOINLINE c10::TypedOperatorHandle<_make_per_channel_quantized_tensor::schema> create__make_per_channel_quantized_tensor_typed_handle() { |
| 5751 | return c10::Dispatcher::singleton() |
| 5752 | .findSchemaOrThrow(_make_per_channel_quantized_tensor::name, _make_per_channel_quantized_tensor::overload_name) |
| 5753 | .typed<_make_per_channel_quantized_tensor::schema>(); |
| 5754 | } |
| 5755 | |
| 5756 | // aten::_make_per_channel_quantized_tensor(Tensor self, Tensor scale, Tensor zero_point, int axis) -> Tensor |
| 5757 | at::Tensor _make_per_channel_quantized_tensor::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis) { |
| 5758 | |
| 5759 | static auto op = create__make_per_channel_quantized_tensor_typed_handle(); |
| 5760 | return op.call(self, scale, zero_point, axis); |
| 5761 | } |
| 5762 | |
| 5763 | // aten::_make_per_channel_quantized_tensor(Tensor self, Tensor scale, Tensor zero_point, int axis) -> Tensor |
| 5764 | at::Tensor _make_per_channel_quantized_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis) { |
| 5765 | |
| 5766 | static auto op = create__make_per_channel_quantized_tensor_typed_handle(); |
| 5767 | return op.redispatch(dispatchKeySet, self, scale, zero_point, axis); |
| 5768 | } |
| 5769 | |
| 5770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask_backward, name, "aten::fake_quantize_per_tensor_affine_cachemask_backward") |
| 5771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask_backward, overload_name, "") |
| 5772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask_backward, schema_str, "fake_quantize_per_tensor_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor") |
| 5773 | |
| 5774 | // aten::fake_quantize_per_tensor_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor |
| 5775 | static C10_NOINLINE c10::TypedOperatorHandle<fake_quantize_per_tensor_affine_cachemask_backward::schema> create_fake_quantize_per_tensor_affine_cachemask_backward_typed_handle() { |
| 5776 | return c10::Dispatcher::singleton() |
| 5777 | .findSchemaOrThrow(fake_quantize_per_tensor_affine_cachemask_backward::name, fake_quantize_per_tensor_affine_cachemask_backward::overload_name) |
| 5778 | .typed<fake_quantize_per_tensor_affine_cachemask_backward::schema>(); |
| 5779 | } |
| 5780 | |
| 5781 | // aten::fake_quantize_per_tensor_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor |
| 5782 | at::Tensor fake_quantize_per_tensor_affine_cachemask_backward::call(const at::Tensor & grad, const at::Tensor & mask) { |
| 5783 | |
| 5784 | static auto op = create_fake_quantize_per_tensor_affine_cachemask_backward_typed_handle(); |
| 5785 | return op.call(grad, mask); |
| 5786 | } |
| 5787 | |
| 5788 | // aten::fake_quantize_per_tensor_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor |
| 5789 | at::Tensor fake_quantize_per_tensor_affine_cachemask_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & mask) { |
| 5790 | |
| 5791 | static auto op = create_fake_quantize_per_tensor_affine_cachemask_backward_typed_handle(); |
| 5792 | return op.redispatch(dispatchKeySet, grad, mask); |
| 5793 | } |
| 5794 | |
| 5795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask_backward, name, "aten::fake_quantize_per_channel_affine_cachemask_backward") |
| 5796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask_backward, overload_name, "") |
| 5797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_channel_affine_cachemask_backward, schema_str, "fake_quantize_per_channel_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor") |
| 5798 | |
| 5799 | // aten::fake_quantize_per_channel_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor |
| 5800 | static C10_NOINLINE c10::TypedOperatorHandle<fake_quantize_per_channel_affine_cachemask_backward::schema> create_fake_quantize_per_channel_affine_cachemask_backward_typed_handle() { |
| 5801 | return c10::Dispatcher::singleton() |
| 5802 | .findSchemaOrThrow(fake_quantize_per_channel_affine_cachemask_backward::name, fake_quantize_per_channel_affine_cachemask_backward::overload_name) |
| 5803 | .typed<fake_quantize_per_channel_affine_cachemask_backward::schema>(); |
| 5804 | } |
| 5805 | |
| 5806 | // aten::fake_quantize_per_channel_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor |
| 5807 | at::Tensor fake_quantize_per_channel_affine_cachemask_backward::call(const at::Tensor & grad, const at::Tensor & mask) { |
| 5808 | |
| 5809 | static auto op = create_fake_quantize_per_channel_affine_cachemask_backward_typed_handle(); |
| 5810 | return op.call(grad, mask); |
| 5811 | } |
| 5812 | |
| 5813 | // aten::fake_quantize_per_channel_affine_cachemask_backward(Tensor grad, Tensor mask) -> Tensor |
| 5814 | at::Tensor fake_quantize_per_channel_affine_cachemask_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & mask) { |
| 5815 | |
| 5816 | static auto op = create_fake_quantize_per_channel_affine_cachemask_backward_typed_handle(); |
| 5817 | return op.redispatch(dispatchKeySet, grad, mask); |
| 5818 | } |
| 5819 | |
| 5820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_saturate_weight_to_fp16, name, "aten::_saturate_weight_to_fp16") |
| 5821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_saturate_weight_to_fp16, overload_name, "") |
| 5822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_saturate_weight_to_fp16, schema_str, "_saturate_weight_to_fp16(Tensor weight) -> Tensor") |
| 5823 | |
| 5824 | // aten::_saturate_weight_to_fp16(Tensor weight) -> Tensor |
| 5825 | static C10_NOINLINE c10::TypedOperatorHandle<_saturate_weight_to_fp16::schema> create__saturate_weight_to_fp16_typed_handle() { |
| 5826 | return c10::Dispatcher::singleton() |
| 5827 | .findSchemaOrThrow(_saturate_weight_to_fp16::name, _saturate_weight_to_fp16::overload_name) |
| 5828 | .typed<_saturate_weight_to_fp16::schema>(); |
| 5829 | } |
| 5830 | |
| 5831 | // aten::_saturate_weight_to_fp16(Tensor weight) -> Tensor |
| 5832 | at::Tensor _saturate_weight_to_fp16::call(const at::Tensor & weight) { |
| 5833 | |
| 5834 | static auto op = create__saturate_weight_to_fp16_typed_handle(); |
| 5835 | return op.call(weight); |
| 5836 | } |
| 5837 | |
| 5838 | // aten::_saturate_weight_to_fp16(Tensor weight) -> Tensor |
| 5839 | at::Tensor _saturate_weight_to_fp16::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight) { |
| 5840 | |
| 5841 | static auto op = create__saturate_weight_to_fp16_typed_handle(); |
| 5842 | return op.redispatch(dispatchKeySet, weight); |
| 5843 | } |
| 5844 | |
| 5845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_autocast_to_reduced_precision, name, "aten::_autocast_to_reduced_precision") |
| 5846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_autocast_to_reduced_precision, overload_name, "") |
| 5847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_autocast_to_reduced_precision, schema_str, "_autocast_to_reduced_precision(Tensor(a) self, bool cuda_enabled, bool cpu_enabled, ScalarType cuda_dtype, ScalarType cpu_dtype) -> Tensor(a)") |
| 5848 | |
| 5849 | // aten::_autocast_to_reduced_precision(Tensor(a) self, bool cuda_enabled, bool cpu_enabled, ScalarType cuda_dtype, ScalarType cpu_dtype) -> Tensor(a) |
| 5850 | static C10_NOINLINE c10::TypedOperatorHandle<_autocast_to_reduced_precision::schema> create__autocast_to_reduced_precision_typed_handle() { |
| 5851 | return c10::Dispatcher::singleton() |
| 5852 | .findSchemaOrThrow(_autocast_to_reduced_precision::name, _autocast_to_reduced_precision::overload_name) |
| 5853 | .typed<_autocast_to_reduced_precision::schema>(); |
| 5854 | } |
| 5855 | |
| 5856 | // aten::_autocast_to_reduced_precision(Tensor(a) self, bool cuda_enabled, bool cpu_enabled, ScalarType cuda_dtype, ScalarType cpu_dtype) -> Tensor(a) |
| 5857 | at::Tensor _autocast_to_reduced_precision::call(const at::Tensor & self, bool cuda_enabled, bool cpu_enabled, at::ScalarType cuda_dtype, at::ScalarType cpu_dtype) { |
| 5858 | |
| 5859 | static auto op = create__autocast_to_reduced_precision_typed_handle(); |
| 5860 | return op.call(self, cuda_enabled, cpu_enabled, cuda_dtype, cpu_dtype); |
| 5861 | } |
| 5862 | |
| 5863 | // aten::_autocast_to_reduced_precision(Tensor(a) self, bool cuda_enabled, bool cpu_enabled, ScalarType cuda_dtype, ScalarType cpu_dtype) -> Tensor(a) |
| 5864 | at::Tensor _autocast_to_reduced_precision::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool cuda_enabled, bool cpu_enabled, at::ScalarType cuda_dtype, at::ScalarType cpu_dtype) { |
| 5865 | |
| 5866 | static auto op = create__autocast_to_reduced_precision_typed_handle(); |
| 5867 | return op.redispatch(dispatchKeySet, self, cuda_enabled, cpu_enabled, cuda_dtype, cpu_dtype); |
| 5868 | } |
| 5869 | |
| 5870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Tensor, name, "aten::result_type") |
| 5871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Tensor, overload_name, "Tensor") |
| 5872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Tensor, schema_str, "result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType") |
| 5873 | |
| 5874 | // aten::result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType |
| 5875 | static C10_NOINLINE c10::TypedOperatorHandle<result_type_Tensor::schema> create_result_type_Tensor_typed_handle() { |
| 5876 | return c10::Dispatcher::singleton() |
| 5877 | .findSchemaOrThrow(result_type_Tensor::name, result_type_Tensor::overload_name) |
| 5878 | .typed<result_type_Tensor::schema>(); |
| 5879 | } |
| 5880 | |
| 5881 | // aten::result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType |
| 5882 | at::ScalarType result_type_Tensor::call(const at::Tensor & tensor, const at::Tensor & other) { |
| 5883 | |
| 5884 | static auto op = create_result_type_Tensor_typed_handle(); |
| 5885 | return op.call(tensor, other); |
| 5886 | } |
| 5887 | |
| 5888 | // aten::result_type.Tensor(Tensor tensor, Tensor other) -> ScalarType |
| 5889 | at::ScalarType result_type_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & tensor, const at::Tensor & other) { |
| 5890 | |
| 5891 | static auto op = create_result_type_Tensor_typed_handle(); |
| 5892 | return op.redispatch(dispatchKeySet, tensor, other); |
| 5893 | } |
| 5894 | |
| 5895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar, name, "aten::result_type") |
| 5896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar, overload_name, "Scalar") |
| 5897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar, schema_str, "result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType") |
| 5898 | |
| 5899 | // aten::result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType |
| 5900 | static C10_NOINLINE c10::TypedOperatorHandle<result_type_Scalar::schema> create_result_type_Scalar_typed_handle() { |
| 5901 | return c10::Dispatcher::singleton() |
| 5902 | .findSchemaOrThrow(result_type_Scalar::name, result_type_Scalar::overload_name) |
| 5903 | .typed<result_type_Scalar::schema>(); |
| 5904 | } |
| 5905 | |
| 5906 | // aten::result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType |
| 5907 | at::ScalarType result_type_Scalar::call(const at::Tensor & tensor, const at::Scalar & other) { |
| 5908 | |
| 5909 | static auto op = create_result_type_Scalar_typed_handle(); |
| 5910 | return op.call(tensor, other); |
| 5911 | } |
| 5912 | |
| 5913 | // aten::result_type.Scalar(Tensor tensor, Scalar other) -> ScalarType |
| 5914 | at::ScalarType result_type_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & tensor, const at::Scalar & other) { |
| 5915 | |
| 5916 | static auto op = create_result_type_Scalar_typed_handle(); |
| 5917 | return op.redispatch(dispatchKeySet, tensor, other); |
| 5918 | } |
| 5919 | |
| 5920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar_Tensor, name, "aten::result_type") |
| 5921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar_Tensor, overload_name, "Scalar_Tensor") |
| 5922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar_Tensor, schema_str, "result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType") |
| 5923 | |
| 5924 | // aten::result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType |
| 5925 | static C10_NOINLINE c10::TypedOperatorHandle<result_type_Scalar_Tensor::schema> create_result_type_Scalar_Tensor_typed_handle() { |
| 5926 | return c10::Dispatcher::singleton() |
| 5927 | .findSchemaOrThrow(result_type_Scalar_Tensor::name, result_type_Scalar_Tensor::overload_name) |
| 5928 | .typed<result_type_Scalar_Tensor::schema>(); |
| 5929 | } |
| 5930 | |
| 5931 | // aten::result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType |
| 5932 | at::ScalarType result_type_Scalar_Tensor::call(const at::Scalar & scalar, const at::Tensor & tensor) { |
| 5933 | |
| 5934 | static auto op = create_result_type_Scalar_Tensor_typed_handle(); |
| 5935 | return op.call(scalar, tensor); |
| 5936 | } |
| 5937 | |
| 5938 | // aten::result_type.Scalar_Tensor(Scalar scalar, Tensor tensor) -> ScalarType |
| 5939 | at::ScalarType result_type_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & scalar, const at::Tensor & tensor) { |
| 5940 | |
| 5941 | static auto op = create_result_type_Scalar_Tensor_typed_handle(); |
| 5942 | return op.redispatch(dispatchKeySet, scalar, tensor); |
| 5943 | } |
| 5944 | |
| 5945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar_Scalar, name, "aten::result_type") |
| 5946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar_Scalar, overload_name, "Scalar_Scalar") |
| 5947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(result_type_Scalar_Scalar, schema_str, "result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType") |
| 5948 | |
| 5949 | // aten::result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType |
| 5950 | static C10_NOINLINE c10::TypedOperatorHandle<result_type_Scalar_Scalar::schema> create_result_type_Scalar_Scalar_typed_handle() { |
| 5951 | return c10::Dispatcher::singleton() |
| 5952 | .findSchemaOrThrow(result_type_Scalar_Scalar::name, result_type_Scalar_Scalar::overload_name) |
| 5953 | .typed<result_type_Scalar_Scalar::schema>(); |
| 5954 | } |
| 5955 | |
| 5956 | // aten::result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType |
| 5957 | at::ScalarType result_type_Scalar_Scalar::call(const at::Scalar & scalar1, const at::Scalar & scalar2) { |
| 5958 | |
| 5959 | static auto op = create_result_type_Scalar_Scalar_typed_handle(); |
| 5960 | return op.call(scalar1, scalar2); |
| 5961 | } |
| 5962 | |
| 5963 | // aten::result_type.Scalar_Scalar(Scalar scalar1, Scalar scalar2) -> ScalarType |
| 5964 | at::ScalarType result_type_Scalar_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & scalar1, const at::Scalar & scalar2) { |
| 5965 | |
| 5966 | static auto op = create_result_type_Scalar_Scalar_typed_handle(); |
| 5967 | return op.redispatch(dispatchKeySet, scalar1, scalar2); |
| 5968 | } |
| 5969 | |
| 5970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_lstm_cell_backward, name, "aten::_thnn_fused_lstm_cell_backward") |
| 5971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_lstm_cell_backward, overload_name, "") |
| 5972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_lstm_cell_backward, schema_str, "_thnn_fused_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor)") |
| 5973 | |
| 5974 | // aten::_thnn_fused_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 5975 | static C10_NOINLINE c10::TypedOperatorHandle<_thnn_fused_lstm_cell_backward::schema> create__thnn_fused_lstm_cell_backward_typed_handle() { |
| 5976 | return c10::Dispatcher::singleton() |
| 5977 | .findSchemaOrThrow(_thnn_fused_lstm_cell_backward::name, _thnn_fused_lstm_cell_backward::overload_name) |
| 5978 | .typed<_thnn_fused_lstm_cell_backward::schema>(); |
| 5979 | } |
| 5980 | |
| 5981 | // aten::_thnn_fused_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 5982 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_fused_lstm_cell_backward::call(const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias) { |
| 5983 | |
| 5984 | static auto op = create__thnn_fused_lstm_cell_backward_typed_handle(); |
| 5985 | return op.call(grad_hy, grad_cy, cx, cy, workspace, has_bias); |
| 5986 | } |
| 5987 | |
| 5988 | // aten::_thnn_fused_lstm_cell_backward(Tensor? grad_hy, Tensor? grad_cy, Tensor cx, Tensor cy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
| 5989 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_fused_lstm_cell_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, const at::Tensor & cx, const at::Tensor & cy, const at::Tensor & workspace, bool has_bias) { |
| 5990 | |
| 5991 | static auto op = create__thnn_fused_lstm_cell_backward_typed_handle(); |
| 5992 | return op.redispatch(dispatchKeySet, grad_hy, grad_cy, cx, cy, workspace, has_bias); |
| 5993 | } |
| 5994 | |
| 5995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lstm_cell, name, "aten::lstm_cell") |
| 5996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lstm_cell, overload_name, "") |
| 5997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lstm_cell, schema_str, "lstm_cell(Tensor input, Tensor[] hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> (Tensor, Tensor)") |
| 5998 | |
| 5999 | // aten::lstm_cell(Tensor input, Tensor[] hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> (Tensor, Tensor) |
| 6000 | static C10_NOINLINE c10::TypedOperatorHandle<lstm_cell::schema> create_lstm_cell_typed_handle() { |
| 6001 | return c10::Dispatcher::singleton() |
| 6002 | .findSchemaOrThrow(lstm_cell::name, lstm_cell::overload_name) |
| 6003 | .typed<lstm_cell::schema>(); |
| 6004 | } |
| 6005 | |
| 6006 | // aten::lstm_cell(Tensor input, Tensor[] hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> (Tensor, Tensor) |
| 6007 | ::std::tuple<at::Tensor,at::Tensor> lstm_cell::call(const at::Tensor & input, at::TensorList 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) { |
| 6008 | |
| 6009 | static auto op = create_lstm_cell_typed_handle(); |
| 6010 | return op.call(input, hx, w_ih, w_hh, b_ih, b_hh); |
| 6011 | } |
| 6012 | |
| 6013 | // aten::lstm_cell(Tensor input, Tensor[] hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> (Tensor, Tensor) |
| 6014 | ::std::tuple<at::Tensor,at::Tensor> lstm_cell::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList 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) { |
| 6015 | |
| 6016 | static auto op = create_lstm_cell_typed_handle(); |
| 6017 | return op.redispatch(dispatchKeySet, input, hx, w_ih, w_hh, b_ih, b_hh); |
| 6018 | } |
| 6019 | |
| 6020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_rnn_relu_cell, name, "aten::quantized_rnn_relu_cell") |
| 6021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_rnn_relu_cell, overload_name, "") |
| 6022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_rnn_relu_cell, schema_str, "quantized_rnn_relu_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") |
| 6023 | |
| 6024 | // aten::quantized_rnn_relu_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 |
| 6025 | static C10_NOINLINE c10::TypedOperatorHandle<quantized_rnn_relu_cell::schema> create_quantized_rnn_relu_cell_typed_handle() { |
| 6026 | return c10::Dispatcher::singleton() |
| 6027 | .findSchemaOrThrow(quantized_rnn_relu_cell::name, quantized_rnn_relu_cell::overload_name) |
| 6028 | .typed<quantized_rnn_relu_cell::schema>(); |
| 6029 | } |
| 6030 | |
| 6031 | // aten::quantized_rnn_relu_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 |
| 6032 | at::Tensor quantized_rnn_relu_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) { |
| 6033 | |
| 6034 | static auto op = create_quantized_rnn_relu_cell_typed_handle(); |
| 6035 | 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); |
| 6036 | } |
| 6037 | |
| 6038 | // aten::quantized_rnn_relu_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 |
| 6039 | at::Tensor quantized_rnn_relu_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) { |
| 6040 | |
| 6041 | static auto op = create_quantized_rnn_relu_cell_typed_handle(); |
| 6042 | 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); |
| 6043 | } |
| 6044 | |
| 6045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill__Scalar, name, "aten::masked_fill_") |
| 6046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill__Scalar, overload_name, "Scalar") |
| 6047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill__Scalar, schema_str, "masked_fill_.Scalar(Tensor(a!) self, Tensor mask, Scalar value) -> Tensor(a!)") |
| 6048 | |
| 6049 | // aten::masked_fill_.Scalar(Tensor(a!) self, Tensor mask, Scalar value) -> Tensor(a!) |
| 6050 | static C10_NOINLINE c10::TypedOperatorHandle<masked_fill__Scalar::schema> create_masked_fill__Scalar_typed_handle() { |
| 6051 | return c10::Dispatcher::singleton() |
| 6052 | .findSchemaOrThrow(masked_fill__Scalar::name, masked_fill__Scalar::overload_name) |
| 6053 | .typed<masked_fill__Scalar::schema>(); |
| 6054 | } |
| 6055 | |
| 6056 | // aten::masked_fill_.Scalar(Tensor(a!) self, Tensor mask, Scalar value) -> Tensor(a!) |
| 6057 | at::Tensor & masked_fill__Scalar::call(at::Tensor & self, const at::Tensor & mask, const at::Scalar & value) { |
| 6058 | |
| 6059 | static auto op = create_masked_fill__Scalar_typed_handle(); |
| 6060 | return op.call(self, mask, value); |
| 6061 | } |
| 6062 | |
| 6063 | // aten::masked_fill_.Scalar(Tensor(a!) self, Tensor mask, Scalar value) -> Tensor(a!) |
| 6064 | at::Tensor & masked_fill__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & mask, const at::Scalar & value) { |
| 6065 | |
| 6066 | static auto op = create_masked_fill__Scalar_typed_handle(); |
| 6067 | return op.redispatch(dispatchKeySet, self, mask, value); |
| 6068 | } |
| 6069 | |
| 6070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Scalar, name, "aten::masked_fill") |
| 6071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Scalar, overload_name, "Scalar") |
| 6072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Scalar, schema_str, "masked_fill.Scalar(Tensor self, Tensor mask, Scalar value) -> Tensor") |
| 6073 | |
| 6074 | // aten::masked_fill.Scalar(Tensor self, Tensor mask, Scalar value) -> Tensor |
| 6075 | static C10_NOINLINE c10::TypedOperatorHandle<masked_fill_Scalar::schema> create_masked_fill_Scalar_typed_handle() { |
| 6076 | return c10::Dispatcher::singleton() |
| 6077 | .findSchemaOrThrow(masked_fill_Scalar::name, masked_fill_Scalar::overload_name) |
| 6078 | .typed<masked_fill_Scalar::schema>(); |
| 6079 | } |
| 6080 | |
| 6081 | // aten::masked_fill.Scalar(Tensor self, Tensor mask, Scalar value) -> Tensor |
| 6082 | at::Tensor masked_fill_Scalar::call(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value) { |
| 6083 | |
| 6084 | static auto op = create_masked_fill_Scalar_typed_handle(); |
| 6085 | return op.call(self, mask, value); |
| 6086 | } |
| 6087 | |
| 6088 | // aten::masked_fill.Scalar(Tensor self, Tensor mask, Scalar value) -> Tensor |
| 6089 | at::Tensor masked_fill_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value) { |
| 6090 | |
| 6091 | static auto op = create_masked_fill_Scalar_typed_handle(); |
| 6092 | return op.redispatch(dispatchKeySet, self, mask, value); |
| 6093 | } |
| 6094 | |
| 6095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill__Tensor, name, "aten::masked_fill_") |
| 6096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill__Tensor, overload_name, "Tensor") |
| 6097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill__Tensor, schema_str, "masked_fill_.Tensor(Tensor(a!) self, Tensor mask, Tensor value) -> Tensor(a!)") |
| 6098 | |
| 6099 | // aten::masked_fill_.Tensor(Tensor(a!) self, Tensor mask, Tensor value) -> Tensor(a!) |
| 6100 | static C10_NOINLINE c10::TypedOperatorHandle<masked_fill__Tensor::schema> create_masked_fill__Tensor_typed_handle() { |
| 6101 | return c10::Dispatcher::singleton() |
| 6102 | .findSchemaOrThrow(masked_fill__Tensor::name, masked_fill__Tensor::overload_name) |
| 6103 | .typed<masked_fill__Tensor::schema>(); |
| 6104 | } |
| 6105 | |
| 6106 | // aten::masked_fill_.Tensor(Tensor(a!) self, Tensor mask, Tensor value) -> Tensor(a!) |
| 6107 | at::Tensor & masked_fill__Tensor::call(at::Tensor & self, const at::Tensor & mask, const at::Tensor & value) { |
| 6108 | |
| 6109 | static auto op = create_masked_fill__Tensor_typed_handle(); |
| 6110 | return op.call(self, mask, value); |
| 6111 | } |
| 6112 | |
| 6113 | // aten::masked_fill_.Tensor(Tensor(a!) self, Tensor mask, Tensor value) -> Tensor(a!) |
| 6114 | at::Tensor & masked_fill__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & mask, const at::Tensor & value) { |
| 6115 | |
| 6116 | static auto op = create_masked_fill__Tensor_typed_handle(); |
| 6117 | return op.redispatch(dispatchKeySet, self, mask, value); |
| 6118 | } |
| 6119 | |
| 6120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Tensor, name, "aten::masked_fill") |
| 6121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Tensor, overload_name, "Tensor") |
| 6122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Tensor, schema_str, "masked_fill.Tensor(Tensor self, Tensor mask, Tensor value) -> Tensor") |
| 6123 | |
| 6124 | // aten::masked_fill.Tensor(Tensor self, Tensor mask, Tensor value) -> Tensor |
| 6125 | static C10_NOINLINE c10::TypedOperatorHandle<masked_fill_Tensor::schema> create_masked_fill_Tensor_typed_handle() { |
| 6126 | return c10::Dispatcher::singleton() |
| 6127 | .findSchemaOrThrow(masked_fill_Tensor::name, masked_fill_Tensor::overload_name) |
| 6128 | .typed<masked_fill_Tensor::schema>(); |
| 6129 | } |
| 6130 | |
| 6131 | // aten::masked_fill.Tensor(Tensor self, Tensor mask, Tensor value) -> Tensor |
| 6132 | at::Tensor masked_fill_Tensor::call(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value) { |
| 6133 | |
| 6134 | static auto op = create_masked_fill_Tensor_typed_handle(); |
| 6135 | return op.call(self, mask, value); |
| 6136 | } |
| 6137 | |
| 6138 | // aten::masked_fill.Tensor(Tensor self, Tensor mask, Tensor value) -> Tensor |
| 6139 | at::Tensor masked_fill_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value) { |
| 6140 | |
| 6141 | static auto op = create_masked_fill_Tensor_typed_handle(); |
| 6142 | return op.redispatch(dispatchKeySet, self, mask, value); |
| 6143 | } |
| 6144 | |
| 6145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter_, name, "aten::masked_scatter_") |
| 6146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter_, overload_name, "") |
| 6147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter_, schema_str, "masked_scatter_(Tensor(a!) self, Tensor mask, Tensor source) -> Tensor(a!)") |
| 6148 | |
| 6149 | // aten::masked_scatter_(Tensor(a!) self, Tensor mask, Tensor source) -> Tensor(a!) |
| 6150 | static C10_NOINLINE c10::TypedOperatorHandle<masked_scatter_::schema> create_masked_scatter__typed_handle() { |
| 6151 | return c10::Dispatcher::singleton() |
| 6152 | .findSchemaOrThrow(masked_scatter_::name, masked_scatter_::overload_name) |
| 6153 | .typed<masked_scatter_::schema>(); |
| 6154 | } |
| 6155 | |
| 6156 | // aten::masked_scatter_(Tensor(a!) self, Tensor mask, Tensor source) -> Tensor(a!) |
| 6157 | at::Tensor & masked_scatter_::call(at::Tensor & self, const at::Tensor & mask, const at::Tensor & source) { |
| 6158 | |
| 6159 | static auto op = create_masked_scatter__typed_handle(); |
| 6160 | return op.call(self, mask, source); |
| 6161 | } |
| 6162 | |
| 6163 | // aten::masked_scatter_(Tensor(a!) self, Tensor mask, Tensor source) -> Tensor(a!) |
| 6164 | at::Tensor & masked_scatter_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & mask, const at::Tensor & source) { |
| 6165 | |
| 6166 | static auto op = create_masked_scatter__typed_handle(); |
| 6167 | return op.redispatch(dispatchKeySet, self, mask, source); |
| 6168 | } |
| 6169 | |
| 6170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter, name, "aten::masked_scatter") |
| 6171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter, overload_name, "") |
| 6172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter, schema_str, "masked_scatter(Tensor self, Tensor mask, Tensor source) -> Tensor") |
| 6173 | |
| 6174 | // aten::masked_scatter(Tensor self, Tensor mask, Tensor source) -> Tensor |
| 6175 | static C10_NOINLINE c10::TypedOperatorHandle<masked_scatter::schema> create_masked_scatter_typed_handle() { |
| 6176 | return c10::Dispatcher::singleton() |
| 6177 | .findSchemaOrThrow(masked_scatter::name, masked_scatter::overload_name) |
| 6178 | .typed<masked_scatter::schema>(); |
| 6179 | } |
| 6180 | |
| 6181 | // aten::masked_scatter(Tensor self, Tensor mask, Tensor source) -> Tensor |
| 6182 | at::Tensor masked_scatter::call(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source) { |
| 6183 | |
| 6184 | static auto op = create_masked_scatter_typed_handle(); |
| 6185 | return op.call(self, mask, source); |
| 6186 | } |
| 6187 | |
| 6188 | // aten::masked_scatter(Tensor self, Tensor mask, Tensor source) -> Tensor |
| 6189 | at::Tensor masked_scatter::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source) { |
| 6190 | |
| 6191 | static auto op = create_masked_scatter_typed_handle(); |
| 6192 | return op.redispatch(dispatchKeySet, self, mask, source); |
| 6193 | } |
| 6194 | |
| 6195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_softmax_backward, name, "aten::_masked_softmax_backward") |
| 6196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_softmax_backward, overload_name, "") |
| 6197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_softmax_backward, schema_str, "_masked_softmax_backward(Tensor grad_output, Tensor output, Tensor mask, int? dim=None) -> Tensor") |
| 6198 | |
| 6199 | // aten::_masked_softmax_backward(Tensor grad_output, Tensor output, Tensor mask, int? dim=None) -> Tensor |
| 6200 | static C10_NOINLINE c10::TypedOperatorHandle<_masked_softmax_backward::schema> create__masked_softmax_backward_typed_handle() { |
| 6201 | return c10::Dispatcher::singleton() |
| 6202 | .findSchemaOrThrow(_masked_softmax_backward::name, _masked_softmax_backward::overload_name) |
| 6203 | .typed<_masked_softmax_backward::schema>(); |
| 6204 | } |
| 6205 | |
| 6206 | // aten::_masked_softmax_backward(Tensor grad_output, Tensor output, Tensor mask, int? dim=None) -> Tensor |
| 6207 | at::Tensor _masked_softmax_backward::call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & mask, c10::optional<int64_t> dim) { |
| 6208 | |
| 6209 | static auto op = create__masked_softmax_backward_typed_handle(); |
| 6210 | return op.call(grad_output, output, mask, dim); |
| 6211 | } |
| 6212 | |
| 6213 | // aten::_masked_softmax_backward(Tensor grad_output, Tensor output, Tensor mask, int? dim=None) -> Tensor |
| 6214 | at::Tensor _masked_softmax_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & mask, c10::optional<int64_t> dim) { |
| 6215 | |
| 6216 | static auto op = create__masked_softmax_backward_typed_handle(); |
| 6217 | return op.redispatch(dispatchKeySet, grad_output, output, mask, dim); |
| 6218 | } |
| 6219 | |
| 6220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_out, name, "aten::index_add") |
| 6221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_out, overload_name, "out") |
| 6222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_out, schema_str, "index_add.out(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)") |
| 6223 | |
| 6224 | // aten::index_add.out(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6225 | static C10_NOINLINE c10::TypedOperatorHandle<index_add_out::schema> create_index_add_out_typed_handle() { |
| 6226 | return c10::Dispatcher::singleton() |
| 6227 | .findSchemaOrThrow(index_add_out::name, index_add_out::overload_name) |
| 6228 | .typed<index_add_out::schema>(); |
| 6229 | } |
| 6230 | |
| 6231 | // aten::index_add.out(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6232 | at::Tensor & index_add_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha, at::Tensor & out) { |
| 6233 | |
| 6234 | static auto op = create_index_add_out_typed_handle(); |
| 6235 | return op.call(self, dim, index, source, alpha, out); |
| 6236 | } |
| 6237 | |
| 6238 | // aten::index_add.out(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
| 6239 | at::Tensor & index_add_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha, at::Tensor & out) { |
| 6240 | |
| 6241 | static auto op = create_index_add_out_typed_handle(); |
| 6242 | return op.redispatch(dispatchKeySet, self, dim, index, source, alpha, out); |
| 6243 | } |
| 6244 | |
| 6245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_, name, "aten::index_add_") |
| 6246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_, overload_name, "") |
| 6247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_, schema_str, "index_add_(Tensor(a!) self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor(a!)") |
| 6248 | |
| 6249 | // aten::index_add_(Tensor(a!) self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor(a!) |
| 6250 | static C10_NOINLINE c10::TypedOperatorHandle<index_add_::schema> create_index_add__typed_handle() { |
| 6251 | return c10::Dispatcher::singleton() |
| 6252 | .findSchemaOrThrow(index_add_::name, index_add_::overload_name) |
| 6253 | .typed<index_add_::schema>(); |
| 6254 | } |
| 6255 | |
| 6256 | // aten::index_add_(Tensor(a!) self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor(a!) |
| 6257 | at::Tensor & index_add_::call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha) { |
| 6258 | |
| 6259 | static auto op = create_index_add__typed_handle(); |
| 6260 | return op.call(self, dim, index, source, alpha); |
| 6261 | } |
| 6262 | |
| 6263 | // aten::index_add_(Tensor(a!) self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor(a!) |
| 6264 | at::Tensor & index_add_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha) { |
| 6265 | |
| 6266 | static auto op = create_index_add__typed_handle(); |
| 6267 | return op.redispatch(dispatchKeySet, self, dim, index, source, alpha); |
| 6268 | } |
| 6269 | |
| 6270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add, name, "aten::index_add") |
| 6271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add, overload_name, "") |
| 6272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add, schema_str, "index_add(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor") |
| 6273 | |
| 6274 | // aten::index_add(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor |
| 6275 | static C10_NOINLINE c10::TypedOperatorHandle<index_add::schema> create_index_add_typed_handle() { |
| 6276 | return c10::Dispatcher::singleton() |
| 6277 | .findSchemaOrThrow(index_add::name, index_add::overload_name) |
| 6278 | .typed<index_add::schema>(); |
| 6279 | } |
| 6280 | |
| 6281 | // aten::index_add(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor |
| 6282 | at::Tensor index_add::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha) { |
| 6283 | |
| 6284 | static auto op = create_index_add_typed_handle(); |
| 6285 | return op.call(self, dim, index, source, alpha); |
| 6286 | } |
| 6287 | |
| 6288 | // aten::index_add(Tensor self, int dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor |
| 6289 | at::Tensor index_add::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha) { |
| 6290 | |
| 6291 | static auto op = create_index_add_typed_handle(); |
| 6292 | return op.redispatch(dispatchKeySet, self, dim, index, source, alpha); |
| 6293 | } |
| 6294 | |
| 6295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_dimname, name, "aten::index_add") |
| 6296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_dimname, overload_name, "dimname") |
| 6297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_add_dimname, schema_str, "index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor") |
| 6298 | |
| 6299 | // aten::index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor |
| 6300 | static C10_NOINLINE c10::TypedOperatorHandle<index_add_dimname::schema> create_index_add_dimname_typed_handle() { |
| 6301 | return c10::Dispatcher::singleton() |
| 6302 | .findSchemaOrThrow(index_add_dimname::name, index_add_dimname::overload_name) |
| 6303 | .typed<index_add_dimname::schema>(); |
| 6304 | } |
| 6305 | |
| 6306 | // aten::index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor |
| 6307 | at::Tensor index_add_dimname::call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha) { |
| 6308 | |
| 6309 | static auto op = create_index_add_dimname_typed_handle(); |
| 6310 | return op.call(self, dim, index, source, alpha); |
| 6311 | } |
| 6312 | |
| 6313 | // aten::index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source, *, Scalar alpha=1) -> Tensor |
| 6314 | at::Tensor index_add_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & source, const at::Scalar & alpha) { |
| 6315 | |
| 6316 | static auto op = create_index_add_dimname_typed_handle(); |
| 6317 | return op.redispatch(dispatchKeySet, self, dim, index, source, alpha); |
| 6318 | } |
| 6319 | |
| 6320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Tensor_out, name, "aten::bitwise_or") |
| 6321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Tensor_out, overload_name, "Tensor_out") |
| 6322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Tensor_out, schema_str, "bitwise_or.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 6323 | |
| 6324 | // aten::bitwise_or.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6325 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or_Tensor_out::schema> create_bitwise_or_Tensor_out_typed_handle() { |
| 6326 | return c10::Dispatcher::singleton() |
| 6327 | .findSchemaOrThrow(bitwise_or_Tensor_out::name, bitwise_or_Tensor_out::overload_name) |
| 6328 | .typed<bitwise_or_Tensor_out::schema>(); |
| 6329 | } |
| 6330 | |
| 6331 | // aten::bitwise_or.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6332 | at::Tensor & bitwise_or_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 6333 | |
| 6334 | static auto op = create_bitwise_or_Tensor_out_typed_handle(); |
| 6335 | return op.call(self, other, out); |
| 6336 | } |
| 6337 | |
| 6338 | // aten::bitwise_or.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6339 | at::Tensor & bitwise_or_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 6340 | |
| 6341 | static auto op = create_bitwise_or_Tensor_out_typed_handle(); |
| 6342 | return op.redispatch(dispatchKeySet, self, other, out); |
| 6343 | } |
| 6344 | |
| 6345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_out, name, "aten::bitwise_or") |
| 6346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_out, overload_name, "Scalar_out") |
| 6347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_out, schema_str, "bitwise_or.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 6348 | |
| 6349 | // aten::bitwise_or.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 6350 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or_Scalar_out::schema> create_bitwise_or_Scalar_out_typed_handle() { |
| 6351 | return c10::Dispatcher::singleton() |
| 6352 | .findSchemaOrThrow(bitwise_or_Scalar_out::name, bitwise_or_Scalar_out::overload_name) |
| 6353 | .typed<bitwise_or_Scalar_out::schema>(); |
| 6354 | } |
| 6355 | |
| 6356 | // aten::bitwise_or.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 6357 | at::Tensor & bitwise_or_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 6358 | |
| 6359 | static auto op = create_bitwise_or_Scalar_out_typed_handle(); |
| 6360 | return op.call(self, other, out); |
| 6361 | } |
| 6362 | |
| 6363 | // aten::bitwise_or.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 6364 | at::Tensor & bitwise_or_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 6365 | |
| 6366 | static auto op = create_bitwise_or_Scalar_out_typed_handle(); |
| 6367 | return op.redispatch(dispatchKeySet, self, other, out); |
| 6368 | } |
| 6369 | |
| 6370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar, name, "aten::bitwise_or") |
| 6371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar, overload_name, "Scalar") |
| 6372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar, schema_str, "bitwise_or.Scalar(Tensor self, Scalar other) -> Tensor") |
| 6373 | |
| 6374 | // aten::bitwise_or.Scalar(Tensor self, Scalar other) -> Tensor |
| 6375 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or_Scalar::schema> create_bitwise_or_Scalar_typed_handle() { |
| 6376 | return c10::Dispatcher::singleton() |
| 6377 | .findSchemaOrThrow(bitwise_or_Scalar::name, bitwise_or_Scalar::overload_name) |
| 6378 | .typed<bitwise_or_Scalar::schema>(); |
| 6379 | } |
| 6380 | |
| 6381 | // aten::bitwise_or.Scalar(Tensor self, Scalar other) -> Tensor |
| 6382 | at::Tensor bitwise_or_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 6383 | |
| 6384 | static auto op = create_bitwise_or_Scalar_typed_handle(); |
| 6385 | return op.call(self, other); |
| 6386 | } |
| 6387 | |
| 6388 | // aten::bitwise_or.Scalar(Tensor self, Scalar other) -> Tensor |
| 6389 | at::Tensor bitwise_or_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 6390 | |
| 6391 | static auto op = create_bitwise_or_Scalar_typed_handle(); |
| 6392 | return op.redispatch(dispatchKeySet, self, other); |
| 6393 | } |
| 6394 | |
| 6395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_Tensor, name, "aten::bitwise_or") |
| 6396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_Tensor, overload_name, "Scalar_Tensor") |
| 6397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_Tensor, schema_str, "bitwise_or.Scalar_Tensor(Scalar self, Tensor other) -> Tensor") |
| 6398 | |
| 6399 | // aten::bitwise_or.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 6400 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or_Scalar_Tensor::schema> create_bitwise_or_Scalar_Tensor_typed_handle() { |
| 6401 | return c10::Dispatcher::singleton() |
| 6402 | .findSchemaOrThrow(bitwise_or_Scalar_Tensor::name, bitwise_or_Scalar_Tensor::overload_name) |
| 6403 | .typed<bitwise_or_Scalar_Tensor::schema>(); |
| 6404 | } |
| 6405 | |
| 6406 | // aten::bitwise_or.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 6407 | at::Tensor bitwise_or_Scalar_Tensor::call(const at::Scalar & self, const at::Tensor & other) { |
| 6408 | |
| 6409 | static auto op = create_bitwise_or_Scalar_Tensor_typed_handle(); |
| 6410 | return op.call(self, other); |
| 6411 | } |
| 6412 | |
| 6413 | // aten::bitwise_or.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 6414 | at::Tensor bitwise_or_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other) { |
| 6415 | |
| 6416 | static auto op = create_bitwise_or_Scalar_Tensor_typed_handle(); |
| 6417 | return op.redispatch(dispatchKeySet, self, other); |
| 6418 | } |
| 6419 | |
| 6420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Tensor, name, "aten::bitwise_or") |
| 6421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Tensor, overload_name, "Tensor") |
| 6422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Tensor, schema_str, "bitwise_or.Tensor(Tensor self, Tensor other) -> Tensor") |
| 6423 | |
| 6424 | // aten::bitwise_or.Tensor(Tensor self, Tensor other) -> Tensor |
| 6425 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or_Tensor::schema> create_bitwise_or_Tensor_typed_handle() { |
| 6426 | return c10::Dispatcher::singleton() |
| 6427 | .findSchemaOrThrow(bitwise_or_Tensor::name, bitwise_or_Tensor::overload_name) |
| 6428 | .typed<bitwise_or_Tensor::schema>(); |
| 6429 | } |
| 6430 | |
| 6431 | // aten::bitwise_or.Tensor(Tensor self, Tensor other) -> Tensor |
| 6432 | at::Tensor bitwise_or_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 6433 | |
| 6434 | static auto op = create_bitwise_or_Tensor_typed_handle(); |
| 6435 | return op.call(self, other); |
| 6436 | } |
| 6437 | |
| 6438 | // aten::bitwise_or.Tensor(Tensor self, Tensor other) -> Tensor |
| 6439 | at::Tensor bitwise_or_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 6440 | |
| 6441 | static auto op = create_bitwise_or_Tensor_typed_handle(); |
| 6442 | return op.redispatch(dispatchKeySet, self, other); |
| 6443 | } |
| 6444 | |
| 6445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or__Scalar, name, "aten::bitwise_or_") |
| 6446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or__Scalar, overload_name, "Scalar") |
| 6447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or__Scalar, schema_str, "bitwise_or_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 6448 | |
| 6449 | // aten::bitwise_or_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 6450 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or__Scalar::schema> create_bitwise_or__Scalar_typed_handle() { |
| 6451 | return c10::Dispatcher::singleton() |
| 6452 | .findSchemaOrThrow(bitwise_or__Scalar::name, bitwise_or__Scalar::overload_name) |
| 6453 | .typed<bitwise_or__Scalar::schema>(); |
| 6454 | } |
| 6455 | |
| 6456 | // aten::bitwise_or_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 6457 | at::Tensor & bitwise_or__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 6458 | |
| 6459 | static auto op = create_bitwise_or__Scalar_typed_handle(); |
| 6460 | return op.call(self, other); |
| 6461 | } |
| 6462 | |
| 6463 | // aten::bitwise_or_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 6464 | at::Tensor & bitwise_or__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 6465 | |
| 6466 | static auto op = create_bitwise_or__Scalar_typed_handle(); |
| 6467 | return op.redispatch(dispatchKeySet, self, other); |
| 6468 | } |
| 6469 | |
| 6470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or__Tensor, name, "aten::bitwise_or_") |
| 6471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or__Tensor, overload_name, "Tensor") |
| 6472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or__Tensor, schema_str, "bitwise_or_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 6473 | |
| 6474 | // aten::bitwise_or_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 6475 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or__Tensor::schema> create_bitwise_or__Tensor_typed_handle() { |
| 6476 | return c10::Dispatcher::singleton() |
| 6477 | .findSchemaOrThrow(bitwise_or__Tensor::name, bitwise_or__Tensor::overload_name) |
| 6478 | .typed<bitwise_or__Tensor::schema>(); |
| 6479 | } |
| 6480 | |
| 6481 | // aten::bitwise_or_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 6482 | at::Tensor & bitwise_or__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 6483 | |
| 6484 | static auto op = create_bitwise_or__Tensor_typed_handle(); |
| 6485 | return op.call(self, other); |
| 6486 | } |
| 6487 | |
| 6488 | // aten::bitwise_or_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 6489 | at::Tensor & bitwise_or__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 6490 | |
| 6491 | static auto op = create_bitwise_or__Tensor_typed_handle(); |
| 6492 | return op.redispatch(dispatchKeySet, self, other); |
| 6493 | } |
| 6494 | |
| 6495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diag_out, name, "aten::diag") |
| 6496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diag_out, overload_name, "out") |
| 6497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diag_out, schema_str, "diag.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)") |
| 6498 | |
| 6499 | // aten::diag.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) |
| 6500 | static C10_NOINLINE c10::TypedOperatorHandle<diag_out::schema> create_diag_out_typed_handle() { |
| 6501 | return c10::Dispatcher::singleton() |
| 6502 | .findSchemaOrThrow(diag_out::name, diag_out::overload_name) |
| 6503 | .typed<diag_out::schema>(); |
| 6504 | } |
| 6505 | |
| 6506 | // aten::diag.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) |
| 6507 | at::Tensor & diag_out::call(const at::Tensor & self, int64_t diagonal, at::Tensor & out) { |
| 6508 | |
| 6509 | static auto op = create_diag_out_typed_handle(); |
| 6510 | return op.call(self, diagonal, out); |
| 6511 | } |
| 6512 | |
| 6513 | // aten::diag.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) |
| 6514 | at::Tensor & diag_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal, at::Tensor & out) { |
| 6515 | |
| 6516 | static auto op = create_diag_out_typed_handle(); |
| 6517 | return op.redispatch(dispatchKeySet, self, diagonal, out); |
| 6518 | } |
| 6519 | |
| 6520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diag, name, "aten::diag") |
| 6521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diag, overload_name, "") |
| 6522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diag, schema_str, "diag(Tensor self, int diagonal=0) -> Tensor") |
| 6523 | |
| 6524 | // aten::diag(Tensor self, int diagonal=0) -> Tensor |
| 6525 | static C10_NOINLINE c10::TypedOperatorHandle<diag::schema> create_diag_typed_handle() { |
| 6526 | return c10::Dispatcher::singleton() |
| 6527 | .findSchemaOrThrow(diag::name, diag::overload_name) |
| 6528 | .typed<diag::schema>(); |
| 6529 | } |
| 6530 | |
| 6531 | // aten::diag(Tensor self, int diagonal=0) -> Tensor |
| 6532 | at::Tensor diag::call(const at::Tensor & self, int64_t diagonal) { |
| 6533 | |
| 6534 | static auto op = create_diag_typed_handle(); |
| 6535 | return op.call(self, diagonal); |
| 6536 | } |
| 6537 | |
| 6538 | // aten::diag(Tensor self, int diagonal=0) -> Tensor |
| 6539 | at::Tensor diag::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal) { |
| 6540 | |
| 6541 | static auto op = create_diag_typed_handle(); |
| 6542 | return op.redispatch(dispatchKeySet, self, diagonal); |
| 6543 | } |
| 6544 | |
| 6545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triu_indices, name, "aten::triu_indices") |
| 6546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triu_indices, overload_name, "") |
| 6547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triu_indices, schema_str, "triu_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor") |
| 6548 | |
| 6549 | // aten::triu_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6550 | static C10_NOINLINE c10::TypedOperatorHandle<triu_indices::schema> create_triu_indices_typed_handle() { |
| 6551 | return c10::Dispatcher::singleton() |
| 6552 | .findSchemaOrThrow(triu_indices::name, triu_indices::overload_name) |
| 6553 | .typed<triu_indices::schema>(); |
| 6554 | } |
| 6555 | |
| 6556 | // aten::triu_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6557 | at::Tensor triu_indices::call(int64_t row, int64_t col, int64_t offset, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6558 | |
| 6559 | static auto op = create_triu_indices_typed_handle(); |
| 6560 | return op.call(row, col, offset, dtype, layout, device, pin_memory); |
| 6561 | } |
| 6562 | |
| 6563 | // aten::triu_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
| 6564 | at::Tensor triu_indices::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t row, int64_t col, int64_t offset, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
| 6565 | |
| 6566 | static auto op = create_triu_indices_typed_handle(); |
| 6567 | return op.redispatch(dispatchKeySet, row, col, offset, dtype, layout, device, pin_memory); |
| 6568 | } |
| 6569 | |
| 6570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace, name, "aten::trace") |
| 6571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace, overload_name, "") |
| 6572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace, schema_str, "trace(Tensor self) -> Tensor") |
| 6573 | |
| 6574 | // aten::trace(Tensor self) -> Tensor |
| 6575 | static C10_NOINLINE c10::TypedOperatorHandle<trace::schema> create_trace_typed_handle() { |
| 6576 | return c10::Dispatcher::singleton() |
| 6577 | .findSchemaOrThrow(trace::name, trace::overload_name) |
| 6578 | .typed<trace::schema>(); |
| 6579 | } |
| 6580 | |
| 6581 | // aten::trace(Tensor self) -> Tensor |
| 6582 | at::Tensor trace::call(const at::Tensor & self) { |
| 6583 | |
| 6584 | static auto op = create_trace_typed_handle(); |
| 6585 | return op.call(self); |
| 6586 | } |
| 6587 | |
| 6588 | // aten::trace(Tensor self) -> Tensor |
| 6589 | at::Tensor trace::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 6590 | |
| 6591 | static auto op = create_trace_typed_handle(); |
| 6592 | return op.redispatch(dispatchKeySet, self); |
| 6593 | } |
| 6594 | |
| 6595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Scalar_out, name, "aten::greater_equal") |
| 6596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Scalar_out, overload_name, "Scalar_out") |
| 6597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Scalar_out, schema_str, "greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 6598 | |
| 6599 | // aten::greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 6600 | static C10_NOINLINE c10::TypedOperatorHandle<greater_equal_Scalar_out::schema> create_greater_equal_Scalar_out_typed_handle() { |
| 6601 | return c10::Dispatcher::singleton() |
| 6602 | .findSchemaOrThrow(greater_equal_Scalar_out::name, greater_equal_Scalar_out::overload_name) |
| 6603 | .typed<greater_equal_Scalar_out::schema>(); |
| 6604 | } |
| 6605 | |
| 6606 | // aten::greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 6607 | at::Tensor & greater_equal_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 6608 | |
| 6609 | static auto op = create_greater_equal_Scalar_out_typed_handle(); |
| 6610 | return op.call(self, other, out); |
| 6611 | } |
| 6612 | |
| 6613 | // aten::greater_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 6614 | at::Tensor & greater_equal_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 6615 | |
| 6616 | static auto op = create_greater_equal_Scalar_out_typed_handle(); |
| 6617 | return op.redispatch(dispatchKeySet, self, other, out); |
| 6618 | } |
| 6619 | |
| 6620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Scalar, name, "aten::greater_equal") |
| 6621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Scalar, overload_name, "Scalar") |
| 6622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Scalar, schema_str, "greater_equal.Scalar(Tensor self, Scalar other) -> Tensor") |
| 6623 | |
| 6624 | // aten::greater_equal.Scalar(Tensor self, Scalar other) -> Tensor |
| 6625 | static C10_NOINLINE c10::TypedOperatorHandle<greater_equal_Scalar::schema> create_greater_equal_Scalar_typed_handle() { |
| 6626 | return c10::Dispatcher::singleton() |
| 6627 | .findSchemaOrThrow(greater_equal_Scalar::name, greater_equal_Scalar::overload_name) |
| 6628 | .typed<greater_equal_Scalar::schema>(); |
| 6629 | } |
| 6630 | |
| 6631 | // aten::greater_equal.Scalar(Tensor self, Scalar other) -> Tensor |
| 6632 | at::Tensor greater_equal_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 6633 | |
| 6634 | static auto op = create_greater_equal_Scalar_typed_handle(); |
| 6635 | return op.call(self, other); |
| 6636 | } |
| 6637 | |
| 6638 | // aten::greater_equal.Scalar(Tensor self, Scalar other) -> Tensor |
| 6639 | at::Tensor greater_equal_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 6640 | |
| 6641 | static auto op = create_greater_equal_Scalar_typed_handle(); |
| 6642 | return op.redispatch(dispatchKeySet, self, other); |
| 6643 | } |
| 6644 | |
| 6645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Tensor_out, name, "aten::greater_equal") |
| 6646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Tensor_out, overload_name, "Tensor_out") |
| 6647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Tensor_out, schema_str, "greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 6648 | |
| 6649 | // aten::greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6650 | static C10_NOINLINE c10::TypedOperatorHandle<greater_equal_Tensor_out::schema> create_greater_equal_Tensor_out_typed_handle() { |
| 6651 | return c10::Dispatcher::singleton() |
| 6652 | .findSchemaOrThrow(greater_equal_Tensor_out::name, greater_equal_Tensor_out::overload_name) |
| 6653 | .typed<greater_equal_Tensor_out::schema>(); |
| 6654 | } |
| 6655 | |
| 6656 | // aten::greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6657 | at::Tensor & greater_equal_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 6658 | |
| 6659 | static auto op = create_greater_equal_Tensor_out_typed_handle(); |
| 6660 | return op.call(self, other, out); |
| 6661 | } |
| 6662 | |
| 6663 | // aten::greater_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 6664 | at::Tensor & greater_equal_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 6665 | |
| 6666 | static auto op = create_greater_equal_Tensor_out_typed_handle(); |
| 6667 | return op.redispatch(dispatchKeySet, self, other, out); |
| 6668 | } |
| 6669 | |
| 6670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Tensor, name, "aten::greater_equal") |
| 6671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Tensor, overload_name, "Tensor") |
| 6672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal_Tensor, schema_str, "greater_equal.Tensor(Tensor self, Tensor other) -> Tensor") |
| 6673 | |
| 6674 | // aten::greater_equal.Tensor(Tensor self, Tensor other) -> Tensor |
| 6675 | static C10_NOINLINE c10::TypedOperatorHandle<greater_equal_Tensor::schema> create_greater_equal_Tensor_typed_handle() { |
| 6676 | return c10::Dispatcher::singleton() |
| 6677 | .findSchemaOrThrow(greater_equal_Tensor::name, greater_equal_Tensor::overload_name) |
| 6678 | .typed<greater_equal_Tensor::schema>(); |
| 6679 | } |
| 6680 | |
| 6681 | // aten::greater_equal.Tensor(Tensor self, Tensor other) -> Tensor |
| 6682 | at::Tensor greater_equal_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 6683 | |
| 6684 | static auto op = create_greater_equal_Tensor_typed_handle(); |
| 6685 | return op.call(self, other); |
| 6686 | } |
| 6687 | |
| 6688 | // aten::greater_equal.Tensor(Tensor self, Tensor other) -> Tensor |
| 6689 | at::Tensor greater_equal_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 6690 | |
| 6691 | static auto op = create_greater_equal_Tensor_typed_handle(); |
| 6692 | return op.redispatch(dispatchKeySet, self, other); |
| 6693 | } |
| 6694 | |
| 6695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal__Scalar, name, "aten::greater_equal_") |
| 6696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal__Scalar, overload_name, "Scalar") |
| 6697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal__Scalar, schema_str, "greater_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 6698 | |
| 6699 | // aten::greater_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 6700 | static C10_NOINLINE c10::TypedOperatorHandle<greater_equal__Scalar::schema> create_greater_equal__Scalar_typed_handle() { |
| 6701 | return c10::Dispatcher::singleton() |
| 6702 | .findSchemaOrThrow(greater_equal__Scalar::name, greater_equal__Scalar::overload_name) |
| 6703 | .typed<greater_equal__Scalar::schema>(); |
| 6704 | } |
| 6705 | |
| 6706 | // aten::greater_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 6707 | at::Tensor & greater_equal__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 6708 | |
| 6709 | static auto op = create_greater_equal__Scalar_typed_handle(); |
| 6710 | return op.call(self, other); |
| 6711 | } |
| 6712 | |
| 6713 | // aten::greater_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 6714 | at::Tensor & greater_equal__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 6715 | |
| 6716 | static auto op = create_greater_equal__Scalar_typed_handle(); |
| 6717 | return op.redispatch(dispatchKeySet, self, other); |
| 6718 | } |
| 6719 | |
| 6720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal__Tensor, name, "aten::greater_equal_") |
| 6721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal__Tensor, overload_name, "Tensor") |
| 6722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(greater_equal__Tensor, schema_str, "greater_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 6723 | |
| 6724 | // aten::greater_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 6725 | static C10_NOINLINE c10::TypedOperatorHandle<greater_equal__Tensor::schema> create_greater_equal__Tensor_typed_handle() { |
| 6726 | return c10::Dispatcher::singleton() |
| 6727 | .findSchemaOrThrow(greater_equal__Tensor::name, greater_equal__Tensor::overload_name) |
| 6728 | .typed<greater_equal__Tensor::schema>(); |
| 6729 | } |
| 6730 | |
| 6731 | // aten::greater_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 6732 | at::Tensor & greater_equal__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 6733 | |
| 6734 | static auto op = create_greater_equal__Tensor_typed_handle(); |
| 6735 | return op.call(self, other); |
| 6736 | } |
| 6737 | |
| 6738 | // aten::greater_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 6739 | at::Tensor & greater_equal__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 6740 | |
| 6741 | static auto op = create_greater_equal__Tensor_typed_handle(); |
| 6742 | return op.redispatch(dispatchKeySet, self, other); |
| 6743 | } |
| 6744 | |
| 6745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_out, name, "aten::take") |
| 6746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_out, overload_name, "out") |
| 6747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take_out, schema_str, "take.out(Tensor self, Tensor index, *, Tensor(a!) out) -> Tensor(a!)") |
| 6748 | |
| 6749 | // aten::take.out(Tensor self, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 6750 | static C10_NOINLINE c10::TypedOperatorHandle<take_out::schema> create_take_out_typed_handle() { |
| 6751 | return c10::Dispatcher::singleton() |
| 6752 | .findSchemaOrThrow(take_out::name, take_out::overload_name) |
| 6753 | .typed<take_out::schema>(); |
| 6754 | } |
| 6755 | |
| 6756 | // aten::take.out(Tensor self, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 6757 | at::Tensor & take_out::call(const at::Tensor & self, const at::Tensor & index, at::Tensor & out) { |
| 6758 | |
| 6759 | static auto op = create_take_out_typed_handle(); |
| 6760 | return op.call(self, index, out); |
| 6761 | } |
| 6762 | |
| 6763 | // aten::take.out(Tensor self, Tensor index, *, Tensor(a!) out) -> Tensor(a!) |
| 6764 | at::Tensor & take_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & index, at::Tensor & out) { |
| 6765 | |
| 6766 | static auto op = create_take_out_typed_handle(); |
| 6767 | return op.redispatch(dispatchKeySet, self, index, out); |
| 6768 | } |
| 6769 | |
| 6770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take, name, "aten::take") |
| 6771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take, overload_name, "") |
| 6772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(take, schema_str, "take(Tensor self, Tensor index) -> Tensor") |
| 6773 | |
| 6774 | // aten::take(Tensor self, Tensor index) -> Tensor |
| 6775 | static C10_NOINLINE c10::TypedOperatorHandle<take::schema> create_take_typed_handle() { |
| 6776 | return c10::Dispatcher::singleton() |
| 6777 | .findSchemaOrThrow(take::name, take::overload_name) |
| 6778 | .typed<take::schema>(); |
| 6779 | } |
| 6780 | |
| 6781 | // aten::take(Tensor self, Tensor index) -> Tensor |
| 6782 | at::Tensor take::call(const at::Tensor & self, const at::Tensor & index) { |
| 6783 | |
| 6784 | static auto op = create_take_typed_handle(); |
| 6785 | return op.call(self, index); |
| 6786 | } |
| 6787 | |
| 6788 | // aten::take(Tensor self, Tensor index) -> Tensor |
| 6789 | at::Tensor take::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & index) { |
| 6790 | |
| 6791 | static auto op = create_take_typed_handle(); |
| 6792 | return op.redispatch(dispatchKeySet, self, index); |
| 6793 | } |
| 6794 | |
| 6795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_backward, name, "aten::index_select_backward") |
| 6796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_backward, overload_name, "") |
| 6797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_select_backward, schema_str, "index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor") |
| 6798 | |
| 6799 | // aten::index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor |
| 6800 | static C10_NOINLINE c10::TypedOperatorHandle<index_select_backward::schema> create_index_select_backward_typed_handle() { |
| 6801 | return c10::Dispatcher::singleton() |
| 6802 | .findSchemaOrThrow(index_select_backward::name, index_select_backward::overload_name) |
| 6803 | .typed<index_select_backward::schema>(); |
| 6804 | } |
| 6805 | |
| 6806 | // aten::index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor |
| 6807 | at::Tensor index_select_backward::call(const at::Tensor & grad, c10::SymIntArrayRef self_sizes, int64_t dim, const at::Tensor & index) { |
| 6808 | |
| 6809 | static auto op = create_index_select_backward_typed_handle(); |
| 6810 | return op.call(grad, self_sizes, dim, index); |
| 6811 | } |
| 6812 | |
| 6813 | // aten::index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor |
| 6814 | at::Tensor index_select_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, c10::SymIntArrayRef self_sizes, int64_t dim, const at::Tensor & index) { |
| 6815 | |
| 6816 | static auto op = create_index_select_backward_typed_handle(); |
| 6817 | return op.redispatch(dispatchKeySet, grad, self_sizes, dim, index); |
| 6818 | } |
| 6819 | |
| 6820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argwhere, name, "aten::argwhere") |
| 6821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argwhere, overload_name, "") |
| 6822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(argwhere, schema_str, "argwhere(Tensor self) -> Tensor") |
| 6823 | |
| 6824 | // aten::argwhere(Tensor self) -> Tensor |
| 6825 | static C10_NOINLINE c10::TypedOperatorHandle<argwhere::schema> create_argwhere_typed_handle() { |
| 6826 | return c10::Dispatcher::singleton() |
| 6827 | .findSchemaOrThrow(argwhere::name, argwhere::overload_name) |
| 6828 | .typed<argwhere::schema>(); |
| 6829 | } |
| 6830 | |
| 6831 | // aten::argwhere(Tensor self) -> Tensor |
| 6832 | at::Tensor argwhere::call(const at::Tensor & self) { |
| 6833 | |
| 6834 | static auto op = create_argwhere_typed_handle(); |
| 6835 | return op.call(self); |
| 6836 | } |
| 6837 | |
| 6838 | // aten::argwhere(Tensor self) -> Tensor |
| 6839 | at::Tensor argwhere::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 6840 | |
| 6841 | static auto op = create_argwhere_typed_handle(); |
| 6842 | return op.redispatch(dispatchKeySet, self); |
| 6843 | } |
| 6844 | |
| 6845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(svd_U, name, "aten::svd") |
| 6846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(svd_U, overload_name, "U") |
| 6847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(svd_U, schema_str, "svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V)") |
| 6848 | |
| 6849 | // aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) |
| 6850 | static C10_NOINLINE c10::TypedOperatorHandle<svd_U::schema> create_svd_U_typed_handle() { |
| 6851 | return c10::Dispatcher::singleton() |
| 6852 | .findSchemaOrThrow(svd_U::name, svd_U::overload_name) |
| 6853 | .typed<svd_U::schema>(); |
| 6854 | } |
| 6855 | |
| 6856 | // aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) |
| 6857 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> svd_U::call(const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V) { |
| 6858 | |
| 6859 | static auto op = create_svd_U_typed_handle(); |
| 6860 | return op.call(self, some, compute_uv, U, S, V); |
| 6861 | } |
| 6862 | |
| 6863 | // aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) |
| 6864 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> svd_U::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool some, bool compute_uv, at::Tensor & U, at::Tensor & S, at::Tensor & V) { |
| 6865 | |
| 6866 | static auto op = create_svd_U_typed_handle(); |
| 6867 | return op.redispatch(dispatchKeySet, self, some, compute_uv, U, S, V); |
| 6868 | } |
| 6869 | |
| 6870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(svd, name, "aten::svd") |
| 6871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(svd, overload_name, "") |
| 6872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(svd, schema_str, "svd(Tensor self, bool some=True, bool compute_uv=True) -> (Tensor U, Tensor S, Tensor V)") |
| 6873 | |
| 6874 | // aten::svd(Tensor self, bool some=True, bool compute_uv=True) -> (Tensor U, Tensor S, Tensor V) |
| 6875 | static C10_NOINLINE c10::TypedOperatorHandle<svd::schema> create_svd_typed_handle() { |
| 6876 | return c10::Dispatcher::singleton() |
| 6877 | .findSchemaOrThrow(svd::name, svd::overload_name) |
| 6878 | .typed<svd::schema>(); |
| 6879 | } |
| 6880 | |
| 6881 | // aten::svd(Tensor self, bool some=True, bool compute_uv=True) -> (Tensor U, Tensor S, Tensor V) |
| 6882 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> svd::call(const at::Tensor & self, bool some, bool compute_uv) { |
| 6883 | |
| 6884 | static auto op = create_svd_typed_handle(); |
| 6885 | return op.call(self, some, compute_uv); |
| 6886 | } |
| 6887 | |
| 6888 | // aten::svd(Tensor self, bool some=True, bool compute_uv=True) -> (Tensor U, Tensor S, Tensor V) |
| 6889 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> svd::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool some, bool compute_uv) { |
| 6890 | |
| 6891 | static auto op = create_svd_typed_handle(); |
| 6892 | return op.redispatch(dispatchKeySet, self, some, compute_uv); |
| 6893 | } |
| 6894 | |
| 6895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geqrf_a, name, "aten::geqrf") |
| 6896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geqrf_a, overload_name, "a") |
| 6897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geqrf_a, schema_str, "geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau)") |
| 6898 | |
| 6899 | // aten::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau) |
| 6900 | static C10_NOINLINE c10::TypedOperatorHandle<geqrf_a::schema> create_geqrf_a_typed_handle() { |
| 6901 | return c10::Dispatcher::singleton() |
| 6902 | .findSchemaOrThrow(geqrf_a::name, geqrf_a::overload_name) |
| 6903 | .typed<geqrf_a::schema>(); |
| 6904 | } |
| 6905 | |
| 6906 | // aten::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau) |
| 6907 | ::std::tuple<at::Tensor &,at::Tensor &> geqrf_a::call(const at::Tensor & self, at::Tensor & a, at::Tensor & tau) { |
| 6908 | |
| 6909 | static auto op = create_geqrf_a_typed_handle(); |
| 6910 | return op.call(self, a, tau); |
| 6911 | } |
| 6912 | |
| 6913 | // aten::geqrf.a(Tensor self, *, Tensor(a!) a, Tensor(b!) tau) -> (Tensor(a!) a, Tensor(b!) tau) |
| 6914 | ::std::tuple<at::Tensor &,at::Tensor &> geqrf_a::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & a, at::Tensor & tau) { |
| 6915 | |
| 6916 | static auto op = create_geqrf_a_typed_handle(); |
| 6917 | return op.redispatch(dispatchKeySet, self, a, tau); |
| 6918 | } |
| 6919 | |
| 6920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geqrf, name, "aten::geqrf") |
| 6921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geqrf, overload_name, "") |
| 6922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(geqrf, schema_str, "geqrf(Tensor self) -> (Tensor a, Tensor tau)") |
| 6923 | |
| 6924 | // aten::geqrf(Tensor self) -> (Tensor a, Tensor tau) |
| 6925 | static C10_NOINLINE c10::TypedOperatorHandle<geqrf::schema> create_geqrf_typed_handle() { |
| 6926 | return c10::Dispatcher::singleton() |
| 6927 | .findSchemaOrThrow(geqrf::name, geqrf::overload_name) |
| 6928 | .typed<geqrf::schema>(); |
| 6929 | } |
| 6930 | |
| 6931 | // aten::geqrf(Tensor self) -> (Tensor a, Tensor tau) |
| 6932 | ::std::tuple<at::Tensor,at::Tensor> geqrf::call(const at::Tensor & self) { |
| 6933 | |
| 6934 | static auto op = create_geqrf_typed_handle(); |
| 6935 | return op.call(self); |
| 6936 | } |
| 6937 | |
| 6938 | // aten::geqrf(Tensor self) -> (Tensor a, Tensor tau) |
| 6939 | ::std::tuple<at::Tensor,at::Tensor> geqrf::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 6940 | |
| 6941 | static auto op = create_geqrf_typed_handle(); |
| 6942 | return op.redispatch(dispatchKeySet, self); |
| 6943 | } |
| 6944 | |
| 6945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(orgqr, name, "aten::orgqr") |
| 6946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(orgqr, overload_name, "") |
| 6947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(orgqr, schema_str, "orgqr(Tensor self, Tensor input2) -> Tensor") |
| 6948 | |
| 6949 | // aten::orgqr(Tensor self, Tensor input2) -> Tensor |
| 6950 | static C10_NOINLINE c10::TypedOperatorHandle<orgqr::schema> create_orgqr_typed_handle() { |
| 6951 | return c10::Dispatcher::singleton() |
| 6952 | .findSchemaOrThrow(orgqr::name, orgqr::overload_name) |
| 6953 | .typed<orgqr::schema>(); |
| 6954 | } |
| 6955 | |
| 6956 | // aten::orgqr(Tensor self, Tensor input2) -> Tensor |
| 6957 | at::Tensor orgqr::call(const at::Tensor & self, const at::Tensor & input2) { |
| 6958 | |
| 6959 | static auto op = create_orgqr_typed_handle(); |
| 6960 | return op.call(self, input2); |
| 6961 | } |
| 6962 | |
| 6963 | // aten::orgqr(Tensor self, Tensor input2) -> Tensor |
| 6964 | at::Tensor orgqr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & input2) { |
| 6965 | |
| 6966 | static auto op = create_orgqr_typed_handle(); |
| 6967 | return op.redispatch(dispatchKeySet, self, input2); |
| 6968 | } |
| 6969 | |
| 6970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(orgqr_out, name, "aten::orgqr") |
| 6971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(orgqr_out, overload_name, "out") |
| 6972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(orgqr_out, schema_str, "orgqr.out(Tensor self, Tensor input2, *, Tensor(a!) out) -> Tensor(a!)") |
| 6973 | |
| 6974 | // aten::orgqr.out(Tensor self, Tensor input2, *, Tensor(a!) out) -> Tensor(a!) |
| 6975 | static C10_NOINLINE c10::TypedOperatorHandle<orgqr_out::schema> create_orgqr_out_typed_handle() { |
| 6976 | return c10::Dispatcher::singleton() |
| 6977 | .findSchemaOrThrow(orgqr_out::name, orgqr_out::overload_name) |
| 6978 | .typed<orgqr_out::schema>(); |
| 6979 | } |
| 6980 | |
| 6981 | // aten::orgqr.out(Tensor self, Tensor input2, *, Tensor(a!) out) -> Tensor(a!) |
| 6982 | at::Tensor & orgqr_out::call(const at::Tensor & self, const at::Tensor & input2, at::Tensor & out) { |
| 6983 | |
| 6984 | static auto op = create_orgqr_out_typed_handle(); |
| 6985 | return op.call(self, input2, out); |
| 6986 | } |
| 6987 | |
| 6988 | // aten::orgqr.out(Tensor self, Tensor input2, *, Tensor(a!) out) -> Tensor(a!) |
| 6989 | at::Tensor & orgqr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & input2, at::Tensor & out) { |
| 6990 | |
| 6991 | static auto op = create_orgqr_out_typed_handle(); |
| 6992 | return op.redispatch(dispatchKeySet, self, input2, out); |
| 6993 | } |
| 6994 | |
| 6995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv, name, "aten::erfinv") |
| 6996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv, overload_name, "") |
| 6997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv, schema_str, "erfinv(Tensor self) -> Tensor") |
| 6998 | |
| 6999 | // aten::erfinv(Tensor self) -> Tensor |
| 7000 | static C10_NOINLINE c10::TypedOperatorHandle<erfinv::schema> create_erfinv_typed_handle() { |
| 7001 | return c10::Dispatcher::singleton() |
| 7002 | .findSchemaOrThrow(erfinv::name, erfinv::overload_name) |
| 7003 | .typed<erfinv::schema>(); |
| 7004 | } |
| 7005 | |
| 7006 | // aten::erfinv(Tensor self) -> Tensor |
| 7007 | at::Tensor erfinv::call(const at::Tensor & self) { |
| 7008 | |
| 7009 | static auto op = create_erfinv_typed_handle(); |
| 7010 | return op.call(self); |
| 7011 | } |
| 7012 | |
| 7013 | // aten::erfinv(Tensor self) -> Tensor |
| 7014 | at::Tensor erfinv::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7015 | |
| 7016 | static auto op = create_erfinv_typed_handle(); |
| 7017 | return op.redispatch(dispatchKeySet, self); |
| 7018 | } |
| 7019 | |
| 7020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv_, name, "aten::erfinv_") |
| 7021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv_, overload_name, "") |
| 7022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv_, schema_str, "erfinv_(Tensor(a!) self) -> Tensor(a!)") |
| 7023 | |
| 7024 | // aten::erfinv_(Tensor(a!) self) -> Tensor(a!) |
| 7025 | static C10_NOINLINE c10::TypedOperatorHandle<erfinv_::schema> create_erfinv__typed_handle() { |
| 7026 | return c10::Dispatcher::singleton() |
| 7027 | .findSchemaOrThrow(erfinv_::name, erfinv_::overload_name) |
| 7028 | .typed<erfinv_::schema>(); |
| 7029 | } |
| 7030 | |
| 7031 | // aten::erfinv_(Tensor(a!) self) -> Tensor(a!) |
| 7032 | at::Tensor & erfinv_::call(at::Tensor & self) { |
| 7033 | |
| 7034 | static auto op = create_erfinv__typed_handle(); |
| 7035 | return op.call(self); |
| 7036 | } |
| 7037 | |
| 7038 | // aten::erfinv_(Tensor(a!) self) -> Tensor(a!) |
| 7039 | at::Tensor & erfinv_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
| 7040 | |
| 7041 | static auto op = create_erfinv__typed_handle(); |
| 7042 | return op.redispatch(dispatchKeySet, self); |
| 7043 | } |
| 7044 | |
| 7045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv_out, name, "aten::erfinv") |
| 7046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv_out, overload_name, "out") |
| 7047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(erfinv_out, schema_str, "erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 7048 | |
| 7049 | // aten::erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7050 | static C10_NOINLINE c10::TypedOperatorHandle<erfinv_out::schema> create_erfinv_out_typed_handle() { |
| 7051 | return c10::Dispatcher::singleton() |
| 7052 | .findSchemaOrThrow(erfinv_out::name, erfinv_out::overload_name) |
| 7053 | .typed<erfinv_out::schema>(); |
| 7054 | } |
| 7055 | |
| 7056 | // aten::erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7057 | at::Tensor & erfinv_out::call(const at::Tensor & self, at::Tensor & out) { |
| 7058 | |
| 7059 | static auto op = create_erfinv_out_typed_handle(); |
| 7060 | return op.call(self, out); |
| 7061 | } |
| 7062 | |
| 7063 | // aten::erfinv.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7064 | at::Tensor & erfinv_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 7065 | |
| 7066 | static auto op = create_erfinv_out_typed_handle(); |
| 7067 | return op.redispatch(dispatchKeySet, self, out); |
| 7068 | } |
| 7069 | |
| 7070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(signbit, name, "aten::signbit") |
| 7071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(signbit, overload_name, "") |
| 7072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(signbit, schema_str, "signbit(Tensor self) -> Tensor") |
| 7073 | |
| 7074 | // aten::signbit(Tensor self) -> Tensor |
| 7075 | static C10_NOINLINE c10::TypedOperatorHandle<signbit::schema> create_signbit_typed_handle() { |
| 7076 | return c10::Dispatcher::singleton() |
| 7077 | .findSchemaOrThrow(signbit::name, signbit::overload_name) |
| 7078 | .typed<signbit::schema>(); |
| 7079 | } |
| 7080 | |
| 7081 | // aten::signbit(Tensor self) -> Tensor |
| 7082 | at::Tensor signbit::call(const at::Tensor & self) { |
| 7083 | |
| 7084 | static auto op = create_signbit_typed_handle(); |
| 7085 | return op.call(self); |
| 7086 | } |
| 7087 | |
| 7088 | // aten::signbit(Tensor self) -> Tensor |
| 7089 | at::Tensor signbit::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7090 | |
| 7091 | static auto op = create_signbit_typed_handle(); |
| 7092 | return op.redispatch(dispatchKeySet, self); |
| 7093 | } |
| 7094 | |
| 7095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(signbit_out, name, "aten::signbit") |
| 7096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(signbit_out, overload_name, "out") |
| 7097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(signbit_out, schema_str, "signbit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 7098 | |
| 7099 | // aten::signbit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7100 | static C10_NOINLINE c10::TypedOperatorHandle<signbit_out::schema> create_signbit_out_typed_handle() { |
| 7101 | return c10::Dispatcher::singleton() |
| 7102 | .findSchemaOrThrow(signbit_out::name, signbit_out::overload_name) |
| 7103 | .typed<signbit_out::schema>(); |
| 7104 | } |
| 7105 | |
| 7106 | // aten::signbit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7107 | at::Tensor & signbit_out::call(const at::Tensor & self, at::Tensor & out) { |
| 7108 | |
| 7109 | static auto op = create_signbit_out_typed_handle(); |
| 7110 | return op.call(self, out); |
| 7111 | } |
| 7112 | |
| 7113 | // aten::signbit.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7114 | at::Tensor & signbit_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 7115 | |
| 7116 | static auto op = create_signbit_out_typed_handle(); |
| 7117 | return op.redispatch(dispatchKeySet, self, out); |
| 7118 | } |
| 7119 | |
| 7120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dist, name, "aten::dist") |
| 7121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dist, overload_name, "") |
| 7122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dist, schema_str, "dist(Tensor self, Tensor other, Scalar p=2) -> Tensor") |
| 7123 | |
| 7124 | // aten::dist(Tensor self, Tensor other, Scalar p=2) -> Tensor |
| 7125 | static C10_NOINLINE c10::TypedOperatorHandle<dist::schema> create_dist_typed_handle() { |
| 7126 | return c10::Dispatcher::singleton() |
| 7127 | .findSchemaOrThrow(dist::name, dist::overload_name) |
| 7128 | .typed<dist::schema>(); |
| 7129 | } |
| 7130 | |
| 7131 | // aten::dist(Tensor self, Tensor other, Scalar p=2) -> Tensor |
| 7132 | at::Tensor dist::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & p) { |
| 7133 | |
| 7134 | static auto op = create_dist_typed_handle(); |
| 7135 | return op.call(self, other, p); |
| 7136 | } |
| 7137 | |
| 7138 | // aten::dist(Tensor self, Tensor other, Scalar p=2) -> Tensor |
| 7139 | at::Tensor dist::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & p) { |
| 7140 | |
| 7141 | static auto op = create_dist_typed_handle(); |
| 7142 | return op.redispatch(dispatchKeySet, self, other, p); |
| 7143 | } |
| 7144 | |
| 7145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_histogramdd_from_bin_cts, name, "aten::_histogramdd_from_bin_cts") |
| 7146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_histogramdd_from_bin_cts, overload_name, "") |
| 7147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_histogramdd_from_bin_cts, schema_str, "_histogramdd_from_bin_cts(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor") |
| 7148 | |
| 7149 | // aten::_histogramdd_from_bin_cts(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor |
| 7150 | static C10_NOINLINE c10::TypedOperatorHandle<_histogramdd_from_bin_cts::schema> create__histogramdd_from_bin_cts_typed_handle() { |
| 7151 | return c10::Dispatcher::singleton() |
| 7152 | .findSchemaOrThrow(_histogramdd_from_bin_cts::name, _histogramdd_from_bin_cts::overload_name) |
| 7153 | .typed<_histogramdd_from_bin_cts::schema>(); |
| 7154 | } |
| 7155 | |
| 7156 | // aten::_histogramdd_from_bin_cts(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor |
| 7157 | at::Tensor _histogramdd_from_bin_cts::call(const at::Tensor & self, at::IntArrayRef bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
| 7158 | |
| 7159 | static auto op = create__histogramdd_from_bin_cts_typed_handle(); |
| 7160 | return op.call(self, bins, range, weight, density); |
| 7161 | } |
| 7162 | |
| 7163 | // aten::_histogramdd_from_bin_cts(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False) -> Tensor |
| 7164 | at::Tensor _histogramdd_from_bin_cts::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
| 7165 | |
| 7166 | static auto op = create__histogramdd_from_bin_cts_typed_handle(); |
| 7167 | return op.redispatch(dispatchKeySet, self, bins, range, weight, density); |
| 7168 | } |
| 7169 | |
| 7170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Scalar_out, name, "aten::fmod") |
| 7171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Scalar_out, overload_name, "Scalar_out") |
| 7172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Scalar_out, schema_str, "fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 7173 | |
| 7174 | // aten::fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7175 | static C10_NOINLINE c10::TypedOperatorHandle<fmod_Scalar_out::schema> create_fmod_Scalar_out_typed_handle() { |
| 7176 | return c10::Dispatcher::singleton() |
| 7177 | .findSchemaOrThrow(fmod_Scalar_out::name, fmod_Scalar_out::overload_name) |
| 7178 | .typed<fmod_Scalar_out::schema>(); |
| 7179 | } |
| 7180 | |
| 7181 | // aten::fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7182 | at::Tensor & fmod_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 7183 | |
| 7184 | static auto op = create_fmod_Scalar_out_typed_handle(); |
| 7185 | return op.call(self, other, out); |
| 7186 | } |
| 7187 | |
| 7188 | // aten::fmod.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7189 | at::Tensor & fmod_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 7190 | |
| 7191 | static auto op = create_fmod_Scalar_out_typed_handle(); |
| 7192 | return op.redispatch(dispatchKeySet, self, other, out); |
| 7193 | } |
| 7194 | |
| 7195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Scalar, name, "aten::fmod") |
| 7196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Scalar, overload_name, "Scalar") |
| 7197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Scalar, schema_str, "fmod.Scalar(Tensor self, Scalar other) -> Tensor") |
| 7198 | |
| 7199 | // aten::fmod.Scalar(Tensor self, Scalar other) -> Tensor |
| 7200 | static C10_NOINLINE c10::TypedOperatorHandle<fmod_Scalar::schema> create_fmod_Scalar_typed_handle() { |
| 7201 | return c10::Dispatcher::singleton() |
| 7202 | .findSchemaOrThrow(fmod_Scalar::name, fmod_Scalar::overload_name) |
| 7203 | .typed<fmod_Scalar::schema>(); |
| 7204 | } |
| 7205 | |
| 7206 | // aten::fmod.Scalar(Tensor self, Scalar other) -> Tensor |
| 7207 | at::Tensor fmod_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 7208 | |
| 7209 | static auto op = create_fmod_Scalar_typed_handle(); |
| 7210 | return op.call(self, other); |
| 7211 | } |
| 7212 | |
| 7213 | // aten::fmod.Scalar(Tensor self, Scalar other) -> Tensor |
| 7214 | at::Tensor fmod_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 7215 | |
| 7216 | static auto op = create_fmod_Scalar_typed_handle(); |
| 7217 | return op.redispatch(dispatchKeySet, self, other); |
| 7218 | } |
| 7219 | |
| 7220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod__Scalar, name, "aten::fmod_") |
| 7221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod__Scalar, overload_name, "Scalar") |
| 7222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod__Scalar, schema_str, "fmod_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 7223 | |
| 7224 | // aten::fmod_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7225 | static C10_NOINLINE c10::TypedOperatorHandle<fmod__Scalar::schema> create_fmod__Scalar_typed_handle() { |
| 7226 | return c10::Dispatcher::singleton() |
| 7227 | .findSchemaOrThrow(fmod__Scalar::name, fmod__Scalar::overload_name) |
| 7228 | .typed<fmod__Scalar::schema>(); |
| 7229 | } |
| 7230 | |
| 7231 | // aten::fmod_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7232 | at::Tensor & fmod__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 7233 | |
| 7234 | static auto op = create_fmod__Scalar_typed_handle(); |
| 7235 | return op.call(self, other); |
| 7236 | } |
| 7237 | |
| 7238 | // aten::fmod_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7239 | at::Tensor & fmod__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 7240 | |
| 7241 | static auto op = create_fmod__Scalar_typed_handle(); |
| 7242 | return op.redispatch(dispatchKeySet, self, other); |
| 7243 | } |
| 7244 | |
| 7245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Tensor_out, name, "aten::fmod") |
| 7246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Tensor_out, overload_name, "Tensor_out") |
| 7247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Tensor_out, schema_str, "fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 7248 | |
| 7249 | // aten::fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7250 | static C10_NOINLINE c10::TypedOperatorHandle<fmod_Tensor_out::schema> create_fmod_Tensor_out_typed_handle() { |
| 7251 | return c10::Dispatcher::singleton() |
| 7252 | .findSchemaOrThrow(fmod_Tensor_out::name, fmod_Tensor_out::overload_name) |
| 7253 | .typed<fmod_Tensor_out::schema>(); |
| 7254 | } |
| 7255 | |
| 7256 | // aten::fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7257 | at::Tensor & fmod_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 7258 | |
| 7259 | static auto op = create_fmod_Tensor_out_typed_handle(); |
| 7260 | return op.call(self, other, out); |
| 7261 | } |
| 7262 | |
| 7263 | // aten::fmod.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7264 | at::Tensor & fmod_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 7265 | |
| 7266 | static auto op = create_fmod_Tensor_out_typed_handle(); |
| 7267 | return op.redispatch(dispatchKeySet, self, other, out); |
| 7268 | } |
| 7269 | |
| 7270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Tensor, name, "aten::fmod") |
| 7271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Tensor, overload_name, "Tensor") |
| 7272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod_Tensor, schema_str, "fmod.Tensor(Tensor self, Tensor other) -> Tensor") |
| 7273 | |
| 7274 | // aten::fmod.Tensor(Tensor self, Tensor other) -> Tensor |
| 7275 | static C10_NOINLINE c10::TypedOperatorHandle<fmod_Tensor::schema> create_fmod_Tensor_typed_handle() { |
| 7276 | return c10::Dispatcher::singleton() |
| 7277 | .findSchemaOrThrow(fmod_Tensor::name, fmod_Tensor::overload_name) |
| 7278 | .typed<fmod_Tensor::schema>(); |
| 7279 | } |
| 7280 | |
| 7281 | // aten::fmod.Tensor(Tensor self, Tensor other) -> Tensor |
| 7282 | at::Tensor fmod_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 7283 | |
| 7284 | static auto op = create_fmod_Tensor_typed_handle(); |
| 7285 | return op.call(self, other); |
| 7286 | } |
| 7287 | |
| 7288 | // aten::fmod.Tensor(Tensor self, Tensor other) -> Tensor |
| 7289 | at::Tensor fmod_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 7290 | |
| 7291 | static auto op = create_fmod_Tensor_typed_handle(); |
| 7292 | return op.redispatch(dispatchKeySet, self, other); |
| 7293 | } |
| 7294 | |
| 7295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod__Tensor, name, "aten::fmod_") |
| 7296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod__Tensor, overload_name, "Tensor") |
| 7297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmod__Tensor, schema_str, "fmod_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 7298 | |
| 7299 | // aten::fmod_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7300 | static C10_NOINLINE c10::TypedOperatorHandle<fmod__Tensor::schema> create_fmod__Tensor_typed_handle() { |
| 7301 | return c10::Dispatcher::singleton() |
| 7302 | .findSchemaOrThrow(fmod__Tensor::name, fmod__Tensor::overload_name) |
| 7303 | .typed<fmod__Tensor::schema>(); |
| 7304 | } |
| 7305 | |
| 7306 | // aten::fmod_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7307 | at::Tensor & fmod__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 7308 | |
| 7309 | static auto op = create_fmod__Tensor_typed_handle(); |
| 7310 | return op.call(self, other); |
| 7311 | } |
| 7312 | |
| 7313 | // aten::fmod_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7314 | at::Tensor & fmod__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 7315 | |
| 7316 | static auto op = create_fmod__Tensor_typed_handle(); |
| 7317 | return op.redispatch(dispatchKeySet, self, other); |
| 7318 | } |
| 7319 | |
| 7320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_out, name, "aten::remainder") |
| 7321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_out, overload_name, "Scalar_out") |
| 7322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_out, schema_str, "remainder.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)") |
| 7323 | |
| 7324 | // aten::remainder.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7325 | static C10_NOINLINE c10::TypedOperatorHandle<remainder_Scalar_out::schema> create_remainder_Scalar_out_typed_handle() { |
| 7326 | return c10::Dispatcher::singleton() |
| 7327 | .findSchemaOrThrow(remainder_Scalar_out::name, remainder_Scalar_out::overload_name) |
| 7328 | .typed<remainder_Scalar_out::schema>(); |
| 7329 | } |
| 7330 | |
| 7331 | // aten::remainder.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7332 | at::Tensor & remainder_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 7333 | |
| 7334 | static auto op = create_remainder_Scalar_out_typed_handle(); |
| 7335 | return op.call(self, other, out); |
| 7336 | } |
| 7337 | |
| 7338 | // aten::remainder.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
| 7339 | at::Tensor & remainder_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
| 7340 | |
| 7341 | static auto op = create_remainder_Scalar_out_typed_handle(); |
| 7342 | return op.redispatch(dispatchKeySet, self, other, out); |
| 7343 | } |
| 7344 | |
| 7345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar, name, "aten::remainder") |
| 7346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar, overload_name, "Scalar") |
| 7347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar, schema_str, "remainder.Scalar(Tensor self, Scalar other) -> Tensor") |
| 7348 | |
| 7349 | // aten::remainder.Scalar(Tensor self, Scalar other) -> Tensor |
| 7350 | static C10_NOINLINE c10::TypedOperatorHandle<remainder_Scalar::schema> create_remainder_Scalar_typed_handle() { |
| 7351 | return c10::Dispatcher::singleton() |
| 7352 | .findSchemaOrThrow(remainder_Scalar::name, remainder_Scalar::overload_name) |
| 7353 | .typed<remainder_Scalar::schema>(); |
| 7354 | } |
| 7355 | |
| 7356 | // aten::remainder.Scalar(Tensor self, Scalar other) -> Tensor |
| 7357 | at::Tensor remainder_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
| 7358 | |
| 7359 | static auto op = create_remainder_Scalar_typed_handle(); |
| 7360 | return op.call(self, other); |
| 7361 | } |
| 7362 | |
| 7363 | // aten::remainder.Scalar(Tensor self, Scalar other) -> Tensor |
| 7364 | at::Tensor remainder_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
| 7365 | |
| 7366 | static auto op = create_remainder_Scalar_typed_handle(); |
| 7367 | return op.redispatch(dispatchKeySet, self, other); |
| 7368 | } |
| 7369 | |
| 7370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder__Scalar, name, "aten::remainder_") |
| 7371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder__Scalar, overload_name, "Scalar") |
| 7372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder__Scalar, schema_str, "remainder_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)") |
| 7373 | |
| 7374 | // aten::remainder_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7375 | static C10_NOINLINE c10::TypedOperatorHandle<remainder__Scalar::schema> create_remainder__Scalar_typed_handle() { |
| 7376 | return c10::Dispatcher::singleton() |
| 7377 | .findSchemaOrThrow(remainder__Scalar::name, remainder__Scalar::overload_name) |
| 7378 | .typed<remainder__Scalar::schema>(); |
| 7379 | } |
| 7380 | |
| 7381 | // aten::remainder_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7382 | at::Tensor & remainder__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
| 7383 | |
| 7384 | static auto op = create_remainder__Scalar_typed_handle(); |
| 7385 | return op.call(self, other); |
| 7386 | } |
| 7387 | |
| 7388 | // aten::remainder_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
| 7389 | at::Tensor & remainder__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
| 7390 | |
| 7391 | static auto op = create_remainder__Scalar_typed_handle(); |
| 7392 | return op.redispatch(dispatchKeySet, self, other); |
| 7393 | } |
| 7394 | |
| 7395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Tensor_out, name, "aten::remainder") |
| 7396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Tensor_out, overload_name, "Tensor_out") |
| 7397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Tensor_out, schema_str, "remainder.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 7398 | |
| 7399 | // aten::remainder.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7400 | static C10_NOINLINE c10::TypedOperatorHandle<remainder_Tensor_out::schema> create_remainder_Tensor_out_typed_handle() { |
| 7401 | return c10::Dispatcher::singleton() |
| 7402 | .findSchemaOrThrow(remainder_Tensor_out::name, remainder_Tensor_out::overload_name) |
| 7403 | .typed<remainder_Tensor_out::schema>(); |
| 7404 | } |
| 7405 | |
| 7406 | // aten::remainder.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7407 | at::Tensor & remainder_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 7408 | |
| 7409 | static auto op = create_remainder_Tensor_out_typed_handle(); |
| 7410 | return op.call(self, other, out); |
| 7411 | } |
| 7412 | |
| 7413 | // aten::remainder.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 7414 | at::Tensor & remainder_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 7415 | |
| 7416 | static auto op = create_remainder_Tensor_out_typed_handle(); |
| 7417 | return op.redispatch(dispatchKeySet, self, other, out); |
| 7418 | } |
| 7419 | |
| 7420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Tensor, name, "aten::remainder") |
| 7421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Tensor, overload_name, "Tensor") |
| 7422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Tensor, schema_str, "remainder.Tensor(Tensor self, Tensor other) -> Tensor") |
| 7423 | |
| 7424 | // aten::remainder.Tensor(Tensor self, Tensor other) -> Tensor |
| 7425 | static C10_NOINLINE c10::TypedOperatorHandle<remainder_Tensor::schema> create_remainder_Tensor_typed_handle() { |
| 7426 | return c10::Dispatcher::singleton() |
| 7427 | .findSchemaOrThrow(remainder_Tensor::name, remainder_Tensor::overload_name) |
| 7428 | .typed<remainder_Tensor::schema>(); |
| 7429 | } |
| 7430 | |
| 7431 | // aten::remainder.Tensor(Tensor self, Tensor other) -> Tensor |
| 7432 | at::Tensor remainder_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
| 7433 | |
| 7434 | static auto op = create_remainder_Tensor_typed_handle(); |
| 7435 | return op.call(self, other); |
| 7436 | } |
| 7437 | |
| 7438 | // aten::remainder.Tensor(Tensor self, Tensor other) -> Tensor |
| 7439 | at::Tensor remainder_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 7440 | |
| 7441 | static auto op = create_remainder_Tensor_typed_handle(); |
| 7442 | return op.redispatch(dispatchKeySet, self, other); |
| 7443 | } |
| 7444 | |
| 7445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder__Tensor, name, "aten::remainder_") |
| 7446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder__Tensor, overload_name, "Tensor") |
| 7447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder__Tensor, schema_str, "remainder_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)") |
| 7448 | |
| 7449 | // aten::remainder_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7450 | static C10_NOINLINE c10::TypedOperatorHandle<remainder__Tensor::schema> create_remainder__Tensor_typed_handle() { |
| 7451 | return c10::Dispatcher::singleton() |
| 7452 | .findSchemaOrThrow(remainder__Tensor::name, remainder__Tensor::overload_name) |
| 7453 | .typed<remainder__Tensor::schema>(); |
| 7454 | } |
| 7455 | |
| 7456 | // aten::remainder_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7457 | at::Tensor & remainder__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
| 7458 | |
| 7459 | static auto op = create_remainder__Tensor_typed_handle(); |
| 7460 | return op.call(self, other); |
| 7461 | } |
| 7462 | |
| 7463 | // aten::remainder_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
| 7464 | at::Tensor & remainder__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
| 7465 | |
| 7466 | static auto op = create_remainder__Tensor_typed_handle(); |
| 7467 | return op.redispatch(dispatchKeySet, self, other); |
| 7468 | } |
| 7469 | |
| 7470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_Tensor, name, "aten::remainder") |
| 7471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_Tensor, overload_name, "Scalar_Tensor") |
| 7472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_Tensor, schema_str, "remainder.Scalar_Tensor(Scalar self, Tensor other) -> Tensor") |
| 7473 | |
| 7474 | // aten::remainder.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 7475 | static C10_NOINLINE c10::TypedOperatorHandle<remainder_Scalar_Tensor::schema> create_remainder_Scalar_Tensor_typed_handle() { |
| 7476 | return c10::Dispatcher::singleton() |
| 7477 | .findSchemaOrThrow(remainder_Scalar_Tensor::name, remainder_Scalar_Tensor::overload_name) |
| 7478 | .typed<remainder_Scalar_Tensor::schema>(); |
| 7479 | } |
| 7480 | |
| 7481 | // aten::remainder.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 7482 | at::Tensor remainder_Scalar_Tensor::call(const at::Scalar & self, const at::Tensor & other) { |
| 7483 | |
| 7484 | static auto op = create_remainder_Scalar_Tensor_typed_handle(); |
| 7485 | return op.call(self, other); |
| 7486 | } |
| 7487 | |
| 7488 | // aten::remainder.Scalar_Tensor(Scalar self, Tensor other) -> Tensor |
| 7489 | at::Tensor remainder_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other) { |
| 7490 | |
| 7491 | static auto op = create_remainder_Scalar_Tensor_typed_handle(); |
| 7492 | return op.redispatch(dispatchKeySet, self, other); |
| 7493 | } |
| 7494 | |
| 7495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile, name, "aten::nanquantile") |
| 7496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile, overload_name, "") |
| 7497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile, schema_str, "nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor") |
| 7498 | |
| 7499 | // aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor |
| 7500 | static C10_NOINLINE c10::TypedOperatorHandle<nanquantile::schema> create_nanquantile_typed_handle() { |
| 7501 | return c10::Dispatcher::singleton() |
| 7502 | .findSchemaOrThrow(nanquantile::name, nanquantile::overload_name) |
| 7503 | .typed<nanquantile::schema>(); |
| 7504 | } |
| 7505 | |
| 7506 | // aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor |
| 7507 | at::Tensor nanquantile::call(const at::Tensor & self, const at::Tensor & q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation) { |
| 7508 | |
| 7509 | static auto op = create_nanquantile_typed_handle(); |
| 7510 | return op.call(self, q, dim, keepdim, interpolation); |
| 7511 | } |
| 7512 | |
| 7513 | // aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor |
| 7514 | at::Tensor nanquantile::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation) { |
| 7515 | |
| 7516 | static auto op = create_nanquantile_typed_handle(); |
| 7517 | return op.redispatch(dispatchKeySet, self, q, dim, keepdim, interpolation); |
| 7518 | } |
| 7519 | |
| 7520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_out, name, "aten::nanquantile") |
| 7521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_out, overload_name, "out") |
| 7522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_out, schema_str, "nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!)") |
| 7523 | |
| 7524 | // aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) |
| 7525 | static C10_NOINLINE c10::TypedOperatorHandle<nanquantile_out::schema> create_nanquantile_out_typed_handle() { |
| 7526 | return c10::Dispatcher::singleton() |
| 7527 | .findSchemaOrThrow(nanquantile_out::name, nanquantile_out::overload_name) |
| 7528 | .typed<nanquantile_out::schema>(); |
| 7529 | } |
| 7530 | |
| 7531 | // aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) |
| 7532 | at::Tensor & nanquantile_out::call(const at::Tensor & self, const at::Tensor & q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { |
| 7533 | |
| 7534 | static auto op = create_nanquantile_out_typed_handle(); |
| 7535 | return op.call(self, q, dim, keepdim, interpolation, out); |
| 7536 | } |
| 7537 | |
| 7538 | // aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) |
| 7539 | at::Tensor & nanquantile_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { |
| 7540 | |
| 7541 | static auto op = create_nanquantile_out_typed_handle(); |
| 7542 | return op.redispatch(dispatchKeySet, self, q, dim, keepdim, interpolation, out); |
| 7543 | } |
| 7544 | |
| 7545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_scalar, name, "aten::nanquantile") |
| 7546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_scalar, overload_name, "scalar") |
| 7547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_scalar, schema_str, "nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor") |
| 7548 | |
| 7549 | // aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor |
| 7550 | static C10_NOINLINE c10::TypedOperatorHandle<nanquantile_scalar::schema> create_nanquantile_scalar_typed_handle() { |
| 7551 | return c10::Dispatcher::singleton() |
| 7552 | .findSchemaOrThrow(nanquantile_scalar::name, nanquantile_scalar::overload_name) |
| 7553 | .typed<nanquantile_scalar::schema>(); |
| 7554 | } |
| 7555 | |
| 7556 | // aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor |
| 7557 | at::Tensor nanquantile_scalar::call(const at::Tensor & self, double q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation) { |
| 7558 | |
| 7559 | static auto op = create_nanquantile_scalar_typed_handle(); |
| 7560 | return op.call(self, q, dim, keepdim, interpolation); |
| 7561 | } |
| 7562 | |
| 7563 | // aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor |
| 7564 | at::Tensor nanquantile_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation) { |
| 7565 | |
| 7566 | static auto op = create_nanquantile_scalar_typed_handle(); |
| 7567 | return op.redispatch(dispatchKeySet, self, q, dim, keepdim, interpolation); |
| 7568 | } |
| 7569 | |
| 7570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_scalar_out, name, "aten::nanquantile") |
| 7571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_scalar_out, overload_name, "scalar_out") |
| 7572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanquantile_scalar_out, schema_str, "nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!)") |
| 7573 | |
| 7574 | // aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) |
| 7575 | static C10_NOINLINE c10::TypedOperatorHandle<nanquantile_scalar_out::schema> create_nanquantile_scalar_out_typed_handle() { |
| 7576 | return c10::Dispatcher::singleton() |
| 7577 | .findSchemaOrThrow(nanquantile_scalar_out::name, nanquantile_scalar_out::overload_name) |
| 7578 | .typed<nanquantile_scalar_out::schema>(); |
| 7579 | } |
| 7580 | |
| 7581 | // aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) |
| 7582 | at::Tensor & nanquantile_scalar_out::call(const at::Tensor & self, double q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { |
| 7583 | |
| 7584 | static auto op = create_nanquantile_scalar_out_typed_handle(); |
| 7585 | return op.call(self, q, dim, keepdim, interpolation, out); |
| 7586 | } |
| 7587 | |
| 7588 | // aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) |
| 7589 | at::Tensor & nanquantile_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double q, c10::optional<int64_t> dim, bool keepdim, c10::string_view interpolation, at::Tensor & out) { |
| 7590 | |
| 7591 | static auto op = create_nanquantile_scalar_out_typed_handle(); |
| 7592 | return op.redispatch(dispatchKeySet, self, q, dim, keepdim, interpolation, out); |
| 7593 | } |
| 7594 | |
| 7595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any, name, "aten::any") |
| 7596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any, overload_name, "") |
| 7597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any, schema_str, "any(Tensor self) -> Tensor") |
| 7598 | |
| 7599 | // aten::any(Tensor self) -> Tensor |
| 7600 | static C10_NOINLINE c10::TypedOperatorHandle<any::schema> create_any_typed_handle() { |
| 7601 | return c10::Dispatcher::singleton() |
| 7602 | .findSchemaOrThrow(any::name, any::overload_name) |
| 7603 | .typed<any::schema>(); |
| 7604 | } |
| 7605 | |
| 7606 | // aten::any(Tensor self) -> Tensor |
| 7607 | at::Tensor any::call(const at::Tensor & self) { |
| 7608 | |
| 7609 | static auto op = create_any_typed_handle(); |
| 7610 | return op.call(self); |
| 7611 | } |
| 7612 | |
| 7613 | // aten::any(Tensor self) -> Tensor |
| 7614 | at::Tensor any::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 7615 | |
| 7616 | static auto op = create_any_typed_handle(); |
| 7617 | return op.redispatch(dispatchKeySet, self); |
| 7618 | } |
| 7619 | |
| 7620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_all_out, name, "aten::any") |
| 7621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_all_out, overload_name, "all_out") |
| 7622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(any_all_out, schema_str, "any.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 7623 | |
| 7624 | // aten::any.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7625 | static C10_NOINLINE c10::TypedOperatorHandle<any_all_out::schema> create_any_all_out_typed_handle() { |
| 7626 | return c10::Dispatcher::singleton() |
| 7627 | .findSchemaOrThrow(any_all_out::name, any_all_out::overload_name) |
| 7628 | .typed<any_all_out::schema>(); |
| 7629 | } |
| 7630 | |
| 7631 | // aten::any.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7632 | at::Tensor & any_all_out::call(const at::Tensor & self, at::Tensor & out) { |
| 7633 | |
| 7634 | static auto op = create_any_all_out_typed_handle(); |
| 7635 | return op.call(self, out); |
| 7636 | } |
| 7637 | |
| 7638 | // aten::any.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 7639 | at::Tensor & any_all_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 7640 | |
| 7641 | static auto op = create_any_all_out_typed_handle(); |
| 7642 | return op.redispatch(dispatchKeySet, self, out); |
| 7643 | } |
| 7644 | |
| 7645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm_out, name, "aten::renorm") |
| 7646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm_out, overload_name, "out") |
| 7647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm_out, schema_str, "renorm.out(Tensor self, Scalar p, int dim, Scalar maxnorm, *, Tensor(a!) out) -> Tensor(a!)") |
| 7648 | |
| 7649 | // aten::renorm.out(Tensor self, Scalar p, int dim, Scalar maxnorm, *, Tensor(a!) out) -> Tensor(a!) |
| 7650 | static C10_NOINLINE c10::TypedOperatorHandle<renorm_out::schema> create_renorm_out_typed_handle() { |
| 7651 | return c10::Dispatcher::singleton() |
| 7652 | .findSchemaOrThrow(renorm_out::name, renorm_out::overload_name) |
| 7653 | .typed<renorm_out::schema>(); |
| 7654 | } |
| 7655 | |
| 7656 | // aten::renorm.out(Tensor self, Scalar p, int dim, Scalar maxnorm, *, Tensor(a!) out) -> Tensor(a!) |
| 7657 | at::Tensor & renorm_out::call(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm, at::Tensor & out) { |
| 7658 | |
| 7659 | static auto op = create_renorm_out_typed_handle(); |
| 7660 | return op.call(self, p, dim, maxnorm, out); |
| 7661 | } |
| 7662 | |
| 7663 | // aten::renorm.out(Tensor self, Scalar p, int dim, Scalar maxnorm, *, Tensor(a!) out) -> Tensor(a!) |
| 7664 | at::Tensor & renorm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm, at::Tensor & out) { |
| 7665 | |
| 7666 | static auto op = create_renorm_out_typed_handle(); |
| 7667 | return op.redispatch(dispatchKeySet, self, p, dim, maxnorm, out); |
| 7668 | } |
| 7669 | |
| 7670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm, name, "aten::renorm") |
| 7671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm, overload_name, "") |
| 7672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm, schema_str, "renorm(Tensor self, Scalar p, int dim, Scalar maxnorm) -> Tensor") |
| 7673 | |
| 7674 | // aten::renorm(Tensor self, Scalar p, int dim, Scalar maxnorm) -> Tensor |
| 7675 | static C10_NOINLINE c10::TypedOperatorHandle<renorm::schema> create_renorm_typed_handle() { |
| 7676 | return c10::Dispatcher::singleton() |
| 7677 | .findSchemaOrThrow(renorm::name, renorm::overload_name) |
| 7678 | .typed<renorm::schema>(); |
| 7679 | } |
| 7680 | |
| 7681 | // aten::renorm(Tensor self, Scalar p, int dim, Scalar maxnorm) -> Tensor |
| 7682 | at::Tensor renorm::call(const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm) { |
| 7683 | |
| 7684 | static auto op = create_renorm_typed_handle(); |
| 7685 | return op.call(self, p, dim, maxnorm); |
| 7686 | } |
| 7687 | |
| 7688 | // aten::renorm(Tensor self, Scalar p, int dim, Scalar maxnorm) -> Tensor |
| 7689 | at::Tensor renorm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm) { |
| 7690 | |
| 7691 | static auto op = create_renorm_typed_handle(); |
| 7692 | return op.redispatch(dispatchKeySet, self, p, dim, maxnorm); |
| 7693 | } |
| 7694 | |
| 7695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm_, name, "aten::renorm_") |
| 7696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm_, overload_name, "") |
| 7697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(renorm_, schema_str, "renorm_(Tensor(a!) self, Scalar p, int dim, Scalar maxnorm) -> Tensor(a!)") |
| 7698 | |
| 7699 | // aten::renorm_(Tensor(a!) self, Scalar p, int dim, Scalar maxnorm) -> Tensor(a!) |
| 7700 | static C10_NOINLINE c10::TypedOperatorHandle<renorm_::schema> create_renorm__typed_handle() { |
| 7701 | return c10::Dispatcher::singleton() |
| 7702 | .findSchemaOrThrow(renorm_::name, renorm_::overload_name) |
| 7703 | .typed<renorm_::schema>(); |
| 7704 | } |
| 7705 | |
| 7706 | // aten::renorm_(Tensor(a!) self, Scalar p, int dim, Scalar maxnorm) -> Tensor(a!) |
| 7707 | at::Tensor & renorm_::call(at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm) { |
| 7708 | |
| 7709 | static auto op = create_renorm__typed_handle(); |
| 7710 | return op.call(self, p, dim, maxnorm); |
| 7711 | } |
| 7712 | |
| 7713 | // aten::renorm_(Tensor(a!) self, Scalar p, int dim, Scalar maxnorm) -> Tensor(a!) |
| 7714 | at::Tensor & renorm_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & p, int64_t dim, const at::Scalar & maxnorm) { |
| 7715 | |
| 7716 | static auto op = create_renorm__typed_handle(); |
| 7717 | return op.redispatch(dispatchKeySet, self, p, dim, maxnorm); |
| 7718 | } |
| 7719 | |
| 7720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold, name, "aten::unfold") |
| 7721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold, overload_name, "") |
| 7722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold, schema_str, "unfold(Tensor(a) self, int dimension, int size, int step) -> Tensor(a)") |
| 7723 | |
| 7724 | // aten::unfold(Tensor(a) self, int dimension, int size, int step) -> Tensor(a) |
| 7725 | static C10_NOINLINE c10::TypedOperatorHandle<unfold::schema> create_unfold_typed_handle() { |
| 7726 | return c10::Dispatcher::singleton() |
| 7727 | .findSchemaOrThrow(unfold::name, unfold::overload_name) |
| 7728 | .typed<unfold::schema>(); |
| 7729 | } |
| 7730 | |
| 7731 | // aten::unfold(Tensor(a) self, int dimension, int size, int step) -> Tensor(a) |
| 7732 | at::Tensor unfold::call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) { |
| 7733 | |
| 7734 | static auto op = create_unfold_typed_handle(); |
| 7735 | return op.call(self, dimension, size, step); |
| 7736 | } |
| 7737 | |
| 7738 | // aten::unfold(Tensor(a) self, int dimension, int size, int step) -> Tensor(a) |
| 7739 | at::Tensor unfold::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) { |
| 7740 | |
| 7741 | static auto op = create_unfold_typed_handle(); |
| 7742 | return op.redispatch(dispatchKeySet, self, dimension, size, step); |
| 7743 | } |
| 7744 | |
| 7745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Tensor_out, name, "aten::float_power") |
| 7746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Tensor_out, overload_name, "Tensor_Tensor_out") |
| 7747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Tensor_out, schema_str, "float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)") |
| 7748 | |
| 7749 | // aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7750 | static C10_NOINLINE c10::TypedOperatorHandle<float_power_Tensor_Tensor_out::schema> create_float_power_Tensor_Tensor_out_typed_handle() { |
| 7751 | return c10::Dispatcher::singleton() |
| 7752 | .findSchemaOrThrow(float_power_Tensor_Tensor_out::name, float_power_Tensor_Tensor_out::overload_name) |
| 7753 | .typed<float_power_Tensor_Tensor_out::schema>(); |
| 7754 | } |
| 7755 | |
| 7756 | // aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7757 | at::Tensor & float_power_Tensor_Tensor_out::call(const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out) { |
| 7758 | |
| 7759 | static auto op = create_float_power_Tensor_Tensor_out_typed_handle(); |
| 7760 | return op.call(self, exponent, out); |
| 7761 | } |
| 7762 | |
| 7763 | // aten::float_power.Tensor_Tensor_out(Tensor self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7764 | at::Tensor & float_power_Tensor_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent, at::Tensor & out) { |
| 7765 | |
| 7766 | static auto op = create_float_power_Tensor_Tensor_out_typed_handle(); |
| 7767 | return op.redispatch(dispatchKeySet, self, exponent, out); |
| 7768 | } |
| 7769 | |
| 7770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Tensor, name, "aten::float_power") |
| 7771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Tensor, overload_name, "Tensor_Tensor") |
| 7772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Tensor, schema_str, "float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor") |
| 7773 | |
| 7774 | // aten::float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor |
| 7775 | static C10_NOINLINE c10::TypedOperatorHandle<float_power_Tensor_Tensor::schema> create_float_power_Tensor_Tensor_typed_handle() { |
| 7776 | return c10::Dispatcher::singleton() |
| 7777 | .findSchemaOrThrow(float_power_Tensor_Tensor::name, float_power_Tensor_Tensor::overload_name) |
| 7778 | .typed<float_power_Tensor_Tensor::schema>(); |
| 7779 | } |
| 7780 | |
| 7781 | // aten::float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor |
| 7782 | at::Tensor float_power_Tensor_Tensor::call(const at::Tensor & self, const at::Tensor & exponent) { |
| 7783 | |
| 7784 | static auto op = create_float_power_Tensor_Tensor_typed_handle(); |
| 7785 | return op.call(self, exponent); |
| 7786 | } |
| 7787 | |
| 7788 | // aten::float_power.Tensor_Tensor(Tensor self, Tensor exponent) -> Tensor |
| 7789 | at::Tensor float_power_Tensor_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & exponent) { |
| 7790 | |
| 7791 | static auto op = create_float_power_Tensor_Tensor_typed_handle(); |
| 7792 | return op.redispatch(dispatchKeySet, self, exponent); |
| 7793 | } |
| 7794 | |
| 7795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Scalar_out, name, "aten::float_power") |
| 7796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Scalar_out, overload_name, "Scalar_out") |
| 7797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Scalar_out, schema_str, "float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!)") |
| 7798 | |
| 7799 | // aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7800 | static C10_NOINLINE c10::TypedOperatorHandle<float_power_Scalar_out::schema> create_float_power_Scalar_out_typed_handle() { |
| 7801 | return c10::Dispatcher::singleton() |
| 7802 | .findSchemaOrThrow(float_power_Scalar_out::name, float_power_Scalar_out::overload_name) |
| 7803 | .typed<float_power_Scalar_out::schema>(); |
| 7804 | } |
| 7805 | |
| 7806 | // aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7807 | at::Tensor & float_power_Scalar_out::call(const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out) { |
| 7808 | |
| 7809 | static auto op = create_float_power_Scalar_out_typed_handle(); |
| 7810 | return op.call(self, exponent, out); |
| 7811 | } |
| 7812 | |
| 7813 | // aten::float_power.Scalar_out(Scalar self, Tensor exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7814 | at::Tensor & float_power_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent, at::Tensor & out) { |
| 7815 | |
| 7816 | static auto op = create_float_power_Scalar_out_typed_handle(); |
| 7817 | return op.redispatch(dispatchKeySet, self, exponent, out); |
| 7818 | } |
| 7819 | |
| 7820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Scalar, name, "aten::float_power") |
| 7821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Scalar, overload_name, "Scalar") |
| 7822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Scalar, schema_str, "float_power.Scalar(Scalar self, Tensor exponent) -> Tensor") |
| 7823 | |
| 7824 | // aten::float_power.Scalar(Scalar self, Tensor exponent) -> Tensor |
| 7825 | static C10_NOINLINE c10::TypedOperatorHandle<float_power_Scalar::schema> create_float_power_Scalar_typed_handle() { |
| 7826 | return c10::Dispatcher::singleton() |
| 7827 | .findSchemaOrThrow(float_power_Scalar::name, float_power_Scalar::overload_name) |
| 7828 | .typed<float_power_Scalar::schema>(); |
| 7829 | } |
| 7830 | |
| 7831 | // aten::float_power.Scalar(Scalar self, Tensor exponent) -> Tensor |
| 7832 | at::Tensor float_power_Scalar::call(const at::Scalar & self, const at::Tensor & exponent) { |
| 7833 | |
| 7834 | static auto op = create_float_power_Scalar_typed_handle(); |
| 7835 | return op.call(self, exponent); |
| 7836 | } |
| 7837 | |
| 7838 | // aten::float_power.Scalar(Scalar self, Tensor exponent) -> Tensor |
| 7839 | at::Tensor float_power_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & exponent) { |
| 7840 | |
| 7841 | static auto op = create_float_power_Scalar_typed_handle(); |
| 7842 | return op.redispatch(dispatchKeySet, self, exponent); |
| 7843 | } |
| 7844 | |
| 7845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Scalar_out, name, "aten::float_power") |
| 7846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Scalar_out, overload_name, "Tensor_Scalar_out") |
| 7847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Scalar_out, schema_str, "float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!)") |
| 7848 | |
| 7849 | // aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7850 | static C10_NOINLINE c10::TypedOperatorHandle<float_power_Tensor_Scalar_out::schema> create_float_power_Tensor_Scalar_out_typed_handle() { |
| 7851 | return c10::Dispatcher::singleton() |
| 7852 | .findSchemaOrThrow(float_power_Tensor_Scalar_out::name, float_power_Tensor_Scalar_out::overload_name) |
| 7853 | .typed<float_power_Tensor_Scalar_out::schema>(); |
| 7854 | } |
| 7855 | |
| 7856 | // aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7857 | at::Tensor & float_power_Tensor_Scalar_out::call(const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out) { |
| 7858 | |
| 7859 | static auto op = create_float_power_Tensor_Scalar_out_typed_handle(); |
| 7860 | return op.call(self, exponent, out); |
| 7861 | } |
| 7862 | |
| 7863 | // aten::float_power.Tensor_Scalar_out(Tensor self, Scalar exponent, *, Tensor(a!) out) -> Tensor(a!) |
| 7864 | at::Tensor & float_power_Tensor_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent, at::Tensor & out) { |
| 7865 | |
| 7866 | static auto op = create_float_power_Tensor_Scalar_out_typed_handle(); |
| 7867 | return op.redispatch(dispatchKeySet, self, exponent, out); |
| 7868 | } |
| 7869 | |
| 7870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Scalar, name, "aten::float_power") |
| 7871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Scalar, overload_name, "Tensor_Scalar") |
| 7872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power_Tensor_Scalar, schema_str, "float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor") |
| 7873 | |
| 7874 | // aten::float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor |
| 7875 | static C10_NOINLINE c10::TypedOperatorHandle<float_power_Tensor_Scalar::schema> create_float_power_Tensor_Scalar_typed_handle() { |
| 7876 | return c10::Dispatcher::singleton() |
| 7877 | .findSchemaOrThrow(float_power_Tensor_Scalar::name, float_power_Tensor_Scalar::overload_name) |
| 7878 | .typed<float_power_Tensor_Scalar::schema>(); |
| 7879 | } |
| 7880 | |
| 7881 | // aten::float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor |
| 7882 | at::Tensor float_power_Tensor_Scalar::call(const at::Tensor & self, const at::Scalar & exponent) { |
| 7883 | |
| 7884 | static auto op = create_float_power_Tensor_Scalar_typed_handle(); |
| 7885 | return op.call(self, exponent); |
| 7886 | } |
| 7887 | |
| 7888 | // aten::float_power.Tensor_Scalar(Tensor self, Scalar exponent) -> Tensor |
| 7889 | at::Tensor float_power_Tensor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & exponent) { |
| 7890 | |
| 7891 | static auto op = create_float_power_Tensor_Scalar_typed_handle(); |
| 7892 | return op.redispatch(dispatchKeySet, self, exponent); |
| 7893 | } |
| 7894 | |
| 7895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power__Scalar, name, "aten::float_power_") |
| 7896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power__Scalar, overload_name, "Scalar") |
| 7897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power__Scalar, schema_str, "float_power_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!)") |
| 7898 | |
| 7899 | // aten::float_power_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!) |
| 7900 | static C10_NOINLINE c10::TypedOperatorHandle<float_power__Scalar::schema> create_float_power__Scalar_typed_handle() { |
| 7901 | return c10::Dispatcher::singleton() |
| 7902 | .findSchemaOrThrow(float_power__Scalar::name, float_power__Scalar::overload_name) |
| 7903 | .typed<float_power__Scalar::schema>(); |
| 7904 | } |
| 7905 | |
| 7906 | // aten::float_power_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!) |
| 7907 | at::Tensor & float_power__Scalar::call(at::Tensor & self, const at::Scalar & exponent) { |
| 7908 | |
| 7909 | static auto op = create_float_power__Scalar_typed_handle(); |
| 7910 | return op.call(self, exponent); |
| 7911 | } |
| 7912 | |
| 7913 | // aten::float_power_.Scalar(Tensor(a!) self, Scalar exponent) -> Tensor(a!) |
| 7914 | at::Tensor & float_power__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & exponent) { |
| 7915 | |
| 7916 | static auto op = create_float_power__Scalar_typed_handle(); |
| 7917 | return op.redispatch(dispatchKeySet, self, exponent); |
| 7918 | } |
| 7919 | |
| 7920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power__Tensor, name, "aten::float_power_") |
| 7921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power__Tensor, overload_name, "Tensor") |
| 7922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(float_power__Tensor, schema_str, "float_power_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!)") |
| 7923 | |
| 7924 | // aten::float_power_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!) |
| 7925 | static C10_NOINLINE c10::TypedOperatorHandle<float_power__Tensor::schema> create_float_power__Tensor_typed_handle() { |
| 7926 | return c10::Dispatcher::singleton() |
| 7927 | .findSchemaOrThrow(float_power__Tensor::name, float_power__Tensor::overload_name) |
| 7928 | .typed<float_power__Tensor::schema>(); |
| 7929 | } |
| 7930 | |
| 7931 | // aten::float_power_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!) |
| 7932 | at::Tensor & float_power__Tensor::call(at::Tensor & self, const at::Tensor & exponent) { |
| 7933 | |
| 7934 | static auto op = create_float_power__Tensor_typed_handle(); |
| 7935 | return op.call(self, exponent); |
| 7936 | } |
| 7937 | |
| 7938 | // aten::float_power_.Tensor(Tensor(a!) self, Tensor exponent) -> Tensor(a!) |
| 7939 | at::Tensor & float_power__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & exponent) { |
| 7940 | |
| 7941 | static auto op = create_float_power__Tensor_typed_handle(); |
| 7942 | return op.redispatch(dispatchKeySet, self, exponent); |
| 7943 | } |
| 7944 | |
| 7945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_Scalar, name, "aten::_foreach_clamp_max") |
| 7946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_Scalar, overload_name, "Scalar") |
| 7947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_Scalar, schema_str, "_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[]") |
| 7948 | |
| 7949 | // aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 7950 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max_Scalar::schema> create__foreach_clamp_max_Scalar_typed_handle() { |
| 7951 | return c10::Dispatcher::singleton() |
| 7952 | .findSchemaOrThrow(_foreach_clamp_max_Scalar::name, _foreach_clamp_max_Scalar::overload_name) |
| 7953 | .typed<_foreach_clamp_max_Scalar::schema>(); |
| 7954 | } |
| 7955 | |
| 7956 | // aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 7957 | ::std::vector<at::Tensor> _foreach_clamp_max_Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 7958 | |
| 7959 | static auto op = create__foreach_clamp_max_Scalar_typed_handle(); |
| 7960 | return op.call(self, scalar); |
| 7961 | } |
| 7962 | |
| 7963 | // aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] |
| 7964 | ::std::vector<at::Tensor> _foreach_clamp_max_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 7965 | |
| 7966 | static auto op = create__foreach_clamp_max_Scalar_typed_handle(); |
| 7967 | return op.redispatch(dispatchKeySet, self, scalar); |
| 7968 | } |
| 7969 | |
| 7970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__Scalar, name, "aten::_foreach_clamp_max_") |
| 7971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__Scalar, overload_name, "Scalar") |
| 7972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__Scalar, schema_str, "_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> ()") |
| 7973 | |
| 7974 | // aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 7975 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max__Scalar::schema> create__foreach_clamp_max__Scalar_typed_handle() { |
| 7976 | return c10::Dispatcher::singleton() |
| 7977 | .findSchemaOrThrow(_foreach_clamp_max__Scalar::name, _foreach_clamp_max__Scalar::overload_name) |
| 7978 | .typed<_foreach_clamp_max__Scalar::schema>(); |
| 7979 | } |
| 7980 | |
| 7981 | // aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 7982 | void _foreach_clamp_max__Scalar::call(at::TensorList self, const at::Scalar & scalar) { |
| 7983 | |
| 7984 | static auto op = create__foreach_clamp_max__Scalar_typed_handle(); |
| 7985 | return op.call(self, scalar); |
| 7986 | } |
| 7987 | |
| 7988 | // aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () |
| 7989 | void _foreach_clamp_max__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar) { |
| 7990 | |
| 7991 | static auto op = create__foreach_clamp_max__Scalar_typed_handle(); |
| 7992 | return op.redispatch(dispatchKeySet, self, scalar); |
| 7993 | } |
| 7994 | |
| 7995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_List, name, "aten::_foreach_clamp_max") |
| 7996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_List, overload_name, "List") |
| 7997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_List, schema_str, "_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[]") |
| 7998 | |
| 7999 | // aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 8000 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max_List::schema> create__foreach_clamp_max_List_typed_handle() { |
| 8001 | return c10::Dispatcher::singleton() |
| 8002 | .findSchemaOrThrow(_foreach_clamp_max_List::name, _foreach_clamp_max_List::overload_name) |
| 8003 | .typed<_foreach_clamp_max_List::schema>(); |
| 8004 | } |
| 8005 | |
| 8006 | // aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 8007 | ::std::vector<at::Tensor> _foreach_clamp_max_List::call(at::TensorList self, at::TensorList other) { |
| 8008 | |
| 8009 | static auto op = create__foreach_clamp_max_List_typed_handle(); |
| 8010 | return op.call(self, other); |
| 8011 | } |
| 8012 | |
| 8013 | // aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] |
| 8014 | ::std::vector<at::Tensor> _foreach_clamp_max_List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other) { |
| 8015 | |
| 8016 | static auto op = create__foreach_clamp_max_List_typed_handle(); |
| 8017 | return op.redispatch(dispatchKeySet, self, other); |
| 8018 | } |
| 8019 | |
| 8020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__List, name, "aten::_foreach_clamp_max_") |
| 8021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__List, overload_name, "List") |
| 8022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__List, schema_str, "_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> ()") |
| 8023 | |
| 8024 | // aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 8025 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max__List::schema> create__foreach_clamp_max__List_typed_handle() { |
| 8026 | return c10::Dispatcher::singleton() |
| 8027 | .findSchemaOrThrow(_foreach_clamp_max__List::name, _foreach_clamp_max__List::overload_name) |
| 8028 | .typed<_foreach_clamp_max__List::schema>(); |
| 8029 | } |
| 8030 | |
| 8031 | // aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 8032 | void _foreach_clamp_max__List::call(at::TensorList self, at::TensorList other) { |
| 8033 | |
| 8034 | static auto op = create__foreach_clamp_max__List_typed_handle(); |
| 8035 | return op.call(self, other); |
| 8036 | } |
| 8037 | |
| 8038 | // aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () |
| 8039 | void _foreach_clamp_max__List::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other) { |
| 8040 | |
| 8041 | static auto op = create__foreach_clamp_max__List_typed_handle(); |
| 8042 | return op.redispatch(dispatchKeySet, self, other); |
| 8043 | } |
| 8044 | |
| 8045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_ScalarList, name, "aten::_foreach_clamp_max") |
| 8046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_ScalarList, overload_name, "ScalarList") |
| 8047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_ScalarList, schema_str, "_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[]") |
| 8048 | |
| 8049 | // aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 8050 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max_ScalarList::schema> create__foreach_clamp_max_ScalarList_typed_handle() { |
| 8051 | return c10::Dispatcher::singleton() |
| 8052 | .findSchemaOrThrow(_foreach_clamp_max_ScalarList::name, _foreach_clamp_max_ScalarList::overload_name) |
| 8053 | .typed<_foreach_clamp_max_ScalarList::schema>(); |
| 8054 | } |
| 8055 | |
| 8056 | // aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 8057 | ::std::vector<at::Tensor> _foreach_clamp_max_ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 8058 | |
| 8059 | static auto op = create__foreach_clamp_max_ScalarList_typed_handle(); |
| 8060 | return op.call(self, scalars); |
| 8061 | } |
| 8062 | |
| 8063 | // aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] |
| 8064 | ::std::vector<at::Tensor> _foreach_clamp_max_ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 8065 | |
| 8066 | static auto op = create__foreach_clamp_max_ScalarList_typed_handle(); |
| 8067 | return op.redispatch(dispatchKeySet, self, scalars); |
| 8068 | } |
| 8069 | |
| 8070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__ScalarList, name, "aten::_foreach_clamp_max_") |
| 8071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__ScalarList, overload_name, "ScalarList") |
| 8072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max__ScalarList, schema_str, "_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> ()") |
| 8073 | |
| 8074 | // aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 8075 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max__ScalarList::schema> create__foreach_clamp_max__ScalarList_typed_handle() { |
| 8076 | return c10::Dispatcher::singleton() |
| 8077 | .findSchemaOrThrow(_foreach_clamp_max__ScalarList::name, _foreach_clamp_max__ScalarList::overload_name) |
| 8078 | .typed<_foreach_clamp_max__ScalarList::schema>(); |
| 8079 | } |
| 8080 | |
| 8081 | // aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 8082 | void _foreach_clamp_max__ScalarList::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 8083 | |
| 8084 | static auto op = create__foreach_clamp_max__ScalarList_typed_handle(); |
| 8085 | return op.call(self, scalars); |
| 8086 | } |
| 8087 | |
| 8088 | // aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () |
| 8089 | void _foreach_clamp_max__ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars) { |
| 8090 | |
| 8091 | static auto op = create__foreach_clamp_max__ScalarList_typed_handle(); |
| 8092 | return op.redispatch(dispatchKeySet, self, scalars); |
| 8093 | } |
| 8094 | |
| 8095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs, name, "aten::_foreach_abs") |
| 8096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs, overload_name, "") |
| 8097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs, schema_str, "_foreach_abs(Tensor[] self) -> Tensor[]") |
| 8098 | |
| 8099 | // aten::_foreach_abs(Tensor[] self) -> Tensor[] |
| 8100 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_abs::schema> create__foreach_abs_typed_handle() { |
| 8101 | return c10::Dispatcher::singleton() |
| 8102 | .findSchemaOrThrow(_foreach_abs::name, _foreach_abs::overload_name) |
| 8103 | .typed<_foreach_abs::schema>(); |
| 8104 | } |
| 8105 | |
| 8106 | // aten::_foreach_abs(Tensor[] self) -> Tensor[] |
| 8107 | ::std::vector<at::Tensor> _foreach_abs::call(at::TensorList self) { |
| 8108 | |
| 8109 | static auto op = create__foreach_abs_typed_handle(); |
| 8110 | return op.call(self); |
| 8111 | } |
| 8112 | |
| 8113 | // aten::_foreach_abs(Tensor[] self) -> Tensor[] |
| 8114 | ::std::vector<at::Tensor> _foreach_abs::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8115 | |
| 8116 | static auto op = create__foreach_abs_typed_handle(); |
| 8117 | return op.redispatch(dispatchKeySet, self); |
| 8118 | } |
| 8119 | |
| 8120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs_, name, "aten::_foreach_abs_") |
| 8121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs_, overload_name, "") |
| 8122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs_, schema_str, "_foreach_abs_(Tensor(a!)[] self) -> ()") |
| 8123 | |
| 8124 | // aten::_foreach_abs_(Tensor(a!)[] self) -> () |
| 8125 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_abs_::schema> create__foreach_abs__typed_handle() { |
| 8126 | return c10::Dispatcher::singleton() |
| 8127 | .findSchemaOrThrow(_foreach_abs_::name, _foreach_abs_::overload_name) |
| 8128 | .typed<_foreach_abs_::schema>(); |
| 8129 | } |
| 8130 | |
| 8131 | // aten::_foreach_abs_(Tensor(a!)[] self) -> () |
| 8132 | void _foreach_abs_::call(at::TensorList self) { |
| 8133 | |
| 8134 | static auto op = create__foreach_abs__typed_handle(); |
| 8135 | return op.call(self); |
| 8136 | } |
| 8137 | |
| 8138 | // aten::_foreach_abs_(Tensor(a!)[] self) -> () |
| 8139 | void _foreach_abs_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8140 | |
| 8141 | static auto op = create__foreach_abs__typed_handle(); |
| 8142 | return op.redispatch(dispatchKeySet, self); |
| 8143 | } |
| 8144 | |
| 8145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1, name, "aten::_foreach_expm1") |
| 8146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1, overload_name, "") |
| 8147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1, schema_str, "_foreach_expm1(Tensor[] self) -> Tensor[]") |
| 8148 | |
| 8149 | // aten::_foreach_expm1(Tensor[] self) -> Tensor[] |
| 8150 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_expm1::schema> create__foreach_expm1_typed_handle() { |
| 8151 | return c10::Dispatcher::singleton() |
| 8152 | .findSchemaOrThrow(_foreach_expm1::name, _foreach_expm1::overload_name) |
| 8153 | .typed<_foreach_expm1::schema>(); |
| 8154 | } |
| 8155 | |
| 8156 | // aten::_foreach_expm1(Tensor[] self) -> Tensor[] |
| 8157 | ::std::vector<at::Tensor> _foreach_expm1::call(at::TensorList self) { |
| 8158 | |
| 8159 | static auto op = create__foreach_expm1_typed_handle(); |
| 8160 | return op.call(self); |
| 8161 | } |
| 8162 | |
| 8163 | // aten::_foreach_expm1(Tensor[] self) -> Tensor[] |
| 8164 | ::std::vector<at::Tensor> _foreach_expm1::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8165 | |
| 8166 | static auto op = create__foreach_expm1_typed_handle(); |
| 8167 | return op.redispatch(dispatchKeySet, self); |
| 8168 | } |
| 8169 | |
| 8170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1_, name, "aten::_foreach_expm1_") |
| 8171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1_, overload_name, "") |
| 8172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1_, schema_str, "_foreach_expm1_(Tensor(a!)[] self) -> ()") |
| 8173 | |
| 8174 | // aten::_foreach_expm1_(Tensor(a!)[] self) -> () |
| 8175 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_expm1_::schema> create__foreach_expm1__typed_handle() { |
| 8176 | return c10::Dispatcher::singleton() |
| 8177 | .findSchemaOrThrow(_foreach_expm1_::name, _foreach_expm1_::overload_name) |
| 8178 | .typed<_foreach_expm1_::schema>(); |
| 8179 | } |
| 8180 | |
| 8181 | // aten::_foreach_expm1_(Tensor(a!)[] self) -> () |
| 8182 | void _foreach_expm1_::call(at::TensorList self) { |
| 8183 | |
| 8184 | static auto op = create__foreach_expm1__typed_handle(); |
| 8185 | return op.call(self); |
| 8186 | } |
| 8187 | |
| 8188 | // aten::_foreach_expm1_(Tensor(a!)[] self) -> () |
| 8189 | void _foreach_expm1_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8190 | |
| 8191 | static auto op = create__foreach_expm1__typed_handle(); |
| 8192 | return op.redispatch(dispatchKeySet, self); |
| 8193 | } |
| 8194 | |
| 8195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10, name, "aten::_foreach_log10") |
| 8196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10, overload_name, "") |
| 8197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10, schema_str, "_foreach_log10(Tensor[] self) -> Tensor[]") |
| 8198 | |
| 8199 | // aten::_foreach_log10(Tensor[] self) -> Tensor[] |
| 8200 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log10::schema> create__foreach_log10_typed_handle() { |
| 8201 | return c10::Dispatcher::singleton() |
| 8202 | .findSchemaOrThrow(_foreach_log10::name, _foreach_log10::overload_name) |
| 8203 | .typed<_foreach_log10::schema>(); |
| 8204 | } |
| 8205 | |
| 8206 | // aten::_foreach_log10(Tensor[] self) -> Tensor[] |
| 8207 | ::std::vector<at::Tensor> _foreach_log10::call(at::TensorList self) { |
| 8208 | |
| 8209 | static auto op = create__foreach_log10_typed_handle(); |
| 8210 | return op.call(self); |
| 8211 | } |
| 8212 | |
| 8213 | // aten::_foreach_log10(Tensor[] self) -> Tensor[] |
| 8214 | ::std::vector<at::Tensor> _foreach_log10::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8215 | |
| 8216 | static auto op = create__foreach_log10_typed_handle(); |
| 8217 | return op.redispatch(dispatchKeySet, self); |
| 8218 | } |
| 8219 | |
| 8220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10_, name, "aten::_foreach_log10_") |
| 8221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10_, overload_name, "") |
| 8222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10_, schema_str, "_foreach_log10_(Tensor(a!)[] self) -> ()") |
| 8223 | |
| 8224 | // aten::_foreach_log10_(Tensor(a!)[] self) -> () |
| 8225 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log10_::schema> create__foreach_log10__typed_handle() { |
| 8226 | return c10::Dispatcher::singleton() |
| 8227 | .findSchemaOrThrow(_foreach_log10_::name, _foreach_log10_::overload_name) |
| 8228 | .typed<_foreach_log10_::schema>(); |
| 8229 | } |
| 8230 | |
| 8231 | // aten::_foreach_log10_(Tensor(a!)[] self) -> () |
| 8232 | void _foreach_log10_::call(at::TensorList self) { |
| 8233 | |
| 8234 | static auto op = create__foreach_log10__typed_handle(); |
| 8235 | return op.call(self); |
| 8236 | } |
| 8237 | |
| 8238 | // aten::_foreach_log10_(Tensor(a!)[] self) -> () |
| 8239 | void _foreach_log10_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8240 | |
| 8241 | static auto op = create__foreach_log10__typed_handle(); |
| 8242 | return op.redispatch(dispatchKeySet, self); |
| 8243 | } |
| 8244 | |
| 8245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan, name, "aten::_foreach_tan") |
| 8246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan, overload_name, "") |
| 8247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan, schema_str, "_foreach_tan(Tensor[] self) -> Tensor[]") |
| 8248 | |
| 8249 | // aten::_foreach_tan(Tensor[] self) -> Tensor[] |
| 8250 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_tan::schema> create__foreach_tan_typed_handle() { |
| 8251 | return c10::Dispatcher::singleton() |
| 8252 | .findSchemaOrThrow(_foreach_tan::name, _foreach_tan::overload_name) |
| 8253 | .typed<_foreach_tan::schema>(); |
| 8254 | } |
| 8255 | |
| 8256 | // aten::_foreach_tan(Tensor[] self) -> Tensor[] |
| 8257 | ::std::vector<at::Tensor> _foreach_tan::call(at::TensorList self) { |
| 8258 | |
| 8259 | static auto op = create__foreach_tan_typed_handle(); |
| 8260 | return op.call(self); |
| 8261 | } |
| 8262 | |
| 8263 | // aten::_foreach_tan(Tensor[] self) -> Tensor[] |
| 8264 | ::std::vector<at::Tensor> _foreach_tan::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8265 | |
| 8266 | static auto op = create__foreach_tan_typed_handle(); |
| 8267 | return op.redispatch(dispatchKeySet, self); |
| 8268 | } |
| 8269 | |
| 8270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan_, name, "aten::_foreach_tan_") |
| 8271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan_, overload_name, "") |
| 8272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan_, schema_str, "_foreach_tan_(Tensor(a!)[] self) -> ()") |
| 8273 | |
| 8274 | // aten::_foreach_tan_(Tensor(a!)[] self) -> () |
| 8275 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_tan_::schema> create__foreach_tan__typed_handle() { |
| 8276 | return c10::Dispatcher::singleton() |
| 8277 | .findSchemaOrThrow(_foreach_tan_::name, _foreach_tan_::overload_name) |
| 8278 | .typed<_foreach_tan_::schema>(); |
| 8279 | } |
| 8280 | |
| 8281 | // aten::_foreach_tan_(Tensor(a!)[] self) -> () |
| 8282 | void _foreach_tan_::call(at::TensorList self) { |
| 8283 | |
| 8284 | static auto op = create__foreach_tan__typed_handle(); |
| 8285 | return op.call(self); |
| 8286 | } |
| 8287 | |
| 8288 | // aten::_foreach_tan_(Tensor(a!)[] self) -> () |
| 8289 | void _foreach_tan_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8290 | |
| 8291 | static auto op = create__foreach_tan__typed_handle(); |
| 8292 | return op.redispatch(dispatchKeySet, self); |
| 8293 | } |
| 8294 | |
| 8295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh, name, "aten::_foreach_sinh") |
| 8296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh, overload_name, "") |
| 8297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh, schema_str, "_foreach_sinh(Tensor[] self) -> Tensor[]") |
| 8298 | |
| 8299 | // aten::_foreach_sinh(Tensor[] self) -> Tensor[] |
| 8300 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sinh::schema> create__foreach_sinh_typed_handle() { |
| 8301 | return c10::Dispatcher::singleton() |
| 8302 | .findSchemaOrThrow(_foreach_sinh::name, _foreach_sinh::overload_name) |
| 8303 | .typed<_foreach_sinh::schema>(); |
| 8304 | } |
| 8305 | |
| 8306 | // aten::_foreach_sinh(Tensor[] self) -> Tensor[] |
| 8307 | ::std::vector<at::Tensor> _foreach_sinh::call(at::TensorList self) { |
| 8308 | |
| 8309 | static auto op = create__foreach_sinh_typed_handle(); |
| 8310 | return op.call(self); |
| 8311 | } |
| 8312 | |
| 8313 | // aten::_foreach_sinh(Tensor[] self) -> Tensor[] |
| 8314 | ::std::vector<at::Tensor> _foreach_sinh::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8315 | |
| 8316 | static auto op = create__foreach_sinh_typed_handle(); |
| 8317 | return op.redispatch(dispatchKeySet, self); |
| 8318 | } |
| 8319 | |
| 8320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh_, name, "aten::_foreach_sinh_") |
| 8321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh_, overload_name, "") |
| 8322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh_, schema_str, "_foreach_sinh_(Tensor(a!)[] self) -> ()") |
| 8323 | |
| 8324 | // aten::_foreach_sinh_(Tensor(a!)[] self) -> () |
| 8325 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sinh_::schema> create__foreach_sinh__typed_handle() { |
| 8326 | return c10::Dispatcher::singleton() |
| 8327 | .findSchemaOrThrow(_foreach_sinh_::name, _foreach_sinh_::overload_name) |
| 8328 | .typed<_foreach_sinh_::schema>(); |
| 8329 | } |
| 8330 | |
| 8331 | // aten::_foreach_sinh_(Tensor(a!)[] self) -> () |
| 8332 | void _foreach_sinh_::call(at::TensorList self) { |
| 8333 | |
| 8334 | static auto op = create__foreach_sinh__typed_handle(); |
| 8335 | return op.call(self); |
| 8336 | } |
| 8337 | |
| 8338 | // aten::_foreach_sinh_(Tensor(a!)[] self) -> () |
| 8339 | void _foreach_sinh_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
| 8340 | |
| 8341 | static auto op = create__foreach_sinh__typed_handle(); |
| 8342 | return op.redispatch(dispatchKeySet, self); |
| 8343 | } |
| 8344 | |
| 8345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Tensor, name, "aten::searchsorted") |
| 8346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Tensor, overload_name, "Tensor") |
| 8347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Tensor, schema_str, "searchsorted.Tensor(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor") |
| 8348 | |
| 8349 | // aten::searchsorted.Tensor(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor |
| 8350 | static C10_NOINLINE c10::TypedOperatorHandle<searchsorted_Tensor::schema> create_searchsorted_Tensor_typed_handle() { |
| 8351 | return c10::Dispatcher::singleton() |
| 8352 | .findSchemaOrThrow(searchsorted_Tensor::name, searchsorted_Tensor::overload_name) |
| 8353 | .typed<searchsorted_Tensor::schema>(); |
| 8354 | } |
| 8355 | |
| 8356 | // aten::searchsorted.Tensor(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor |
| 8357 | at::Tensor searchsorted_Tensor::call(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter) { |
| 8358 | |
| 8359 | static auto op = create_searchsorted_Tensor_typed_handle(); |
| 8360 | return op.call(sorted_sequence, self, out_int32, right, side, sorter); |
| 8361 | } |
| 8362 | |
| 8363 | // aten::searchsorted.Tensor(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor |
| 8364 | at::Tensor searchsorted_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter) { |
| 8365 | |
| 8366 | static auto op = create_searchsorted_Tensor_typed_handle(); |
| 8367 | return op.redispatch(dispatchKeySet, sorted_sequence, self, out_int32, right, side, sorter); |
| 8368 | } |
| 8369 | |
| 8370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Tensor_out, name, "aten::searchsorted") |
| 8371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Tensor_out, overload_name, "Tensor_out") |
| 8372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Tensor_out, schema_str, "searchsorted.Tensor_out(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!)") |
| 8373 | |
| 8374 | // aten::searchsorted.Tensor_out(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) |
| 8375 | static C10_NOINLINE c10::TypedOperatorHandle<searchsorted_Tensor_out::schema> create_searchsorted_Tensor_out_typed_handle() { |
| 8376 | return c10::Dispatcher::singleton() |
| 8377 | .findSchemaOrThrow(searchsorted_Tensor_out::name, searchsorted_Tensor_out::overload_name) |
| 8378 | .typed<searchsorted_Tensor_out::schema>(); |
| 8379 | } |
| 8380 | |
| 8381 | // aten::searchsorted.Tensor_out(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) |
| 8382 | at::Tensor & searchsorted_Tensor_out::call(const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter, at::Tensor & out) { |
| 8383 | |
| 8384 | static auto op = create_searchsorted_Tensor_out_typed_handle(); |
| 8385 | return op.call(sorted_sequence, self, out_int32, right, side, sorter, out); |
| 8386 | } |
| 8387 | |
| 8388 | // aten::searchsorted.Tensor_out(Tensor sorted_sequence, Tensor self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) |
| 8389 | at::Tensor & searchsorted_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sorted_sequence, const at::Tensor & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter, at::Tensor & out) { |
| 8390 | |
| 8391 | static auto op = create_searchsorted_Tensor_out_typed_handle(); |
| 8392 | return op.redispatch(dispatchKeySet, sorted_sequence, self, out_int32, right, side, sorter, out); |
| 8393 | } |
| 8394 | |
| 8395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Scalar, name, "aten::searchsorted") |
| 8396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Scalar, overload_name, "Scalar") |
| 8397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Scalar, schema_str, "searchsorted.Scalar(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor") |
| 8398 | |
| 8399 | // aten::searchsorted.Scalar(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor |
| 8400 | static C10_NOINLINE c10::TypedOperatorHandle<searchsorted_Scalar::schema> create_searchsorted_Scalar_typed_handle() { |
| 8401 | return c10::Dispatcher::singleton() |
| 8402 | .findSchemaOrThrow(searchsorted_Scalar::name, searchsorted_Scalar::overload_name) |
| 8403 | .typed<searchsorted_Scalar::schema>(); |
| 8404 | } |
| 8405 | |
| 8406 | // aten::searchsorted.Scalar(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor |
| 8407 | at::Tensor searchsorted_Scalar::call(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter) { |
| 8408 | |
| 8409 | static auto op = create_searchsorted_Scalar_typed_handle(); |
| 8410 | return op.call(sorted_sequence, self, out_int32, right, side, sorter); |
| 8411 | } |
| 8412 | |
| 8413 | // aten::searchsorted.Scalar(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None) -> Tensor |
| 8414 | at::Tensor searchsorted_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter) { |
| 8415 | |
| 8416 | static auto op = create_searchsorted_Scalar_typed_handle(); |
| 8417 | return op.redispatch(dispatchKeySet, sorted_sequence, self, out_int32, right, side, sorter); |
| 8418 | } |
| 8419 | |
| 8420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smooth_l1_loss_out, name, "aten::smooth_l1_loss") |
| 8421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smooth_l1_loss_out, overload_name, "out") |
| 8422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smooth_l1_loss_out, schema_str, "smooth_l1_loss.out(Tensor self, Tensor target, int reduction=Mean, float beta=1.0, *, Tensor(a!) out) -> Tensor(a!)") |
| 8423 | |
| 8424 | // aten::smooth_l1_loss.out(Tensor self, Tensor target, int reduction=Mean, float beta=1.0, *, Tensor(a!) out) -> Tensor(a!) |
| 8425 | static C10_NOINLINE c10::TypedOperatorHandle<smooth_l1_loss_out::schema> create_smooth_l1_loss_out_typed_handle() { |
| 8426 | return c10::Dispatcher::singleton() |
| 8427 | .findSchemaOrThrow(smooth_l1_loss_out::name, smooth_l1_loss_out::overload_name) |
| 8428 | .typed<smooth_l1_loss_out::schema>(); |
| 8429 | } |
| 8430 | |
| 8431 | // aten::smooth_l1_loss.out(Tensor self, Tensor target, int reduction=Mean, float beta=1.0, *, Tensor(a!) out) -> Tensor(a!) |
| 8432 | at::Tensor & smooth_l1_loss_out::call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out) { |
| 8433 | |
| 8434 | static auto op = create_smooth_l1_loss_out_typed_handle(); |
| 8435 | return op.call(self, target, reduction, beta, out); |
| 8436 | } |
| 8437 | |
| 8438 | // aten::smooth_l1_loss.out(Tensor self, Tensor target, int reduction=Mean, float beta=1.0, *, Tensor(a!) out) -> Tensor(a!) |
| 8439 | at::Tensor & smooth_l1_loss_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta, at::Tensor & out) { |
| 8440 | |
| 8441 | static auto op = create_smooth_l1_loss_out_typed_handle(); |
| 8442 | return op.redispatch(dispatchKeySet, self, target, reduction, beta, out); |
| 8443 | } |
| 8444 | |
| 8445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smooth_l1_loss, name, "aten::smooth_l1_loss") |
| 8446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smooth_l1_loss, overload_name, "") |
| 8447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(smooth_l1_loss, schema_str, "smooth_l1_loss(Tensor self, Tensor target, int reduction=Mean, float beta=1.0) -> Tensor") |
| 8448 | |
| 8449 | // aten::smooth_l1_loss(Tensor self, Tensor target, int reduction=Mean, float beta=1.0) -> Tensor |
| 8450 | static C10_NOINLINE c10::TypedOperatorHandle<smooth_l1_loss::schema> create_smooth_l1_loss_typed_handle() { |
| 8451 | return c10::Dispatcher::singleton() |
| 8452 | .findSchemaOrThrow(smooth_l1_loss::name, smooth_l1_loss::overload_name) |
| 8453 | .typed<smooth_l1_loss::schema>(); |
| 8454 | } |
| 8455 | |
| 8456 | // aten::smooth_l1_loss(Tensor self, Tensor target, int reduction=Mean, float beta=1.0) -> Tensor |
| 8457 | at::Tensor smooth_l1_loss::call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta) { |
| 8458 | |
| 8459 | static auto op = create_smooth_l1_loss_typed_handle(); |
| 8460 | return op.call(self, target, reduction, beta); |
| 8461 | } |
| 8462 | |
| 8463 | // aten::smooth_l1_loss(Tensor self, Tensor target, int reduction=Mean, float beta=1.0) -> Tensor |
| 8464 | at::Tensor smooth_l1_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, double beta) { |
| 8465 | |
| 8466 | static auto op = create_smooth_l1_loss_typed_handle(); |
| 8467 | return op.redispatch(dispatchKeySet, self, target, reduction, beta); |
| 8468 | } |
| 8469 | |
| 8470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_out, name, "aten::elu") |
| 8471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_out, overload_name, "out") |
| 8472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_out, schema_str, "elu.out(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 8473 | |
| 8474 | // aten::elu.out(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1, *, Tensor(a!) out) -> Tensor(a!) |
| 8475 | static C10_NOINLINE c10::TypedOperatorHandle<elu_out::schema> create_elu_out_typed_handle() { |
| 8476 | return c10::Dispatcher::singleton() |
| 8477 | .findSchemaOrThrow(elu_out::name, elu_out::overload_name) |
| 8478 | .typed<elu_out::schema>(); |
| 8479 | } |
| 8480 | |
| 8481 | // aten::elu.out(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1, *, Tensor(a!) out) -> Tensor(a!) |
| 8482 | at::Tensor & elu_out::call(const at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, at::Tensor & out) { |
| 8483 | |
| 8484 | static auto op = create_elu_out_typed_handle(); |
| 8485 | return op.call(self, alpha, scale, input_scale, out); |
| 8486 | } |
| 8487 | |
| 8488 | // aten::elu.out(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1, *, Tensor(a!) out) -> Tensor(a!) |
| 8489 | at::Tensor & elu_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale, at::Tensor & out) { |
| 8490 | |
| 8491 | static auto op = create_elu_out_typed_handle(); |
| 8492 | return op.redispatch(dispatchKeySet, self, alpha, scale, input_scale, out); |
| 8493 | } |
| 8494 | |
| 8495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu, name, "aten::elu") |
| 8496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu, overload_name, "") |
| 8497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu, schema_str, "elu(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor") |
| 8498 | |
| 8499 | // aten::elu(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor |
| 8500 | static C10_NOINLINE c10::TypedOperatorHandle<elu::schema> create_elu_typed_handle() { |
| 8501 | return c10::Dispatcher::singleton() |
| 8502 | .findSchemaOrThrow(elu::name, elu::overload_name) |
| 8503 | .typed<elu::schema>(); |
| 8504 | } |
| 8505 | |
| 8506 | // aten::elu(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor |
| 8507 | at::Tensor elu::call(const at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale) { |
| 8508 | |
| 8509 | static auto op = create_elu_typed_handle(); |
| 8510 | return op.call(self, alpha, scale, input_scale); |
| 8511 | } |
| 8512 | |
| 8513 | // aten::elu(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor |
| 8514 | at::Tensor elu::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale) { |
| 8515 | |
| 8516 | static auto op = create_elu_typed_handle(); |
| 8517 | return op.redispatch(dispatchKeySet, self, alpha, scale, input_scale); |
| 8518 | } |
| 8519 | |
| 8520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_, name, "aten::elu_") |
| 8521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_, overload_name, "") |
| 8522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(elu_, schema_str, "elu_(Tensor(a!) self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor(a!)") |
| 8523 | |
| 8524 | // aten::elu_(Tensor(a!) self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor(a!) |
| 8525 | static C10_NOINLINE c10::TypedOperatorHandle<elu_::schema> create_elu__typed_handle() { |
| 8526 | return c10::Dispatcher::singleton() |
| 8527 | .findSchemaOrThrow(elu_::name, elu_::overload_name) |
| 8528 | .typed<elu_::schema>(); |
| 8529 | } |
| 8530 | |
| 8531 | // aten::elu_(Tensor(a!) self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor(a!) |
| 8532 | at::Tensor & elu_::call(at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale) { |
| 8533 | |
| 8534 | static auto op = create_elu__typed_handle(); |
| 8535 | return op.call(self, alpha, scale, input_scale); |
| 8536 | } |
| 8537 | |
| 8538 | // aten::elu_(Tensor(a!) self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> Tensor(a!) |
| 8539 | at::Tensor & elu_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & alpha, const at::Scalar & scale, const at::Scalar & input_scale) { |
| 8540 | |
| 8541 | static auto op = create_elu__typed_handle(); |
| 8542 | return op.redispatch(dispatchKeySet, self, alpha, scale, input_scale); |
| 8543 | } |
| 8544 | |
| 8545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_backward_grad_input, name, "aten::glu_backward") |
| 8546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_backward_grad_input, overload_name, "grad_input") |
| 8547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_backward_grad_input, schema_str, "glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 8548 | |
| 8549 | // aten::glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8550 | static C10_NOINLINE c10::TypedOperatorHandle<glu_backward_grad_input::schema> create_glu_backward_grad_input_typed_handle() { |
| 8551 | return c10::Dispatcher::singleton() |
| 8552 | .findSchemaOrThrow(glu_backward_grad_input::name, glu_backward_grad_input::overload_name) |
| 8553 | .typed<glu_backward_grad_input::schema>(); |
| 8554 | } |
| 8555 | |
| 8556 | // aten::glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8557 | at::Tensor & glu_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input) { |
| 8558 | |
| 8559 | static auto op = create_glu_backward_grad_input_typed_handle(); |
| 8560 | return op.call(grad_output, self, dim, grad_input); |
| 8561 | } |
| 8562 | |
| 8563 | // aten::glu_backward.grad_input(Tensor grad_output, Tensor self, int dim, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8564 | at::Tensor & glu_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, at::Tensor & grad_input) { |
| 8565 | |
| 8566 | static auto op = create_glu_backward_grad_input_typed_handle(); |
| 8567 | return op.redispatch(dispatchKeySet, grad_output, self, dim, grad_input); |
| 8568 | } |
| 8569 | |
| 8570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_backward, name, "aten::glu_backward") |
| 8571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_backward, overload_name, "") |
| 8572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_backward, schema_str, "glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor") |
| 8573 | |
| 8574 | // aten::glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor |
| 8575 | static C10_NOINLINE c10::TypedOperatorHandle<glu_backward::schema> create_glu_backward_typed_handle() { |
| 8576 | return c10::Dispatcher::singleton() |
| 8577 | .findSchemaOrThrow(glu_backward::name, glu_backward::overload_name) |
| 8578 | .typed<glu_backward::schema>(); |
| 8579 | } |
| 8580 | |
| 8581 | // aten::glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor |
| 8582 | at::Tensor glu_backward::call(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim) { |
| 8583 | |
| 8584 | static auto op = create_glu_backward_typed_handle(); |
| 8585 | return op.call(grad_output, self, dim); |
| 8586 | } |
| 8587 | |
| 8588 | // aten::glu_backward(Tensor grad_output, Tensor self, int dim) -> Tensor |
| 8589 | at::Tensor glu_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim) { |
| 8590 | |
| 8591 | static auto op = create_glu_backward_typed_handle(); |
| 8592 | return op.redispatch(dispatchKeySet, grad_output, self, dim); |
| 8593 | } |
| 8594 | |
| 8595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardtanh_backward_grad_input, name, "aten::hardtanh_backward") |
| 8596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardtanh_backward_grad_input, overload_name, "grad_input") |
| 8597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardtanh_backward_grad_input, schema_str, "hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 8598 | |
| 8599 | // aten::hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8600 | static C10_NOINLINE c10::TypedOperatorHandle<hardtanh_backward_grad_input::schema> create_hardtanh_backward_grad_input_typed_handle() { |
| 8601 | return c10::Dispatcher::singleton() |
| 8602 | .findSchemaOrThrow(hardtanh_backward_grad_input::name, hardtanh_backward_grad_input::overload_name) |
| 8603 | .typed<hardtanh_backward_grad_input::schema>(); |
| 8604 | } |
| 8605 | |
| 8606 | // aten::hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8607 | at::Tensor & hardtanh_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input) { |
| 8608 | |
| 8609 | static auto op = create_hardtanh_backward_grad_input_typed_handle(); |
| 8610 | return op.call(grad_output, self, min_val, max_val, grad_input); |
| 8611 | } |
| 8612 | |
| 8613 | // aten::hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8614 | at::Tensor & hardtanh_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input) { |
| 8615 | |
| 8616 | static auto op = create_hardtanh_backward_grad_input_typed_handle(); |
| 8617 | return op.redispatch(dispatchKeySet, grad_output, self, min_val, max_val, grad_input); |
| 8618 | } |
| 8619 | |
| 8620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardtanh_backward, name, "aten::hardtanh_backward") |
| 8621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardtanh_backward, overload_name, "") |
| 8622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardtanh_backward, schema_str, "hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor") |
| 8623 | |
| 8624 | // aten::hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor |
| 8625 | static C10_NOINLINE c10::TypedOperatorHandle<hardtanh_backward::schema> create_hardtanh_backward_typed_handle() { |
| 8626 | return c10::Dispatcher::singleton() |
| 8627 | .findSchemaOrThrow(hardtanh_backward::name, hardtanh_backward::overload_name) |
| 8628 | .typed<hardtanh_backward::schema>(); |
| 8629 | } |
| 8630 | |
| 8631 | // aten::hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor |
| 8632 | at::Tensor hardtanh_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val) { |
| 8633 | |
| 8634 | static auto op = create_hardtanh_backward_typed_handle(); |
| 8635 | return op.call(grad_output, self, min_val, max_val); |
| 8636 | } |
| 8637 | |
| 8638 | // aten::hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor |
| 8639 | at::Tensor hardtanh_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val) { |
| 8640 | |
| 8641 | static auto op = create_hardtanh_backward_typed_handle(); |
| 8642 | return op.redispatch(dispatchKeySet, grad_output, self, min_val, max_val); |
| 8643 | } |
| 8644 | |
| 8645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(leaky_relu_backward_grad_input, name, "aten::leaky_relu_backward") |
| 8646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(leaky_relu_backward_grad_input, overload_name, "grad_input") |
| 8647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(leaky_relu_backward_grad_input, schema_str, "leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 8648 | |
| 8649 | // aten::leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8650 | static C10_NOINLINE c10::TypedOperatorHandle<leaky_relu_backward_grad_input::schema> create_leaky_relu_backward_grad_input_typed_handle() { |
| 8651 | return c10::Dispatcher::singleton() |
| 8652 | .findSchemaOrThrow(leaky_relu_backward_grad_input::name, leaky_relu_backward_grad_input::overload_name) |
| 8653 | .typed<leaky_relu_backward_grad_input::schema>(); |
| 8654 | } |
| 8655 | |
| 8656 | // aten::leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8657 | at::Tensor & leaky_relu_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result, at::Tensor & grad_input) { |
| 8658 | |
| 8659 | static auto op = create_leaky_relu_backward_grad_input_typed_handle(); |
| 8660 | return op.call(grad_output, self, negative_slope, self_is_result, grad_input); |
| 8661 | } |
| 8662 | |
| 8663 | // aten::leaky_relu_backward.grad_input(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8664 | at::Tensor & leaky_relu_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result, at::Tensor & grad_input) { |
| 8665 | |
| 8666 | static auto op = create_leaky_relu_backward_grad_input_typed_handle(); |
| 8667 | return op.redispatch(dispatchKeySet, grad_output, self, negative_slope, self_is_result, grad_input); |
| 8668 | } |
| 8669 | |
| 8670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(leaky_relu_backward, name, "aten::leaky_relu_backward") |
| 8671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(leaky_relu_backward, overload_name, "") |
| 8672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(leaky_relu_backward, schema_str, "leaky_relu_backward(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result) -> Tensor") |
| 8673 | |
| 8674 | // aten::leaky_relu_backward(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result) -> Tensor |
| 8675 | static C10_NOINLINE c10::TypedOperatorHandle<leaky_relu_backward::schema> create_leaky_relu_backward_typed_handle() { |
| 8676 | return c10::Dispatcher::singleton() |
| 8677 | .findSchemaOrThrow(leaky_relu_backward::name, leaky_relu_backward::overload_name) |
| 8678 | .typed<leaky_relu_backward::schema>(); |
| 8679 | } |
| 8680 | |
| 8681 | // aten::leaky_relu_backward(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result) -> Tensor |
| 8682 | at::Tensor leaky_relu_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result) { |
| 8683 | |
| 8684 | static auto op = create_leaky_relu_backward_typed_handle(); |
| 8685 | return op.call(grad_output, self, negative_slope, self_is_result); |
| 8686 | } |
| 8687 | |
| 8688 | // aten::leaky_relu_backward(Tensor grad_output, Tensor self, Scalar negative_slope, bool self_is_result) -> Tensor |
| 8689 | at::Tensor leaky_relu_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & negative_slope, bool self_is_result) { |
| 8690 | |
| 8691 | static auto op = create_leaky_relu_backward_typed_handle(); |
| 8692 | return op.redispatch(dispatchKeySet, grad_output, self, negative_slope, self_is_result); |
| 8693 | } |
| 8694 | |
| 8695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_out, name, "aten::softplus") |
| 8696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_out, overload_name, "out") |
| 8697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus_out, schema_str, "softplus.out(Tensor self, Scalar beta=1, Scalar threshold=20, *, Tensor(a!) out) -> Tensor(a!)") |
| 8698 | |
| 8699 | // aten::softplus.out(Tensor self, Scalar beta=1, Scalar threshold=20, *, Tensor(a!) out) -> Tensor(a!) |
| 8700 | static C10_NOINLINE c10::TypedOperatorHandle<softplus_out::schema> create_softplus_out_typed_handle() { |
| 8701 | return c10::Dispatcher::singleton() |
| 8702 | .findSchemaOrThrow(softplus_out::name, softplus_out::overload_name) |
| 8703 | .typed<softplus_out::schema>(); |
| 8704 | } |
| 8705 | |
| 8706 | // aten::softplus.out(Tensor self, Scalar beta=1, Scalar threshold=20, *, Tensor(a!) out) -> Tensor(a!) |
| 8707 | at::Tensor & softplus_out::call(const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & out) { |
| 8708 | |
| 8709 | static auto op = create_softplus_out_typed_handle(); |
| 8710 | return op.call(self, beta, threshold, out); |
| 8711 | } |
| 8712 | |
| 8713 | // aten::softplus.out(Tensor self, Scalar beta=1, Scalar threshold=20, *, Tensor(a!) out) -> Tensor(a!) |
| 8714 | at::Tensor & softplus_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold, at::Tensor & out) { |
| 8715 | |
| 8716 | static auto op = create_softplus_out_typed_handle(); |
| 8717 | return op.redispatch(dispatchKeySet, self, beta, threshold, out); |
| 8718 | } |
| 8719 | |
| 8720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus, name, "aten::softplus") |
| 8721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus, overload_name, "") |
| 8722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softplus, schema_str, "softplus(Tensor self, Scalar beta=1, Scalar threshold=20) -> Tensor") |
| 8723 | |
| 8724 | // aten::softplus(Tensor self, Scalar beta=1, Scalar threshold=20) -> Tensor |
| 8725 | static C10_NOINLINE c10::TypedOperatorHandle<softplus::schema> create_softplus_typed_handle() { |
| 8726 | return c10::Dispatcher::singleton() |
| 8727 | .findSchemaOrThrow(softplus::name, softplus::overload_name) |
| 8728 | .typed<softplus::schema>(); |
| 8729 | } |
| 8730 | |
| 8731 | // aten::softplus(Tensor self, Scalar beta=1, Scalar threshold=20) -> Tensor |
| 8732 | at::Tensor softplus::call(const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { |
| 8733 | |
| 8734 | static auto op = create_softplus_typed_handle(); |
| 8735 | return op.call(self, beta, threshold); |
| 8736 | } |
| 8737 | |
| 8738 | // aten::softplus(Tensor self, Scalar beta=1, Scalar threshold=20) -> Tensor |
| 8739 | at::Tensor softplus::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & beta, const at::Scalar & threshold) { |
| 8740 | |
| 8741 | static auto op = create_softplus_typed_handle(); |
| 8742 | return op.redispatch(dispatchKeySet, self, beta, threshold); |
| 8743 | } |
| 8744 | |
| 8745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d, name, "aten::mkldnn_adaptive_avg_pool2d") |
| 8746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d, overload_name, "") |
| 8747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d, schema_str, "mkldnn_adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensor") |
| 8748 | |
| 8749 | // aten::mkldnn_adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensor |
| 8750 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_adaptive_avg_pool2d::schema> create_mkldnn_adaptive_avg_pool2d_typed_handle() { |
| 8751 | return c10::Dispatcher::singleton() |
| 8752 | .findSchemaOrThrow(mkldnn_adaptive_avg_pool2d::name, mkldnn_adaptive_avg_pool2d::overload_name) |
| 8753 | .typed<mkldnn_adaptive_avg_pool2d::schema>(); |
| 8754 | } |
| 8755 | |
| 8756 | // aten::mkldnn_adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensor |
| 8757 | at::Tensor mkldnn_adaptive_avg_pool2d::call(const at::Tensor & self, at::IntArrayRef output_size) { |
| 8758 | |
| 8759 | static auto op = create_mkldnn_adaptive_avg_pool2d_typed_handle(); |
| 8760 | return op.call(self, output_size); |
| 8761 | } |
| 8762 | |
| 8763 | // aten::mkldnn_adaptive_avg_pool2d(Tensor self, int[2] output_size) -> Tensor |
| 8764 | at::Tensor mkldnn_adaptive_avg_pool2d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size) { |
| 8765 | |
| 8766 | static auto op = create_mkldnn_adaptive_avg_pool2d_typed_handle(); |
| 8767 | return op.redispatch(dispatchKeySet, self, output_size); |
| 8768 | } |
| 8769 | |
| 8770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_out, name, "aten::mkldnn_adaptive_avg_pool2d") |
| 8771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_out, overload_name, "out") |
| 8772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_adaptive_avg_pool2d_out, schema_str, "mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!)") |
| 8773 | |
| 8774 | // aten::mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!) |
| 8775 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_adaptive_avg_pool2d_out::schema> create_mkldnn_adaptive_avg_pool2d_out_typed_handle() { |
| 8776 | return c10::Dispatcher::singleton() |
| 8777 | .findSchemaOrThrow(mkldnn_adaptive_avg_pool2d_out::name, mkldnn_adaptive_avg_pool2d_out::overload_name) |
| 8778 | .typed<mkldnn_adaptive_avg_pool2d_out::schema>(); |
| 8779 | } |
| 8780 | |
| 8781 | // aten::mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!) |
| 8782 | at::Tensor & mkldnn_adaptive_avg_pool2d_out::call(const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { |
| 8783 | |
| 8784 | static auto op = create_mkldnn_adaptive_avg_pool2d_out_typed_handle(); |
| 8785 | return op.call(self, output_size, out); |
| 8786 | } |
| 8787 | |
| 8788 | // aten::mkldnn_adaptive_avg_pool2d.out(Tensor self, int[2] output_size, *, Tensor(a!) out) -> Tensor(a!) |
| 8789 | at::Tensor & mkldnn_adaptive_avg_pool2d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef output_size, at::Tensor & out) { |
| 8790 | |
| 8791 | static auto op = create_mkldnn_adaptive_avg_pool2d_out_typed_handle(); |
| 8792 | return op.redispatch(dispatchKeySet, self, output_size, out); |
| 8793 | } |
| 8794 | |
| 8795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d, name, "aten::_adaptive_avg_pool2d") |
| 8796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d, overload_name, "") |
| 8797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d, schema_str, "_adaptive_avg_pool2d(Tensor self, SymInt[2] output_size) -> Tensor") |
| 8798 | |
| 8799 | // aten::_adaptive_avg_pool2d(Tensor self, SymInt[2] output_size) -> Tensor |
| 8800 | static C10_NOINLINE c10::TypedOperatorHandle<_adaptive_avg_pool2d::schema> create__adaptive_avg_pool2d_typed_handle() { |
| 8801 | return c10::Dispatcher::singleton() |
| 8802 | .findSchemaOrThrow(_adaptive_avg_pool2d::name, _adaptive_avg_pool2d::overload_name) |
| 8803 | .typed<_adaptive_avg_pool2d::schema>(); |
| 8804 | } |
| 8805 | |
| 8806 | // aten::_adaptive_avg_pool2d(Tensor self, SymInt[2] output_size) -> Tensor |
| 8807 | at::Tensor _adaptive_avg_pool2d::call(const at::Tensor & self, c10::SymIntArrayRef output_size) { |
| 8808 | |
| 8809 | static auto op = create__adaptive_avg_pool2d_typed_handle(); |
| 8810 | return op.call(self, output_size); |
| 8811 | } |
| 8812 | |
| 8813 | // aten::_adaptive_avg_pool2d(Tensor self, SymInt[2] output_size) -> Tensor |
| 8814 | at::Tensor _adaptive_avg_pool2d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size) { |
| 8815 | |
| 8816 | static auto op = create__adaptive_avg_pool2d_typed_handle(); |
| 8817 | return op.redispatch(dispatchKeySet, self, output_size); |
| 8818 | } |
| 8819 | |
| 8820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_out, name, "aten::avg_pool3d") |
| 8821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_out, overload_name, "out") |
| 8822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_out, schema_str, "avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 8823 | |
| 8824 | // aten::avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) |
| 8825 | static C10_NOINLINE c10::TypedOperatorHandle<avg_pool3d_out::schema> create_avg_pool3d_out_typed_handle() { |
| 8826 | return c10::Dispatcher::singleton() |
| 8827 | .findSchemaOrThrow(avg_pool3d_out::name, avg_pool3d_out::overload_name) |
| 8828 | .typed<avg_pool3d_out::schema>(); |
| 8829 | } |
| 8830 | |
| 8831 | // aten::avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) |
| 8832 | at::Tensor & avg_pool3d_out::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override, at::Tensor & out) { |
| 8833 | |
| 8834 | static auto op = create_avg_pool3d_out_typed_handle(); |
| 8835 | return op.call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); |
| 8836 | } |
| 8837 | |
| 8838 | // aten::avg_pool3d.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) |
| 8839 | at::Tensor & avg_pool3d_out::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, c10::optional<int64_t> divisor_override, at::Tensor & out) { |
| 8840 | |
| 8841 | static auto op = create_avg_pool3d_out_typed_handle(); |
| 8842 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); |
| 8843 | } |
| 8844 | |
| 8845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d, name, "aten::avg_pool3d") |
| 8846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d, overload_name, "") |
| 8847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d, schema_str, "avg_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor") |
| 8848 | |
| 8849 | // aten::avg_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor |
| 8850 | static C10_NOINLINE c10::TypedOperatorHandle<avg_pool3d::schema> create_avg_pool3d_typed_handle() { |
| 8851 | return c10::Dispatcher::singleton() |
| 8852 | .findSchemaOrThrow(avg_pool3d::name, avg_pool3d::overload_name) |
| 8853 | .typed<avg_pool3d::schema>(); |
| 8854 | } |
| 8855 | |
| 8856 | // aten::avg_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor |
| 8857 | at::Tensor avg_pool3d::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override) { |
| 8858 | |
| 8859 | static auto op = create_avg_pool3d_typed_handle(); |
| 8860 | return op.call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); |
| 8861 | } |
| 8862 | |
| 8863 | // aten::avg_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor |
| 8864 | at::Tensor avg_pool3d::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, c10::optional<int64_t> divisor_override) { |
| 8865 | |
| 8866 | static auto op = create_avg_pool3d_typed_handle(); |
| 8867 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); |
| 8868 | } |
| 8869 | |
| 8870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_backward_grad_input, name, "aten::avg_pool3d_backward") |
| 8871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_backward_grad_input, overload_name, "grad_input") |
| 8872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_backward_grad_input, schema_str, "avg_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 8873 | |
| 8874 | // aten::avg_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8875 | static C10_NOINLINE c10::TypedOperatorHandle<avg_pool3d_backward_grad_input::schema> create_avg_pool3d_backward_grad_input_typed_handle() { |
| 8876 | return c10::Dispatcher::singleton() |
| 8877 | .findSchemaOrThrow(avg_pool3d_backward_grad_input::name, avg_pool3d_backward_grad_input::overload_name) |
| 8878 | .typed<avg_pool3d_backward_grad_input::schema>(); |
| 8879 | } |
| 8880 | |
| 8881 | // aten::avg_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8882 | at::Tensor & avg_pool3d_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override, at::Tensor & grad_input) { |
| 8883 | |
| 8884 | static auto op = create_avg_pool3d_backward_grad_input_typed_handle(); |
| 8885 | return op.call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); |
| 8886 | } |
| 8887 | |
| 8888 | // aten::avg_pool3d_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8889 | at::Tensor & avg_pool3d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override, at::Tensor & grad_input) { |
| 8890 | |
| 8891 | static auto op = create_avg_pool3d_backward_grad_input_typed_handle(); |
| 8892 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, grad_input); |
| 8893 | } |
| 8894 | |
| 8895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_backward, name, "aten::avg_pool3d_backward") |
| 8896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_backward, overload_name, "") |
| 8897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool3d_backward, schema_str, "avg_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override) -> Tensor") |
| 8898 | |
| 8899 | // aten::avg_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override) -> Tensor |
| 8900 | static C10_NOINLINE c10::TypedOperatorHandle<avg_pool3d_backward::schema> create_avg_pool3d_backward_typed_handle() { |
| 8901 | return c10::Dispatcher::singleton() |
| 8902 | .findSchemaOrThrow(avg_pool3d_backward::name, avg_pool3d_backward::overload_name) |
| 8903 | .typed<avg_pool3d_backward::schema>(); |
| 8904 | } |
| 8905 | |
| 8906 | // aten::avg_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override) -> Tensor |
| 8907 | at::Tensor avg_pool3d_backward::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override) { |
| 8908 | |
| 8909 | static auto op = create_avg_pool3d_backward_typed_handle(); |
| 8910 | return op.call(grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); |
| 8911 | } |
| 8912 | |
| 8913 | // aten::avg_pool3d_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, bool ceil_mode, bool count_include_pad, int? divisor_override) -> Tensor |
| 8914 | at::Tensor avg_pool3d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override) { |
| 8915 | |
| 8916 | static auto op = create_avg_pool3d_backward_typed_handle(); |
| 8917 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); |
| 8918 | } |
| 8919 | |
| 8920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_backward_grad_input, name, "aten::max_pool2d_with_indices_backward") |
| 8921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_backward_grad_input, overload_name, "grad_input") |
| 8922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_backward_grad_input, schema_str, "max_pool2d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 8923 | |
| 8924 | // aten::max_pool2d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8925 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool2d_with_indices_backward_grad_input::schema> create_max_pool2d_with_indices_backward_grad_input_typed_handle() { |
| 8926 | return c10::Dispatcher::singleton() |
| 8927 | .findSchemaOrThrow(max_pool2d_with_indices_backward_grad_input::name, max_pool2d_with_indices_backward_grad_input::overload_name) |
| 8928 | .typed<max_pool2d_with_indices_backward_grad_input::schema>(); |
| 8929 | } |
| 8930 | |
| 8931 | // aten::max_pool2d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8932 | at::Tensor & max_pool2d_with_indices_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input) { |
| 8933 | |
| 8934 | static auto op = create_max_pool2d_with_indices_backward_grad_input_typed_handle(); |
| 8935 | return op.call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices, grad_input); |
| 8936 | } |
| 8937 | |
| 8938 | // aten::max_pool2d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 8939 | at::Tensor & max_pool2d_with_indices_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices, at::Tensor & grad_input) { |
| 8940 | |
| 8941 | static auto op = create_max_pool2d_with_indices_backward_grad_input_typed_handle(); |
| 8942 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices, grad_input); |
| 8943 | } |
| 8944 | |
| 8945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_backward, name, "aten::max_pool2d_with_indices_backward") |
| 8946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_backward, overload_name, "") |
| 8947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool2d_with_indices_backward, schema_str, "max_pool2d_with_indices_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices) -> Tensor") |
| 8948 | |
| 8949 | // aten::max_pool2d_with_indices_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices) -> Tensor |
| 8950 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool2d_with_indices_backward::schema> create_max_pool2d_with_indices_backward_typed_handle() { |
| 8951 | return c10::Dispatcher::singleton() |
| 8952 | .findSchemaOrThrow(max_pool2d_with_indices_backward::name, max_pool2d_with_indices_backward::overload_name) |
| 8953 | .typed<max_pool2d_with_indices_backward::schema>(); |
| 8954 | } |
| 8955 | |
| 8956 | // aten::max_pool2d_with_indices_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices) -> Tensor |
| 8957 | at::Tensor max_pool2d_with_indices_backward::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices) { |
| 8958 | |
| 8959 | static auto op = create_max_pool2d_with_indices_backward_typed_handle(); |
| 8960 | return op.call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices); |
| 8961 | } |
| 8962 | |
| 8963 | // aten::max_pool2d_with_indices_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride, int[2] padding, int[2] dilation, bool ceil_mode, Tensor indices) -> Tensor |
| 8964 | at::Tensor max_pool2d_with_indices_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode, const at::Tensor & indices) { |
| 8965 | |
| 8966 | static auto op = create_max_pool2d_with_indices_backward_typed_handle(); |
| 8967 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices); |
| 8968 | } |
| 8969 | |
| 8970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_out, name, "aten::max_pool3d_with_indices") |
| 8971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_out, overload_name, "out") |
| 8972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_out, schema_str, "max_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!))") |
| 8973 | |
| 8974 | // aten::max_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) |
| 8975 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool3d_with_indices_out::schema> create_max_pool3d_with_indices_out_typed_handle() { |
| 8976 | return c10::Dispatcher::singleton() |
| 8977 | .findSchemaOrThrow(max_pool3d_with_indices_out::name, max_pool3d_with_indices_out::overload_name) |
| 8978 | .typed<max_pool3d_with_indices_out::schema>(); |
| 8979 | } |
| 8980 | |
| 8981 | // aten::max_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) |
| 8982 | ::std::tuple<at::Tensor &,at::Tensor &> max_pool3d_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) { |
| 8983 | |
| 8984 | static auto op = create_max_pool3d_with_indices_out_typed_handle(); |
| 8985 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); |
| 8986 | } |
| 8987 | |
| 8988 | // aten::max_pool3d_with_indices.out(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False, *, Tensor(a!) out, Tensor(b!) indices) -> (Tensor(a!), Tensor(b!)) |
| 8989 | ::std::tuple<at::Tensor &,at::Tensor &> max_pool3d_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) { |
| 8990 | |
| 8991 | static auto op = create_max_pool3d_with_indices_out_typed_handle(); |
| 8992 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode, out, indices); |
| 8993 | } |
| 8994 | |
| 8995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices, name, "aten::max_pool3d_with_indices") |
| 8996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices, overload_name, "") |
| 8997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices, schema_str, "max_pool3d_with_indices(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor)") |
| 8998 | |
| 8999 | // aten::max_pool3d_with_indices(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 9000 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool3d_with_indices::schema> create_max_pool3d_with_indices_typed_handle() { |
| 9001 | return c10::Dispatcher::singleton() |
| 9002 | .findSchemaOrThrow(max_pool3d_with_indices::name, max_pool3d_with_indices::overload_name) |
| 9003 | .typed<max_pool3d_with_indices::schema>(); |
| 9004 | } |
| 9005 | |
| 9006 | // aten::max_pool3d_with_indices(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 9007 | ::std::tuple<at::Tensor,at::Tensor> max_pool3d_with_indices::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
| 9008 | |
| 9009 | static auto op = create_max_pool3d_with_indices_typed_handle(); |
| 9010 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode); |
| 9011 | } |
| 9012 | |
| 9013 | // aten::max_pool3d_with_indices(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> (Tensor, Tensor) |
| 9014 | ::std::tuple<at::Tensor,at::Tensor> max_pool3d_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) { |
| 9015 | |
| 9016 | static auto op = create_max_pool3d_with_indices_typed_handle(); |
| 9017 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode); |
| 9018 | } |
| 9019 | |
| 9020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_out, name, "aten::reflection_pad2d") |
| 9021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_out, overload_name, "out") |
| 9022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_out, schema_str, "reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!)") |
| 9023 | |
| 9024 | // aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) |
| 9025 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad2d_out::schema> create_reflection_pad2d_out_typed_handle() { |
| 9026 | return c10::Dispatcher::singleton() |
| 9027 | .findSchemaOrThrow(reflection_pad2d_out::name, reflection_pad2d_out::overload_name) |
| 9028 | .typed<reflection_pad2d_out::schema>(); |
| 9029 | } |
| 9030 | |
| 9031 | // aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) |
| 9032 | at::Tensor & reflection_pad2d_out::call(const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { |
| 9033 | |
| 9034 | static auto op = create_reflection_pad2d_out_typed_handle(); |
| 9035 | return op.call(self, padding, out); |
| 9036 | } |
| 9037 | |
| 9038 | // aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) |
| 9039 | at::Tensor & reflection_pad2d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & out) { |
| 9040 | |
| 9041 | static auto op = create_reflection_pad2d_out_typed_handle(); |
| 9042 | return op.redispatch(dispatchKeySet, self, padding, out); |
| 9043 | } |
| 9044 | |
| 9045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d, name, "aten::reflection_pad2d") |
| 9046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d, overload_name, "") |
| 9047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d, schema_str, "reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor") |
| 9048 | |
| 9049 | // aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor |
| 9050 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad2d::schema> create_reflection_pad2d_typed_handle() { |
| 9051 | return c10::Dispatcher::singleton() |
| 9052 | .findSchemaOrThrow(reflection_pad2d::name, reflection_pad2d::overload_name) |
| 9053 | .typed<reflection_pad2d::schema>(); |
| 9054 | } |
| 9055 | |
| 9056 | // aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor |
| 9057 | at::Tensor reflection_pad2d::call(const at::Tensor & self, c10::SymIntArrayRef padding) { |
| 9058 | |
| 9059 | static auto op = create_reflection_pad2d_typed_handle(); |
| 9060 | return op.call(self, padding); |
| 9061 | } |
| 9062 | |
| 9063 | // aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor |
| 9064 | at::Tensor reflection_pad2d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef padding) { |
| 9065 | |
| 9066 | static auto op = create_reflection_pad2d_typed_handle(); |
| 9067 | return op.redispatch(dispatchKeySet, self, padding); |
| 9068 | } |
| 9069 | |
| 9070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_vec, name, "aten::_upsample_bilinear2d_aa") |
| 9071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_vec, overload_name, "vec") |
| 9072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_vec, schema_str, "_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor") |
| 9073 | |
| 9074 | // aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 9075 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bilinear2d_aa_vec::schema> create__upsample_bilinear2d_aa_vec_typed_handle() { |
| 9076 | return c10::Dispatcher::singleton() |
| 9077 | .findSchemaOrThrow(_upsample_bilinear2d_aa_vec::name, _upsample_bilinear2d_aa_vec::overload_name) |
| 9078 | .typed<_upsample_bilinear2d_aa_vec::schema>(); |
| 9079 | } |
| 9080 | |
| 9081 | // aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 9082 | at::Tensor _upsample_bilinear2d_aa_vec::call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 9083 | |
| 9084 | static auto op = create__upsample_bilinear2d_aa_vec_typed_handle(); |
| 9085 | return op.call(input, output_size, align_corners, scale_factors); |
| 9086 | } |
| 9087 | |
| 9088 | // aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor |
| 9089 | at::Tensor _upsample_bilinear2d_aa_vec::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, bool align_corners, c10::optional<at::ArrayRef<double>> scale_factors) { |
| 9090 | |
| 9091 | static auto op = create__upsample_bilinear2d_aa_vec_typed_handle(); |
| 9092 | return op.redispatch(dispatchKeySet, input, output_size, align_corners, scale_factors); |
| 9093 | } |
| 9094 | |
| 9095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_linear1d_backward_grad_input, name, "aten::upsample_linear1d_backward") |
| 9096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_linear1d_backward_grad_input, overload_name, "grad_input") |
| 9097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_linear1d_backward_grad_input, schema_str, "upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 9098 | |
| 9099 | // aten::upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9100 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_linear1d_backward_grad_input::schema> create_upsample_linear1d_backward_grad_input_typed_handle() { |
| 9101 | return c10::Dispatcher::singleton() |
| 9102 | .findSchemaOrThrow(upsample_linear1d_backward_grad_input::name, upsample_linear1d_backward_grad_input::overload_name) |
| 9103 | .typed<upsample_linear1d_backward_grad_input::schema>(); |
| 9104 | } |
| 9105 | |
| 9106 | // aten::upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9107 | at::Tensor & upsample_linear1d_backward_grad_input::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales, at::Tensor & grad_input) { |
| 9108 | |
| 9109 | static auto op = create_upsample_linear1d_backward_grad_input_typed_handle(); |
| 9110 | return op.call(grad_output, output_size, input_size, align_corners, scales, grad_input); |
| 9111 | } |
| 9112 | |
| 9113 | // aten::upsample_linear1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9114 | at::Tensor & upsample_linear1d_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, at::Tensor & grad_input) { |
| 9115 | |
| 9116 | static auto op = create_upsample_linear1d_backward_grad_input_typed_handle(); |
| 9117 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales, grad_input); |
| 9118 | } |
| 9119 | |
| 9120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_linear1d_backward, name, "aten::upsample_linear1d_backward") |
| 9121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_linear1d_backward, overload_name, "") |
| 9122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_linear1d_backward, schema_str, "upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None) -> Tensor") |
| 9123 | |
| 9124 | // aten::upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None) -> Tensor |
| 9125 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_linear1d_backward::schema> create_upsample_linear1d_backward_typed_handle() { |
| 9126 | return c10::Dispatcher::singleton() |
| 9127 | .findSchemaOrThrow(upsample_linear1d_backward::name, upsample_linear1d_backward::overload_name) |
| 9128 | .typed<upsample_linear1d_backward::schema>(); |
| 9129 | } |
| 9130 | |
| 9131 | // aten::upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None) -> Tensor |
| 9132 | at::Tensor upsample_linear1d_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales) { |
| 9133 | |
| 9134 | static auto op = create_upsample_linear1d_backward_typed_handle(); |
| 9135 | return op.call(grad_output, output_size, input_size, align_corners, scales); |
| 9136 | } |
| 9137 | |
| 9138 | // aten::upsample_linear1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, bool align_corners, float? scales=None) -> Tensor |
| 9139 | at::Tensor upsample_linear1d_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) { |
| 9140 | |
| 9141 | static auto op = create_upsample_linear1d_backward_typed_handle(); |
| 9142 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales); |
| 9143 | } |
| 9144 | |
| 9145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_out, name, "aten::_upsample_bilinear2d_aa") |
| 9146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_out, overload_name, "out") |
| 9147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa_out, schema_str, "_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 9148 | |
| 9149 | // aten::_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9150 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bilinear2d_aa_out::schema> create__upsample_bilinear2d_aa_out_typed_handle() { |
| 9151 | return c10::Dispatcher::singleton() |
| 9152 | .findSchemaOrThrow(_upsample_bilinear2d_aa_out::name, _upsample_bilinear2d_aa_out::overload_name) |
| 9153 | .typed<_upsample_bilinear2d_aa_out::schema>(); |
| 9154 | } |
| 9155 | |
| 9156 | // aten::_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9157 | at::Tensor & _upsample_bilinear2d_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) { |
| 9158 | |
| 9159 | static auto op = create__upsample_bilinear2d_aa_out_typed_handle(); |
| 9160 | return op.call(self, output_size, align_corners, scales_h, scales_w, out); |
| 9161 | } |
| 9162 | |
| 9163 | // aten::_upsample_bilinear2d_aa.out(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9164 | at::Tensor & _upsample_bilinear2d_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) { |
| 9165 | |
| 9166 | static auto op = create__upsample_bilinear2d_aa_out_typed_handle(); |
| 9167 | return op.redispatch(dispatchKeySet, self, output_size, align_corners, scales_h, scales_w, out); |
| 9168 | } |
| 9169 | |
| 9170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa, name, "aten::_upsample_bilinear2d_aa") |
| 9171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa, overload_name, "") |
| 9172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bilinear2d_aa, schema_str, "_upsample_bilinear2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor") |
| 9173 | |
| 9174 | // aten::_upsample_bilinear2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 9175 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bilinear2d_aa::schema> create__upsample_bilinear2d_aa_typed_handle() { |
| 9176 | return c10::Dispatcher::singleton() |
| 9177 | .findSchemaOrThrow(_upsample_bilinear2d_aa::name, _upsample_bilinear2d_aa::overload_name) |
| 9178 | .typed<_upsample_bilinear2d_aa::schema>(); |
| 9179 | } |
| 9180 | |
| 9181 | // aten::_upsample_bilinear2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 9182 | at::Tensor _upsample_bilinear2d_aa::call(const at::Tensor & self, c10::SymIntArrayRef output_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 9183 | |
| 9184 | static auto op = create__upsample_bilinear2d_aa_typed_handle(); |
| 9185 | return op.call(self, output_size, align_corners, scales_h, scales_w); |
| 9186 | } |
| 9187 | |
| 9188 | // aten::_upsample_bilinear2d_aa(Tensor self, SymInt[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
| 9189 | at::Tensor _upsample_bilinear2d_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) { |
| 9190 | |
| 9191 | static auto op = create__upsample_bilinear2d_aa_typed_handle(); |
| 9192 | return op.redispatch(dispatchKeySet, self, output_size, align_corners, scales_h, scales_w); |
| 9193 | } |
| 9194 | |
| 9195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest1d_backward_grad_input, name, "aten::upsample_nearest1d_backward") |
| 9196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest1d_backward_grad_input, overload_name, "grad_input") |
| 9197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest1d_backward_grad_input, schema_str, "upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 9198 | |
| 9199 | // aten::upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9200 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_nearest1d_backward_grad_input::schema> create_upsample_nearest1d_backward_grad_input_typed_handle() { |
| 9201 | return c10::Dispatcher::singleton() |
| 9202 | .findSchemaOrThrow(upsample_nearest1d_backward_grad_input::name, upsample_nearest1d_backward_grad_input::overload_name) |
| 9203 | .typed<upsample_nearest1d_backward_grad_input::schema>(); |
| 9204 | } |
| 9205 | |
| 9206 | // aten::upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9207 | at::Tensor & upsample_nearest1d_backward_grad_input::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales, at::Tensor & grad_input) { |
| 9208 | |
| 9209 | static auto op = create_upsample_nearest1d_backward_grad_input_typed_handle(); |
| 9210 | return op.call(grad_output, output_size, input_size, scales, grad_input); |
| 9211 | } |
| 9212 | |
| 9213 | // aten::upsample_nearest1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9214 | at::Tensor & upsample_nearest1d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales, at::Tensor & grad_input) { |
| 9215 | |
| 9216 | static auto op = create_upsample_nearest1d_backward_grad_input_typed_handle(); |
| 9217 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales, grad_input); |
| 9218 | } |
| 9219 | |
| 9220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest1d_backward, name, "aten::upsample_nearest1d_backward") |
| 9221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest1d_backward, overload_name, "") |
| 9222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest1d_backward, schema_str, "upsample_nearest1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor") |
| 9223 | |
| 9224 | // aten::upsample_nearest1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor |
| 9225 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_nearest1d_backward::schema> create_upsample_nearest1d_backward_typed_handle() { |
| 9226 | return c10::Dispatcher::singleton() |
| 9227 | .findSchemaOrThrow(upsample_nearest1d_backward::name, upsample_nearest1d_backward::overload_name) |
| 9228 | .typed<upsample_nearest1d_backward::schema>(); |
| 9229 | } |
| 9230 | |
| 9231 | // aten::upsample_nearest1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor |
| 9232 | at::Tensor upsample_nearest1d_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales) { |
| 9233 | |
| 9234 | static auto op = create_upsample_nearest1d_backward_typed_handle(); |
| 9235 | return op.call(grad_output, output_size, input_size, scales); |
| 9236 | } |
| 9237 | |
| 9238 | // aten::upsample_nearest1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor |
| 9239 | at::Tensor upsample_nearest1d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales) { |
| 9240 | |
| 9241 | static auto op = create_upsample_nearest1d_backward_typed_handle(); |
| 9242 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales); |
| 9243 | } |
| 9244 | |
| 9245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest2d_backward_grad_input, name, "aten::upsample_nearest2d_backward") |
| 9246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest2d_backward_grad_input, overload_name, "grad_input") |
| 9247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest2d_backward_grad_input, schema_str, "upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)") |
| 9248 | |
| 9249 | // aten::upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9250 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_nearest2d_backward_grad_input::schema> create_upsample_nearest2d_backward_grad_input_typed_handle() { |
| 9251 | return c10::Dispatcher::singleton() |
| 9252 | .findSchemaOrThrow(upsample_nearest2d_backward_grad_input::name, upsample_nearest2d_backward_grad_input::overload_name) |
| 9253 | .typed<upsample_nearest2d_backward_grad_input::schema>(); |
| 9254 | } |
| 9255 | |
| 9256 | // aten::upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9257 | at::Tensor & upsample_nearest2d_backward_grad_input::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
| 9258 | |
| 9259 | static auto op = create_upsample_nearest2d_backward_grad_input_typed_handle(); |
| 9260 | return op.call(grad_output, output_size, input_size, scales_h, scales_w, grad_input); |
| 9261 | } |
| 9262 | |
| 9263 | // aten::upsample_nearest2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
| 9264 | at::Tensor & upsample_nearest2d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
| 9265 | |
| 9266 | static auto op = create_upsample_nearest2d_backward_grad_input_typed_handle(); |
| 9267 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales_h, scales_w, grad_input); |
| 9268 | } |
| 9269 | |
| 9270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest2d_backward, name, "aten::upsample_nearest2d_backward") |
| 9271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest2d_backward, overload_name, "") |
| 9272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_nearest2d_backward, schema_str, "upsample_nearest2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor") |
| 9273 | |
| 9274 | // aten::upsample_nearest2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor |
| 9275 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_nearest2d_backward::schema> create_upsample_nearest2d_backward_typed_handle() { |
| 9276 | return c10::Dispatcher::singleton() |
| 9277 | .findSchemaOrThrow(upsample_nearest2d_backward::name, upsample_nearest2d_backward::overload_name) |
| 9278 | .typed<upsample_nearest2d_backward::schema>(); |
| 9279 | } |
| 9280 | |
| 9281 | // aten::upsample_nearest2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor |
| 9282 | at::Tensor upsample_nearest2d_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 9283 | |
| 9284 | static auto op = create_upsample_nearest2d_backward_typed_handle(); |
| 9285 | return op.call(grad_output, output_size, input_size, scales_h, scales_w); |
| 9286 | } |
| 9287 | |
| 9288 | // aten::upsample_nearest2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor |
| 9289 | at::Tensor upsample_nearest2d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
| 9290 | |
| 9291 | static auto op = create_upsample_nearest2d_backward_typed_handle(); |
| 9292 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales_h, scales_w); |
| 9293 | } |
| 9294 | |
| 9295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_transpose3d_out, name, "aten::slow_conv_transpose3d") |
| 9296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_transpose3d_out, overload_name, "out") |
| 9297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_transpose3d_out, schema_str, "slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 9298 | |
| 9299 | // aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) |
| 9300 | static C10_NOINLINE c10::TypedOperatorHandle<slow_conv_transpose3d_out::schema> create_slow_conv_transpose3d_out_typed_handle() { |
| 9301 | return c10::Dispatcher::singleton() |
| 9302 | .findSchemaOrThrow(slow_conv_transpose3d_out::name, slow_conv_transpose3d_out::overload_name) |
| 9303 | .typed<slow_conv_transpose3d_out::schema>(); |
| 9304 | } |
| 9305 | |
| 9306 | // aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) |
| 9307 | at::Tensor & slow_conv_transpose3d_out::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out) { |
| 9308 | |
| 9309 | static auto op = create_slow_conv_transpose3d_out_typed_handle(); |
| 9310 | return op.call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation, out); |
| 9311 | } |
| 9312 | |
| 9313 | // aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) |
| 9314 | at::Tensor & slow_conv_transpose3d_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, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef dilation, at::Tensor & out) { |
| 9315 | |
| 9316 | static auto op = create_slow_conv_transpose3d_out_typed_handle(); |
| 9317 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding, output_padding, dilation, out); |
| 9318 | } |
| 9319 | |
| 9320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_transpose3d, name, "aten::slow_conv_transpose3d") |
| 9321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_transpose3d, overload_name, "") |
| 9322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_transpose3d, schema_str, "slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor") |
| 9323 | |
| 9324 | // aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor |
| 9325 | static C10_NOINLINE c10::TypedOperatorHandle<slow_conv_transpose3d::schema> create_slow_conv_transpose3d_typed_handle() { |
| 9326 | return c10::Dispatcher::singleton() |
| 9327 | .findSchemaOrThrow(slow_conv_transpose3d::name, slow_conv_transpose3d::overload_name) |
| 9328 | .typed<slow_conv_transpose3d::schema>(); |
| 9329 | } |
| 9330 | |
| 9331 | // aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor |
| 9332 | at::Tensor slow_conv_transpose3d::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef dilation) { |
| 9333 | |
| 9334 | static auto op = create_slow_conv_transpose3d_typed_handle(); |
| 9335 | return op.call(self, weight, kernel_size, bias, stride, padding, output_padding, dilation); |
| 9336 | } |
| 9337 | |
| 9338 | // aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor |
| 9339 | at::Tensor slow_conv_transpose3d::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, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef dilation) { |
| 9340 | |
| 9341 | static auto op = create_slow_conv_transpose3d_typed_handle(); |
| 9342 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding, output_padding, dilation); |
| 9343 | } |
| 9344 | |
| 9345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv3d_forward_output, name, "aten::slow_conv3d_forward") |
| 9346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv3d_forward_output, overload_name, "output") |
| 9347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv3d_forward_output, schema_str, "slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!)") |
| 9348 | |
| 9349 | // aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!) |
| 9350 | static C10_NOINLINE c10::TypedOperatorHandle<slow_conv3d_forward_output::schema> create_slow_conv3d_forward_output_typed_handle() { |
| 9351 | return c10::Dispatcher::singleton() |
| 9352 | .findSchemaOrThrow(slow_conv3d_forward_output::name, slow_conv3d_forward_output::overload_name) |
| 9353 | .typed<slow_conv3d_forward_output::schema>(); |
| 9354 | } |
| 9355 | |
| 9356 | // aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!) |
| 9357 | at::Tensor & slow_conv3d_forward_output::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::Tensor & output) { |
| 9358 | |
| 9359 | static auto op = create_slow_conv3d_forward_output_typed_handle(); |
| 9360 | return op.call(self, weight, kernel_size, bias, stride, padding, output); |
| 9361 | } |
| 9362 | |
| 9363 | // aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!) |
| 9364 | at::Tensor & slow_conv3d_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, c10::SymIntArrayRef padding, at::Tensor & output) { |
| 9365 | |
| 9366 | static auto op = create_slow_conv3d_forward_output_typed_handle(); |
| 9367 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding, output); |
| 9368 | } |
| 9369 | |
| 9370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv3d_forward, name, "aten::slow_conv3d_forward") |
| 9371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv3d_forward, overload_name, "") |
| 9372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv3d_forward, schema_str, "slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor") |
| 9373 | |
| 9374 | // aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor |
| 9375 | static C10_NOINLINE c10::TypedOperatorHandle<slow_conv3d_forward::schema> create_slow_conv3d_forward_typed_handle() { |
| 9376 | return c10::Dispatcher::singleton() |
| 9377 | .findSchemaOrThrow(slow_conv3d_forward::name, slow_conv3d_forward::overload_name) |
| 9378 | .typed<slow_conv3d_forward::schema>(); |
| 9379 | } |
| 9380 | |
| 9381 | // aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor |
| 9382 | at::Tensor slow_conv3d_forward::call(const at::Tensor & self, const at::Tensor & weight, at::IntArrayRef kernel_size, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, c10::SymIntArrayRef padding) { |
| 9383 | |
| 9384 | static auto op = create_slow_conv3d_forward_typed_handle(); |
| 9385 | return op.call(self, weight, kernel_size, bias, stride, padding); |
| 9386 | } |
| 9387 | |
| 9388 | // aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor |
| 9389 | at::Tensor slow_conv3d_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, c10::SymIntArrayRef padding) { |
| 9390 | |
| 9391 | static auto op = create_slow_conv3d_forward_typed_handle(); |
| 9392 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding); |
| 9393 | } |
| 9394 | |
| 9395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(im2col_out, name, "aten::im2col") |
| 9396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(im2col_out, overload_name, "out") |
| 9397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(im2col_out, schema_str, "im2col.out(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, *, Tensor(a!) out) -> Tensor(a!)") |
| 9398 | |
| 9399 | // aten::im2col.out(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, *, Tensor(a!) out) -> Tensor(a!) |
| 9400 | static C10_NOINLINE c10::TypedOperatorHandle<im2col_out::schema> create_im2col_out_typed_handle() { |
| 9401 | return c10::Dispatcher::singleton() |
| 9402 | .findSchemaOrThrow(im2col_out::name, im2col_out::overload_name) |
| 9403 | .typed<im2col_out::schema>(); |
| 9404 | } |
| 9405 | |
| 9406 | // aten::im2col.out(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, *, Tensor(a!) out) -> Tensor(a!) |
| 9407 | at::Tensor & im2col_out::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out) { |
| 9408 | |
| 9409 | static auto op = create_im2col_out_typed_handle(); |
| 9410 | return op.call(self, kernel_size, dilation, padding, stride, out); |
| 9411 | } |
| 9412 | |
| 9413 | // aten::im2col.out(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride, *, Tensor(a!) out) -> Tensor(a!) |
| 9414 | at::Tensor & im2col_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride, at::Tensor & out) { |
| 9415 | |
| 9416 | static auto op = create_im2col_out_typed_handle(); |
| 9417 | return op.redispatch(dispatchKeySet, self, kernel_size, dilation, padding, stride, out); |
| 9418 | } |
| 9419 | |
| 9420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(im2col, name, "aten::im2col") |
| 9421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(im2col, overload_name, "") |
| 9422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(im2col, schema_str, "im2col(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride) -> Tensor") |
| 9423 | |
| 9424 | // aten::im2col(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride) -> Tensor |
| 9425 | static C10_NOINLINE c10::TypedOperatorHandle<im2col::schema> create_im2col_typed_handle() { |
| 9426 | return c10::Dispatcher::singleton() |
| 9427 | .findSchemaOrThrow(im2col::name, im2col::overload_name) |
| 9428 | .typed<im2col::schema>(); |
| 9429 | } |
| 9430 | |
| 9431 | // aten::im2col(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride) -> Tensor |
| 9432 | at::Tensor im2col::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride) { |
| 9433 | |
| 9434 | static auto op = create_im2col_typed_handle(); |
| 9435 | return op.call(self, kernel_size, dilation, padding, stride); |
| 9436 | } |
| 9437 | |
| 9438 | // aten::im2col(Tensor self, int[2] kernel_size, int[2] dilation, int[2] padding, int[2] stride) -> Tensor |
| 9439 | at::Tensor im2col::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef dilation, at::IntArrayRef padding, at::IntArrayRef stride) { |
| 9440 | |
| 9441 | static auto op = create_im2col_typed_handle(); |
| 9442 | return op.redispatch(dispatchKeySet, self, kernel_size, dilation, padding, stride); |
| 9443 | } |
| 9444 | |
| 9445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isneginf, name, "aten::isneginf") |
| 9446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isneginf, overload_name, "") |
| 9447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isneginf, schema_str, "isneginf(Tensor self) -> Tensor") |
| 9448 | |
| 9449 | // aten::isneginf(Tensor self) -> Tensor |
| 9450 | static C10_NOINLINE c10::TypedOperatorHandle<isneginf::schema> create_isneginf_typed_handle() { |
| 9451 | return c10::Dispatcher::singleton() |
| 9452 | .findSchemaOrThrow(isneginf::name, isneginf::overload_name) |
| 9453 | .typed<isneginf::schema>(); |
| 9454 | } |
| 9455 | |
| 9456 | // aten::isneginf(Tensor self) -> Tensor |
| 9457 | at::Tensor isneginf::call(const at::Tensor & self) { |
| 9458 | |
| 9459 | static auto op = create_isneginf_typed_handle(); |
| 9460 | return op.call(self); |
| 9461 | } |
| 9462 | |
| 9463 | // aten::isneginf(Tensor self) -> Tensor |
| 9464 | at::Tensor isneginf::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9465 | |
| 9466 | static auto op = create_isneginf_typed_handle(); |
| 9467 | return op.redispatch(dispatchKeySet, self); |
| 9468 | } |
| 9469 | |
| 9470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isneginf_out, name, "aten::isneginf") |
| 9471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isneginf_out, overload_name, "out") |
| 9472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isneginf_out, schema_str, "isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 9473 | |
| 9474 | // aten::isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9475 | static C10_NOINLINE c10::TypedOperatorHandle<isneginf_out::schema> create_isneginf_out_typed_handle() { |
| 9476 | return c10::Dispatcher::singleton() |
| 9477 | .findSchemaOrThrow(isneginf_out::name, isneginf_out::overload_name) |
| 9478 | .typed<isneginf_out::schema>(); |
| 9479 | } |
| 9480 | |
| 9481 | // aten::isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9482 | at::Tensor & isneginf_out::call(const at::Tensor & self, at::Tensor & out) { |
| 9483 | |
| 9484 | static auto op = create_isneginf_out_typed_handle(); |
| 9485 | return op.call(self, out); |
| 9486 | } |
| 9487 | |
| 9488 | // aten::isneginf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9489 | at::Tensor & isneginf_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 9490 | |
| 9491 | static auto op = create_isneginf_out_typed_handle(); |
| 9492 | return op.redispatch(dispatchKeySet, self, out); |
| 9493 | } |
| 9494 | |
| 9495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_add_batch_dim, name, "aten::_add_batch_dim") |
| 9496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_add_batch_dim, overload_name, "") |
| 9497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_add_batch_dim, schema_str, "_add_batch_dim(Tensor self, int batch_dim, int level) -> Tensor") |
| 9498 | |
| 9499 | // aten::_add_batch_dim(Tensor self, int batch_dim, int level) -> Tensor |
| 9500 | static C10_NOINLINE c10::TypedOperatorHandle<_add_batch_dim::schema> create__add_batch_dim_typed_handle() { |
| 9501 | return c10::Dispatcher::singleton() |
| 9502 | .findSchemaOrThrow(_add_batch_dim::name, _add_batch_dim::overload_name) |
| 9503 | .typed<_add_batch_dim::schema>(); |
| 9504 | } |
| 9505 | |
| 9506 | // aten::_add_batch_dim(Tensor self, int batch_dim, int level) -> Tensor |
| 9507 | at::Tensor _add_batch_dim::call(const at::Tensor & self, int64_t batch_dim, int64_t level) { |
| 9508 | |
| 9509 | static auto op = create__add_batch_dim_typed_handle(); |
| 9510 | return op.call(self, batch_dim, level); |
| 9511 | } |
| 9512 | |
| 9513 | // aten::_add_batch_dim(Tensor self, int batch_dim, int level) -> Tensor |
| 9514 | at::Tensor _add_batch_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t batch_dim, int64_t level) { |
| 9515 | |
| 9516 | static auto op = create__add_batch_dim_typed_handle(); |
| 9517 | return op.redispatch(dispatchKeySet, self, batch_dim, level); |
| 9518 | } |
| 9519 | |
| 9520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_psi, name, "aten::special_psi") |
| 9521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_psi, overload_name, "") |
| 9522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_psi, schema_str, "special_psi(Tensor self) -> Tensor") |
| 9523 | |
| 9524 | // aten::special_psi(Tensor self) -> Tensor |
| 9525 | static C10_NOINLINE c10::TypedOperatorHandle<special_psi::schema> create_special_psi_typed_handle() { |
| 9526 | return c10::Dispatcher::singleton() |
| 9527 | .findSchemaOrThrow(special_psi::name, special_psi::overload_name) |
| 9528 | .typed<special_psi::schema>(); |
| 9529 | } |
| 9530 | |
| 9531 | // aten::special_psi(Tensor self) -> Tensor |
| 9532 | at::Tensor special_psi::call(const at::Tensor & self) { |
| 9533 | |
| 9534 | static auto op = create_special_psi_typed_handle(); |
| 9535 | return op.call(self); |
| 9536 | } |
| 9537 | |
| 9538 | // aten::special_psi(Tensor self) -> Tensor |
| 9539 | at::Tensor special_psi::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9540 | |
| 9541 | static auto op = create_special_psi_typed_handle(); |
| 9542 | return op.redispatch(dispatchKeySet, self); |
| 9543 | } |
| 9544 | |
| 9545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_psi_out, name, "aten::special_psi") |
| 9546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_psi_out, overload_name, "out") |
| 9547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_psi_out, schema_str, "special_psi.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 9548 | |
| 9549 | // aten::special_psi.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9550 | static C10_NOINLINE c10::TypedOperatorHandle<special_psi_out::schema> create_special_psi_out_typed_handle() { |
| 9551 | return c10::Dispatcher::singleton() |
| 9552 | .findSchemaOrThrow(special_psi_out::name, special_psi_out::overload_name) |
| 9553 | .typed<special_psi_out::schema>(); |
| 9554 | } |
| 9555 | |
| 9556 | // aten::special_psi.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9557 | at::Tensor & special_psi_out::call(const at::Tensor & self, at::Tensor & out) { |
| 9558 | |
| 9559 | static auto op = create_special_psi_out_typed_handle(); |
| 9560 | return op.call(self, out); |
| 9561 | } |
| 9562 | |
| 9563 | // aten::special_psi.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9564 | at::Tensor & special_psi_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 9565 | |
| 9566 | static auto op = create_special_psi_out_typed_handle(); |
| 9567 | return op.redispatch(dispatchKeySet, self, out); |
| 9568 | } |
| 9569 | |
| 9570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfcx, name, "aten::special_erfcx") |
| 9571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfcx, overload_name, "") |
| 9572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfcx, schema_str, "special_erfcx(Tensor self) -> Tensor") |
| 9573 | |
| 9574 | // aten::special_erfcx(Tensor self) -> Tensor |
| 9575 | static C10_NOINLINE c10::TypedOperatorHandle<special_erfcx::schema> create_special_erfcx_typed_handle() { |
| 9576 | return c10::Dispatcher::singleton() |
| 9577 | .findSchemaOrThrow(special_erfcx::name, special_erfcx::overload_name) |
| 9578 | .typed<special_erfcx::schema>(); |
| 9579 | } |
| 9580 | |
| 9581 | // aten::special_erfcx(Tensor self) -> Tensor |
| 9582 | at::Tensor special_erfcx::call(const at::Tensor & self) { |
| 9583 | |
| 9584 | static auto op = create_special_erfcx_typed_handle(); |
| 9585 | return op.call(self); |
| 9586 | } |
| 9587 | |
| 9588 | // aten::special_erfcx(Tensor self) -> Tensor |
| 9589 | at::Tensor special_erfcx::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9590 | |
| 9591 | static auto op = create_special_erfcx_typed_handle(); |
| 9592 | return op.redispatch(dispatchKeySet, self); |
| 9593 | } |
| 9594 | |
| 9595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfcx_out, name, "aten::special_erfcx") |
| 9596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfcx_out, overload_name, "out") |
| 9597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_erfcx_out, schema_str, "special_erfcx.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 9598 | |
| 9599 | // aten::special_erfcx.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9600 | static C10_NOINLINE c10::TypedOperatorHandle<special_erfcx_out::schema> create_special_erfcx_out_typed_handle() { |
| 9601 | return c10::Dispatcher::singleton() |
| 9602 | .findSchemaOrThrow(special_erfcx_out::name, special_erfcx_out::overload_name) |
| 9603 | .typed<special_erfcx_out::schema>(); |
| 9604 | } |
| 9605 | |
| 9606 | // aten::special_erfcx.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9607 | at::Tensor & special_erfcx_out::call(const at::Tensor & self, at::Tensor & out) { |
| 9608 | |
| 9609 | static auto op = create_special_erfcx_out_typed_handle(); |
| 9610 | return op.call(self, out); |
| 9611 | } |
| 9612 | |
| 9613 | // aten::special_erfcx.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9614 | at::Tensor & special_erfcx_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 9615 | |
| 9616 | static auto op = create_special_erfcx_out_typed_handle(); |
| 9617 | return op.redispatch(dispatchKeySet, self, out); |
| 9618 | } |
| 9619 | |
| 9620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i0e, name, "aten::special_i0e") |
| 9621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i0e, overload_name, "") |
| 9622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i0e, schema_str, "special_i0e(Tensor self) -> Tensor") |
| 9623 | |
| 9624 | // aten::special_i0e(Tensor self) -> Tensor |
| 9625 | static C10_NOINLINE c10::TypedOperatorHandle<special_i0e::schema> create_special_i0e_typed_handle() { |
| 9626 | return c10::Dispatcher::singleton() |
| 9627 | .findSchemaOrThrow(special_i0e::name, special_i0e::overload_name) |
| 9628 | .typed<special_i0e::schema>(); |
| 9629 | } |
| 9630 | |
| 9631 | // aten::special_i0e(Tensor self) -> Tensor |
| 9632 | at::Tensor special_i0e::call(const at::Tensor & self) { |
| 9633 | |
| 9634 | static auto op = create_special_i0e_typed_handle(); |
| 9635 | return op.call(self); |
| 9636 | } |
| 9637 | |
| 9638 | // aten::special_i0e(Tensor self) -> Tensor |
| 9639 | at::Tensor special_i0e::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9640 | |
| 9641 | static auto op = create_special_i0e_typed_handle(); |
| 9642 | return op.redispatch(dispatchKeySet, self); |
| 9643 | } |
| 9644 | |
| 9645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i0e_out, name, "aten::special_i0e") |
| 9646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i0e_out, overload_name, "out") |
| 9647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i0e_out, schema_str, "special_i0e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 9648 | |
| 9649 | // aten::special_i0e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9650 | static C10_NOINLINE c10::TypedOperatorHandle<special_i0e_out::schema> create_special_i0e_out_typed_handle() { |
| 9651 | return c10::Dispatcher::singleton() |
| 9652 | .findSchemaOrThrow(special_i0e_out::name, special_i0e_out::overload_name) |
| 9653 | .typed<special_i0e_out::schema>(); |
| 9654 | } |
| 9655 | |
| 9656 | // aten::special_i0e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9657 | at::Tensor & special_i0e_out::call(const at::Tensor & self, at::Tensor & out) { |
| 9658 | |
| 9659 | static auto op = create_special_i0e_out_typed_handle(); |
| 9660 | return op.call(self, out); |
| 9661 | } |
| 9662 | |
| 9663 | // aten::special_i0e.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9664 | at::Tensor & special_i0e_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 9665 | |
| 9666 | static auto op = create_special_i0e_out_typed_handle(); |
| 9667 | return op.redispatch(dispatchKeySet, self, out); |
| 9668 | } |
| 9669 | |
| 9670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1, name, "aten::special_i1") |
| 9671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1, overload_name, "") |
| 9672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1, schema_str, "special_i1(Tensor self) -> Tensor") |
| 9673 | |
| 9674 | // aten::special_i1(Tensor self) -> Tensor |
| 9675 | static C10_NOINLINE c10::TypedOperatorHandle<special_i1::schema> create_special_i1_typed_handle() { |
| 9676 | return c10::Dispatcher::singleton() |
| 9677 | .findSchemaOrThrow(special_i1::name, special_i1::overload_name) |
| 9678 | .typed<special_i1::schema>(); |
| 9679 | } |
| 9680 | |
| 9681 | // aten::special_i1(Tensor self) -> Tensor |
| 9682 | at::Tensor special_i1::call(const at::Tensor & self) { |
| 9683 | |
| 9684 | static auto op = create_special_i1_typed_handle(); |
| 9685 | return op.call(self); |
| 9686 | } |
| 9687 | |
| 9688 | // aten::special_i1(Tensor self) -> Tensor |
| 9689 | at::Tensor special_i1::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 9690 | |
| 9691 | static auto op = create_special_i1_typed_handle(); |
| 9692 | return op.redispatch(dispatchKeySet, self); |
| 9693 | } |
| 9694 | |
| 9695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1_out, name, "aten::special_i1") |
| 9696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1_out, overload_name, "out") |
| 9697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_i1_out, schema_str, "special_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 9698 | |
| 9699 | // aten::special_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9700 | static C10_NOINLINE c10::TypedOperatorHandle<special_i1_out::schema> create_special_i1_out_typed_handle() { |
| 9701 | return c10::Dispatcher::singleton() |
| 9702 | .findSchemaOrThrow(special_i1_out::name, special_i1_out::overload_name) |
| 9703 | .typed<special_i1_out::schema>(); |
| 9704 | } |
| 9705 | |
| 9706 | // aten::special_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9707 | at::Tensor & special_i1_out::call(const at::Tensor & self, at::Tensor & out) { |
| 9708 | |
| 9709 | static auto op = create_special_i1_out_typed_handle(); |
| 9710 | return op.call(self, out); |
| 9711 | } |
| 9712 | |
| 9713 | // aten::special_i1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 9714 | at::Tensor & special_i1_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 9715 | |
| 9716 | static auto op = create_special_i1_out_typed_handle(); |
| 9717 | return op.redispatch(dispatchKeySet, self, out); |
| 9718 | } |
| 9719 | |
| 9720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logit, name, "aten::special_logit") |
| 9721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logit, overload_name, "") |
| 9722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logit, schema_str, "special_logit(Tensor self, float? eps=None) -> Tensor") |
| 9723 | |
| 9724 | // aten::special_logit(Tensor self, float? eps=None) -> Tensor |
| 9725 | static C10_NOINLINE c10::TypedOperatorHandle<special_logit::schema> create_special_logit_typed_handle() { |
| 9726 | return c10::Dispatcher::singleton() |
| 9727 | .findSchemaOrThrow(special_logit::name, special_logit::overload_name) |
| 9728 | .typed<special_logit::schema>(); |
| 9729 | } |
| 9730 | |
| 9731 | // aten::special_logit(Tensor self, float? eps=None) -> Tensor |
| 9732 | at::Tensor special_logit::call(const at::Tensor & self, c10::optional<double> eps) { |
| 9733 | |
| 9734 | static auto op = create_special_logit_typed_handle(); |
| 9735 | return op.call(self, eps); |
| 9736 | } |
| 9737 | |
| 9738 | // aten::special_logit(Tensor self, float? eps=None) -> Tensor |
| 9739 | at::Tensor special_logit::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<double> eps) { |
| 9740 | |
| 9741 | static auto op = create_special_logit_typed_handle(); |
| 9742 | return op.redispatch(dispatchKeySet, self, eps); |
| 9743 | } |
| 9744 | |
| 9745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logit_out, name, "aten::special_logit") |
| 9746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logit_out, overload_name, "out") |
| 9747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_logit_out, schema_str, "special_logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 9748 | |
| 9749 | // aten::special_logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9750 | static C10_NOINLINE c10::TypedOperatorHandle<special_logit_out::schema> create_special_logit_out_typed_handle() { |
| 9751 | return c10::Dispatcher::singleton() |
| 9752 | .findSchemaOrThrow(special_logit_out::name, special_logit_out::overload_name) |
| 9753 | .typed<special_logit_out::schema>(); |
| 9754 | } |
| 9755 | |
| 9756 | // aten::special_logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9757 | at::Tensor & special_logit_out::call(const at::Tensor & self, c10::optional<double> eps, at::Tensor & out) { |
| 9758 | |
| 9759 | static auto op = create_special_logit_out_typed_handle(); |
| 9760 | return op.call(self, eps, out); |
| 9761 | } |
| 9762 | |
| 9763 | // aten::special_logit.out(Tensor self, float? eps=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9764 | at::Tensor & special_logit_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<double> eps, at::Tensor & out) { |
| 9765 | |
| 9766 | static auto op = create_special_logit_out_typed_handle(); |
| 9767 | return op.redispatch(dispatchKeySet, self, eps, out); |
| 9768 | } |
| 9769 | |
| 9770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_log_softmax, name, "aten::special_log_softmax") |
| 9771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_log_softmax, overload_name, "") |
| 9772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_log_softmax, schema_str, "special_log_softmax(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor") |
| 9773 | |
| 9774 | // aten::special_log_softmax(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor |
| 9775 | static C10_NOINLINE c10::TypedOperatorHandle<special_log_softmax::schema> create_special_log_softmax_typed_handle() { |
| 9776 | return c10::Dispatcher::singleton() |
| 9777 | .findSchemaOrThrow(special_log_softmax::name, special_log_softmax::overload_name) |
| 9778 | .typed<special_log_softmax::schema>(); |
| 9779 | } |
| 9780 | |
| 9781 | // aten::special_log_softmax(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor |
| 9782 | at::Tensor special_log_softmax::call(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
| 9783 | |
| 9784 | static auto op = create_special_log_softmax_typed_handle(); |
| 9785 | return op.call(self, dim, dtype); |
| 9786 | } |
| 9787 | |
| 9788 | // aten::special_log_softmax(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor |
| 9789 | at::Tensor special_log_softmax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
| 9790 | |
| 9791 | static auto op = create_special_log_softmax_typed_handle(); |
| 9792 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
| 9793 | } |
| 9794 | |
| 9795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammaincc_out, name, "aten::special_gammaincc") |
| 9796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammaincc_out, overload_name, "out") |
| 9797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammaincc_out, schema_str, "special_gammaincc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 9798 | |
| 9799 | // aten::special_gammaincc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9800 | static C10_NOINLINE c10::TypedOperatorHandle<special_gammaincc_out::schema> create_special_gammaincc_out_typed_handle() { |
| 9801 | return c10::Dispatcher::singleton() |
| 9802 | .findSchemaOrThrow(special_gammaincc_out::name, special_gammaincc_out::overload_name) |
| 9803 | .typed<special_gammaincc_out::schema>(); |
| 9804 | } |
| 9805 | |
| 9806 | // aten::special_gammaincc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9807 | at::Tensor & special_gammaincc_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 9808 | |
| 9809 | static auto op = create_special_gammaincc_out_typed_handle(); |
| 9810 | return op.call(self, other, out); |
| 9811 | } |
| 9812 | |
| 9813 | // aten::special_gammaincc.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 9814 | at::Tensor & special_gammaincc_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
| 9815 | |
| 9816 | static auto op = create_special_gammaincc_out_typed_handle(); |
| 9817 | return op.redispatch(dispatchKeySet, self, other, out); |
| 9818 | } |
| 9819 | |
| 9820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammaincc, name, "aten::special_gammaincc") |
| 9821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammaincc, overload_name, "") |
| 9822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_gammaincc, schema_str, "special_gammaincc(Tensor self, Tensor other) -> Tensor") |
| 9823 | |
| 9824 | // aten::special_gammaincc(Tensor self, Tensor other) -> Tensor |
| 9825 | static C10_NOINLINE c10::TypedOperatorHandle<special_gammaincc::schema> create_special_gammaincc_typed_handle() { |
| 9826 | return c10::Dispatcher::singleton() |
| 9827 | .findSchemaOrThrow(special_gammaincc::name, special_gammaincc::overload_name) |
| 9828 | .typed<special_gammaincc::schema>(); |
| 9829 | } |
| 9830 | |
| 9831 | // aten::special_gammaincc(Tensor self, Tensor other) -> Tensor |
| 9832 | at::Tensor special_gammaincc::call(const at::Tensor & self, const at::Tensor & other) { |
| 9833 | |
| 9834 | static auto op = create_special_gammaincc_typed_handle(); |
| 9835 | return op.call(self, other); |
| 9836 | } |
| 9837 | |
| 9838 | // aten::special_gammaincc(Tensor self, Tensor other) -> Tensor |
| 9839 | at::Tensor special_gammaincc::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
| 9840 | |
| 9841 | static auto op = create_special_gammaincc_typed_handle(); |
| 9842 | return op.redispatch(dispatchKeySet, self, other); |
| 9843 | } |
| 9844 | |
| 9845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_multigammaln, name, "aten::special_multigammaln") |
| 9846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_multigammaln, overload_name, "") |
| 9847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_multigammaln, schema_str, "special_multigammaln(Tensor self, int p) -> Tensor") |
| 9848 | |
| 9849 | // aten::special_multigammaln(Tensor self, int p) -> Tensor |
| 9850 | static C10_NOINLINE c10::TypedOperatorHandle<special_multigammaln::schema> create_special_multigammaln_typed_handle() { |
| 9851 | return c10::Dispatcher::singleton() |
| 9852 | .findSchemaOrThrow(special_multigammaln::name, special_multigammaln::overload_name) |
| 9853 | .typed<special_multigammaln::schema>(); |
| 9854 | } |
| 9855 | |
| 9856 | // aten::special_multigammaln(Tensor self, int p) -> Tensor |
| 9857 | at::Tensor special_multigammaln::call(const at::Tensor & self, int64_t p) { |
| 9858 | |
| 9859 | static auto op = create_special_multigammaln_typed_handle(); |
| 9860 | return op.call(self, p); |
| 9861 | } |
| 9862 | |
| 9863 | // aten::special_multigammaln(Tensor self, int p) -> Tensor |
| 9864 | at::Tensor special_multigammaln::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p) { |
| 9865 | |
| 9866 | static auto op = create_special_multigammaln_typed_handle(); |
| 9867 | return op.redispatch(dispatchKeySet, self, p); |
| 9868 | } |
| 9869 | |
| 9870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_multigammaln_out, name, "aten::special_multigammaln") |
| 9871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_multigammaln_out, overload_name, "out") |
| 9872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_multigammaln_out, schema_str, "special_multigammaln.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!)") |
| 9873 | |
| 9874 | // aten::special_multigammaln.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) |
| 9875 | static C10_NOINLINE c10::TypedOperatorHandle<special_multigammaln_out::schema> create_special_multigammaln_out_typed_handle() { |
| 9876 | return c10::Dispatcher::singleton() |
| 9877 | .findSchemaOrThrow(special_multigammaln_out::name, special_multigammaln_out::overload_name) |
| 9878 | .typed<special_multigammaln_out::schema>(); |
| 9879 | } |
| 9880 | |
| 9881 | // aten::special_multigammaln.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) |
| 9882 | at::Tensor & special_multigammaln_out::call(const at::Tensor & self, int64_t p, at::Tensor & out) { |
| 9883 | |
| 9884 | static auto op = create_special_multigammaln_out_typed_handle(); |
| 9885 | return op.call(self, p, out); |
| 9886 | } |
| 9887 | |
| 9888 | // aten::special_multigammaln.out(Tensor self, int p, *, Tensor(a!) out) -> Tensor(a!) |
| 9889 | at::Tensor & special_multigammaln_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t p, at::Tensor & out) { |
| 9890 | |
| 9891 | static auto op = create_special_multigammaln_out_typed_handle(); |
| 9892 | return op.redispatch(dispatchKeySet, self, p, out); |
| 9893 | } |
| 9894 | |
| 9895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fft2, name, "aten::fft_fft2") |
| 9896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fft2, overload_name, "") |
| 9897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fft2, schema_str, "fft_fft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor") |
| 9898 | |
| 9899 | // aten::fft_fft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
| 9900 | static C10_NOINLINE c10::TypedOperatorHandle<fft_fft2::schema> create_fft_fft2_typed_handle() { |
| 9901 | return c10::Dispatcher::singleton() |
| 9902 | .findSchemaOrThrow(fft_fft2::name, fft_fft2::overload_name) |
| 9903 | .typed<fft_fft2::schema>(); |
| 9904 | } |
| 9905 | |
| 9906 | // aten::fft_fft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
| 9907 | at::Tensor fft_fft2::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 9908 | |
| 9909 | static auto op = create_fft_fft2_typed_handle(); |
| 9910 | return op.call(self, s, dim, norm); |
| 9911 | } |
| 9912 | |
| 9913 | // aten::fft_fft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
| 9914 | at::Tensor fft_fft2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 9915 | |
| 9916 | static auto op = create_fft_fft2_typed_handle(); |
| 9917 | return op.redispatch(dispatchKeySet, self, s, dim, norm); |
| 9918 | } |
| 9919 | |
| 9920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fft2_out, name, "aten::fft_fft2") |
| 9921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fft2_out, overload_name, "out") |
| 9922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fft2_out, schema_str, "fft_fft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 9923 | |
| 9924 | // aten::fft_fft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9925 | static C10_NOINLINE c10::TypedOperatorHandle<fft_fft2_out::schema> create_fft_fft2_out_typed_handle() { |
| 9926 | return c10::Dispatcher::singleton() |
| 9927 | .findSchemaOrThrow(fft_fft2_out::name, fft_fft2_out::overload_name) |
| 9928 | .typed<fft_fft2_out::schema>(); |
| 9929 | } |
| 9930 | |
| 9931 | // aten::fft_fft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9932 | at::Tensor & fft_fft2_out::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
| 9933 | |
| 9934 | static auto op = create_fft_fft2_out_typed_handle(); |
| 9935 | return op.call(self, s, dim, norm, out); |
| 9936 | } |
| 9937 | |
| 9938 | // aten::fft_fft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9939 | at::Tensor & fft_fft2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
| 9940 | |
| 9941 | static auto op = create_fft_fft2_out_typed_handle(); |
| 9942 | return op.redispatch(dispatchKeySet, self, s, dim, norm, out); |
| 9943 | } |
| 9944 | |
| 9945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftn, name, "aten::fft_fftn") |
| 9946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftn, overload_name, "") |
| 9947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftn, schema_str, "fft_fftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor") |
| 9948 | |
| 9949 | // aten::fft_fftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
| 9950 | static C10_NOINLINE c10::TypedOperatorHandle<fft_fftn::schema> create_fft_fftn_typed_handle() { |
| 9951 | return c10::Dispatcher::singleton() |
| 9952 | .findSchemaOrThrow(fft_fftn::name, fft_fftn::overload_name) |
| 9953 | .typed<fft_fftn::schema>(); |
| 9954 | } |
| 9955 | |
| 9956 | // aten::fft_fftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
| 9957 | at::Tensor fft_fftn::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 9958 | |
| 9959 | static auto op = create_fft_fftn_typed_handle(); |
| 9960 | return op.call(self, s, dim, norm); |
| 9961 | } |
| 9962 | |
| 9963 | // aten::fft_fftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
| 9964 | at::Tensor fft_fftn::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm) { |
| 9965 | |
| 9966 | static auto op = create_fft_fftn_typed_handle(); |
| 9967 | return op.redispatch(dispatchKeySet, self, s, dim, norm); |
| 9968 | } |
| 9969 | |
| 9970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftn_out, name, "aten::fft_fftn") |
| 9971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftn_out, overload_name, "out") |
| 9972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftn_out, schema_str, "fft_fftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 9973 | |
| 9974 | // aten::fft_fftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9975 | static C10_NOINLINE c10::TypedOperatorHandle<fft_fftn_out::schema> create_fft_fftn_out_typed_handle() { |
| 9976 | return c10::Dispatcher::singleton() |
| 9977 | .findSchemaOrThrow(fft_fftn_out::name, fft_fftn_out::overload_name) |
| 9978 | .typed<fft_fftn_out::schema>(); |
| 9979 | } |
| 9980 | |
| 9981 | // aten::fft_fftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9982 | at::Tensor & fft_fftn_out::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
| 9983 | |
| 9984 | static auto op = create_fft_fftn_out_typed_handle(); |
| 9985 | return op.call(self, s, dim, norm, out); |
| 9986 | } |
| 9987 | |
| 9988 | // aten::fft_fftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
| 9989 | at::Tensor & fft_fftn_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
| 9990 | |
| 9991 | static auto op = create_fft_fftn_out_typed_handle(); |
| 9992 | return op.redispatch(dispatchKeySet, self, s, dim, norm, out); |
| 9993 | } |
| 9994 | |
| 9995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftshift, name, "aten::fft_fftshift") |
| 9996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftshift, overload_name, "") |
| 9997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_fftshift, schema_str, "fft_fftshift(Tensor self, int[1]? dim=None) -> Tensor") |
| 9998 | |
| 9999 | // aten::fft_fftshift(Tensor self, int[1]? dim=None) -> Tensor |
| 10000 | static C10_NOINLINE c10::TypedOperatorHandle<fft_fftshift::schema> create_fft_fftshift_typed_handle() { |
| 10001 | return c10::Dispatcher::singleton() |
| 10002 | .findSchemaOrThrow(fft_fftshift::name, fft_fftshift::overload_name) |
| 10003 | .typed<fft_fftshift::schema>(); |
| 10004 | } |
| 10005 | |
| 10006 | // aten::fft_fftshift(Tensor self, int[1]? dim=None) -> Tensor |
| 10007 | at::Tensor fft_fftshift::call(const at::Tensor & self, at::OptionalIntArrayRef dim) { |
| 10008 | |
| 10009 | static auto op = create_fft_fftshift_typed_handle(); |
| 10010 | return op.call(self, dim); |
| 10011 | } |
| 10012 | |
| 10013 | // aten::fft_fftshift(Tensor self, int[1]? dim=None) -> Tensor |
| 10014 | at::Tensor fft_fftshift::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim) { |
| 10015 | |
| 10016 | static auto op = create_fft_fftshift_typed_handle(); |
| 10017 | return op.redispatch(dispatchKeySet, self, dim); |
| 10018 | } |
| 10019 | |
| 10020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_factor, name, "aten::linalg_lu_factor") |
| 10021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_factor, overload_name, "") |
| 10022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_factor, schema_str, "linalg_lu_factor(Tensor A, *, bool pivot=True) -> (Tensor LU, Tensor pivots)") |
| 10023 | |
| 10024 | // aten::linalg_lu_factor(Tensor A, *, bool pivot=True) -> (Tensor LU, Tensor pivots) |
| 10025 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lu_factor::schema> create_linalg_lu_factor_typed_handle() { |
| 10026 | return c10::Dispatcher::singleton() |
| 10027 | .findSchemaOrThrow(linalg_lu_factor::name, linalg_lu_factor::overload_name) |
| 10028 | .typed<linalg_lu_factor::schema>(); |
| 10029 | } |
| 10030 | |
| 10031 | // aten::linalg_lu_factor(Tensor A, *, bool pivot=True) -> (Tensor LU, Tensor pivots) |
| 10032 | ::std::tuple<at::Tensor,at::Tensor> linalg_lu_factor::call(const at::Tensor & A, bool pivot) { |
| 10033 | |
| 10034 | static auto op = create_linalg_lu_factor_typed_handle(); |
| 10035 | return op.call(A, pivot); |
| 10036 | } |
| 10037 | |
| 10038 | // aten::linalg_lu_factor(Tensor A, *, bool pivot=True) -> (Tensor LU, Tensor pivots) |
| 10039 | ::std::tuple<at::Tensor,at::Tensor> linalg_lu_factor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot) { |
| 10040 | |
| 10041 | static auto op = create_linalg_lu_factor_typed_handle(); |
| 10042 | return op.redispatch(dispatchKeySet, A, pivot); |
| 10043 | } |
| 10044 | |
| 10045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_factor_out, name, "aten::linalg_lu_factor") |
| 10046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_factor_out, overload_name, "out") |
| 10047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_factor_out, schema_str, "linalg_lu_factor.out(Tensor A, *, bool pivot=True, Tensor(a!) LU, Tensor(b!) pivots) -> (Tensor(a!) LU, Tensor(b!) pivots)") |
| 10048 | |
| 10049 | // aten::linalg_lu_factor.out(Tensor A, *, bool pivot=True, Tensor(a!) LU, Tensor(b!) pivots) -> (Tensor(a!) LU, Tensor(b!) pivots) |
| 10050 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lu_factor_out::schema> create_linalg_lu_factor_out_typed_handle() { |
| 10051 | return c10::Dispatcher::singleton() |
| 10052 | .findSchemaOrThrow(linalg_lu_factor_out::name, linalg_lu_factor_out::overload_name) |
| 10053 | .typed<linalg_lu_factor_out::schema>(); |
| 10054 | } |
| 10055 | |
| 10056 | // aten::linalg_lu_factor.out(Tensor A, *, bool pivot=True, Tensor(a!) LU, Tensor(b!) pivots) -> (Tensor(a!) LU, Tensor(b!) pivots) |
| 10057 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_lu_factor_out::call(const at::Tensor & A, bool pivot, at::Tensor & LU, at::Tensor & pivots) { |
| 10058 | |
| 10059 | static auto op = create_linalg_lu_factor_out_typed_handle(); |
| 10060 | return op.call(A, pivot, LU, pivots); |
| 10061 | } |
| 10062 | |
| 10063 | // aten::linalg_lu_factor.out(Tensor A, *, bool pivot=True, Tensor(a!) LU, Tensor(b!) pivots) -> (Tensor(a!) LU, Tensor(b!) pivots) |
| 10064 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_lu_factor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool pivot, at::Tensor & LU, at::Tensor & pivots) { |
| 10065 | |
| 10066 | static auto op = create_linalg_lu_factor_out_typed_handle(); |
| 10067 | return op.redispatch(dispatchKeySet, A, pivot, LU, pivots); |
| 10068 | } |
| 10069 | |
| 10070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_solve, name, "aten::linalg_lu_solve") |
| 10071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_solve, overload_name, "") |
| 10072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_solve, schema_str, "linalg_lu_solve(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False) -> Tensor") |
| 10073 | |
| 10074 | // aten::linalg_lu_solve(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False) -> Tensor |
| 10075 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lu_solve::schema> create_linalg_lu_solve_typed_handle() { |
| 10076 | return c10::Dispatcher::singleton() |
| 10077 | .findSchemaOrThrow(linalg_lu_solve::name, linalg_lu_solve::overload_name) |
| 10078 | .typed<linalg_lu_solve::schema>(); |
| 10079 | } |
| 10080 | |
| 10081 | // aten::linalg_lu_solve(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False) -> Tensor |
| 10082 | at::Tensor linalg_lu_solve::call(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint) { |
| 10083 | |
| 10084 | static auto op = create_linalg_lu_solve_typed_handle(); |
| 10085 | return op.call(LU, pivots, B, left, adjoint); |
| 10086 | } |
| 10087 | |
| 10088 | // aten::linalg_lu_solve(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False) -> Tensor |
| 10089 | at::Tensor linalg_lu_solve::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint) { |
| 10090 | |
| 10091 | static auto op = create_linalg_lu_solve_typed_handle(); |
| 10092 | return op.redispatch(dispatchKeySet, LU, pivots, B, left, adjoint); |
| 10093 | } |
| 10094 | |
| 10095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_solve_out, name, "aten::linalg_lu_solve") |
| 10096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_solve_out, overload_name, "out") |
| 10097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_lu_solve_out, schema_str, "linalg_lu_solve.out(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False, Tensor(a!) out) -> Tensor(a!)") |
| 10098 | |
| 10099 | // aten::linalg_lu_solve.out(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False, Tensor(a!) out) -> Tensor(a!) |
| 10100 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_lu_solve_out::schema> create_linalg_lu_solve_out_typed_handle() { |
| 10101 | return c10::Dispatcher::singleton() |
| 10102 | .findSchemaOrThrow(linalg_lu_solve_out::name, linalg_lu_solve_out::overload_name) |
| 10103 | .typed<linalg_lu_solve_out::schema>(); |
| 10104 | } |
| 10105 | |
| 10106 | // aten::linalg_lu_solve.out(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False, Tensor(a!) out) -> Tensor(a!) |
| 10107 | at::Tensor & linalg_lu_solve_out::call(const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint, at::Tensor & out) { |
| 10108 | |
| 10109 | static auto op = create_linalg_lu_solve_out_typed_handle(); |
| 10110 | return op.call(LU, pivots, B, left, adjoint, out); |
| 10111 | } |
| 10112 | |
| 10113 | // aten::linalg_lu_solve.out(Tensor LU, Tensor pivots, Tensor B, *, bool left=True, bool adjoint=False, Tensor(a!) out) -> Tensor(a!) |
| 10114 | at::Tensor & linalg_lu_solve_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & LU, const at::Tensor & pivots, const at::Tensor & B, bool left, bool adjoint, at::Tensor & out) { |
| 10115 | |
| 10116 | static auto op = create_linalg_lu_solve_out_typed_handle(); |
| 10117 | return op.redispatch(dispatchKeySet, LU, pivots, B, left, adjoint, out); |
| 10118 | } |
| 10119 | |
| 10120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_det, name, "aten::linalg_det") |
| 10121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_det, overload_name, "") |
| 10122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_det, schema_str, "linalg_det(Tensor A) -> Tensor") |
| 10123 | |
| 10124 | // aten::linalg_det(Tensor A) -> Tensor |
| 10125 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_det::schema> create_linalg_det_typed_handle() { |
| 10126 | return c10::Dispatcher::singleton() |
| 10127 | .findSchemaOrThrow(linalg_det::name, linalg_det::overload_name) |
| 10128 | .typed<linalg_det::schema>(); |
| 10129 | } |
| 10130 | |
| 10131 | // aten::linalg_det(Tensor A) -> Tensor |
| 10132 | at::Tensor linalg_det::call(const at::Tensor & A) { |
| 10133 | |
| 10134 | static auto op = create_linalg_det_typed_handle(); |
| 10135 | return op.call(A); |
| 10136 | } |
| 10137 | |
| 10138 | // aten::linalg_det(Tensor A) -> Tensor |
| 10139 | at::Tensor linalg_det::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A) { |
| 10140 | |
| 10141 | static auto op = create_linalg_det_typed_handle(); |
| 10142 | return op.redispatch(dispatchKeySet, A); |
| 10143 | } |
| 10144 | |
| 10145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_det_out, name, "aten::linalg_det") |
| 10146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_det_out, overload_name, "out") |
| 10147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_det_out, schema_str, "linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!)") |
| 10148 | |
| 10149 | // aten::linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) |
| 10150 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_det_out::schema> create_linalg_det_out_typed_handle() { |
| 10151 | return c10::Dispatcher::singleton() |
| 10152 | .findSchemaOrThrow(linalg_det_out::name, linalg_det_out::overload_name) |
| 10153 | .typed<linalg_det_out::schema>(); |
| 10154 | } |
| 10155 | |
| 10156 | // aten::linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) |
| 10157 | at::Tensor & linalg_det_out::call(const at::Tensor & A, at::Tensor & out) { |
| 10158 | |
| 10159 | static auto op = create_linalg_det_out_typed_handle(); |
| 10160 | return op.call(A, out); |
| 10161 | } |
| 10162 | |
| 10163 | // aten::linalg_det.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) |
| 10164 | at::Tensor & linalg_det_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, at::Tensor & out) { |
| 10165 | |
| 10166 | static auto op = create_linalg_det_out_typed_handle(); |
| 10167 | return op.redispatch(dispatchKeySet, A, out); |
| 10168 | } |
| 10169 | |
| 10170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_slogdet, name, "aten::_linalg_slogdet") |
| 10171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_slogdet, overload_name, "") |
| 10172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_slogdet, schema_str, "_linalg_slogdet(Tensor A) -> (Tensor sign, Tensor logabsdet, Tensor LU, Tensor pivots)") |
| 10173 | |
| 10174 | // aten::_linalg_slogdet(Tensor A) -> (Tensor sign, Tensor logabsdet, Tensor LU, Tensor pivots) |
| 10175 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_slogdet::schema> create__linalg_slogdet_typed_handle() { |
| 10176 | return c10::Dispatcher::singleton() |
| 10177 | .findSchemaOrThrow(_linalg_slogdet::name, _linalg_slogdet::overload_name) |
| 10178 | .typed<_linalg_slogdet::schema>(); |
| 10179 | } |
| 10180 | |
| 10181 | // aten::_linalg_slogdet(Tensor A) -> (Tensor sign, Tensor logabsdet, Tensor LU, Tensor pivots) |
| 10182 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _linalg_slogdet::call(const at::Tensor & A) { |
| 10183 | |
| 10184 | static auto op = create__linalg_slogdet_typed_handle(); |
| 10185 | return op.call(A); |
| 10186 | } |
| 10187 | |
| 10188 | // aten::_linalg_slogdet(Tensor A) -> (Tensor sign, Tensor logabsdet, Tensor LU, Tensor pivots) |
| 10189 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _linalg_slogdet::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A) { |
| 10190 | |
| 10191 | static auto op = create__linalg_slogdet_typed_handle(); |
| 10192 | return op.redispatch(dispatchKeySet, A); |
| 10193 | } |
| 10194 | |
| 10195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_slogdet_sign, name, "aten::_linalg_slogdet") |
| 10196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_slogdet_sign, overload_name, "sign") |
| 10197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_slogdet_sign, schema_str, "_linalg_slogdet.sign(Tensor A, *, Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots) -> (Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots)") |
| 10198 | |
| 10199 | // aten::_linalg_slogdet.sign(Tensor A, *, Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots) -> (Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots) |
| 10200 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_slogdet_sign::schema> create__linalg_slogdet_sign_typed_handle() { |
| 10201 | return c10::Dispatcher::singleton() |
| 10202 | .findSchemaOrThrow(_linalg_slogdet_sign::name, _linalg_slogdet_sign::overload_name) |
| 10203 | .typed<_linalg_slogdet_sign::schema>(); |
| 10204 | } |
| 10205 | |
| 10206 | // aten::_linalg_slogdet.sign(Tensor A, *, Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots) -> (Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots) |
| 10207 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _linalg_slogdet_sign::call(const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet, at::Tensor & LU, at::Tensor & pivots) { |
| 10208 | |
| 10209 | static auto op = create__linalg_slogdet_sign_typed_handle(); |
| 10210 | return op.call(A, sign, logabsdet, LU, pivots); |
| 10211 | } |
| 10212 | |
| 10213 | // aten::_linalg_slogdet.sign(Tensor A, *, Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots) -> (Tensor(a!) sign, Tensor(b!) logabsdet, Tensor(c!) LU, Tensor(d!) pivots) |
| 10214 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _linalg_slogdet_sign::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, at::Tensor & sign, at::Tensor & logabsdet, at::Tensor & LU, at::Tensor & pivots) { |
| 10215 | |
| 10216 | static auto op = create__linalg_slogdet_sign_typed_handle(); |
| 10217 | return op.redispatch(dispatchKeySet, A, sign, logabsdet, LU, pivots); |
| 10218 | } |
| 10219 | |
| 10220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_inv, name, "aten::linalg_inv") |
| 10221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_inv, overload_name, "") |
| 10222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_inv, schema_str, "linalg_inv(Tensor A) -> Tensor") |
| 10223 | |
| 10224 | // aten::linalg_inv(Tensor A) -> Tensor |
| 10225 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_inv::schema> create_linalg_inv_typed_handle() { |
| 10226 | return c10::Dispatcher::singleton() |
| 10227 | .findSchemaOrThrow(linalg_inv::name, linalg_inv::overload_name) |
| 10228 | .typed<linalg_inv::schema>(); |
| 10229 | } |
| 10230 | |
| 10231 | // aten::linalg_inv(Tensor A) -> Tensor |
| 10232 | at::Tensor linalg_inv::call(const at::Tensor & A) { |
| 10233 | |
| 10234 | static auto op = create_linalg_inv_typed_handle(); |
| 10235 | return op.call(A); |
| 10236 | } |
| 10237 | |
| 10238 | // aten::linalg_inv(Tensor A) -> Tensor |
| 10239 | at::Tensor linalg_inv::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A) { |
| 10240 | |
| 10241 | static auto op = create_linalg_inv_typed_handle(); |
| 10242 | return op.redispatch(dispatchKeySet, A); |
| 10243 | } |
| 10244 | |
| 10245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_inv_out, name, "aten::linalg_inv") |
| 10246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_inv_out, overload_name, "out") |
| 10247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_inv_out, schema_str, "linalg_inv.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!)") |
| 10248 | |
| 10249 | // aten::linalg_inv.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) |
| 10250 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_inv_out::schema> create_linalg_inv_out_typed_handle() { |
| 10251 | return c10::Dispatcher::singleton() |
| 10252 | .findSchemaOrThrow(linalg_inv_out::name, linalg_inv_out::overload_name) |
| 10253 | .typed<linalg_inv_out::schema>(); |
| 10254 | } |
| 10255 | |
| 10256 | // aten::linalg_inv.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) |
| 10257 | at::Tensor & linalg_inv_out::call(const at::Tensor & A, at::Tensor & out) { |
| 10258 | |
| 10259 | static auto op = create_linalg_inv_out_typed_handle(); |
| 10260 | return op.call(A, out); |
| 10261 | } |
| 10262 | |
| 10263 | // aten::linalg_inv.out(Tensor A, *, Tensor(a!) out) -> Tensor(a!) |
| 10264 | at::Tensor & linalg_inv_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, at::Tensor & out) { |
| 10265 | |
| 10266 | static auto op = create_linalg_inv_out_typed_handle(); |
| 10267 | return op.redispatch(dispatchKeySet, A, out); |
| 10268 | } |
| 10269 | |
| 10270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(outer, name, "aten::outer") |
| 10271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(outer, overload_name, "") |
| 10272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(outer, schema_str, "outer(Tensor self, Tensor vec2) -> Tensor") |
| 10273 | |
| 10274 | // aten::outer(Tensor self, Tensor vec2) -> Tensor |
| 10275 | static C10_NOINLINE c10::TypedOperatorHandle<outer::schema> create_outer_typed_handle() { |
| 10276 | return c10::Dispatcher::singleton() |
| 10277 | .findSchemaOrThrow(outer::name, outer::overload_name) |
| 10278 | .typed<outer::schema>(); |
| 10279 | } |
| 10280 | |
| 10281 | // aten::outer(Tensor self, Tensor vec2) -> Tensor |
| 10282 | at::Tensor outer::call(const at::Tensor & self, const at::Tensor & vec2) { |
| 10283 | |
| 10284 | static auto op = create_outer_typed_handle(); |
| 10285 | return op.call(self, vec2); |
| 10286 | } |
| 10287 | |
| 10288 | // aten::outer(Tensor self, Tensor vec2) -> Tensor |
| 10289 | at::Tensor outer::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2) { |
| 10290 | |
| 10291 | static auto op = create_outer_typed_handle(); |
| 10292 | return op.redispatch(dispatchKeySet, self, vec2); |
| 10293 | } |
| 10294 | |
| 10295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(outer_out, name, "aten::outer") |
| 10296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(outer_out, overload_name, "out") |
| 10297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(outer_out, schema_str, "outer.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)") |
| 10298 | |
| 10299 | // aten::outer.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) |
| 10300 | static C10_NOINLINE c10::TypedOperatorHandle<outer_out::schema> create_outer_out_typed_handle() { |
| 10301 | return c10::Dispatcher::singleton() |
| 10302 | .findSchemaOrThrow(outer_out::name, outer_out::overload_name) |
| 10303 | .typed<outer_out::schema>(); |
| 10304 | } |
| 10305 | |
| 10306 | // aten::outer.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) |
| 10307 | at::Tensor & outer_out::call(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out) { |
| 10308 | |
| 10309 | static auto op = create_outer_out_typed_handle(); |
| 10310 | return op.call(self, vec2, out); |
| 10311 | } |
| 10312 | |
| 10313 | // aten::outer.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) |
| 10314 | at::Tensor & outer_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out) { |
| 10315 | |
| 10316 | static auto op = create_outer_out_typed_handle(); |
| 10317 | return op.redispatch(dispatchKeySet, self, vec2, out); |
| 10318 | } |
| 10319 | |
| 10320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ger, name, "aten::ger") |
| 10321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ger, overload_name, "") |
| 10322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ger, schema_str, "ger(Tensor self, Tensor vec2) -> Tensor") |
| 10323 | |
| 10324 | // aten::ger(Tensor self, Tensor vec2) -> Tensor |
| 10325 | static C10_NOINLINE c10::TypedOperatorHandle<ger::schema> create_ger_typed_handle() { |
| 10326 | return c10::Dispatcher::singleton() |
| 10327 | .findSchemaOrThrow(ger::name, ger::overload_name) |
| 10328 | .typed<ger::schema>(); |
| 10329 | } |
| 10330 | |
| 10331 | // aten::ger(Tensor self, Tensor vec2) -> Tensor |
| 10332 | at::Tensor ger::call(const at::Tensor & self, const at::Tensor & vec2) { |
| 10333 | |
| 10334 | static auto op = create_ger_typed_handle(); |
| 10335 | return op.call(self, vec2); |
| 10336 | } |
| 10337 | |
| 10338 | // aten::ger(Tensor self, Tensor vec2) -> Tensor |
| 10339 | at::Tensor ger::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2) { |
| 10340 | |
| 10341 | static auto op = create_ger_typed_handle(); |
| 10342 | return op.redispatch(dispatchKeySet, self, vec2); |
| 10343 | } |
| 10344 | |
| 10345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ger_out, name, "aten::ger") |
| 10346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ger_out, overload_name, "out") |
| 10347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ger_out, schema_str, "ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)") |
| 10348 | |
| 10349 | // aten::ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) |
| 10350 | static C10_NOINLINE c10::TypedOperatorHandle<ger_out::schema> create_ger_out_typed_handle() { |
| 10351 | return c10::Dispatcher::singleton() |
| 10352 | .findSchemaOrThrow(ger_out::name, ger_out::overload_name) |
| 10353 | .typed<ger_out::schema>(); |
| 10354 | } |
| 10355 | |
| 10356 | // aten::ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) |
| 10357 | at::Tensor & ger_out::call(const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out) { |
| 10358 | |
| 10359 | static auto op = create_ger_out_typed_handle(); |
| 10360 | return op.call(self, vec2, out); |
| 10361 | } |
| 10362 | |
| 10363 | // aten::ger.out(Tensor self, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!) |
| 10364 | at::Tensor & ger_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & vec2, at::Tensor & out) { |
| 10365 | |
| 10366 | static auto op = create_ger_out_typed_handle(); |
| 10367 | return op.redispatch(dispatchKeySet, self, vec2, out); |
| 10368 | } |
| 10369 | |
| 10370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_svd, name, "aten::_linalg_svd") |
| 10371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_svd, overload_name, "") |
| 10372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_svd, schema_str, "_linalg_svd(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh)") |
| 10373 | |
| 10374 | // aten::_linalg_svd(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh) |
| 10375 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_svd::schema> create__linalg_svd_typed_handle() { |
| 10376 | return c10::Dispatcher::singleton() |
| 10377 | .findSchemaOrThrow(_linalg_svd::name, _linalg_svd::overload_name) |
| 10378 | .typed<_linalg_svd::schema>(); |
| 10379 | } |
| 10380 | |
| 10381 | // aten::_linalg_svd(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh) |
| 10382 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _linalg_svd::call(const at::Tensor & A, bool full_matrices, bool compute_uv, c10::optional<c10::string_view> driver) { |
| 10383 | |
| 10384 | static auto op = create__linalg_svd_typed_handle(); |
| 10385 | return op.call(A, full_matrices, compute_uv, driver); |
| 10386 | } |
| 10387 | |
| 10388 | // aten::_linalg_svd(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh) |
| 10389 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _linalg_svd::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool full_matrices, bool compute_uv, c10::optional<c10::string_view> driver) { |
| 10390 | |
| 10391 | static auto op = create__linalg_svd_typed_handle(); |
| 10392 | return op.redispatch(dispatchKeySet, A, full_matrices, compute_uv, driver); |
| 10393 | } |
| 10394 | |
| 10395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_svd_U, name, "aten::_linalg_svd") |
| 10396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_svd_U, overload_name, "U") |
| 10397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_svd_U, schema_str, "_linalg_svd.U(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh)") |
| 10398 | |
| 10399 | // aten::_linalg_svd.U(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) |
| 10400 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_svd_U::schema> create__linalg_svd_U_typed_handle() { |
| 10401 | return c10::Dispatcher::singleton() |
| 10402 | .findSchemaOrThrow(_linalg_svd_U::name, _linalg_svd_U::overload_name) |
| 10403 | .typed<_linalg_svd_U::schema>(); |
| 10404 | } |
| 10405 | |
| 10406 | // aten::_linalg_svd.U(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) |
| 10407 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _linalg_svd_U::call(const at::Tensor & A, bool full_matrices, bool compute_uv, c10::optional<c10::string_view> driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh) { |
| 10408 | |
| 10409 | static auto op = create__linalg_svd_U_typed_handle(); |
| 10410 | return op.call(A, full_matrices, compute_uv, driver, U, S, Vh); |
| 10411 | } |
| 10412 | |
| 10413 | // aten::_linalg_svd.U(Tensor A, bool full_matrices=False, bool compute_uv=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) |
| 10414 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _linalg_svd_U::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool full_matrices, bool compute_uv, c10::optional<c10::string_view> driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh) { |
| 10415 | |
| 10416 | static auto op = create__linalg_svd_U_typed_handle(); |
| 10417 | return op.redispatch(dispatchKeySet, A, full_matrices, compute_uv, driver, U, S, Vh); |
| 10418 | } |
| 10419 | |
| 10420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_solve_ex, name, "aten::_linalg_solve_ex") |
| 10421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_solve_ex, overload_name, "") |
| 10422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_solve_ex, schema_str, "_linalg_solve_ex(Tensor A, Tensor B, *, bool left=True, bool check_errors=False) -> (Tensor result, Tensor LU, Tensor pivots, Tensor info)") |
| 10423 | |
| 10424 | // aten::_linalg_solve_ex(Tensor A, Tensor B, *, bool left=True, bool check_errors=False) -> (Tensor result, Tensor LU, Tensor pivots, Tensor info) |
| 10425 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_solve_ex::schema> create__linalg_solve_ex_typed_handle() { |
| 10426 | return c10::Dispatcher::singleton() |
| 10427 | .findSchemaOrThrow(_linalg_solve_ex::name, _linalg_solve_ex::overload_name) |
| 10428 | .typed<_linalg_solve_ex::schema>(); |
| 10429 | } |
| 10430 | |
| 10431 | // aten::_linalg_solve_ex(Tensor A, Tensor B, *, bool left=True, bool check_errors=False) -> (Tensor result, Tensor LU, Tensor pivots, Tensor info) |
| 10432 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _linalg_solve_ex::call(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors) { |
| 10433 | |
| 10434 | static auto op = create__linalg_solve_ex_typed_handle(); |
| 10435 | return op.call(A, B, left, check_errors); |
| 10436 | } |
| 10437 | |
| 10438 | // aten::_linalg_solve_ex(Tensor A, Tensor B, *, bool left=True, bool check_errors=False) -> (Tensor result, Tensor LU, Tensor pivots, Tensor info) |
| 10439 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _linalg_solve_ex::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors) { |
| 10440 | |
| 10441 | static auto op = create__linalg_solve_ex_typed_handle(); |
| 10442 | return op.redispatch(dispatchKeySet, A, B, left, check_errors); |
| 10443 | } |
| 10444 | |
| 10445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_solve_ex_result, name, "aten::_linalg_solve_ex") |
| 10446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_solve_ex_result, overload_name, "result") |
| 10447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_linalg_solve_ex_result, schema_str, "_linalg_solve_ex.result(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info)") |
| 10448 | |
| 10449 | // aten::_linalg_solve_ex.result(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) |
| 10450 | static C10_NOINLINE c10::TypedOperatorHandle<_linalg_solve_ex_result::schema> create__linalg_solve_ex_result_typed_handle() { |
| 10451 | return c10::Dispatcher::singleton() |
| 10452 | .findSchemaOrThrow(_linalg_solve_ex_result::name, _linalg_solve_ex_result::overload_name) |
| 10453 | .typed<_linalg_solve_ex_result::schema>(); |
| 10454 | } |
| 10455 | |
| 10456 | // aten::_linalg_solve_ex.result(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) |
| 10457 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _linalg_solve_ex_result::call(const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info) { |
| 10458 | |
| 10459 | static auto op = create__linalg_solve_ex_result_typed_handle(); |
| 10460 | return op.call(A, B, left, check_errors, result, LU, pivots, info); |
| 10461 | } |
| 10462 | |
| 10463 | // aten::_linalg_solve_ex.result(Tensor A, Tensor B, *, bool left=True, bool check_errors=False, Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) -> (Tensor(a!) result, Tensor(b!) LU, Tensor(c!) pivots, Tensor(d!) info) |
| 10464 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _linalg_solve_ex_result::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, const at::Tensor & B, bool left, bool check_errors, at::Tensor & result, at::Tensor & LU, at::Tensor & pivots, at::Tensor & info) { |
| 10465 | |
| 10466 | static auto op = create__linalg_solve_ex_result_typed_handle(); |
| 10467 | return op.redispatch(dispatchKeySet, A, B, left, check_errors, result, LU, pivots, info); |
| 10468 | } |
| 10469 | |
| 10470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_qr, name, "aten::linalg_qr") |
| 10471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_qr, overload_name, "") |
| 10472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_qr, schema_str, "linalg_qr(Tensor A, str mode='reduced') -> (Tensor Q, Tensor R)") |
| 10473 | |
| 10474 | // aten::linalg_qr(Tensor A, str mode='reduced') -> (Tensor Q, Tensor R) |
| 10475 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_qr::schema> create_linalg_qr_typed_handle() { |
| 10476 | return c10::Dispatcher::singleton() |
| 10477 | .findSchemaOrThrow(linalg_qr::name, linalg_qr::overload_name) |
| 10478 | .typed<linalg_qr::schema>(); |
| 10479 | } |
| 10480 | |
| 10481 | // aten::linalg_qr(Tensor A, str mode='reduced') -> (Tensor Q, Tensor R) |
| 10482 | ::std::tuple<at::Tensor,at::Tensor> linalg_qr::call(const at::Tensor & A, c10::string_view mode) { |
| 10483 | |
| 10484 | static auto op = create_linalg_qr_typed_handle(); |
| 10485 | return op.call(A, mode); |
| 10486 | } |
| 10487 | |
| 10488 | // aten::linalg_qr(Tensor A, str mode='reduced') -> (Tensor Q, Tensor R) |
| 10489 | ::std::tuple<at::Tensor,at::Tensor> linalg_qr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view mode) { |
| 10490 | |
| 10491 | static auto op = create_linalg_qr_typed_handle(); |
| 10492 | return op.redispatch(dispatchKeySet, A, mode); |
| 10493 | } |
| 10494 | |
| 10495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_qr_out, name, "aten::linalg_qr") |
| 10496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_qr_out, overload_name, "out") |
| 10497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_qr_out, schema_str, "linalg_qr.out(Tensor A, str mode='reduced', *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R)") |
| 10498 | |
| 10499 | // aten::linalg_qr.out(Tensor A, str mode='reduced', *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R) |
| 10500 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_qr_out::schema> create_linalg_qr_out_typed_handle() { |
| 10501 | return c10::Dispatcher::singleton() |
| 10502 | .findSchemaOrThrow(linalg_qr_out::name, linalg_qr_out::overload_name) |
| 10503 | .typed<linalg_qr_out::schema>(); |
| 10504 | } |
| 10505 | |
| 10506 | // aten::linalg_qr.out(Tensor A, str mode='reduced', *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R) |
| 10507 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_qr_out::call(const at::Tensor & A, c10::string_view mode, at::Tensor & Q, at::Tensor & R) { |
| 10508 | |
| 10509 | static auto op = create_linalg_qr_out_typed_handle(); |
| 10510 | return op.call(A, mode, Q, R); |
| 10511 | } |
| 10512 | |
| 10513 | // aten::linalg_qr.out(Tensor A, str mode='reduced', *, Tensor(a!) Q, Tensor(b!) R) -> (Tensor(a!) Q, Tensor(b!) R) |
| 10514 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_qr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, c10::string_view mode, at::Tensor & Q, at::Tensor & R) { |
| 10515 | |
| 10516 | static auto op = create_linalg_qr_out_typed_handle(); |
| 10517 | return op.redispatch(dispatchKeySet, A, mode, Q, R); |
| 10518 | } |
| 10519 | |
| 10520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nested_to_padded_tensor, name, "aten::nested_to_padded_tensor") |
| 10521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nested_to_padded_tensor, overload_name, "") |
| 10522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nested_to_padded_tensor, schema_str, "nested_to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor") |
| 10523 | |
| 10524 | // aten::nested_to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor |
| 10525 | static C10_NOINLINE c10::TypedOperatorHandle<nested_to_padded_tensor::schema> create_nested_to_padded_tensor_typed_handle() { |
| 10526 | return c10::Dispatcher::singleton() |
| 10527 | .findSchemaOrThrow(nested_to_padded_tensor::name, nested_to_padded_tensor::overload_name) |
| 10528 | .typed<nested_to_padded_tensor::schema>(); |
| 10529 | } |
| 10530 | |
| 10531 | // aten::nested_to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor |
| 10532 | at::Tensor nested_to_padded_tensor::call(const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size) { |
| 10533 | |
| 10534 | static auto op = create_nested_to_padded_tensor_typed_handle(); |
| 10535 | return op.call(self, padding, output_size); |
| 10536 | } |
| 10537 | |
| 10538 | // aten::nested_to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor |
| 10539 | at::Tensor nested_to_padded_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double padding, at::OptionalIntArrayRef output_size) { |
| 10540 | |
| 10541 | static auto op = create_nested_to_padded_tensor_typed_handle(); |
| 10542 | return op.redispatch(dispatchKeySet, self, padding, output_size); |
| 10543 | } |
| 10544 | |
| 10545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_warn_in_autograd, name, "aten::_test_warn_in_autograd") |
| 10546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_warn_in_autograd, overload_name, "") |
| 10547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_warn_in_autograd, schema_str, "_test_warn_in_autograd(Tensor self) -> Tensor") |
| 10548 | |
| 10549 | // aten::_test_warn_in_autograd(Tensor self) -> Tensor |
| 10550 | static C10_NOINLINE c10::TypedOperatorHandle<_test_warn_in_autograd::schema> create__test_warn_in_autograd_typed_handle() { |
| 10551 | return c10::Dispatcher::singleton() |
| 10552 | .findSchemaOrThrow(_test_warn_in_autograd::name, _test_warn_in_autograd::overload_name) |
| 10553 | .typed<_test_warn_in_autograd::schema>(); |
| 10554 | } |
| 10555 | |
| 10556 | // aten::_test_warn_in_autograd(Tensor self) -> Tensor |
| 10557 | at::Tensor _test_warn_in_autograd::call(const at::Tensor & self) { |
| 10558 | |
| 10559 | static auto op = create__test_warn_in_autograd_typed_handle(); |
| 10560 | return op.call(self); |
| 10561 | } |
| 10562 | |
| 10563 | // aten::_test_warn_in_autograd(Tensor self) -> Tensor |
| 10564 | at::Tensor _test_warn_in_autograd::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 10565 | |
| 10566 | static auto op = create__test_warn_in_autograd_typed_handle(); |
| 10567 | return op.redispatch(dispatchKeySet, self); |
| 10568 | } |
| 10569 | |
| 10570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_view, name, "aten::_test_autograd_multiple_dispatch_view") |
| 10571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_view, overload_name, "") |
| 10572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_autograd_multiple_dispatch_view, schema_str, "_test_autograd_multiple_dispatch_view(Tensor(a) self) -> Tensor(a)") |
| 10573 | |
| 10574 | // aten::_test_autograd_multiple_dispatch_view(Tensor(a) self) -> Tensor(a) |
| 10575 | static C10_NOINLINE c10::TypedOperatorHandle<_test_autograd_multiple_dispatch_view::schema> create__test_autograd_multiple_dispatch_view_typed_handle() { |
| 10576 | return c10::Dispatcher::singleton() |
| 10577 | .findSchemaOrThrow(_test_autograd_multiple_dispatch_view::name, _test_autograd_multiple_dispatch_view::overload_name) |
| 10578 | .typed<_test_autograd_multiple_dispatch_view::schema>(); |
| 10579 | } |
| 10580 | |
| 10581 | // aten::_test_autograd_multiple_dispatch_view(Tensor(a) self) -> Tensor(a) |
| 10582 | at::Tensor _test_autograd_multiple_dispatch_view::call(const at::Tensor & self) { |
| 10583 | |
| 10584 | static auto op = create__test_autograd_multiple_dispatch_view_typed_handle(); |
| 10585 | return op.call(self); |
| 10586 | } |
| 10587 | |
| 10588 | // aten::_test_autograd_multiple_dispatch_view(Tensor(a) self) -> Tensor(a) |
| 10589 | at::Tensor _test_autograd_multiple_dispatch_view::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 10590 | |
| 10591 | static auto op = create__test_autograd_multiple_dispatch_view_typed_handle(); |
| 10592 | return op.redispatch(dispatchKeySet, self); |
| 10593 | } |
| 10594 | |
| 10595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_copy, name, "aten::diagonal_copy") |
| 10596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_copy, overload_name, "") |
| 10597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_copy, schema_str, "diagonal_copy(Tensor self, int offset=0, int dim1=0, int dim2=1) -> Tensor") |
| 10598 | |
| 10599 | // aten::diagonal_copy(Tensor self, int offset=0, int dim1=0, int dim2=1) -> Tensor |
| 10600 | static C10_NOINLINE c10::TypedOperatorHandle<diagonal_copy::schema> create_diagonal_copy_typed_handle() { |
| 10601 | return c10::Dispatcher::singleton() |
| 10602 | .findSchemaOrThrow(diagonal_copy::name, diagonal_copy::overload_name) |
| 10603 | .typed<diagonal_copy::schema>(); |
| 10604 | } |
| 10605 | |
| 10606 | // aten::diagonal_copy(Tensor self, int offset=0, int dim1=0, int dim2=1) -> Tensor |
| 10607 | at::Tensor diagonal_copy::call(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2) { |
| 10608 | |
| 10609 | static auto op = create_diagonal_copy_typed_handle(); |
| 10610 | return op.call(self, offset, dim1, dim2); |
| 10611 | } |
| 10612 | |
| 10613 | // aten::diagonal_copy(Tensor self, int offset=0, int dim1=0, int dim2=1) -> Tensor |
| 10614 | at::Tensor diagonal_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2) { |
| 10615 | |
| 10616 | static auto op = create_diagonal_copy_typed_handle(); |
| 10617 | return op.redispatch(dispatchKeySet, self, offset, dim1, dim2); |
| 10618 | } |
| 10619 | |
| 10620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(permute_copy, name, "aten::permute_copy") |
| 10621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(permute_copy, overload_name, "") |
| 10622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(permute_copy, schema_str, "permute_copy(Tensor self, int[] dims) -> Tensor") |
| 10623 | |
| 10624 | // aten::permute_copy(Tensor self, int[] dims) -> Tensor |
| 10625 | static C10_NOINLINE c10::TypedOperatorHandle<permute_copy::schema> create_permute_copy_typed_handle() { |
| 10626 | return c10::Dispatcher::singleton() |
| 10627 | .findSchemaOrThrow(permute_copy::name, permute_copy::overload_name) |
| 10628 | .typed<permute_copy::schema>(); |
| 10629 | } |
| 10630 | |
| 10631 | // aten::permute_copy(Tensor self, int[] dims) -> Tensor |
| 10632 | at::Tensor permute_copy::call(const at::Tensor & self, at::IntArrayRef dims) { |
| 10633 | |
| 10634 | static auto op = create_permute_copy_typed_handle(); |
| 10635 | return op.call(self, dims); |
| 10636 | } |
| 10637 | |
| 10638 | // aten::permute_copy(Tensor self, int[] dims) -> Tensor |
| 10639 | at::Tensor permute_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dims) { |
| 10640 | |
| 10641 | static auto op = create_permute_copy_typed_handle(); |
| 10642 | return op.redispatch(dispatchKeySet, self, dims); |
| 10643 | } |
| 10644 | |
| 10645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_copy_int, name, "aten::select_copy") |
| 10646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_copy_int, overload_name, "int") |
| 10647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_copy_int, schema_str, "select_copy.int(Tensor self, int dim, SymInt index) -> Tensor") |
| 10648 | |
| 10649 | // aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor |
| 10650 | static C10_NOINLINE c10::TypedOperatorHandle<select_copy_int::schema> create_select_copy_int_typed_handle() { |
| 10651 | return c10::Dispatcher::singleton() |
| 10652 | .findSchemaOrThrow(select_copy_int::name, select_copy_int::overload_name) |
| 10653 | .typed<select_copy_int::schema>(); |
| 10654 | } |
| 10655 | |
| 10656 | // aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor |
| 10657 | at::Tensor select_copy_int::call(const at::Tensor & self, int64_t dim, c10::SymInt index) { |
| 10658 | |
| 10659 | static auto op = create_select_copy_int_typed_handle(); |
| 10660 | return op.call(self, dim, index); |
| 10661 | } |
| 10662 | |
| 10663 | // aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor |
| 10664 | at::Tensor select_copy_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymInt index) { |
| 10665 | |
| 10666 | static auto op = create_select_copy_int_typed_handle(); |
| 10667 | return op.redispatch(dispatchKeySet, self, dim, index); |
| 10668 | } |
| 10669 | |
| 10670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_copy_Tensor, name, "aten::slice_copy") |
| 10671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_copy_Tensor, overload_name, "Tensor") |
| 10672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_copy_Tensor, schema_str, "slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor") |
| 10673 | |
| 10674 | // aten::slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor |
| 10675 | static C10_NOINLINE c10::TypedOperatorHandle<slice_copy_Tensor::schema> create_slice_copy_Tensor_typed_handle() { |
| 10676 | return c10::Dispatcher::singleton() |
| 10677 | .findSchemaOrThrow(slice_copy_Tensor::name, slice_copy_Tensor::overload_name) |
| 10678 | .typed<slice_copy_Tensor::schema>(); |
| 10679 | } |
| 10680 | |
| 10681 | // aten::slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor |
| 10682 | at::Tensor slice_copy_Tensor::call(const at::Tensor & self, int64_t dim, c10::optional<c10::SymInt> start, c10::optional<c10::SymInt> end, c10::SymInt step) { |
| 10683 | |
| 10684 | static auto op = create_slice_copy_Tensor_typed_handle(); |
| 10685 | return op.call(self, dim, start, end, step); |
| 10686 | } |
| 10687 | |
| 10688 | // aten::slice_copy.Tensor(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1) -> Tensor |
| 10689 | at::Tensor slice_copy_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<c10::SymInt> start, c10::optional<c10::SymInt> end, c10::SymInt step) { |
| 10690 | |
| 10691 | static auto op = create_slice_copy_Tensor_typed_handle(); |
| 10692 | return op.redispatch(dispatchKeySet, self, dim, start, end, step); |
| 10693 | } |
| 10694 | |
| 10695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_with_sizes_copy, name, "aten::split_with_sizes_copy") |
| 10696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_with_sizes_copy, overload_name, "") |
| 10697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_with_sizes_copy, schema_str, "split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[]") |
| 10698 | |
| 10699 | // aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] |
| 10700 | static C10_NOINLINE c10::TypedOperatorHandle<split_with_sizes_copy::schema> create_split_with_sizes_copy_typed_handle() { |
| 10701 | return c10::Dispatcher::singleton() |
| 10702 | .findSchemaOrThrow(split_with_sizes_copy::name, split_with_sizes_copy::overload_name) |
| 10703 | .typed<split_with_sizes_copy::schema>(); |
| 10704 | } |
| 10705 | |
| 10706 | // aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] |
| 10707 | ::std::vector<at::Tensor> split_with_sizes_copy::call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim) { |
| 10708 | |
| 10709 | static auto op = create_split_with_sizes_copy_typed_handle(); |
| 10710 | return op.call(self, split_sizes, dim); |
| 10711 | } |
| 10712 | |
| 10713 | // aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] |
| 10714 | ::std::vector<at::Tensor> split_with_sizes_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim) { |
| 10715 | |
| 10716 | static auto op = create_split_with_sizes_copy_typed_handle(); |
| 10717 | return op.redispatch(dispatchKeySet, self, split_sizes, dim); |
| 10718 | } |
| 10719 | |
| 10720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(t_copy, name, "aten::t_copy") |
| 10721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(t_copy, overload_name, "") |
| 10722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(t_copy, schema_str, "t_copy(Tensor self) -> Tensor") |
| 10723 | |
| 10724 | // aten::t_copy(Tensor self) -> Tensor |
| 10725 | static C10_NOINLINE c10::TypedOperatorHandle<t_copy::schema> create_t_copy_typed_handle() { |
| 10726 | return c10::Dispatcher::singleton() |
| 10727 | .findSchemaOrThrow(t_copy::name, t_copy::overload_name) |
| 10728 | .typed<t_copy::schema>(); |
| 10729 | } |
| 10730 | |
| 10731 | // aten::t_copy(Tensor self) -> Tensor |
| 10732 | at::Tensor t_copy::call(const at::Tensor & self) { |
| 10733 | |
| 10734 | static auto op = create_t_copy_typed_handle(); |
| 10735 | return op.call(self); |
| 10736 | } |
| 10737 | |
| 10738 | // aten::t_copy(Tensor self) -> Tensor |
| 10739 | at::Tensor t_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 10740 | |
| 10741 | static auto op = create_t_copy_typed_handle(); |
| 10742 | return op.redispatch(dispatchKeySet, self); |
| 10743 | } |
| 10744 | |
| 10745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices_copy, name, "aten::col_indices_copy") |
| 10746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices_copy, overload_name, "") |
| 10747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices_copy, schema_str, "col_indices_copy(Tensor self) -> Tensor") |
| 10748 | |
| 10749 | // aten::col_indices_copy(Tensor self) -> Tensor |
| 10750 | static C10_NOINLINE c10::TypedOperatorHandle<col_indices_copy::schema> create_col_indices_copy_typed_handle() { |
| 10751 | return c10::Dispatcher::singleton() |
| 10752 | .findSchemaOrThrow(col_indices_copy::name, col_indices_copy::overload_name) |
| 10753 | .typed<col_indices_copy::schema>(); |
| 10754 | } |
| 10755 | |
| 10756 | // aten::col_indices_copy(Tensor self) -> Tensor |
| 10757 | at::Tensor col_indices_copy::call(const at::Tensor & self) { |
| 10758 | |
| 10759 | static auto op = create_col_indices_copy_typed_handle(); |
| 10760 | return op.call(self); |
| 10761 | } |
| 10762 | |
| 10763 | // aten::col_indices_copy(Tensor self) -> Tensor |
| 10764 | at::Tensor col_indices_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 10765 | |
| 10766 | static auto op = create_col_indices_copy_typed_handle(); |
| 10767 | return op.redispatch(dispatchKeySet, self); |
| 10768 | } |
| 10769 | |
| 10770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_copy_int, name, "aten::unbind_copy") |
| 10771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_copy_int, overload_name, "int") |
| 10772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_copy_int, schema_str, "unbind_copy.int(Tensor self, int dim=0) -> Tensor[]") |
| 10773 | |
| 10774 | // aten::unbind_copy.int(Tensor self, int dim=0) -> Tensor[] |
| 10775 | static C10_NOINLINE c10::TypedOperatorHandle<unbind_copy_int::schema> create_unbind_copy_int_typed_handle() { |
| 10776 | return c10::Dispatcher::singleton() |
| 10777 | .findSchemaOrThrow(unbind_copy_int::name, unbind_copy_int::overload_name) |
| 10778 | .typed<unbind_copy_int::schema>(); |
| 10779 | } |
| 10780 | |
| 10781 | // aten::unbind_copy.int(Tensor self, int dim=0) -> Tensor[] |
| 10782 | ::std::vector<at::Tensor> unbind_copy_int::call(const at::Tensor & self, int64_t dim) { |
| 10783 | |
| 10784 | static auto op = create_unbind_copy_int_typed_handle(); |
| 10785 | return op.call(self, dim); |
| 10786 | } |
| 10787 | |
| 10788 | // aten::unbind_copy.int(Tensor self, int dim=0) -> Tensor[] |
| 10789 | ::std::vector<at::Tensor> unbind_copy_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim) { |
| 10790 | |
| 10791 | static auto op = create_unbind_copy_int_typed_handle(); |
| 10792 | return op.redispatch(dispatchKeySet, self, dim); |
| 10793 | } |
| 10794 | |
| 10795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_copy_int_out, name, "aten::unbind_copy") |
| 10796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_copy_int_out, overload_name, "int_out") |
| 10797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unbind_copy_int_out, schema_str, "unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> ()") |
| 10798 | |
| 10799 | // aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () |
| 10800 | static C10_NOINLINE c10::TypedOperatorHandle<unbind_copy_int_out::schema> create_unbind_copy_int_out_typed_handle() { |
| 10801 | return c10::Dispatcher::singleton() |
| 10802 | .findSchemaOrThrow(unbind_copy_int_out::name, unbind_copy_int_out::overload_name) |
| 10803 | .typed<unbind_copy_int_out::schema>(); |
| 10804 | } |
| 10805 | |
| 10806 | // aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () |
| 10807 | void unbind_copy_int_out::call(const at::Tensor & self, int64_t dim, at::TensorList out) { |
| 10808 | |
| 10809 | static auto op = create_unbind_copy_int_out_typed_handle(); |
| 10810 | return op.call(self, dim, out); |
| 10811 | } |
| 10812 | |
| 10813 | // aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () |
| 10814 | void unbind_copy_int_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::TensorList out) { |
| 10815 | |
| 10816 | static auto op = create_unbind_copy_int_out_typed_handle(); |
| 10817 | return op.redispatch(dispatchKeySet, self, dim, out); |
| 10818 | } |
| 10819 | |
| 10820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_with_sizes_copy_out, name, "aten::split_with_sizes_copy") |
| 10821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_with_sizes_copy_out, overload_name, "out") |
| 10822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(split_with_sizes_copy_out, schema_str, "split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()") |
| 10823 | |
| 10824 | // aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () |
| 10825 | static C10_NOINLINE c10::TypedOperatorHandle<split_with_sizes_copy_out::schema> create_split_with_sizes_copy_out_typed_handle() { |
| 10826 | return c10::Dispatcher::singleton() |
| 10827 | .findSchemaOrThrow(split_with_sizes_copy_out::name, split_with_sizes_copy_out::overload_name) |
| 10828 | .typed<split_with_sizes_copy_out::schema>(); |
| 10829 | } |
| 10830 | |
| 10831 | // aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () |
| 10832 | void split_with_sizes_copy_out::call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) { |
| 10833 | |
| 10834 | static auto op = create_split_with_sizes_copy_out_typed_handle(); |
| 10835 | return op.call(self, split_sizes, dim, out); |
| 10836 | } |
| 10837 | |
| 10838 | // aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () |
| 10839 | void split_with_sizes_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) { |
| 10840 | |
| 10841 | static auto op = create_split_with_sizes_copy_out_typed_handle(); |
| 10842 | return op.redispatch(dispatchKeySet, self, split_sizes, dim, out); |
| 10843 | } |
| 10844 | |
| 10845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alias_copy, name, "aten::alias_copy") |
| 10846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alias_copy, overload_name, "") |
| 10847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alias_copy, schema_str, "alias_copy(Tensor self) -> Tensor") |
| 10848 | |
| 10849 | // aten::alias_copy(Tensor self) -> Tensor |
| 10850 | static C10_NOINLINE c10::TypedOperatorHandle<alias_copy::schema> create_alias_copy_typed_handle() { |
| 10851 | return c10::Dispatcher::singleton() |
| 10852 | .findSchemaOrThrow(alias_copy::name, alias_copy::overload_name) |
| 10853 | .typed<alias_copy::schema>(); |
| 10854 | } |
| 10855 | |
| 10856 | // aten::alias_copy(Tensor self) -> Tensor |
| 10857 | at::Tensor alias_copy::call(const at::Tensor & self) { |
| 10858 | |
| 10859 | static auto op = create_alias_copy_typed_handle(); |
| 10860 | return op.call(self); |
| 10861 | } |
| 10862 | |
| 10863 | // aten::alias_copy(Tensor self) -> Tensor |
| 10864 | at::Tensor alias_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
| 10865 | |
| 10866 | static auto op = create_alias_copy_typed_handle(); |
| 10867 | return op.redispatch(dispatchKeySet, self); |
| 10868 | } |
| 10869 | |
| 10870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_scaled_dot_product_attention_math, name, "aten::_scaled_dot_product_attention_math") |
| 10871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_scaled_dot_product_attention_math, overload_name, "") |
| 10872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_scaled_dot_product_attention_math, schema_str, "_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor)") |
| 10873 | |
| 10874 | // aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor) |
| 10875 | static C10_NOINLINE c10::TypedOperatorHandle<_scaled_dot_product_attention_math::schema> create__scaled_dot_product_attention_math_typed_handle() { |
| 10876 | return c10::Dispatcher::singleton() |
| 10877 | .findSchemaOrThrow(_scaled_dot_product_attention_math::name, _scaled_dot_product_attention_math::overload_name) |
| 10878 | .typed<_scaled_dot_product_attention_math::schema>(); |
| 10879 | } |
| 10880 | |
| 10881 | // aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor) |
| 10882 | ::std::tuple<at::Tensor,at::Tensor> _scaled_dot_product_attention_math::call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const c10::optional<at::Tensor> & attn_mask, double dropout_p, bool is_causal, const c10::optional<at::Tensor> & dropout_mask) { |
| 10883 | |
| 10884 | static auto op = create__scaled_dot_product_attention_math_typed_handle(); |
| 10885 | return op.call(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask); |
| 10886 | } |
| 10887 | |
| 10888 | // aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor) |
| 10889 | ::std::tuple<at::Tensor,at::Tensor> _scaled_dot_product_attention_math::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const c10::optional<at::Tensor> & attn_mask, double dropout_p, bool is_causal, const c10::optional<at::Tensor> & dropout_mask) { |
| 10890 | |
| 10891 | static auto op = create__scaled_dot_product_attention_math_typed_handle(); |
| 10892 | return op.redispatch(dispatchKeySet, query, key, value, attn_mask, dropout_p, is_causal, dropout_mask); |
| 10893 | } |
| 10894 | |
| 10895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_scaled_dot_product_flash_attention_backward, name, "aten::_scaled_dot_product_flash_attention_backward") |
| 10896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_scaled_dot_product_flash_attention_backward, overload_name, "") |
| 10897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_scaled_dot_product_flash_attention_backward, schema_str, "_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value)") |
| 10898 | |
| 10899 | // aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) |
| 10900 | static C10_NOINLINE c10::TypedOperatorHandle<_scaled_dot_product_flash_attention_backward::schema> create__scaled_dot_product_flash_attention_backward_typed_handle() { |
| 10901 | return c10::Dispatcher::singleton() |
| 10902 | .findSchemaOrThrow(_scaled_dot_product_flash_attention_backward::name, _scaled_dot_product_flash_attention_backward::overload_name) |
| 10903 | .typed<_scaled_dot_product_flash_attention_backward::schema>(); |
| 10904 | } |
| 10905 | |
| 10906 | // aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) |
| 10907 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_flash_attention_backward::call(const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, 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, int64_t philox_seed, int64_t philox_offset) { |
| 10908 | |
| 10909 | static auto op = create__scaled_dot_product_flash_attention_backward_typed_handle(); |
| 10910 | return op.call(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); |
| 10911 | } |
| 10912 | |
| 10913 | // aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) |
| 10914 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _scaled_dot_product_flash_attention_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, const at::Tensor & out, const at::Tensor & logsumexp, 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, int64_t philox_seed, int64_t philox_offset) { |
| 10915 | |
| 10916 | static auto op = create__scaled_dot_product_flash_attention_backward_typed_handle(); |
| 10917 | return op.redispatch(dispatchKeySet, grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); |
| 10918 | } |
| 10919 | |
| 10920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_triton_scaled_dot_attention, name, "aten::_triton_scaled_dot_attention") |
| 10921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_triton_scaled_dot_attention, overload_name, "") |
| 10922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_triton_scaled_dot_attention, schema_str, "_triton_scaled_dot_attention(Tensor q, Tensor k, Tensor v, float dropout_p=0.0) -> Tensor") |
| 10923 | |
| 10924 | // aten::_triton_scaled_dot_attention(Tensor q, Tensor k, Tensor v, float dropout_p=0.0) -> Tensor |
| 10925 | static C10_NOINLINE c10::TypedOperatorHandle<_triton_scaled_dot_attention::schema> create__triton_scaled_dot_attention_typed_handle() { |
| 10926 | return c10::Dispatcher::singleton() |
| 10927 | .findSchemaOrThrow(_triton_scaled_dot_attention::name, _triton_scaled_dot_attention::overload_name) |
| 10928 | .typed<_triton_scaled_dot_attention::schema>(); |
| 10929 | } |
| 10930 | |
| 10931 | // aten::_triton_scaled_dot_attention(Tensor q, Tensor k, Tensor v, float dropout_p=0.0) -> Tensor |
| 10932 | at::Tensor _triton_scaled_dot_attention::call(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p) { |
| 10933 | |
| 10934 | static auto op = create__triton_scaled_dot_attention_typed_handle(); |
| 10935 | return op.call(q, k, v, dropout_p); |
| 10936 | } |
| 10937 | |
| 10938 | // aten::_triton_scaled_dot_attention(Tensor q, Tensor k, Tensor v, float dropout_p=0.0) -> Tensor |
| 10939 | at::Tensor _triton_scaled_dot_attention::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p) { |
| 10940 | |
| 10941 | static auto op = create__triton_scaled_dot_attention_typed_handle(); |
| 10942 | return op.redispatch(dispatchKeySet, q, k, v, dropout_p); |
| 10943 | } |
| 10944 | |
| 10945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t, name, "aten::special_chebyshev_polynomial_t") |
| 10946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t, overload_name, "") |
| 10947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t, schema_str, "special_chebyshev_polynomial_t(Tensor x, Tensor n) -> Tensor") |
| 10948 | |
| 10949 | // aten::special_chebyshev_polynomial_t(Tensor x, Tensor n) -> Tensor |
| 10950 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_t::schema> create_special_chebyshev_polynomial_t_typed_handle() { |
| 10951 | return c10::Dispatcher::singleton() |
| 10952 | .findSchemaOrThrow(special_chebyshev_polynomial_t::name, special_chebyshev_polynomial_t::overload_name) |
| 10953 | .typed<special_chebyshev_polynomial_t::schema>(); |
| 10954 | } |
| 10955 | |
| 10956 | // aten::special_chebyshev_polynomial_t(Tensor x, Tensor n) -> Tensor |
| 10957 | at::Tensor special_chebyshev_polynomial_t::call(const at::Tensor & x, const at::Tensor & n) { |
| 10958 | |
| 10959 | static auto op = create_special_chebyshev_polynomial_t_typed_handle(); |
| 10960 | return op.call(x, n); |
| 10961 | } |
| 10962 | |
| 10963 | // aten::special_chebyshev_polynomial_t(Tensor x, Tensor n) -> Tensor |
| 10964 | at::Tensor special_chebyshev_polynomial_t::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
| 10965 | |
| 10966 | static auto op = create_special_chebyshev_polynomial_t_typed_handle(); |
| 10967 | return op.redispatch(dispatchKeySet, x, n); |
| 10968 | } |
| 10969 | |
| 10970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_x_scalar, name, "aten::special_chebyshev_polynomial_t") |
| 10971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_x_scalar, overload_name, "x_scalar") |
| 10972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_x_scalar, schema_str, "special_chebyshev_polynomial_t.x_scalar(Scalar x, Tensor n) -> Tensor") |
| 10973 | |
| 10974 | // aten::special_chebyshev_polynomial_t.x_scalar(Scalar x, Tensor n) -> Tensor |
| 10975 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_t_x_scalar::schema> create_special_chebyshev_polynomial_t_x_scalar_typed_handle() { |
| 10976 | return c10::Dispatcher::singleton() |
| 10977 | .findSchemaOrThrow(special_chebyshev_polynomial_t_x_scalar::name, special_chebyshev_polynomial_t_x_scalar::overload_name) |
| 10978 | .typed<special_chebyshev_polynomial_t_x_scalar::schema>(); |
| 10979 | } |
| 10980 | |
| 10981 | // aten::special_chebyshev_polynomial_t.x_scalar(Scalar x, Tensor n) -> Tensor |
| 10982 | at::Tensor special_chebyshev_polynomial_t_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
| 10983 | |
| 10984 | static auto op = create_special_chebyshev_polynomial_t_x_scalar_typed_handle(); |
| 10985 | return op.call(x, n); |
| 10986 | } |
| 10987 | |
| 10988 | // aten::special_chebyshev_polynomial_t.x_scalar(Scalar x, Tensor n) -> Tensor |
| 10989 | at::Tensor special_chebyshev_polynomial_t_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
| 10990 | |
| 10991 | static auto op = create_special_chebyshev_polynomial_t_x_scalar_typed_handle(); |
| 10992 | return op.redispatch(dispatchKeySet, x, n); |
| 10993 | } |
| 10994 | |
| 10995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_n_scalar, name, "aten::special_chebyshev_polynomial_t") |
| 10996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_n_scalar, overload_name, "n_scalar") |
| 10997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_n_scalar, schema_str, "special_chebyshev_polynomial_t.n_scalar(Tensor x, Scalar n) -> Tensor") |
| 10998 | |
| 10999 | // aten::special_chebyshev_polynomial_t.n_scalar(Tensor x, Scalar n) -> Tensor |
| 11000 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_t_n_scalar::schema> create_special_chebyshev_polynomial_t_n_scalar_typed_handle() { |
| 11001 | return c10::Dispatcher::singleton() |
| 11002 | .findSchemaOrThrow(special_chebyshev_polynomial_t_n_scalar::name, special_chebyshev_polynomial_t_n_scalar::overload_name) |
| 11003 | .typed<special_chebyshev_polynomial_t_n_scalar::schema>(); |
| 11004 | } |
| 11005 | |
| 11006 | // aten::special_chebyshev_polynomial_t.n_scalar(Tensor x, Scalar n) -> Tensor |
| 11007 | at::Tensor special_chebyshev_polynomial_t_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
| 11008 | |
| 11009 | static auto op = create_special_chebyshev_polynomial_t_n_scalar_typed_handle(); |
| 11010 | return op.call(x, n); |
| 11011 | } |
| 11012 | |
| 11013 | // aten::special_chebyshev_polynomial_t.n_scalar(Tensor x, Scalar n) -> Tensor |
| 11014 | at::Tensor special_chebyshev_polynomial_t_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
| 11015 | |
| 11016 | static auto op = create_special_chebyshev_polynomial_t_n_scalar_typed_handle(); |
| 11017 | return op.redispatch(dispatchKeySet, x, n); |
| 11018 | } |
| 11019 | |
| 11020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_out, name, "aten::special_chebyshev_polynomial_t") |
| 11021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_out, overload_name, "out") |
| 11022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_out, schema_str, "special_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 11023 | |
| 11024 | // aten::special_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 11025 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_t_out::schema> create_special_chebyshev_polynomial_t_out_typed_handle() { |
| 11026 | return c10::Dispatcher::singleton() |
| 11027 | .findSchemaOrThrow(special_chebyshev_polynomial_t_out::name, special_chebyshev_polynomial_t_out::overload_name) |
| 11028 | .typed<special_chebyshev_polynomial_t_out::schema>(); |
| 11029 | } |
| 11030 | |
| 11031 | // aten::special_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 11032 | at::Tensor & special_chebyshev_polynomial_t_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 11033 | |
| 11034 | static auto op = create_special_chebyshev_polynomial_t_out_typed_handle(); |
| 11035 | return op.call(x, n, out); |
| 11036 | } |
| 11037 | |
| 11038 | // aten::special_chebyshev_polynomial_t.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 11039 | at::Tensor & special_chebyshev_polynomial_t_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
| 11040 | |
| 11041 | static auto op = create_special_chebyshev_polynomial_t_out_typed_handle(); |
| 11042 | return op.redispatch(dispatchKeySet, x, n, out); |
| 11043 | } |
| 11044 | |
| 11045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_x_scalar_out, name, "aten::special_chebyshev_polynomial_t") |
| 11046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_x_scalar_out, overload_name, "x_scalar_out") |
| 11047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_x_scalar_out, schema_str, "special_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)") |
| 11048 | |
| 11049 | // aten::special_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 11050 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_t_x_scalar_out::schema> create_special_chebyshev_polynomial_t_x_scalar_out_typed_handle() { |
| 11051 | return c10::Dispatcher::singleton() |
| 11052 | .findSchemaOrThrow(special_chebyshev_polynomial_t_x_scalar_out::name, special_chebyshev_polynomial_t_x_scalar_out::overload_name) |
| 11053 | .typed<special_chebyshev_polynomial_t_x_scalar_out::schema>(); |
| 11054 | } |
| 11055 | |
| 11056 | // aten::special_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 11057 | at::Tensor & special_chebyshev_polynomial_t_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 11058 | |
| 11059 | static auto op = create_special_chebyshev_polynomial_t_x_scalar_out_typed_handle(); |
| 11060 | return op.call(x, n, out); |
| 11061 | } |
| 11062 | |
| 11063 | // aten::special_chebyshev_polynomial_t.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
| 11064 | at::Tensor & special_chebyshev_polynomial_t_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
| 11065 | |
| 11066 | static auto op = create_special_chebyshev_polynomial_t_x_scalar_out_typed_handle(); |
| 11067 | return op.redispatch(dispatchKeySet, x, n, out); |
| 11068 | } |
| 11069 | |
| 11070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_n_scalar_out, name, "aten::special_chebyshev_polynomial_t") |
| 11071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_n_scalar_out, overload_name, "n_scalar_out") |
| 11072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_chebyshev_polynomial_t_n_scalar_out, schema_str, "special_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)") |
| 11073 | |
| 11074 | // aten::special_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 11075 | static C10_NOINLINE c10::TypedOperatorHandle<special_chebyshev_polynomial_t_n_scalar_out::schema> create_special_chebyshev_polynomial_t_n_scalar_out_typed_handle() { |
| 11076 | return c10::Dispatcher::singleton() |
| 11077 | .findSchemaOrThrow(special_chebyshev_polynomial_t_n_scalar_out::name, special_chebyshev_polynomial_t_n_scalar_out::overload_name) |
| 11078 | .typed<special_chebyshev_polynomial_t_n_scalar_out::schema>(); |
| 11079 | } |
| 11080 | |
| 11081 | // aten::special_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 11082 | at::Tensor & special_chebyshev_polynomial_t_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 11083 | |
| 11084 | static auto op = create_special_chebyshev_polynomial_t_n_scalar_out_typed_handle(); |
| 11085 | return op.call(x, n, out); |
| 11086 | } |
| 11087 | |
| 11088 | // aten::special_chebyshev_polynomial_t.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
| 11089 | at::Tensor & special_chebyshev_polynomial_t_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
| 11090 | |
| 11091 | static auto op = create_special_chebyshev_polynomial_t_n_scalar_out_typed_handle(); |
| 11092 | return op.redispatch(dispatchKeySet, x, n, out); |
| 11093 | } |
| 11094 | |
| 11095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k1, name, "aten::special_scaled_modified_bessel_k1") |
| 11096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k1, overload_name, "") |
| 11097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k1, schema_str, "special_scaled_modified_bessel_k1(Tensor x) -> Tensor") |
| 11098 | |
| 11099 | // aten::special_scaled_modified_bessel_k1(Tensor x) -> Tensor |
| 11100 | static C10_NOINLINE c10::TypedOperatorHandle<special_scaled_modified_bessel_k1::schema> create_special_scaled_modified_bessel_k1_typed_handle() { |
| 11101 | return c10::Dispatcher::singleton() |
| 11102 | .findSchemaOrThrow(special_scaled_modified_bessel_k1::name, special_scaled_modified_bessel_k1::overload_name) |
| 11103 | .typed<special_scaled_modified_bessel_k1::schema>(); |
| 11104 | } |
| 11105 | |
| 11106 | // aten::special_scaled_modified_bessel_k1(Tensor x) -> Tensor |
| 11107 | at::Tensor special_scaled_modified_bessel_k1::call(const at::Tensor & x) { |
| 11108 | |
| 11109 | static auto op = create_special_scaled_modified_bessel_k1_typed_handle(); |
| 11110 | return op.call(x); |
| 11111 | } |
| 11112 | |
| 11113 | // aten::special_scaled_modified_bessel_k1(Tensor x) -> Tensor |
| 11114 | at::Tensor special_scaled_modified_bessel_k1::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x) { |
| 11115 | |
| 11116 | static auto op = create_special_scaled_modified_bessel_k1_typed_handle(); |
| 11117 | return op.redispatch(dispatchKeySet, x); |
| 11118 | } |
| 11119 | |
| 11120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k1_out, name, "aten::special_scaled_modified_bessel_k1") |
| 11121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k1_out, overload_name, "out") |
| 11122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k1_out, schema_str, "special_scaled_modified_bessel_k1.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!)") |
| 11123 | |
| 11124 | // aten::special_scaled_modified_bessel_k1.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
| 11125 | static C10_NOINLINE c10::TypedOperatorHandle<special_scaled_modified_bessel_k1_out::schema> create_special_scaled_modified_bessel_k1_out_typed_handle() { |
| 11126 | return c10::Dispatcher::singleton() |
| 11127 | .findSchemaOrThrow(special_scaled_modified_bessel_k1_out::name, special_scaled_modified_bessel_k1_out::overload_name) |
| 11128 | .typed<special_scaled_modified_bessel_k1_out::schema>(); |
| 11129 | } |
| 11130 | |
| 11131 | // aten::special_scaled_modified_bessel_k1.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
| 11132 | at::Tensor & special_scaled_modified_bessel_k1_out::call(const at::Tensor & x, at::Tensor & out) { |
| 11133 | |
| 11134 | static auto op = create_special_scaled_modified_bessel_k1_out_typed_handle(); |
| 11135 | return op.call(x, out); |
| 11136 | } |
| 11137 | |
| 11138 | // aten::special_scaled_modified_bessel_k1.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
| 11139 | at::Tensor & special_scaled_modified_bessel_k1_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, at::Tensor & out) { |
| 11140 | |
| 11141 | static auto op = create_special_scaled_modified_bessel_k1_out_typed_handle(); |
| 11142 | return op.redispatch(dispatchKeySet, x, out); |
| 11143 | } |
| 11144 | |
| 11145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foobar, name, "aten::_foobar") |
| 11146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foobar, overload_name, "") |
| 11147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foobar, schema_str, "_foobar(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True) -> Tensor") |
| 11148 | |
| 11149 | // aten::_foobar(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True) -> Tensor |
| 11150 | static C10_NOINLINE c10::TypedOperatorHandle<_foobar::schema> create__foobar_typed_handle() { |
| 11151 | return c10::Dispatcher::singleton() |
| 11152 | .findSchemaOrThrow(_foobar::name, _foobar::overload_name) |
| 11153 | .typed<_foobar::schema>(); |
| 11154 | } |
| 11155 | |
| 11156 | // aten::_foobar(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True) -> Tensor |
| 11157 | at::Tensor _foobar::call(const at::Tensor & self, bool arg1, bool arg2, bool arg3) { |
| 11158 | |
| 11159 | static auto op = create__foobar_typed_handle(); |
| 11160 | return op.call(self, arg1, arg2, arg3); |
| 11161 | } |
| 11162 | |
| 11163 | // aten::_foobar(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True) -> Tensor |
| 11164 | at::Tensor _foobar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool arg1, bool arg2, bool arg3) { |
| 11165 | |
| 11166 | static auto op = create__foobar_typed_handle(); |
| 11167 | return op.redispatch(dispatchKeySet, self, arg1, arg2, arg3); |
| 11168 | } |
| 11169 | |
| 11170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_scale_out, name, "aten::_masked_scale") |
| 11171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_scale_out, overload_name, "out") |
| 11172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_scale_out, schema_str, "_masked_scale.out(Tensor self, Tensor mask, float scale, *, Tensor(a!) out) -> Tensor(a!)") |
| 11173 | |
| 11174 | // aten::_masked_scale.out(Tensor self, Tensor mask, float scale, *, Tensor(a!) out) -> Tensor(a!) |
| 11175 | static C10_NOINLINE c10::TypedOperatorHandle<_masked_scale_out::schema> create__masked_scale_out_typed_handle() { |
| 11176 | return c10::Dispatcher::singleton() |
| 11177 | .findSchemaOrThrow(_masked_scale_out::name, _masked_scale_out::overload_name) |
| 11178 | .typed<_masked_scale_out::schema>(); |
| 11179 | } |
| 11180 | |
| 11181 | // aten::_masked_scale.out(Tensor self, Tensor mask, float scale, *, Tensor(a!) out) -> Tensor(a!) |
| 11182 | at::Tensor & _masked_scale_out::call(const at::Tensor & self, const at::Tensor & mask, double scale, at::Tensor & out) { |
| 11183 | |
| 11184 | static auto op = create__masked_scale_out_typed_handle(); |
| 11185 | return op.call(self, mask, scale, out); |
| 11186 | } |
| 11187 | |
| 11188 | // aten::_masked_scale.out(Tensor self, Tensor mask, float scale, *, Tensor(a!) out) -> Tensor(a!) |
| 11189 | at::Tensor & _masked_scale_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, double scale, at::Tensor & out) { |
| 11190 | |
| 11191 | static auto op = create__masked_scale_out_typed_handle(); |
| 11192 | return op.redispatch(dispatchKeySet, self, mask, scale, out); |
| 11193 | } |
| 11194 | |
| 11195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(constant_pad_nd_out, name, "aten::constant_pad_nd") |
| 11196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(constant_pad_nd_out, overload_name, "out") |
| 11197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(constant_pad_nd_out, schema_str, "constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!)") |
| 11198 | |
| 11199 | // aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) |
| 11200 | static C10_NOINLINE c10::TypedOperatorHandle<constant_pad_nd_out::schema> create_constant_pad_nd_out_typed_handle() { |
| 11201 | return c10::Dispatcher::singleton() |
| 11202 | .findSchemaOrThrow(constant_pad_nd_out::name, constant_pad_nd_out::overload_name) |
| 11203 | .typed<constant_pad_nd_out::schema>(); |
| 11204 | } |
| 11205 | |
| 11206 | // aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) |
| 11207 | at::Tensor & constant_pad_nd_out::call(const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value, at::Tensor & out) { |
| 11208 | |
| 11209 | static auto op = create_constant_pad_nd_out_typed_handle(); |
| 11210 | return op.call(self, pad, value, out); |
| 11211 | } |
| 11212 | |
| 11213 | // aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) |
| 11214 | at::Tensor & constant_pad_nd_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef pad, const at::Scalar & value, at::Tensor & out) { |
| 11215 | |
| 11216 | static auto op = create_constant_pad_nd_out_typed_handle(); |
| 11217 | return op.redispatch(dispatchKeySet, self, pad, value, out); |
| 11218 | } |
| 11219 | |
| 11220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_out, name, "aten::convolution_backward") |
| 11221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_out, overload_name, "out") |
| 11222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_backward_out, schema_str, "convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") |
| 11223 | |
| 11224 | // aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 11225 | static C10_NOINLINE c10::TypedOperatorHandle<convolution_backward_out::schema> create_convolution_backward_out_typed_handle() { |
| 11226 | return c10::Dispatcher::singleton() |
| 11227 | .findSchemaOrThrow(convolution_backward_out::name, convolution_backward_out::overload_name) |
| 11228 | .typed<convolution_backward_out::schema>(); |
| 11229 | } |
| 11230 | |
| 11231 | // aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 11232 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> convolution_backward_out::call(const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 11233 | |
| 11234 | static auto op = create_convolution_backward_out_typed_handle(); |
| 11235 | return op.call(grad_output, input, weight, bias_sizes, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); |
| 11236 | } |
| 11237 | |
| 11238 | // aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 11239 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> convolution_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & input, const at::Tensor & weight, at::OptionalSymIntArrayRef bias_sizes, at::IntArrayRef stride, c10::SymIntArrayRef padding, at::IntArrayRef dilation, bool transposed, c10::SymIntArrayRef output_padding, int64_t groups, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 11240 | |
| 11241 | static auto op = create_convolution_backward_out_typed_handle(); |
| 11242 | return op.redispatch(dispatchKeySet, grad_output, input, weight, bias_sizes, stride, padding, dilation, transposed, output_padding, groups, output_mask, out0, out1, out2); |
| 11243 | } |
| 11244 | |
| 11245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_overrideable_out, name, "aten::convolution_overrideable") |
| 11246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_overrideable_out, overload_name, "out") |
| 11247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(convolution_overrideable_out, schema_str, "convolution_overrideable.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!)") |
| 11248 | |
| 11249 | // aten::convolution_overrideable.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11250 | static C10_NOINLINE c10::TypedOperatorHandle<convolution_overrideable_out::schema> create_convolution_overrideable_out_typed_handle() { |
| 11251 | return c10::Dispatcher::singleton() |
| 11252 | .findSchemaOrThrow(convolution_overrideable_out::name, convolution_overrideable_out::overload_name) |
| 11253 | .typed<convolution_overrideable_out::schema>(); |
| 11254 | } |
| 11255 | |
| 11256 | // aten::convolution_overrideable.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11257 | at::Tensor & convolution_overrideable_out::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, at::Tensor & out) { |
| 11258 | |
| 11259 | static auto op = create_convolution_overrideable_out_typed_handle(); |
| 11260 | return op.call(input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, out); |
| 11261 | } |
| 11262 | |
| 11263 | // aten::convolution_overrideable.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11264 | at::Tensor & convolution_overrideable_out::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, at::Tensor & out) { |
| 11265 | |
| 11266 | static auto op = create_convolution_overrideable_out_typed_handle(); |
| 11267 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, dilation, transposed, output_padding, groups, out); |
| 11268 | } |
| 11269 | |
| 11270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_copy_from_out, name, "aten::_copy_from") |
| 11271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_copy_from_out, overload_name, "out") |
| 11272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_copy_from_out, schema_str, "_copy_from.out(Tensor self, Tensor dst, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 11273 | |
| 11274 | // aten::_copy_from.out(Tensor self, Tensor dst, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11275 | static C10_NOINLINE c10::TypedOperatorHandle<_copy_from_out::schema> create__copy_from_out_typed_handle() { |
| 11276 | return c10::Dispatcher::singleton() |
| 11277 | .findSchemaOrThrow(_copy_from_out::name, _copy_from_out::overload_name) |
| 11278 | .typed<_copy_from_out::schema>(); |
| 11279 | } |
| 11280 | |
| 11281 | // aten::_copy_from.out(Tensor self, Tensor dst, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11282 | at::Tensor & _copy_from_out::call(const at::Tensor & self, const at::Tensor & dst, bool non_blocking, at::Tensor & out) { |
| 11283 | |
| 11284 | static auto op = create__copy_from_out_typed_handle(); |
| 11285 | return op.call(self, dst, non_blocking, out); |
| 11286 | } |
| 11287 | |
| 11288 | // aten::_copy_from.out(Tensor self, Tensor dst, bool non_blocking=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11289 | at::Tensor & _copy_from_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & dst, bool non_blocking, at::Tensor & out) { |
| 11290 | |
| 11291 | static auto op = create__copy_from_out_typed_handle(); |
| 11292 | return op.redispatch(dispatchKeySet, self, dst, non_blocking, out); |
| 11293 | } |
| 11294 | |
| 11295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_out, name, "aten::cudnn_batch_norm") |
| 11296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_out, overload_name, "out") |
| 11297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_batch_norm_out, schema_str, "cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))") |
| 11298 | |
| 11299 | // aten::cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
| 11300 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_batch_norm_out::schema> create_cudnn_batch_norm_out_typed_handle() { |
| 11301 | return c10::Dispatcher::singleton() |
| 11302 | .findSchemaOrThrow(cudnn_batch_norm_out::name, cudnn_batch_norm_out::overload_name) |
| 11303 | .typed<cudnn_batch_norm_out::schema>(); |
| 11304 | } |
| 11305 | |
| 11306 | // aten::cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
| 11307 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> cudnn_batch_norm_out::call(const at::Tensor & input, const 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 exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
| 11308 | |
| 11309 | static auto op = create_cudnn_batch_norm_out_typed_handle(); |
| 11310 | return op.call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2, out3); |
| 11311 | } |
| 11312 | |
| 11313 | // aten::cudnn_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
| 11314 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> cudnn_batch_norm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const 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 exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
| 11315 | |
| 11316 | static auto op = create_cudnn_batch_norm_out_typed_handle(); |
| 11317 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2, out3); |
| 11318 | } |
| 11319 | |
| 11320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mps_convolution_transpose_out, name, "aten::_mps_convolution_transpose") |
| 11321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mps_convolution_transpose_out, overload_name, "out") |
| 11322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mps_convolution_transpose_out, schema_str, "_mps_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!)") |
| 11323 | |
| 11324 | // aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11325 | static C10_NOINLINE c10::TypedOperatorHandle<_mps_convolution_transpose_out::schema> create__mps_convolution_transpose_out_typed_handle() { |
| 11326 | return c10::Dispatcher::singleton() |
| 11327 | .findSchemaOrThrow(_mps_convolution_transpose_out::name, _mps_convolution_transpose_out::overload_name) |
| 11328 | .typed<_mps_convolution_transpose_out::schema>(); |
| 11329 | } |
| 11330 | |
| 11331 | // aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11332 | at::Tensor & _mps_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, at::Tensor & out) { |
| 11333 | |
| 11334 | static auto op = create__mps_convolution_transpose_out_typed_handle(); |
| 11335 | return op.call(self, weight, padding, output_padding, stride, dilation, groups, out); |
| 11336 | } |
| 11337 | |
| 11338 | // aten::_mps_convolution_transpose.out(Tensor self, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11339 | at::Tensor & _mps_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, at::Tensor & out) { |
| 11340 | |
| 11341 | static auto op = create__mps_convolution_transpose_out_typed_handle(); |
| 11342 | return op.redispatch(dispatchKeySet, self, weight, padding, output_padding, stride, dilation, groups, out); |
| 11343 | } |
| 11344 | |
| 11345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_transpose_backward_out, name, "aten::mps_convolution_transpose_backward") |
| 11346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_transpose_backward_out, overload_name, "out") |
| 11347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_transpose_backward_out, schema_str, "mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 11348 | |
| 11349 | // aten::mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 11350 | static C10_NOINLINE c10::TypedOperatorHandle<mps_convolution_transpose_backward_out::schema> create_mps_convolution_transpose_backward_out_typed_handle() { |
| 11351 | return c10::Dispatcher::singleton() |
| 11352 | .findSchemaOrThrow(mps_convolution_transpose_backward_out::name, mps_convolution_transpose_backward_out::overload_name) |
| 11353 | .typed<mps_convolution_transpose_backward_out::schema>(); |
| 11354 | } |
| 11355 | |
| 11356 | // aten::mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 11357 | ::std::tuple<at::Tensor &,at::Tensor &> mps_convolution_transpose_backward_out::call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1) { |
| 11358 | |
| 11359 | static auto op = create_mps_convolution_transpose_backward_out_typed_handle(); |
| 11360 | return op.call(self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask, out0, out1); |
| 11361 | } |
| 11362 | |
| 11363 | // aten::mps_convolution_transpose_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool[2] output_mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 11364 | ::std::tuple<at::Tensor &,at::Tensor &> mps_convolution_transpose_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,2> output_mask, at::Tensor & out0, at::Tensor & out1) { |
| 11365 | |
| 11366 | static auto op = create_mps_convolution_transpose_backward_out_typed_handle(); |
| 11367 | return op.redispatch(dispatchKeySet, self, grad_output, weight, padding, output_padding, stride, dilation, groups, output_mask, out0, out1); |
| 11368 | } |
| 11369 | |
| 11370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_out, name, "aten::embedding") |
| 11371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_out, overload_name, "out") |
| 11372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_out, schema_str, "embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 11373 | |
| 11374 | // aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11375 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_out::schema> create_embedding_out_typed_handle() { |
| 11376 | return c10::Dispatcher::singleton() |
| 11377 | .findSchemaOrThrow(embedding_out::name, embedding_out::overload_name) |
| 11378 | .typed<embedding_out::schema>(); |
| 11379 | } |
| 11380 | |
| 11381 | // aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11382 | at::Tensor & embedding_out::call(const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse, at::Tensor & out) { |
| 11383 | |
| 11384 | static auto op = create_embedding_out_typed_handle(); |
| 11385 | return op.call(weight, indices, padding_idx, scale_grad_by_freq, sparse, out); |
| 11386 | } |
| 11387 | |
| 11388 | // aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11389 | at::Tensor & embedding_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & weight, const at::Tensor & indices, c10::SymInt padding_idx, bool scale_grad_by_freq, bool sparse, at::Tensor & out) { |
| 11390 | |
| 11391 | static auto op = create_embedding_out_typed_handle(); |
| 11392 | return op.redispatch(dispatchKeySet, weight, indices, padding_idx, scale_grad_by_freq, sparse, out); |
| 11393 | } |
| 11394 | |
| 11395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_dense_backward_out, name, "aten::_embedding_bag_dense_backward") |
| 11396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_dense_backward_out, overload_name, "out") |
| 11397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_dense_backward_out, schema_str, "_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!)") |
| 11398 | |
| 11399 | // aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) |
| 11400 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag_dense_backward_out::schema> create__embedding_bag_dense_backward_out_typed_handle() { |
| 11401 | return c10::Dispatcher::singleton() |
| 11402 | .findSchemaOrThrow(_embedding_bag_dense_backward_out::name, _embedding_bag_dense_backward_out::overload_name) |
| 11403 | .typed<_embedding_bag_dense_backward_out::schema>(); |
| 11404 | } |
| 11405 | |
| 11406 | // aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) |
| 11407 | at::Tensor & _embedding_bag_dense_backward_out::call(const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx, at::Tensor & out) { |
| 11408 | |
| 11409 | static auto op = create__embedding_bag_dense_backward_out_typed_handle(); |
| 11410 | return op.call(grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); |
| 11411 | } |
| 11412 | |
| 11413 | // aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) |
| 11414 | at::Tensor & _embedding_bag_dense_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, const at::Tensor & offset2bag, const at::Tensor & bag_size, const at::Tensor & maximum_indices, c10::SymInt num_weights, bool scale_grad_by_freq, int64_t mode, const c10::optional<at::Tensor> & per_sample_weights, int64_t padding_idx, at::Tensor & out) { |
| 11415 | |
| 11416 | static auto op = create__embedding_bag_dense_backward_out_typed_handle(); |
| 11417 | return op.redispatch(dispatchKeySet, grad, indices, offset2bag, bag_size, maximum_indices, num_weights, scale_grad_by_freq, mode, per_sample_weights, padding_idx, out); |
| 11418 | } |
| 11419 | |
| 11420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize_out, name, "aten::resize") |
| 11421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize_out, overload_name, "out") |
| 11422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize_out, schema_str, "resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)") |
| 11423 | |
| 11424 | // aten::resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 11425 | static C10_NOINLINE c10::TypedOperatorHandle<resize_out::schema> create_resize_out_typed_handle() { |
| 11426 | return c10::Dispatcher::singleton() |
| 11427 | .findSchemaOrThrow(resize_out::name, resize_out::overload_name) |
| 11428 | .typed<resize_out::schema>(); |
| 11429 | } |
| 11430 | |
| 11431 | // aten::resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 11432 | const at::Tensor & resize_out::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format, const at::Tensor & out) { |
| 11433 | |
| 11434 | static auto op = create_resize_out_typed_handle(); |
| 11435 | return op.call(self, size, memory_format, out); |
| 11436 | } |
| 11437 | |
| 11438 | // aten::resize.out(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 11439 | const at::Tensor & resize_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format, const at::Tensor & out) { |
| 11440 | |
| 11441 | static auto op = create_resize_out_typed_handle(); |
| 11442 | return op.redispatch(dispatchKeySet, self, size, memory_format, out); |
| 11443 | } |
| 11444 | |
| 11445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize, name, "aten::resize") |
| 11446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize, overload_name, "") |
| 11447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(resize, schema_str, "resize(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor") |
| 11448 | |
| 11449 | // aten::resize(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor |
| 11450 | static C10_NOINLINE c10::TypedOperatorHandle<resize::schema> create_resize_typed_handle() { |
| 11451 | return c10::Dispatcher::singleton() |
| 11452 | .findSchemaOrThrow(resize::name, resize::overload_name) |
| 11453 | .typed<resize::schema>(); |
| 11454 | } |
| 11455 | |
| 11456 | // aten::resize(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor |
| 11457 | at::Tensor resize::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format) { |
| 11458 | |
| 11459 | static auto op = create_resize_typed_handle(); |
| 11460 | return op.call(self, size, memory_format); |
| 11461 | } |
| 11462 | |
| 11463 | // aten::resize(Tensor self, SymInt[] size, *, MemoryFormat? memory_format=None) -> Tensor |
| 11464 | at::Tensor resize::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format) { |
| 11465 | |
| 11466 | static auto op = create_resize_typed_handle(); |
| 11467 | return op.redispatch(dispatchKeySet, self, size, memory_format); |
| 11468 | } |
| 11469 | |
| 11470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_names_out, name, "aten::full") |
| 11471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_names_out, overload_name, "names_out") |
| 11472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_names_out, schema_str, "full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)") |
| 11473 | |
| 11474 | // aten::full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 11475 | static C10_NOINLINE c10::TypedOperatorHandle<full_names_out::schema> create_full_names_out_typed_handle() { |
| 11476 | return c10::Dispatcher::singleton() |
| 11477 | .findSchemaOrThrow(full_names_out::name, full_names_out::overload_name) |
| 11478 | .typed<full_names_out::schema>(); |
| 11479 | } |
| 11480 | |
| 11481 | // aten::full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 11482 | at::Tensor & full_names_out::call(at::IntArrayRef size, const at::Scalar & fill_value, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 11483 | |
| 11484 | static auto op = create_full_names_out_typed_handle(); |
| 11485 | return op.call(size, fill_value, names, out); |
| 11486 | } |
| 11487 | |
| 11488 | // aten::full.names_out(int[] size, Scalar fill_value, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
| 11489 | at::Tensor & full_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Scalar & fill_value, c10::optional<at::DimnameList> names, at::Tensor & out) { |
| 11490 | |
| 11491 | static auto op = create_full_names_out_typed_handle(); |
| 11492 | return op.redispatch(dispatchKeySet, size, fill_value, names, out); |
| 11493 | } |
| 11494 | |
| 11495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_like_out, name, "aten::full_like") |
| 11496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_like_out, overload_name, "out") |
| 11497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(full_like_out, schema_str, "full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)") |
| 11498 | |
| 11499 | // aten::full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 11500 | static C10_NOINLINE c10::TypedOperatorHandle<full_like_out::schema> create_full_like_out_typed_handle() { |
| 11501 | return c10::Dispatcher::singleton() |
| 11502 | .findSchemaOrThrow(full_like_out::name, full_like_out::overload_name) |
| 11503 | .typed<full_like_out::schema>(); |
| 11504 | } |
| 11505 | |
| 11506 | // aten::full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 11507 | at::Tensor & full_like_out::call(const at::Tensor & self, const at::Scalar & fill_value, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
| 11508 | |
| 11509 | static auto op = create_full_like_out_typed_handle(); |
| 11510 | return op.call(self, fill_value, memory_format, out); |
| 11511 | } |
| 11512 | |
| 11513 | // aten::full_like.out(Tensor self, Scalar fill_value, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
| 11514 | at::Tensor & full_like_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & fill_value, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
| 11515 | |
| 11516 | static auto op = create_full_like_out_typed_handle(); |
| 11517 | return op.redispatch(dispatchKeySet, self, fill_value, memory_format, out); |
| 11518 | } |
| 11519 | |
| 11520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_out, name, "aten::grid_sampler_2d") |
| 11521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_out, overload_name, "out") |
| 11522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(grid_sampler_2d_out, schema_str, "grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!)") |
| 11523 | |
| 11524 | // aten::grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) |
| 11525 | static C10_NOINLINE c10::TypedOperatorHandle<grid_sampler_2d_out::schema> create_grid_sampler_2d_out_typed_handle() { |
| 11526 | return c10::Dispatcher::singleton() |
| 11527 | .findSchemaOrThrow(grid_sampler_2d_out::name, grid_sampler_2d_out::overload_name) |
| 11528 | .typed<grid_sampler_2d_out::schema>(); |
| 11529 | } |
| 11530 | |
| 11531 | // aten::grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) |
| 11532 | at::Tensor & grid_sampler_2d_out::call(const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out) { |
| 11533 | |
| 11534 | static auto op = create_grid_sampler_2d_out_typed_handle(); |
| 11535 | return op.call(input, grid, interpolation_mode, padding_mode, align_corners, out); |
| 11536 | } |
| 11537 | |
| 11538 | // aten::grid_sampler_2d.out(Tensor input, Tensor grid, int interpolation_mode, int padding_mode, bool align_corners, *, Tensor(a!) out) -> Tensor(a!) |
| 11539 | at::Tensor & grid_sampler_2d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & grid, int64_t interpolation_mode, int64_t padding_mode, bool align_corners, at::Tensor & out) { |
| 11540 | |
| 11541 | static auto op = create_grid_sampler_2d_out_typed_handle(); |
| 11542 | return op.redispatch(dispatchKeySet, input, grid, interpolation_mode, padding_mode, align_corners, out); |
| 11543 | } |
| 11544 | |
| 11545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_out, name, "aten::kaiser_window") |
| 11546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_out, overload_name, "out") |
| 11547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_out, schema_str, "kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!)") |
| 11548 | |
| 11549 | // aten::kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) |
| 11550 | static C10_NOINLINE c10::TypedOperatorHandle<kaiser_window_out::schema> create_kaiser_window_out_typed_handle() { |
| 11551 | return c10::Dispatcher::singleton() |
| 11552 | .findSchemaOrThrow(kaiser_window_out::name, kaiser_window_out::overload_name) |
| 11553 | .typed<kaiser_window_out::schema>(); |
| 11554 | } |
| 11555 | |
| 11556 | // aten::kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) |
| 11557 | at::Tensor & kaiser_window_out::call(int64_t window_length, at::Tensor & out) { |
| 11558 | |
| 11559 | static auto op = create_kaiser_window_out_typed_handle(); |
| 11560 | return op.call(window_length, out); |
| 11561 | } |
| 11562 | |
| 11563 | // aten::kaiser_window.out(int window_length, *, Tensor(a!) out) -> Tensor(a!) |
| 11564 | at::Tensor & kaiser_window_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, at::Tensor & out) { |
| 11565 | |
| 11566 | static auto op = create_kaiser_window_out_typed_handle(); |
| 11567 | return op.redispatch(dispatchKeySet, window_length, out); |
| 11568 | } |
| 11569 | |
| 11570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_periodic_out, name, "aten::kaiser_window") |
| 11571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_periodic_out, overload_name, "periodic_out") |
| 11572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_periodic_out, schema_str, "kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!)") |
| 11573 | |
| 11574 | // aten::kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) |
| 11575 | static C10_NOINLINE c10::TypedOperatorHandle<kaiser_window_periodic_out::schema> create_kaiser_window_periodic_out_typed_handle() { |
| 11576 | return c10::Dispatcher::singleton() |
| 11577 | .findSchemaOrThrow(kaiser_window_periodic_out::name, kaiser_window_periodic_out::overload_name) |
| 11578 | .typed<kaiser_window_periodic_out::schema>(); |
| 11579 | } |
| 11580 | |
| 11581 | // aten::kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) |
| 11582 | at::Tensor & kaiser_window_periodic_out::call(int64_t window_length, bool periodic, at::Tensor & out) { |
| 11583 | |
| 11584 | static auto op = create_kaiser_window_periodic_out_typed_handle(); |
| 11585 | return op.call(window_length, periodic, out); |
| 11586 | } |
| 11587 | |
| 11588 | // aten::kaiser_window.periodic_out(int window_length, bool periodic, *, Tensor(a!) out) -> Tensor(a!) |
| 11589 | at::Tensor & kaiser_window_periodic_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, at::Tensor & out) { |
| 11590 | |
| 11591 | static auto op = create_kaiser_window_periodic_out_typed_handle(); |
| 11592 | return op.redispatch(dispatchKeySet, window_length, periodic, out); |
| 11593 | } |
| 11594 | |
| 11595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_beta_out, name, "aten::kaiser_window") |
| 11596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_beta_out, overload_name, "beta_out") |
| 11597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(kaiser_window_beta_out, schema_str, "kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!)") |
| 11598 | |
| 11599 | // aten::kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!) |
| 11600 | static C10_NOINLINE c10::TypedOperatorHandle<kaiser_window_beta_out::schema> create_kaiser_window_beta_out_typed_handle() { |
| 11601 | return c10::Dispatcher::singleton() |
| 11602 | .findSchemaOrThrow(kaiser_window_beta_out::name, kaiser_window_beta_out::overload_name) |
| 11603 | .typed<kaiser_window_beta_out::schema>(); |
| 11604 | } |
| 11605 | |
| 11606 | // aten::kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!) |
| 11607 | at::Tensor & kaiser_window_beta_out::call(int64_t window_length, bool periodic, double beta, at::Tensor & out) { |
| 11608 | |
| 11609 | static auto op = create_kaiser_window_beta_out_typed_handle(); |
| 11610 | return op.call(window_length, periodic, beta, out); |
| 11611 | } |
| 11612 | |
| 11613 | // aten::kaiser_window.beta_out(int window_length, bool periodic, float beta, *, Tensor(a!) out) -> Tensor(a!) |
| 11614 | at::Tensor & kaiser_window_beta_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t window_length, bool periodic, double beta, at::Tensor & out) { |
| 11615 | |
| 11616 | static auto op = create_kaiser_window_beta_out_typed_handle(); |
| 11617 | return op.redispatch(dispatchKeySet, window_length, periodic, beta, out); |
| 11618 | } |
| 11619 | |
| 11620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put_out, name, "aten::index_put") |
| 11621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put_out, overload_name, "out") |
| 11622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(index_put_out, schema_str, "index_put.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 11623 | |
| 11624 | // aten::index_put.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11625 | static C10_NOINLINE c10::TypedOperatorHandle<index_put_out::schema> create_index_put_out_typed_handle() { |
| 11626 | return c10::Dispatcher::singleton() |
| 11627 | .findSchemaOrThrow(index_put_out::name, index_put_out::overload_name) |
| 11628 | .typed<index_put_out::schema>(); |
| 11629 | } |
| 11630 | |
| 11631 | // aten::index_put.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11632 | at::Tensor & index_put_out::call(const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, at::Tensor & out) { |
| 11633 | |
| 11634 | static auto op = create_index_put_out_typed_handle(); |
| 11635 | return op.call(self, indices, values, accumulate, out); |
| 11636 | } |
| 11637 | |
| 11638 | // aten::index_put.out(Tensor self, Tensor?[] indices, Tensor values, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11639 | at::Tensor & index_put_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::List<c10::optional<at::Tensor>> & indices, const at::Tensor & values, bool accumulate, at::Tensor & out) { |
| 11640 | |
| 11641 | static auto op = create_index_put_out_typed_handle(); |
| 11642 | return op.redispatch(dispatchKeySet, self, indices, values, accumulate, out); |
| 11643 | } |
| 11644 | |
| 11645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_backward_out, name, "aten::matmul_backward") |
| 11646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_backward_out, overload_name, "out") |
| 11647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matmul_backward_out, schema_str, "matmul_backward.out(Tensor grad, Tensor self, Tensor other, bool[2] mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))") |
| 11648 | |
| 11649 | // aten::matmul_backward.out(Tensor grad, Tensor self, Tensor other, bool[2] mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 11650 | static C10_NOINLINE c10::TypedOperatorHandle<matmul_backward_out::schema> create_matmul_backward_out_typed_handle() { |
| 11651 | return c10::Dispatcher::singleton() |
| 11652 | .findSchemaOrThrow(matmul_backward_out::name, matmul_backward_out::overload_name) |
| 11653 | .typed<matmul_backward_out::schema>(); |
| 11654 | } |
| 11655 | |
| 11656 | // aten::matmul_backward.out(Tensor grad, Tensor self, Tensor other, bool[2] mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 11657 | ::std::tuple<at::Tensor &,at::Tensor &> matmul_backward_out::call(const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array<bool,2> mask, at::Tensor & out0, at::Tensor & out1) { |
| 11658 | |
| 11659 | static auto op = create_matmul_backward_out_typed_handle(); |
| 11660 | return op.call(grad, self, other, mask, out0, out1); |
| 11661 | } |
| 11662 | |
| 11663 | // aten::matmul_backward.out(Tensor grad, Tensor self, Tensor other, bool[2] mask, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
| 11664 | ::std::tuple<at::Tensor &,at::Tensor &> matmul_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, const at::Tensor & other, ::std::array<bool,2> mask, at::Tensor & out0, at::Tensor & out1) { |
| 11665 | |
| 11666 | static auto op = create_matmul_backward_out_typed_handle(); |
| 11667 | return op.redispatch(dispatchKeySet, grad, self, other, mask, out0, out1); |
| 11668 | } |
| 11669 | |
| 11670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool2d_backward_out, name, "aten::mkldnn_max_pool2d_backward") |
| 11671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool2d_backward_out, overload_name, "out") |
| 11672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool2d_backward_out, schema_str, "mkldnn_max_pool2d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)") |
| 11673 | |
| 11674 | // aten::mkldnn_max_pool2d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11675 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_max_pool2d_backward_out::schema> create_mkldnn_max_pool2d_backward_out_typed_handle() { |
| 11676 | return c10::Dispatcher::singleton() |
| 11677 | .findSchemaOrThrow(mkldnn_max_pool2d_backward_out::name, mkldnn_max_pool2d_backward_out::overload_name) |
| 11678 | .typed<mkldnn_max_pool2d_backward_out::schema>(); |
| 11679 | } |
| 11680 | |
| 11681 | // aten::mkldnn_max_pool2d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11682 | at::Tensor & mkldnn_max_pool2d_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) { |
| 11683 | |
| 11684 | static auto op = create_mkldnn_max_pool2d_backward_out_typed_handle(); |
| 11685 | return op.call(grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); |
| 11686 | } |
| 11687 | |
| 11688 | // aten::mkldnn_max_pool2d_backward.out(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
| 11689 | at::Tensor & mkldnn_max_pool2d_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) { |
| 11690 | |
| 11691 | static auto op = create_mkldnn_max_pool2d_backward_out_typed_handle(); |
| 11692 | return op.redispatch(dispatchKeySet, grad_output, output, input, kernel_size, stride, padding, dilation, ceil_mode, out); |
| 11693 | } |
| 11694 | |
| 11695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_out, name, "aten::median") |
| 11696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_out, overload_name, "out") |
| 11697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(median_out, schema_str, "median.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 11698 | |
| 11699 | // aten::median.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11700 | static C10_NOINLINE c10::TypedOperatorHandle<median_out::schema> create_median_out_typed_handle() { |
| 11701 | return c10::Dispatcher::singleton() |
| 11702 | .findSchemaOrThrow(median_out::name, median_out::overload_name) |
| 11703 | .typed<median_out::schema>(); |
| 11704 | } |
| 11705 | |
| 11706 | // aten::median.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11707 | at::Tensor & median_out::call(const at::Tensor & self, at::Tensor & out) { |
| 11708 | |
| 11709 | static auto op = create_median_out_typed_handle(); |
| 11710 | return op.call(self, out); |
| 11711 | } |
| 11712 | |
| 11713 | // aten::median.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11714 | at::Tensor & median_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 11715 | |
| 11716 | static auto op = create_median_out_typed_handle(); |
| 11717 | return op.redispatch(dispatchKeySet, self, out); |
| 11718 | } |
| 11719 | |
| 11720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_out, name, "aten::nanmedian") |
| 11721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_out, overload_name, "out") |
| 11722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nanmedian_out, schema_str, "nanmedian.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 11723 | |
| 11724 | // aten::nanmedian.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11725 | static C10_NOINLINE c10::TypedOperatorHandle<nanmedian_out::schema> create_nanmedian_out_typed_handle() { |
| 11726 | return c10::Dispatcher::singleton() |
| 11727 | .findSchemaOrThrow(nanmedian_out::name, nanmedian_out::overload_name) |
| 11728 | .typed<nanmedian_out::schema>(); |
| 11729 | } |
| 11730 | |
| 11731 | // aten::nanmedian.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11732 | at::Tensor & nanmedian_out::call(const at::Tensor & self, at::Tensor & out) { |
| 11733 | |
| 11734 | static auto op = create_nanmedian_out_typed_handle(); |
| 11735 | return op.call(self, out); |
| 11736 | } |
| 11737 | |
| 11738 | // aten::nanmedian.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11739 | at::Tensor & nanmedian_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 11740 | |
| 11741 | static auto op = create_nanmedian_out_typed_handle(); |
| 11742 | return op.redispatch(dispatchKeySet, self, out); |
| 11743 | } |
| 11744 | |
| 11745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_out, name, "aten::miopen_batch_norm") |
| 11746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_out, overload_name, "out") |
| 11747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_batch_norm_out, schema_str, "miopen_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") |
| 11748 | |
| 11749 | // aten::miopen_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 11750 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_batch_norm_out::schema> create_miopen_batch_norm_out_typed_handle() { |
| 11751 | return c10::Dispatcher::singleton() |
| 11752 | .findSchemaOrThrow(miopen_batch_norm_out::name, miopen_batch_norm_out::overload_name) |
| 11753 | .typed<miopen_batch_norm_out::schema>(); |
| 11754 | } |
| 11755 | |
| 11756 | // aten::miopen_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 11757 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> miopen_batch_norm_out::call(const at::Tensor & input, const 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 exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 11758 | |
| 11759 | static auto op = create_miopen_batch_norm_out_typed_handle(); |
| 11760 | return op.call(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2); |
| 11761 | } |
| 11762 | |
| 11763 | // aten::miopen_batch_norm.out(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 11764 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> miopen_batch_norm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const 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 exponential_average_factor, double epsilon, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 11765 | |
| 11766 | static auto op = create_miopen_batch_norm_out_typed_handle(); |
| 11767 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon, out0, out1, out2); |
| 11768 | } |
| 11769 | |
| 11770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_transpose_out, name, "aten::miopen_convolution_transpose") |
| 11771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_transpose_out, overload_name, "out") |
| 11772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_transpose_out, schema_str, "miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!)") |
| 11773 | |
| 11774 | // aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) |
| 11775 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_convolution_transpose_out::schema> create_miopen_convolution_transpose_out_typed_handle() { |
| 11776 | return c10::Dispatcher::singleton() |
| 11777 | .findSchemaOrThrow(miopen_convolution_transpose_out::name, miopen_convolution_transpose_out::overload_name) |
| 11778 | .typed<miopen_convolution_transpose_out::schema>(); |
| 11779 | } |
| 11780 | |
| 11781 | // aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) |
| 11782 | at::Tensor & miopen_convolution_transpose_out::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { |
| 11783 | |
| 11784 | static auto op = create_miopen_convolution_transpose_out_typed_handle(); |
| 11785 | return op.call(self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); |
| 11786 | } |
| 11787 | |
| 11788 | // aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) |
| 11789 | at::Tensor & miopen_convolution_transpose_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, c10::SymIntArrayRef output_padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { |
| 11790 | |
| 11791 | static auto op = create_miopen_convolution_transpose_out_typed_handle(); |
| 11792 | return op.redispatch(dispatchKeySet, self, weight, bias, padding, output_padding, stride, dilation, groups, benchmark, deterministic, out); |
| 11793 | } |
| 11794 | |
| 11795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_backward_out, name, "aten::miopen_rnn_backward") |
| 11796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_backward_out, overload_name, "out") |
| 11797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_backward_out, schema_str, "miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> ()") |
| 11798 | |
| 11799 | // aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () |
| 11800 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_rnn_backward_out::schema> create_miopen_rnn_backward_out_typed_handle() { |
| 11801 | return c10::Dispatcher::singleton() |
| 11802 | .findSchemaOrThrow(miopen_rnn_backward_out::name, miopen_rnn_backward_out::overload_name) |
| 11803 | .typed<miopen_rnn_backward_out::schema>(); |
| 11804 | } |
| 11805 | |
| 11806 | // aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () |
| 11807 | void miopen_rnn_backward_out::call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, const at::Tensor & output, const c10::optional<at::Tensor> & grad_output, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state, const at::Tensor & reserve, ::std::array<bool,4> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { |
| 11808 | |
| 11809 | static auto op = create_miopen_rnn_backward_out_typed_handle(); |
| 11810 | return op.call(input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); |
| 11811 | } |
| 11812 | |
| 11813 | // aten::miopen_rnn_backward.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor weight_buf, Tensor hx, Tensor? cx, Tensor output, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, Tensor reserve, bool[4] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!)[] out3) -> () |
| 11814 | void miopen_rnn_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & weight_buf, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, const at::Tensor & output, const c10::optional<at::Tensor> & grad_output, const c10::optional<at::Tensor> & grad_hy, const c10::optional<at::Tensor> & grad_cy, int64_t mode, int64_t hidden_size, int64_t num_layers, bool batch_first, double dropout, bool train, bool bidirectional, at::IntArrayRef batch_sizes, const c10::optional<at::Tensor> & dropout_state, const at::Tensor & reserve, ::std::array<bool,4> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::TensorList out3) { |
| 11815 | |
| 11816 | static auto op = create_miopen_rnn_backward_out_typed_handle(); |
| 11817 | return op.redispatch(dispatchKeySet, input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask, out0, out1, out2, out3); |
| 11818 | } |
| 11819 | |
| 11820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(channel_shuffle_out, name, "aten::channel_shuffle") |
| 11821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(channel_shuffle_out, overload_name, "out") |
| 11822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(channel_shuffle_out, schema_str, "channel_shuffle.out(Tensor self, int groups, *, Tensor(a!) out) -> Tensor(a!)") |
| 11823 | |
| 11824 | // aten::channel_shuffle.out(Tensor self, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11825 | static C10_NOINLINE c10::TypedOperatorHandle<channel_shuffle_out::schema> create_channel_shuffle_out_typed_handle() { |
| 11826 | return c10::Dispatcher::singleton() |
| 11827 | .findSchemaOrThrow(channel_shuffle_out::name, channel_shuffle_out::overload_name) |
| 11828 | .typed<channel_shuffle_out::schema>(); |
| 11829 | } |
| 11830 | |
| 11831 | // aten::channel_shuffle.out(Tensor self, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11832 | at::Tensor & channel_shuffle_out::call(const at::Tensor & self, int64_t groups, at::Tensor & out) { |
| 11833 | |
| 11834 | static auto op = create_channel_shuffle_out_typed_handle(); |
| 11835 | return op.call(self, groups, out); |
| 11836 | } |
| 11837 | |
| 11838 | // aten::channel_shuffle.out(Tensor self, int groups, *, Tensor(a!) out) -> Tensor(a!) |
| 11839 | at::Tensor & channel_shuffle_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t groups, at::Tensor & out) { |
| 11840 | |
| 11841 | static auto op = create_channel_shuffle_out_typed_handle(); |
| 11842 | return op.redispatch(dispatchKeySet, self, groups, out); |
| 11843 | } |
| 11844 | |
| 11845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu_out, name, "aten::relu") |
| 11846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu_out, overload_name, "out") |
| 11847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(relu_out, schema_str, "relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 11848 | |
| 11849 | // aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11850 | static C10_NOINLINE c10::TypedOperatorHandle<relu_out::schema> create_relu_out_typed_handle() { |
| 11851 | return c10::Dispatcher::singleton() |
| 11852 | .findSchemaOrThrow(relu_out::name, relu_out::overload_name) |
| 11853 | .typed<relu_out::schema>(); |
| 11854 | } |
| 11855 | |
| 11856 | // aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11857 | at::Tensor & relu_out::call(const at::Tensor & self, at::Tensor & out) { |
| 11858 | |
| 11859 | static auto op = create_relu_out_typed_handle(); |
| 11860 | return op.call(self, out); |
| 11861 | } |
| 11862 | |
| 11863 | // aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11864 | at::Tensor & relu_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 11865 | |
| 11866 | static auto op = create_relu_out_typed_handle(); |
| 11867 | return op.redispatch(dispatchKeySet, self, out); |
| 11868 | } |
| 11869 | |
| 11870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_scatter_out, name, "aten::select_scatter") |
| 11871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_scatter_out, overload_name, "out") |
| 11872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_scatter_out, schema_str, "select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!)") |
| 11873 | |
| 11874 | // aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) |
| 11875 | static C10_NOINLINE c10::TypedOperatorHandle<select_scatter_out::schema> create_select_scatter_out_typed_handle() { |
| 11876 | return c10::Dispatcher::singleton() |
| 11877 | .findSchemaOrThrow(select_scatter_out::name, select_scatter_out::overload_name) |
| 11878 | .typed<select_scatter_out::schema>(); |
| 11879 | } |
| 11880 | |
| 11881 | // aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) |
| 11882 | at::Tensor & select_scatter_out::call(const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index, at::Tensor & out) { |
| 11883 | |
| 11884 | static auto op = create_select_scatter_out_typed_handle(); |
| 11885 | return op.call(self, src, dim, index, out); |
| 11886 | } |
| 11887 | |
| 11888 | // aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) |
| 11889 | at::Tensor & select_scatter_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & src, int64_t dim, c10::SymInt index, at::Tensor & out) { |
| 11890 | |
| 11891 | static auto op = create_select_scatter_out_typed_handle(); |
| 11892 | return op.redispatch(dispatchKeySet, self, src, dim, index, out); |
| 11893 | } |
| 11894 | |
| 11895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_split_with_sizes_out, name, "aten::unsafe_split_with_sizes") |
| 11896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_split_with_sizes_out, overload_name, "out") |
| 11897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_split_with_sizes_out, schema_str, "unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> ()") |
| 11898 | |
| 11899 | // aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () |
| 11900 | static C10_NOINLINE c10::TypedOperatorHandle<unsafe_split_with_sizes_out::schema> create_unsafe_split_with_sizes_out_typed_handle() { |
| 11901 | return c10::Dispatcher::singleton() |
| 11902 | .findSchemaOrThrow(unsafe_split_with_sizes_out::name, unsafe_split_with_sizes_out::overload_name) |
| 11903 | .typed<unsafe_split_with_sizes_out::schema>(); |
| 11904 | } |
| 11905 | |
| 11906 | // aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () |
| 11907 | void unsafe_split_with_sizes_out::call(const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) { |
| 11908 | |
| 11909 | static auto op = create_unsafe_split_with_sizes_out_typed_handle(); |
| 11910 | return op.call(self, split_sizes, dim, out); |
| 11911 | } |
| 11912 | |
| 11913 | // aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () |
| 11914 | void unsafe_split_with_sizes_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef split_sizes, int64_t dim, at::TensorList out) { |
| 11915 | |
| 11916 | static auto op = create_unsafe_split_with_sizes_out_typed_handle(); |
| 11917 | return op.redispatch(dispatchKeySet, self, split_sizes, dim, out); |
| 11918 | } |
| 11919 | |
| 11920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_out, name, "aten::prod") |
| 11921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_out, overload_name, "out") |
| 11922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(prod_out, schema_str, "prod.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)") |
| 11923 | |
| 11924 | // aten::prod.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 11925 | static C10_NOINLINE c10::TypedOperatorHandle<prod_out::schema> create_prod_out_typed_handle() { |
| 11926 | return c10::Dispatcher::singleton() |
| 11927 | .findSchemaOrThrow(prod_out::name, prod_out::overload_name) |
| 11928 | .typed<prod_out::schema>(); |
| 11929 | } |
| 11930 | |
| 11931 | // aten::prod.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 11932 | at::Tensor & prod_out::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 11933 | |
| 11934 | static auto op = create_prod_out_typed_handle(); |
| 11935 | return op.call(self, dtype, out); |
| 11936 | } |
| 11937 | |
| 11938 | // aten::prod.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
| 11939 | at::Tensor & prod_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
| 11940 | |
| 11941 | static auto op = create_prod_out_typed_handle(); |
| 11942 | return op.redispatch(dispatchKeySet, self, dtype, out); |
| 11943 | } |
| 11944 | |
| 11945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask_out, name, "aten::_nested_tensor_from_mask") |
| 11946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask_out, overload_name, "out") |
| 11947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_mask_out, schema_str, "_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!)") |
| 11948 | |
| 11949 | // aten::_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!) |
| 11950 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_from_mask_out::schema> create__nested_tensor_from_mask_out_typed_handle() { |
| 11951 | return c10::Dispatcher::singleton() |
| 11952 | .findSchemaOrThrow(_nested_tensor_from_mask_out::name, _nested_tensor_from_mask_out::overload_name) |
| 11953 | .typed<_nested_tensor_from_mask_out::schema>(); |
| 11954 | } |
| 11955 | |
| 11956 | // aten::_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!) |
| 11957 | at::Tensor & _nested_tensor_from_mask_out::call(const at::Tensor & t, const at::Tensor & mask, bool mask_check, at::Tensor & out) { |
| 11958 | |
| 11959 | static auto op = create__nested_tensor_from_mask_out_typed_handle(); |
| 11960 | return op.call(t, mask, mask_check, out); |
| 11961 | } |
| 11962 | |
| 11963 | // aten::_nested_tensor_from_mask.out(Tensor t, Tensor mask, bool mask_check=True, *, Tensor(a!) out) -> Tensor(a!) |
| 11964 | at::Tensor & _nested_tensor_from_mask_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & t, const at::Tensor & mask, bool mask_check, at::Tensor & out) { |
| 11965 | |
| 11966 | static auto op = create__nested_tensor_from_mask_out_typed_handle(); |
| 11967 | return op.redispatch(dispatchKeySet, t, mask, mask_check, out); |
| 11968 | } |
| 11969 | |
| 11970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_size_out, name, "aten::_nested_tensor_size") |
| 11971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_size_out, overload_name, "out") |
| 11972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_size_out, schema_str, "_nested_tensor_size.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 11973 | |
| 11974 | // aten::_nested_tensor_size.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11975 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_size_out::schema> create__nested_tensor_size_out_typed_handle() { |
| 11976 | return c10::Dispatcher::singleton() |
| 11977 | .findSchemaOrThrow(_nested_tensor_size_out::name, _nested_tensor_size_out::overload_name) |
| 11978 | .typed<_nested_tensor_size_out::schema>(); |
| 11979 | } |
| 11980 | |
| 11981 | // aten::_nested_tensor_size.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11982 | at::Tensor & _nested_tensor_size_out::call(const at::Tensor & self, at::Tensor & out) { |
| 11983 | |
| 11984 | static auto op = create__nested_tensor_size_out_typed_handle(); |
| 11985 | return op.call(self, out); |
| 11986 | } |
| 11987 | |
| 11988 | // aten::_nested_tensor_size.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 11989 | at::Tensor & _nested_tensor_size_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 11990 | |
| 11991 | static auto op = create__nested_tensor_size_out_typed_handle(); |
| 11992 | return op.redispatch(dispatchKeySet, self, out); |
| 11993 | } |
| 11994 | |
| 11995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_view_from_buffer_copy_out, name, "aten::_nested_view_from_buffer_copy") |
| 11996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_view_from_buffer_copy_out, overload_name, "out") |
| 11997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_view_from_buffer_copy_out, schema_str, "_nested_view_from_buffer_copy.out(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets, *, Tensor(a!) out) -> Tensor(a!)") |
| 11998 | |
| 11999 | // aten::_nested_view_from_buffer_copy.out(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets, *, Tensor(a!) out) -> Tensor(a!) |
| 12000 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_view_from_buffer_copy_out::schema> create__nested_view_from_buffer_copy_out_typed_handle() { |
| 12001 | return c10::Dispatcher::singleton() |
| 12002 | .findSchemaOrThrow(_nested_view_from_buffer_copy_out::name, _nested_view_from_buffer_copy_out::overload_name) |
| 12003 | .typed<_nested_view_from_buffer_copy_out::schema>(); |
| 12004 | } |
| 12005 | |
| 12006 | // aten::_nested_view_from_buffer_copy.out(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets, *, Tensor(a!) out) -> Tensor(a!) |
| 12007 | at::Tensor & _nested_view_from_buffer_copy_out::call(const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, at::IntArrayRef offsets, at::Tensor & out) { |
| 12008 | |
| 12009 | static auto op = create__nested_view_from_buffer_copy_out_typed_handle(); |
| 12010 | return op.call(self, nested_size, nested_strides, offsets, out); |
| 12011 | } |
| 12012 | |
| 12013 | // aten::_nested_view_from_buffer_copy.out(Tensor self, Tensor nested_size, Tensor nested_strides, int[] offsets, *, Tensor(a!) out) -> Tensor(a!) |
| 12014 | at::Tensor & _nested_view_from_buffer_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & nested_size, const at::Tensor & nested_strides, at::IntArrayRef offsets, at::Tensor & out) { |
| 12015 | |
| 12016 | static auto op = create__nested_view_from_buffer_copy_out_typed_handle(); |
| 12017 | return op.redispatch(dispatchKeySet, self, nested_size, nested_strides, offsets, out); |
| 12018 | } |
| 12019 | |
| 12020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unique_dim_consecutive_out, name, "aten::unique_dim_consecutive") |
| 12021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unique_dim_consecutive_out, overload_name, "out") |
| 12022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unique_dim_consecutive_out, schema_str, "unique_dim_consecutive.out(Tensor self, int dim, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))") |
| 12023 | |
| 12024 | // aten::unique_dim_consecutive.out(Tensor self, int dim, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 12025 | static C10_NOINLINE c10::TypedOperatorHandle<unique_dim_consecutive_out::schema> create_unique_dim_consecutive_out_typed_handle() { |
| 12026 | return c10::Dispatcher::singleton() |
| 12027 | .findSchemaOrThrow(unique_dim_consecutive_out::name, unique_dim_consecutive_out::overload_name) |
| 12028 | .typed<unique_dim_consecutive_out::schema>(); |
| 12029 | } |
| 12030 | |
| 12031 | // aten::unique_dim_consecutive.out(Tensor self, int dim, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 12032 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_consecutive_out::call(const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 12033 | |
| 12034 | static auto op = create_unique_dim_consecutive_out_typed_handle(); |
| 12035 | return op.call(self, dim, return_inverse, return_counts, out0, out1, out2); |
| 12036 | } |
| 12037 | |
| 12038 | // aten::unique_dim_consecutive.out(Tensor self, int dim, bool return_inverse=False, bool return_counts=False, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
| 12039 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> unique_dim_consecutive_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool return_inverse, bool return_counts, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
| 12040 | |
| 12041 | static auto op = create_unique_dim_consecutive_out_typed_handle(); |
| 12042 | return op.redispatch(dispatchKeySet, self, dim, return_inverse, return_counts, out0, out1, out2); |
| 12043 | } |
| 12044 | |
| 12045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unsafe_view_out, name, "aten::_unsafe_view") |
| 12046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unsafe_view_out, overload_name, "out") |
| 12047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_unsafe_view_out, schema_str, "_unsafe_view.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)") |
| 12048 | |
| 12049 | // aten::_unsafe_view.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12050 | static C10_NOINLINE c10::TypedOperatorHandle<_unsafe_view_out::schema> create__unsafe_view_out_typed_handle() { |
| 12051 | return c10::Dispatcher::singleton() |
| 12052 | .findSchemaOrThrow(_unsafe_view_out::name, _unsafe_view_out::overload_name) |
| 12053 | .typed<_unsafe_view_out::schema>(); |
| 12054 | } |
| 12055 | |
| 12056 | // aten::_unsafe_view.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12057 | at::Tensor & _unsafe_view_out::call(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
| 12058 | |
| 12059 | static auto op = create__unsafe_view_out_typed_handle(); |
| 12060 | return op.call(self, size, out); |
| 12061 | } |
| 12062 | |
| 12063 | // aten::_unsafe_view.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12064 | at::Tensor & _unsafe_view_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
| 12065 | |
| 12066 | static auto op = create__unsafe_view_out_typed_handle(); |
| 12067 | return op.redispatch(dispatchKeySet, self, size, out); |
| 12068 | } |
| 12069 | |
| 12070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_efficientzerotensor_out, name, "aten::_efficientzerotensor") |
| 12071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_efficientzerotensor_out, overload_name, "out") |
| 12072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_efficientzerotensor_out, schema_str, "_efficientzerotensor.out(int[] size, *, Tensor(a!) out) -> Tensor(a!)") |
| 12073 | |
| 12074 | // aten::_efficientzerotensor.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12075 | static C10_NOINLINE c10::TypedOperatorHandle<_efficientzerotensor_out::schema> create__efficientzerotensor_out_typed_handle() { |
| 12076 | return c10::Dispatcher::singleton() |
| 12077 | .findSchemaOrThrow(_efficientzerotensor_out::name, _efficientzerotensor_out::overload_name) |
| 12078 | .typed<_efficientzerotensor_out::schema>(); |
| 12079 | } |
| 12080 | |
| 12081 | // aten::_efficientzerotensor.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12082 | at::Tensor & _efficientzerotensor_out::call(at::IntArrayRef size, at::Tensor & out) { |
| 12083 | |
| 12084 | static auto op = create__efficientzerotensor_out_typed_handle(); |
| 12085 | return op.call(size, out); |
| 12086 | } |
| 12087 | |
| 12088 | // aten::_efficientzerotensor.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12089 | at::Tensor & _efficientzerotensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, at::Tensor & out) { |
| 12090 | |
| 12091 | static auto op = create__efficientzerotensor_out_typed_handle(); |
| 12092 | return op.redispatch(dispatchKeySet, size, out); |
| 12093 | } |
| 12094 | |
| 12095 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson_out, name, "aten::poisson") |
| 12096 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson_out, overload_name, "out") |
| 12097 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(poisson_out, schema_str, "poisson.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 12098 | |
| 12099 | // aten::poisson.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12100 | static C10_NOINLINE c10::TypedOperatorHandle<poisson_out::schema> create_poisson_out_typed_handle() { |
| 12101 | return c10::Dispatcher::singleton() |
| 12102 | .findSchemaOrThrow(poisson_out::name, poisson_out::overload_name) |
| 12103 | .typed<poisson_out::schema>(); |
| 12104 | } |
| 12105 | |
| 12106 | // aten::poisson.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12107 | at::Tensor & poisson_out::call(const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 12108 | |
| 12109 | static auto op = create_poisson_out_typed_handle(); |
| 12110 | return op.call(self, generator, out); |
| 12111 | } |
| 12112 | |
| 12113 | // aten::poisson.out(Tensor self, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12114 | at::Tensor & poisson_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
| 12115 | |
| 12116 | static auto op = create_poisson_out_typed_handle(); |
| 12117 | return op.redispatch(dispatchKeySet, self, generator, out); |
| 12118 | } |
| 12119 | |
| 12120 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Scalar_out, name, "aten::sub") |
| 12121 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Scalar_out, overload_name, "Scalar_out") |
| 12122 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sub_Scalar_out, schema_str, "sub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 12123 | |
| 12124 | // aten::sub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12125 | static C10_NOINLINE c10::TypedOperatorHandle<sub_Scalar_out::schema> create_sub_Scalar_out_typed_handle() { |
| 12126 | return c10::Dispatcher::singleton() |
| 12127 | .findSchemaOrThrow(sub_Scalar_out::name, sub_Scalar_out::overload_name) |
| 12128 | .typed<sub_Scalar_out::schema>(); |
| 12129 | } |
| 12130 | |
| 12131 | // aten::sub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12132 | at::Tensor & sub_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out) { |
| 12133 | |
| 12134 | static auto op = create_sub_Scalar_out_typed_handle(); |
| 12135 | return op.call(self, other, alpha, out); |
| 12136 | } |
| 12137 | |
| 12138 | // aten::sub.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12139 | at::Tensor & sub_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out) { |
| 12140 | |
| 12141 | static auto op = create_sub_Scalar_out_typed_handle(); |
| 12142 | return op.redispatch(dispatchKeySet, self, other, alpha, out); |
| 12143 | } |
| 12144 | |
| 12145 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_size_out, name, "aten::sparse_coo_tensor") |
| 12146 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_size_out, overload_name, "size_out") |
| 12147 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_coo_tensor_size_out, schema_str, "sparse_coo_tensor.size_out(int[] size, *, Tensor(a!) out) -> Tensor(a!)") |
| 12148 | |
| 12149 | // aten::sparse_coo_tensor.size_out(int[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12150 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_coo_tensor_size_out::schema> create_sparse_coo_tensor_size_out_typed_handle() { |
| 12151 | return c10::Dispatcher::singleton() |
| 12152 | .findSchemaOrThrow(sparse_coo_tensor_size_out::name, sparse_coo_tensor_size_out::overload_name) |
| 12153 | .typed<sparse_coo_tensor_size_out::schema>(); |
| 12154 | } |
| 12155 | |
| 12156 | // aten::sparse_coo_tensor.size_out(int[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12157 | at::Tensor & sparse_coo_tensor_size_out::call(at::IntArrayRef size, at::Tensor & out) { |
| 12158 | |
| 12159 | static auto op = create_sparse_coo_tensor_size_out_typed_handle(); |
| 12160 | return op.call(size, out); |
| 12161 | } |
| 12162 | |
| 12163 | // aten::sparse_coo_tensor.size_out(int[] size, *, Tensor(a!) out) -> Tensor(a!) |
| 12164 | at::Tensor & sparse_coo_tensor_size_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, at::Tensor & out) { |
| 12165 | |
| 12166 | static auto op = create_sparse_coo_tensor_size_out_typed_handle(); |
| 12167 | return op.redispatch(dispatchKeySet, size, out); |
| 12168 | } |
| 12169 | |
| 12170 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear_out, name, "aten::sparse_resize_and_clear") |
| 12171 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear_out, overload_name, "out") |
| 12172 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear_out, schema_str, "sparse_resize_and_clear.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!)") |
| 12173 | |
| 12174 | // aten::sparse_resize_and_clear.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 12175 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_resize_and_clear_out::schema> create_sparse_resize_and_clear_out_typed_handle() { |
| 12176 | return c10::Dispatcher::singleton() |
| 12177 | .findSchemaOrThrow(sparse_resize_and_clear_out::name, sparse_resize_and_clear_out::overload_name) |
| 12178 | .typed<sparse_resize_and_clear_out::schema>(); |
| 12179 | } |
| 12180 | |
| 12181 | // aten::sparse_resize_and_clear.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 12182 | const at::Tensor & sparse_resize_and_clear_out::call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out) { |
| 12183 | |
| 12184 | static auto op = create_sparse_resize_and_clear_out_typed_handle(); |
| 12185 | return op.call(self, size, sparse_dim, dense_dim, out); |
| 12186 | } |
| 12187 | |
| 12188 | // aten::sparse_resize_and_clear.out(Tensor self, int[] size, int sparse_dim, int dense_dim, *, Tensor(a!) out) -> Tensor(a!) |
| 12189 | const at::Tensor & sparse_resize_and_clear_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim, const at::Tensor & out) { |
| 12190 | |
| 12191 | static auto op = create_sparse_resize_and_clear_out_typed_handle(); |
| 12192 | return op.redispatch(dispatchKeySet, self, size, sparse_dim, dense_dim, out); |
| 12193 | } |
| 12194 | |
| 12195 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear, name, "aten::sparse_resize_and_clear") |
| 12196 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear, overload_name, "") |
| 12197 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sparse_resize_and_clear, schema_str, "sparse_resize_and_clear(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor") |
| 12198 | |
| 12199 | // aten::sparse_resize_and_clear(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor |
| 12200 | static C10_NOINLINE c10::TypedOperatorHandle<sparse_resize_and_clear::schema> create_sparse_resize_and_clear_typed_handle() { |
| 12201 | return c10::Dispatcher::singleton() |
| 12202 | .findSchemaOrThrow(sparse_resize_and_clear::name, sparse_resize_and_clear::overload_name) |
| 12203 | .typed<sparse_resize_and_clear::schema>(); |
| 12204 | } |
| 12205 | |
| 12206 | // aten::sparse_resize_and_clear(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor |
| 12207 | at::Tensor sparse_resize_and_clear::call(const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 12208 | |
| 12209 | static auto op = create_sparse_resize_and_clear_typed_handle(); |
| 12210 | return op.call(self, size, sparse_dim, dense_dim); |
| 12211 | } |
| 12212 | |
| 12213 | // aten::sparse_resize_and_clear(Tensor self, int[] size, int sparse_dim, int dense_dim) -> Tensor |
| 12214 | at::Tensor sparse_resize_and_clear::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, int64_t sparse_dim, int64_t dense_dim) { |
| 12215 | |
| 12216 | static auto op = create_sparse_resize_and_clear_typed_handle(); |
| 12217 | return op.redispatch(dispatchKeySet, self, size, sparse_dim, dense_dim); |
| 12218 | } |
| 12219 | |
| 12220 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_csr_out, name, "aten::to_sparse_csr") |
| 12221 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_csr_out, overload_name, "out") |
| 12222 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_csr_out, schema_str, "to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 12223 | |
| 12224 | // aten::to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12225 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_csr_out::schema> create_to_sparse_csr_out_typed_handle() { |
| 12226 | return c10::Dispatcher::singleton() |
| 12227 | .findSchemaOrThrow(to_sparse_csr_out::name, to_sparse_csr_out::overload_name) |
| 12228 | .typed<to_sparse_csr_out::schema>(); |
| 12229 | } |
| 12230 | |
| 12231 | // aten::to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12232 | at::Tensor & to_sparse_csr_out::call(const at::Tensor & self, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
| 12233 | |
| 12234 | static auto op = create_to_sparse_csr_out_typed_handle(); |
| 12235 | return op.call(self, dense_dim, out); |
| 12236 | } |
| 12237 | |
| 12238 | // aten::to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12239 | at::Tensor & to_sparse_csr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
| 12240 | |
| 12241 | static auto op = create_to_sparse_csr_out_typed_handle(); |
| 12242 | return op.redispatch(dispatchKeySet, self, dense_dim, out); |
| 12243 | } |
| 12244 | |
| 12245 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsr_out, name, "aten::to_sparse_bsr") |
| 12246 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsr_out, overload_name, "out") |
| 12247 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsr_out, schema_str, "to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 12248 | |
| 12249 | // aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12250 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_bsr_out::schema> create_to_sparse_bsr_out_typed_handle() { |
| 12251 | return c10::Dispatcher::singleton() |
| 12252 | .findSchemaOrThrow(to_sparse_bsr_out::name, to_sparse_bsr_out::overload_name) |
| 12253 | .typed<to_sparse_bsr_out::schema>(); |
| 12254 | } |
| 12255 | |
| 12256 | // aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12257 | at::Tensor & to_sparse_bsr_out::call(const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
| 12258 | |
| 12259 | static auto op = create_to_sparse_bsr_out_typed_handle(); |
| 12260 | return op.call(self, blocksize, dense_dim, out); |
| 12261 | } |
| 12262 | |
| 12263 | // aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12264 | at::Tensor & to_sparse_bsr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
| 12265 | |
| 12266 | static auto op = create_to_sparse_bsr_out_typed_handle(); |
| 12267 | return op.redispatch(dispatchKeySet, self, blocksize, dense_dim, out); |
| 12268 | } |
| 12269 | |
| 12270 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_reorder_conv3d_weight_out, name, "aten::mkldnn_reorder_conv3d_weight") |
| 12271 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_reorder_conv3d_weight_out, overload_name, "out") |
| 12272 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_reorder_conv3d_weight_out, schema_str, "mkldnn_reorder_conv3d_weight.out(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 12273 | |
| 12274 | // aten::mkldnn_reorder_conv3d_weight.out(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12275 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_reorder_conv3d_weight_out::schema> create_mkldnn_reorder_conv3d_weight_out_typed_handle() { |
| 12276 | return c10::Dispatcher::singleton() |
| 12277 | .findSchemaOrThrow(mkldnn_reorder_conv3d_weight_out::name, mkldnn_reorder_conv3d_weight_out::overload_name) |
| 12278 | .typed<mkldnn_reorder_conv3d_weight_out::schema>(); |
| 12279 | } |
| 12280 | |
| 12281 | // aten::mkldnn_reorder_conv3d_weight.out(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12282 | at::Tensor & mkldnn_reorder_conv3d_weight_out::call(const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { |
| 12283 | |
| 12284 | static auto op = create_mkldnn_reorder_conv3d_weight_out_typed_handle(); |
| 12285 | return op.call(self, padding, stride, dilation, groups, out); |
| 12286 | } |
| 12287 | |
| 12288 | // aten::mkldnn_reorder_conv3d_weight.out(Tensor self, int[3] padding=0, int[3] stride=1, int[3] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12289 | at::Tensor & mkldnn_reorder_conv3d_weight_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, at::Tensor & out) { |
| 12290 | |
| 12291 | static auto op = create_mkldnn_reorder_conv3d_weight_out_typed_handle(); |
| 12292 | return op.redispatch(dispatchKeySet, self, padding, stride, dilation, groups, out); |
| 12293 | } |
| 12294 | |
| 12295 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_tensor_quantized_tensor_out, name, "aten::_make_per_tensor_quantized_tensor") |
| 12296 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_tensor_quantized_tensor_out, overload_name, "out") |
| 12297 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_tensor_quantized_tensor_out, schema_str, "_make_per_tensor_quantized_tensor.out(Tensor self, float scale, int zero_point, *, Tensor(a!) out) -> Tensor(a!)") |
| 12298 | |
| 12299 | // aten::_make_per_tensor_quantized_tensor.out(Tensor self, float scale, int zero_point, *, Tensor(a!) out) -> Tensor(a!) |
| 12300 | static C10_NOINLINE c10::TypedOperatorHandle<_make_per_tensor_quantized_tensor_out::schema> create__make_per_tensor_quantized_tensor_out_typed_handle() { |
| 12301 | return c10::Dispatcher::singleton() |
| 12302 | .findSchemaOrThrow(_make_per_tensor_quantized_tensor_out::name, _make_per_tensor_quantized_tensor_out::overload_name) |
| 12303 | .typed<_make_per_tensor_quantized_tensor_out::schema>(); |
| 12304 | } |
| 12305 | |
| 12306 | // aten::_make_per_tensor_quantized_tensor.out(Tensor self, float scale, int zero_point, *, Tensor(a!) out) -> Tensor(a!) |
| 12307 | at::Tensor & _make_per_tensor_quantized_tensor_out::call(const at::Tensor & self, double scale, int64_t zero_point, at::Tensor & out) { |
| 12308 | |
| 12309 | static auto op = create__make_per_tensor_quantized_tensor_out_typed_handle(); |
| 12310 | return op.call(self, scale, zero_point, out); |
| 12311 | } |
| 12312 | |
| 12313 | // aten::_make_per_tensor_quantized_tensor.out(Tensor self, float scale, int zero_point, *, Tensor(a!) out) -> Tensor(a!) |
| 12314 | at::Tensor & _make_per_tensor_quantized_tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::Tensor & out) { |
| 12315 | |
| 12316 | static auto op = create__make_per_tensor_quantized_tensor_out_typed_handle(); |
| 12317 | return op.redispatch(dispatchKeySet, self, scale, zero_point, out); |
| 12318 | } |
| 12319 | |
| 12320 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_channel_quantized_tensor_out, name, "aten::_make_per_channel_quantized_tensor") |
| 12321 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_channel_quantized_tensor_out, overload_name, "out") |
| 12322 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_make_per_channel_quantized_tensor_out, schema_str, "_make_per_channel_quantized_tensor.out(Tensor self, Tensor scale, Tensor zero_point, int axis, *, Tensor(a!) out) -> Tensor(a!)") |
| 12323 | |
| 12324 | // aten::_make_per_channel_quantized_tensor.out(Tensor self, Tensor scale, Tensor zero_point, int axis, *, Tensor(a!) out) -> Tensor(a!) |
| 12325 | static C10_NOINLINE c10::TypedOperatorHandle<_make_per_channel_quantized_tensor_out::schema> create__make_per_channel_quantized_tensor_out_typed_handle() { |
| 12326 | return c10::Dispatcher::singleton() |
| 12327 | .findSchemaOrThrow(_make_per_channel_quantized_tensor_out::name, _make_per_channel_quantized_tensor_out::overload_name) |
| 12328 | .typed<_make_per_channel_quantized_tensor_out::schema>(); |
| 12329 | } |
| 12330 | |
| 12331 | // aten::_make_per_channel_quantized_tensor.out(Tensor self, Tensor scale, Tensor zero_point, int axis, *, Tensor(a!) out) -> Tensor(a!) |
| 12332 | at::Tensor & _make_per_channel_quantized_tensor_out::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, at::Tensor & out) { |
| 12333 | |
| 12334 | static auto op = create__make_per_channel_quantized_tensor_out_typed_handle(); |
| 12335 | return op.call(self, scale, zero_point, axis, out); |
| 12336 | } |
| 12337 | |
| 12338 | // aten::_make_per_channel_quantized_tensor.out(Tensor self, Tensor scale, Tensor zero_point, int axis, *, Tensor(a!) out) -> Tensor(a!) |
| 12339 | at::Tensor & _make_per_channel_quantized_tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t axis, at::Tensor & out) { |
| 12340 | |
| 12341 | static auto op = create__make_per_channel_quantized_tensor_out_typed_handle(); |
| 12342 | return op.redispatch(dispatchKeySet, self, scale, zero_point, axis, out); |
| 12343 | } |
| 12344 | |
| 12345 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Scalar_out, name, "aten::masked_fill") |
| 12346 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Scalar_out, overload_name, "Scalar_out") |
| 12347 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Scalar_out, schema_str, "masked_fill.Scalar_out(Tensor self, Tensor mask, Scalar value, *, Tensor(a!) out) -> Tensor(a!)") |
| 12348 | |
| 12349 | // aten::masked_fill.Scalar_out(Tensor self, Tensor mask, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
| 12350 | static C10_NOINLINE c10::TypedOperatorHandle<masked_fill_Scalar_out::schema> create_masked_fill_Scalar_out_typed_handle() { |
| 12351 | return c10::Dispatcher::singleton() |
| 12352 | .findSchemaOrThrow(masked_fill_Scalar_out::name, masked_fill_Scalar_out::overload_name) |
| 12353 | .typed<masked_fill_Scalar_out::schema>(); |
| 12354 | } |
| 12355 | |
| 12356 | // aten::masked_fill.Scalar_out(Tensor self, Tensor mask, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
| 12357 | at::Tensor & masked_fill_Scalar_out::call(const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value, at::Tensor & out) { |
| 12358 | |
| 12359 | static auto op = create_masked_fill_Scalar_out_typed_handle(); |
| 12360 | return op.call(self, mask, value, out); |
| 12361 | } |
| 12362 | |
| 12363 | // aten::masked_fill.Scalar_out(Tensor self, Tensor mask, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
| 12364 | at::Tensor & masked_fill_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Scalar & value, at::Tensor & out) { |
| 12365 | |
| 12366 | static auto op = create_masked_fill_Scalar_out_typed_handle(); |
| 12367 | return op.redispatch(dispatchKeySet, self, mask, value, out); |
| 12368 | } |
| 12369 | |
| 12370 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Tensor_out, name, "aten::masked_fill") |
| 12371 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Tensor_out, overload_name, "Tensor_out") |
| 12372 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_fill_Tensor_out, schema_str, "masked_fill.Tensor_out(Tensor self, Tensor mask, Tensor value, *, Tensor(a!) out) -> Tensor(a!)") |
| 12373 | |
| 12374 | // aten::masked_fill.Tensor_out(Tensor self, Tensor mask, Tensor value, *, Tensor(a!) out) -> Tensor(a!) |
| 12375 | static C10_NOINLINE c10::TypedOperatorHandle<masked_fill_Tensor_out::schema> create_masked_fill_Tensor_out_typed_handle() { |
| 12376 | return c10::Dispatcher::singleton() |
| 12377 | .findSchemaOrThrow(masked_fill_Tensor_out::name, masked_fill_Tensor_out::overload_name) |
| 12378 | .typed<masked_fill_Tensor_out::schema>(); |
| 12379 | } |
| 12380 | |
| 12381 | // aten::masked_fill.Tensor_out(Tensor self, Tensor mask, Tensor value, *, Tensor(a!) out) -> Tensor(a!) |
| 12382 | at::Tensor & masked_fill_Tensor_out::call(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value, at::Tensor & out) { |
| 12383 | |
| 12384 | static auto op = create_masked_fill_Tensor_out_typed_handle(); |
| 12385 | return op.call(self, mask, value, out); |
| 12386 | } |
| 12387 | |
| 12388 | // aten::masked_fill.Tensor_out(Tensor self, Tensor mask, Tensor value, *, Tensor(a!) out) -> Tensor(a!) |
| 12389 | at::Tensor & masked_fill_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & value, at::Tensor & out) { |
| 12390 | |
| 12391 | static auto op = create_masked_fill_Tensor_out_typed_handle(); |
| 12392 | return op.redispatch(dispatchKeySet, self, mask, value, out); |
| 12393 | } |
| 12394 | |
| 12395 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter_out, name, "aten::masked_scatter") |
| 12396 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter_out, overload_name, "out") |
| 12397 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_scatter_out, schema_str, "masked_scatter.out(Tensor self, Tensor mask, Tensor source, *, Tensor(a!) out) -> Tensor(a!)") |
| 12398 | |
| 12399 | // aten::masked_scatter.out(Tensor self, Tensor mask, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
| 12400 | static C10_NOINLINE c10::TypedOperatorHandle<masked_scatter_out::schema> create_masked_scatter_out_typed_handle() { |
| 12401 | return c10::Dispatcher::singleton() |
| 12402 | .findSchemaOrThrow(masked_scatter_out::name, masked_scatter_out::overload_name) |
| 12403 | .typed<masked_scatter_out::schema>(); |
| 12404 | } |
| 12405 | |
| 12406 | // aten::masked_scatter.out(Tensor self, Tensor mask, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
| 12407 | at::Tensor & masked_scatter_out::call(const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source, at::Tensor & out) { |
| 12408 | |
| 12409 | static auto op = create_masked_scatter_out_typed_handle(); |
| 12410 | return op.call(self, mask, source, out); |
| 12411 | } |
| 12412 | |
| 12413 | // aten::masked_scatter.out(Tensor self, Tensor mask, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
| 12414 | at::Tensor & masked_scatter_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, const at::Tensor & source, at::Tensor & out) { |
| 12415 | |
| 12416 | static auto op = create_masked_scatter_out_typed_handle(); |
| 12417 | return op.redispatch(dispatchKeySet, self, mask, source, out); |
| 12418 | } |
| 12419 | |
| 12420 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_softmax_backward_out, name, "aten::_masked_softmax_backward") |
| 12421 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_softmax_backward_out, overload_name, "out") |
| 12422 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_masked_softmax_backward_out, schema_str, "_masked_softmax_backward.out(Tensor grad_output, Tensor output, Tensor mask, int? dim=None, *, Tensor(a!) out) -> Tensor(a!)") |
| 12423 | |
| 12424 | // aten::_masked_softmax_backward.out(Tensor grad_output, Tensor output, Tensor mask, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12425 | static C10_NOINLINE c10::TypedOperatorHandle<_masked_softmax_backward_out::schema> create__masked_softmax_backward_out_typed_handle() { |
| 12426 | return c10::Dispatcher::singleton() |
| 12427 | .findSchemaOrThrow(_masked_softmax_backward_out::name, _masked_softmax_backward_out::overload_name) |
| 12428 | .typed<_masked_softmax_backward_out::schema>(); |
| 12429 | } |
| 12430 | |
| 12431 | // aten::_masked_softmax_backward.out(Tensor grad_output, Tensor output, Tensor mask, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12432 | at::Tensor & _masked_softmax_backward_out::call(const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & mask, c10::optional<int64_t> dim, at::Tensor & out) { |
| 12433 | |
| 12434 | static auto op = create__masked_softmax_backward_out_typed_handle(); |
| 12435 | return op.call(grad_output, output, mask, dim, out); |
| 12436 | } |
| 12437 | |
| 12438 | // aten::_masked_softmax_backward.out(Tensor grad_output, Tensor output, Tensor mask, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
| 12439 | at::Tensor & _masked_softmax_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & output, const at::Tensor & mask, c10::optional<int64_t> dim, at::Tensor & out) { |
| 12440 | |
| 12441 | static auto op = create__masked_softmax_backward_out_typed_handle(); |
| 12442 | return op.redispatch(dispatchKeySet, grad_output, output, mask, dim, out); |
| 12443 | } |
| 12444 | |
| 12445 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_Tensor_out, name, "aten::bitwise_or") |
| 12446 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_Tensor_out, overload_name, "Scalar_Tensor_out") |
| 12447 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bitwise_or_Scalar_Tensor_out, schema_str, "bitwise_or.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 12448 | |
| 12449 | // aten::bitwise_or.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12450 | static C10_NOINLINE c10::TypedOperatorHandle<bitwise_or_Scalar_Tensor_out::schema> create_bitwise_or_Scalar_Tensor_out_typed_handle() { |
| 12451 | return c10::Dispatcher::singleton() |
| 12452 | .findSchemaOrThrow(bitwise_or_Scalar_Tensor_out::name, bitwise_or_Scalar_Tensor_out::overload_name) |
| 12453 | .typed<bitwise_or_Scalar_Tensor_out::schema>(); |
| 12454 | } |
| 12455 | |
| 12456 | // aten::bitwise_or.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12457 | at::Tensor & bitwise_or_Scalar_Tensor_out::call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 12458 | |
| 12459 | static auto op = create_bitwise_or_Scalar_Tensor_out_typed_handle(); |
| 12460 | return op.call(self, other, out); |
| 12461 | } |
| 12462 | |
| 12463 | // aten::bitwise_or.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12464 | at::Tensor & bitwise_or_Scalar_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 12465 | |
| 12466 | static auto op = create_bitwise_or_Scalar_Tensor_out_typed_handle(); |
| 12467 | return op.redispatch(dispatchKeySet, self, other, out); |
| 12468 | } |
| 12469 | |
| 12470 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triu_indices_out, name, "aten::triu_indices") |
| 12471 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triu_indices_out, overload_name, "out") |
| 12472 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triu_indices_out, schema_str, "triu_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)") |
| 12473 | |
| 12474 | // aten::triu_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!) |
| 12475 | static C10_NOINLINE c10::TypedOperatorHandle<triu_indices_out::schema> create_triu_indices_out_typed_handle() { |
| 12476 | return c10::Dispatcher::singleton() |
| 12477 | .findSchemaOrThrow(triu_indices_out::name, triu_indices_out::overload_name) |
| 12478 | .typed<triu_indices_out::schema>(); |
| 12479 | } |
| 12480 | |
| 12481 | // aten::triu_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!) |
| 12482 | at::Tensor & triu_indices_out::call(int64_t row, int64_t col, int64_t offset, at::Tensor & out) { |
| 12483 | |
| 12484 | static auto op = create_triu_indices_out_typed_handle(); |
| 12485 | return op.call(row, col, offset, out); |
| 12486 | } |
| 12487 | |
| 12488 | // aten::triu_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!) |
| 12489 | at::Tensor & triu_indices_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t row, int64_t col, int64_t offset, at::Tensor & out) { |
| 12490 | |
| 12491 | static auto op = create_triu_indices_out_typed_handle(); |
| 12492 | return op.redispatch(dispatchKeySet, row, col, offset, out); |
| 12493 | } |
| 12494 | |
| 12495 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace_out, name, "aten::trace") |
| 12496 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace_out, overload_name, "out") |
| 12497 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trace_out, schema_str, "trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12498 | |
| 12499 | // aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12500 | static C10_NOINLINE c10::TypedOperatorHandle<trace_out::schema> create_trace_out_typed_handle() { |
| 12501 | return c10::Dispatcher::singleton() |
| 12502 | .findSchemaOrThrow(trace_out::name, trace_out::overload_name) |
| 12503 | .typed<trace_out::schema>(); |
| 12504 | } |
| 12505 | |
| 12506 | // aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12507 | at::Tensor & trace_out::call(const at::Tensor & self, at::Tensor & out) { |
| 12508 | |
| 12509 | static auto op = create_trace_out_typed_handle(); |
| 12510 | return op.call(self, out); |
| 12511 | } |
| 12512 | |
| 12513 | // aten::trace.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12514 | at::Tensor & trace_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 12515 | |
| 12516 | static auto op = create_trace_out_typed_handle(); |
| 12517 | return op.redispatch(dispatchKeySet, self, out); |
| 12518 | } |
| 12519 | |
| 12520 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dist_out, name, "aten::dist") |
| 12521 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dist_out, overload_name, "out") |
| 12522 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dist_out, schema_str, "dist.out(Tensor self, Tensor other, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!)") |
| 12523 | |
| 12524 | // aten::dist.out(Tensor self, Tensor other, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
| 12525 | static C10_NOINLINE c10::TypedOperatorHandle<dist_out::schema> create_dist_out_typed_handle() { |
| 12526 | return c10::Dispatcher::singleton() |
| 12527 | .findSchemaOrThrow(dist_out::name, dist_out::overload_name) |
| 12528 | .typed<dist_out::schema>(); |
| 12529 | } |
| 12530 | |
| 12531 | // aten::dist.out(Tensor self, Tensor other, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
| 12532 | at::Tensor & dist_out::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & p, at::Tensor & out) { |
| 12533 | |
| 12534 | static auto op = create_dist_out_typed_handle(); |
| 12535 | return op.call(self, other, p, out); |
| 12536 | } |
| 12537 | |
| 12538 | // aten::dist.out(Tensor self, Tensor other, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
| 12539 | at::Tensor & dist_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & p, at::Tensor & out) { |
| 12540 | |
| 12541 | static auto op = create_dist_out_typed_handle(); |
| 12542 | return op.redispatch(dispatchKeySet, self, other, p, out); |
| 12543 | } |
| 12544 | |
| 12545 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_histogramdd_from_bin_cts_out, name, "aten::_histogramdd_from_bin_cts") |
| 12546 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_histogramdd_from_bin_cts_out, overload_name, "out") |
| 12547 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_histogramdd_from_bin_cts_out, schema_str, "_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!)") |
| 12548 | |
| 12549 | // aten::_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) |
| 12550 | static C10_NOINLINE c10::TypedOperatorHandle<_histogramdd_from_bin_cts_out::schema> create__histogramdd_from_bin_cts_out_typed_handle() { |
| 12551 | return c10::Dispatcher::singleton() |
| 12552 | .findSchemaOrThrow(_histogramdd_from_bin_cts_out::name, _histogramdd_from_bin_cts_out::overload_name) |
| 12553 | .typed<_histogramdd_from_bin_cts_out::schema>(); |
| 12554 | } |
| 12555 | |
| 12556 | // aten::_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) |
| 12557 | at::Tensor & _histogramdd_from_bin_cts_out::call(const at::Tensor & self, at::IntArrayRef bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density, at::Tensor & out) { |
| 12558 | |
| 12559 | static auto op = create__histogramdd_from_bin_cts_out_typed_handle(); |
| 12560 | return op.call(self, bins, range, weight, density, out); |
| 12561 | } |
| 12562 | |
| 12563 | // aten::_histogramdd_from_bin_cts.out(Tensor self, int[] bins, *, float[]? range=None, Tensor? weight=None, bool density=False, Tensor(a!) out) -> Tensor(a!) |
| 12564 | at::Tensor & _histogramdd_from_bin_cts_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density, at::Tensor & out) { |
| 12565 | |
| 12566 | static auto op = create__histogramdd_from_bin_cts_out_typed_handle(); |
| 12567 | return op.redispatch(dispatchKeySet, self, bins, range, weight, density, out); |
| 12568 | } |
| 12569 | |
| 12570 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_Tensor_out, name, "aten::remainder") |
| 12571 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_Tensor_out, overload_name, "Scalar_Tensor_out") |
| 12572 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(remainder_Scalar_Tensor_out, schema_str, "remainder.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)") |
| 12573 | |
| 12574 | // aten::remainder.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12575 | static C10_NOINLINE c10::TypedOperatorHandle<remainder_Scalar_Tensor_out::schema> create_remainder_Scalar_Tensor_out_typed_handle() { |
| 12576 | return c10::Dispatcher::singleton() |
| 12577 | .findSchemaOrThrow(remainder_Scalar_Tensor_out::name, remainder_Scalar_Tensor_out::overload_name) |
| 12578 | .typed<remainder_Scalar_Tensor_out::schema>(); |
| 12579 | } |
| 12580 | |
| 12581 | // aten::remainder.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12582 | at::Tensor & remainder_Scalar_Tensor_out::call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 12583 | |
| 12584 | static auto op = create_remainder_Scalar_Tensor_out_typed_handle(); |
| 12585 | return op.call(self, other, out); |
| 12586 | } |
| 12587 | |
| 12588 | // aten::remainder.Scalar_Tensor_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
| 12589 | at::Tensor & remainder_Scalar_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
| 12590 | |
| 12591 | static auto op = create_remainder_Scalar_Tensor_out_typed_handle(); |
| 12592 | return op.redispatch(dispatchKeySet, self, other, out); |
| 12593 | } |
| 12594 | |
| 12595 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_Scalar_out, name, "aten::_foreach_clamp_max") |
| 12596 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_Scalar_out, overload_name, "Scalar_out") |
| 12597 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_Scalar_out, schema_str, "_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> ()") |
| 12598 | |
| 12599 | // aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 12600 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max_Scalar_out::schema> create__foreach_clamp_max_Scalar_out_typed_handle() { |
| 12601 | return c10::Dispatcher::singleton() |
| 12602 | .findSchemaOrThrow(_foreach_clamp_max_Scalar_out::name, _foreach_clamp_max_Scalar_out::overload_name) |
| 12603 | .typed<_foreach_clamp_max_Scalar_out::schema>(); |
| 12604 | } |
| 12605 | |
| 12606 | // aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 12607 | void _foreach_clamp_max_Scalar_out::call(at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 12608 | |
| 12609 | static auto op = create__foreach_clamp_max_Scalar_out_typed_handle(); |
| 12610 | return op.call(self, scalar, out); |
| 12611 | } |
| 12612 | |
| 12613 | // aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () |
| 12614 | void _foreach_clamp_max_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & scalar, at::TensorList out) { |
| 12615 | |
| 12616 | static auto op = create__foreach_clamp_max_Scalar_out_typed_handle(); |
| 12617 | return op.redispatch(dispatchKeySet, self, scalar, out); |
| 12618 | } |
| 12619 | |
| 12620 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_List_out, name, "aten::_foreach_clamp_max") |
| 12621 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_List_out, overload_name, "List_out") |
| 12622 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_List_out, schema_str, "_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> ()") |
| 12623 | |
| 12624 | // aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 12625 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max_List_out::schema> create__foreach_clamp_max_List_out_typed_handle() { |
| 12626 | return c10::Dispatcher::singleton() |
| 12627 | .findSchemaOrThrow(_foreach_clamp_max_List_out::name, _foreach_clamp_max_List_out::overload_name) |
| 12628 | .typed<_foreach_clamp_max_List_out::schema>(); |
| 12629 | } |
| 12630 | |
| 12631 | // aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 12632 | void _foreach_clamp_max_List_out::call(at::TensorList self, at::TensorList other, at::TensorList out) { |
| 12633 | |
| 12634 | static auto op = create__foreach_clamp_max_List_out_typed_handle(); |
| 12635 | return op.call(self, other, out); |
| 12636 | } |
| 12637 | |
| 12638 | // aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () |
| 12639 | void _foreach_clamp_max_List_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList other, at::TensorList out) { |
| 12640 | |
| 12641 | static auto op = create__foreach_clamp_max_List_out_typed_handle(); |
| 12642 | return op.redispatch(dispatchKeySet, self, other, out); |
| 12643 | } |
| 12644 | |
| 12645 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_ScalarList_out, name, "aten::_foreach_clamp_max") |
| 12646 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_ScalarList_out, overload_name, "ScalarList_out") |
| 12647 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_clamp_max_ScalarList_out, schema_str, "_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> ()") |
| 12648 | |
| 12649 | // aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 12650 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_clamp_max_ScalarList_out::schema> create__foreach_clamp_max_ScalarList_out_typed_handle() { |
| 12651 | return c10::Dispatcher::singleton() |
| 12652 | .findSchemaOrThrow(_foreach_clamp_max_ScalarList_out::name, _foreach_clamp_max_ScalarList_out::overload_name) |
| 12653 | .typed<_foreach_clamp_max_ScalarList_out::schema>(); |
| 12654 | } |
| 12655 | |
| 12656 | // aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 12657 | void _foreach_clamp_max_ScalarList_out::call(at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 12658 | |
| 12659 | static auto op = create__foreach_clamp_max_ScalarList_out_typed_handle(); |
| 12660 | return op.call(self, scalars, out); |
| 12661 | } |
| 12662 | |
| 12663 | // aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
| 12664 | void _foreach_clamp_max_ScalarList_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
| 12665 | |
| 12666 | static auto op = create__foreach_clamp_max_ScalarList_out_typed_handle(); |
| 12667 | return op.redispatch(dispatchKeySet, self, scalars, out); |
| 12668 | } |
| 12669 | |
| 12670 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs_out, name, "aten::_foreach_abs") |
| 12671 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs_out, overload_name, "out") |
| 12672 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_abs_out, schema_str, "_foreach_abs.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 12673 | |
| 12674 | // aten::_foreach_abs.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12675 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_abs_out::schema> create__foreach_abs_out_typed_handle() { |
| 12676 | return c10::Dispatcher::singleton() |
| 12677 | .findSchemaOrThrow(_foreach_abs_out::name, _foreach_abs_out::overload_name) |
| 12678 | .typed<_foreach_abs_out::schema>(); |
| 12679 | } |
| 12680 | |
| 12681 | // aten::_foreach_abs.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12682 | void _foreach_abs_out::call(at::TensorList self, at::TensorList out) { |
| 12683 | |
| 12684 | static auto op = create__foreach_abs_out_typed_handle(); |
| 12685 | return op.call(self, out); |
| 12686 | } |
| 12687 | |
| 12688 | // aten::_foreach_abs.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12689 | void _foreach_abs_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 12690 | |
| 12691 | static auto op = create__foreach_abs_out_typed_handle(); |
| 12692 | return op.redispatch(dispatchKeySet, self, out); |
| 12693 | } |
| 12694 | |
| 12695 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1_out, name, "aten::_foreach_expm1") |
| 12696 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1_out, overload_name, "out") |
| 12697 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_expm1_out, schema_str, "_foreach_expm1.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 12698 | |
| 12699 | // aten::_foreach_expm1.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12700 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_expm1_out::schema> create__foreach_expm1_out_typed_handle() { |
| 12701 | return c10::Dispatcher::singleton() |
| 12702 | .findSchemaOrThrow(_foreach_expm1_out::name, _foreach_expm1_out::overload_name) |
| 12703 | .typed<_foreach_expm1_out::schema>(); |
| 12704 | } |
| 12705 | |
| 12706 | // aten::_foreach_expm1.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12707 | void _foreach_expm1_out::call(at::TensorList self, at::TensorList out) { |
| 12708 | |
| 12709 | static auto op = create__foreach_expm1_out_typed_handle(); |
| 12710 | return op.call(self, out); |
| 12711 | } |
| 12712 | |
| 12713 | // aten::_foreach_expm1.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12714 | void _foreach_expm1_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 12715 | |
| 12716 | static auto op = create__foreach_expm1_out_typed_handle(); |
| 12717 | return op.redispatch(dispatchKeySet, self, out); |
| 12718 | } |
| 12719 | |
| 12720 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10_out, name, "aten::_foreach_log10") |
| 12721 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10_out, overload_name, "out") |
| 12722 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log10_out, schema_str, "_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 12723 | |
| 12724 | // aten::_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12725 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log10_out::schema> create__foreach_log10_out_typed_handle() { |
| 12726 | return c10::Dispatcher::singleton() |
| 12727 | .findSchemaOrThrow(_foreach_log10_out::name, _foreach_log10_out::overload_name) |
| 12728 | .typed<_foreach_log10_out::schema>(); |
| 12729 | } |
| 12730 | |
| 12731 | // aten::_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12732 | void _foreach_log10_out::call(at::TensorList self, at::TensorList out) { |
| 12733 | |
| 12734 | static auto op = create__foreach_log10_out_typed_handle(); |
| 12735 | return op.call(self, out); |
| 12736 | } |
| 12737 | |
| 12738 | // aten::_foreach_log10.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12739 | void _foreach_log10_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 12740 | |
| 12741 | static auto op = create__foreach_log10_out_typed_handle(); |
| 12742 | return op.redispatch(dispatchKeySet, self, out); |
| 12743 | } |
| 12744 | |
| 12745 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan_out, name, "aten::_foreach_tan") |
| 12746 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan_out, overload_name, "out") |
| 12747 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_tan_out, schema_str, "_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 12748 | |
| 12749 | // aten::_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12750 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_tan_out::schema> create__foreach_tan_out_typed_handle() { |
| 12751 | return c10::Dispatcher::singleton() |
| 12752 | .findSchemaOrThrow(_foreach_tan_out::name, _foreach_tan_out::overload_name) |
| 12753 | .typed<_foreach_tan_out::schema>(); |
| 12754 | } |
| 12755 | |
| 12756 | // aten::_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12757 | void _foreach_tan_out::call(at::TensorList self, at::TensorList out) { |
| 12758 | |
| 12759 | static auto op = create__foreach_tan_out_typed_handle(); |
| 12760 | return op.call(self, out); |
| 12761 | } |
| 12762 | |
| 12763 | // aten::_foreach_tan.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12764 | void _foreach_tan_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 12765 | |
| 12766 | static auto op = create__foreach_tan_out_typed_handle(); |
| 12767 | return op.redispatch(dispatchKeySet, self, out); |
| 12768 | } |
| 12769 | |
| 12770 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh_out, name, "aten::_foreach_sinh") |
| 12771 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh_out, overload_name, "out") |
| 12772 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sinh_out, schema_str, "_foreach_sinh.out(Tensor[] self, *, Tensor(a!)[] out) -> ()") |
| 12773 | |
| 12774 | // aten::_foreach_sinh.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12775 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sinh_out::schema> create__foreach_sinh_out_typed_handle() { |
| 12776 | return c10::Dispatcher::singleton() |
| 12777 | .findSchemaOrThrow(_foreach_sinh_out::name, _foreach_sinh_out::overload_name) |
| 12778 | .typed<_foreach_sinh_out::schema>(); |
| 12779 | } |
| 12780 | |
| 12781 | // aten::_foreach_sinh.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12782 | void _foreach_sinh_out::call(at::TensorList self, at::TensorList out) { |
| 12783 | |
| 12784 | static auto op = create__foreach_sinh_out_typed_handle(); |
| 12785 | return op.call(self, out); |
| 12786 | } |
| 12787 | |
| 12788 | // aten::_foreach_sinh.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
| 12789 | void _foreach_sinh_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
| 12790 | |
| 12791 | static auto op = create__foreach_sinh_out_typed_handle(); |
| 12792 | return op.redispatch(dispatchKeySet, self, out); |
| 12793 | } |
| 12794 | |
| 12795 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Scalar_out, name, "aten::searchsorted") |
| 12796 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Scalar_out, overload_name, "Scalar_out") |
| 12797 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(searchsorted_Scalar_out, schema_str, "searchsorted.Scalar_out(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!)") |
| 12798 | |
| 12799 | // aten::searchsorted.Scalar_out(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) |
| 12800 | static C10_NOINLINE c10::TypedOperatorHandle<searchsorted_Scalar_out::schema> create_searchsorted_Scalar_out_typed_handle() { |
| 12801 | return c10::Dispatcher::singleton() |
| 12802 | .findSchemaOrThrow(searchsorted_Scalar_out::name, searchsorted_Scalar_out::overload_name) |
| 12803 | .typed<searchsorted_Scalar_out::schema>(); |
| 12804 | } |
| 12805 | |
| 12806 | // aten::searchsorted.Scalar_out(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) |
| 12807 | at::Tensor & searchsorted_Scalar_out::call(const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter, at::Tensor & out) { |
| 12808 | |
| 12809 | static auto op = create_searchsorted_Scalar_out_typed_handle(); |
| 12810 | return op.call(sorted_sequence, self, out_int32, right, side, sorter, out); |
| 12811 | } |
| 12812 | |
| 12813 | // aten::searchsorted.Scalar_out(Tensor sorted_sequence, Scalar self, *, bool out_int32=False, bool right=False, str? side=None, Tensor? sorter=None, Tensor(a!) out) -> Tensor(a!) |
| 12814 | at::Tensor & searchsorted_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sorted_sequence, const at::Scalar & self, bool out_int32, bool right, c10::optional<c10::string_view> side, const c10::optional<at::Tensor> & sorter, at::Tensor & out) { |
| 12815 | |
| 12816 | static auto op = create_searchsorted_Scalar_out_typed_handle(); |
| 12817 | return op.redispatch(dispatchKeySet, sorted_sequence, self, out_int32, right, side, sorter, out); |
| 12818 | } |
| 12819 | |
| 12820 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_out, name, "aten::_adaptive_avg_pool2d") |
| 12821 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_out, overload_name, "out") |
| 12822 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_out, schema_str, "_adaptive_avg_pool2d.out(Tensor self, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!)") |
| 12823 | |
| 12824 | // aten::_adaptive_avg_pool2d.out(Tensor self, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) |
| 12825 | static C10_NOINLINE c10::TypedOperatorHandle<_adaptive_avg_pool2d_out::schema> create__adaptive_avg_pool2d_out_typed_handle() { |
| 12826 | return c10::Dispatcher::singleton() |
| 12827 | .findSchemaOrThrow(_adaptive_avg_pool2d_out::name, _adaptive_avg_pool2d_out::overload_name) |
| 12828 | .typed<_adaptive_avg_pool2d_out::schema>(); |
| 12829 | } |
| 12830 | |
| 12831 | // aten::_adaptive_avg_pool2d.out(Tensor self, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) |
| 12832 | at::Tensor & _adaptive_avg_pool2d_out::call(const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out) { |
| 12833 | |
| 12834 | static auto op = create__adaptive_avg_pool2d_out_typed_handle(); |
| 12835 | return op.call(self, output_size, out); |
| 12836 | } |
| 12837 | |
| 12838 | // aten::_adaptive_avg_pool2d.out(Tensor self, SymInt[2] output_size, *, Tensor(a!) out) -> Tensor(a!) |
| 12839 | at::Tensor & _adaptive_avg_pool2d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, at::Tensor & out) { |
| 12840 | |
| 12841 | static auto op = create__adaptive_avg_pool2d_out_typed_handle(); |
| 12842 | return op.redispatch(dispatchKeySet, self, output_size, out); |
| 12843 | } |
| 12844 | |
| 12845 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_warn_in_autograd_out, name, "aten::_test_warn_in_autograd") |
| 12846 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_warn_in_autograd_out, overload_name, "out") |
| 12847 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_warn_in_autograd_out, schema_str, "_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12848 | |
| 12849 | // aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12850 | static C10_NOINLINE c10::TypedOperatorHandle<_test_warn_in_autograd_out::schema> create__test_warn_in_autograd_out_typed_handle() { |
| 12851 | return c10::Dispatcher::singleton() |
| 12852 | .findSchemaOrThrow(_test_warn_in_autograd_out::name, _test_warn_in_autograd_out::overload_name) |
| 12853 | .typed<_test_warn_in_autograd_out::schema>(); |
| 12854 | } |
| 12855 | |
| 12856 | // aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12857 | at::Tensor & _test_warn_in_autograd_out::call(const at::Tensor & self, at::Tensor & out) { |
| 12858 | |
| 12859 | static auto op = create__test_warn_in_autograd_out_typed_handle(); |
| 12860 | return op.call(self, out); |
| 12861 | } |
| 12862 | |
| 12863 | // aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12864 | at::Tensor & _test_warn_in_autograd_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 12865 | |
| 12866 | static auto op = create__test_warn_in_autograd_out_typed_handle(); |
| 12867 | return op.redispatch(dispatchKeySet, self, out); |
| 12868 | } |
| 12869 | |
| 12870 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_copy_out, name, "aten::diagonal_copy") |
| 12871 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_copy_out, overload_name, "out") |
| 12872 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_copy_out, schema_str, "diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 12873 | |
| 12874 | // aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12875 | static C10_NOINLINE c10::TypedOperatorHandle<diagonal_copy_out::schema> create_diagonal_copy_out_typed_handle() { |
| 12876 | return c10::Dispatcher::singleton() |
| 12877 | .findSchemaOrThrow(diagonal_copy_out::name, diagonal_copy_out::overload_name) |
| 12878 | .typed<diagonal_copy_out::schema>(); |
| 12879 | } |
| 12880 | |
| 12881 | // aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12882 | at::Tensor & diagonal_copy_out::call(const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out) { |
| 12883 | |
| 12884 | static auto op = create_diagonal_copy_out_typed_handle(); |
| 12885 | return op.call(self, offset, dim1, dim2, out); |
| 12886 | } |
| 12887 | |
| 12888 | // aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12889 | at::Tensor & diagonal_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out) { |
| 12890 | |
| 12891 | static auto op = create_diagonal_copy_out_typed_handle(); |
| 12892 | return op.redispatch(dispatchKeySet, self, offset, dim1, dim2, out); |
| 12893 | } |
| 12894 | |
| 12895 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(permute_copy_out, name, "aten::permute_copy") |
| 12896 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(permute_copy_out, overload_name, "out") |
| 12897 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(permute_copy_out, schema_str, "permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!)") |
| 12898 | |
| 12899 | // aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) |
| 12900 | static C10_NOINLINE c10::TypedOperatorHandle<permute_copy_out::schema> create_permute_copy_out_typed_handle() { |
| 12901 | return c10::Dispatcher::singleton() |
| 12902 | .findSchemaOrThrow(permute_copy_out::name, permute_copy_out::overload_name) |
| 12903 | .typed<permute_copy_out::schema>(); |
| 12904 | } |
| 12905 | |
| 12906 | // aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) |
| 12907 | at::Tensor & permute_copy_out::call(const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out) { |
| 12908 | |
| 12909 | static auto op = create_permute_copy_out_typed_handle(); |
| 12910 | return op.call(self, dims, out); |
| 12911 | } |
| 12912 | |
| 12913 | // aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) |
| 12914 | at::Tensor & permute_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dims, at::Tensor & out) { |
| 12915 | |
| 12916 | static auto op = create_permute_copy_out_typed_handle(); |
| 12917 | return op.redispatch(dispatchKeySet, self, dims, out); |
| 12918 | } |
| 12919 | |
| 12920 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_copy_int_out, name, "aten::select_copy") |
| 12921 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_copy_int_out, overload_name, "int_out") |
| 12922 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(select_copy_int_out, schema_str, "select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!)") |
| 12923 | |
| 12924 | // aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) |
| 12925 | static C10_NOINLINE c10::TypedOperatorHandle<select_copy_int_out::schema> create_select_copy_int_out_typed_handle() { |
| 12926 | return c10::Dispatcher::singleton() |
| 12927 | .findSchemaOrThrow(select_copy_int_out::name, select_copy_int_out::overload_name) |
| 12928 | .typed<select_copy_int_out::schema>(); |
| 12929 | } |
| 12930 | |
| 12931 | // aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) |
| 12932 | at::Tensor & select_copy_int_out::call(const at::Tensor & self, int64_t dim, c10::SymInt index, at::Tensor & out) { |
| 12933 | |
| 12934 | static auto op = create_select_copy_int_out_typed_handle(); |
| 12935 | return op.call(self, dim, index, out); |
| 12936 | } |
| 12937 | |
| 12938 | // aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) |
| 12939 | at::Tensor & select_copy_int_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::SymInt index, at::Tensor & out) { |
| 12940 | |
| 12941 | static auto op = create_select_copy_int_out_typed_handle(); |
| 12942 | return op.redispatch(dispatchKeySet, self, dim, index, out); |
| 12943 | } |
| 12944 | |
| 12945 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_copy_Tensor_out, name, "aten::slice_copy") |
| 12946 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_copy_Tensor_out, overload_name, "Tensor_out") |
| 12947 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slice_copy_Tensor_out, schema_str, "slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!)") |
| 12948 | |
| 12949 | // aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12950 | static C10_NOINLINE c10::TypedOperatorHandle<slice_copy_Tensor_out::schema> create_slice_copy_Tensor_out_typed_handle() { |
| 12951 | return c10::Dispatcher::singleton() |
| 12952 | .findSchemaOrThrow(slice_copy_Tensor_out::name, slice_copy_Tensor_out::overload_name) |
| 12953 | .typed<slice_copy_Tensor_out::schema>(); |
| 12954 | } |
| 12955 | |
| 12956 | // aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12957 | at::Tensor & slice_copy_Tensor_out::call(const at::Tensor & self, int64_t dim, c10::optional<c10::SymInt> start, c10::optional<c10::SymInt> end, c10::SymInt step, at::Tensor & out) { |
| 12958 | |
| 12959 | static auto op = create_slice_copy_Tensor_out_typed_handle(); |
| 12960 | return op.call(self, dim, start, end, step, out); |
| 12961 | } |
| 12962 | |
| 12963 | // aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) |
| 12964 | at::Tensor & slice_copy_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<c10::SymInt> start, c10::optional<c10::SymInt> end, c10::SymInt step, at::Tensor & out) { |
| 12965 | |
| 12966 | static auto op = create_slice_copy_Tensor_out_typed_handle(); |
| 12967 | return op.redispatch(dispatchKeySet, self, dim, start, end, step, out); |
| 12968 | } |
| 12969 | |
| 12970 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(t_copy_out, name, "aten::t_copy") |
| 12971 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(t_copy_out, overload_name, "out") |
| 12972 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(t_copy_out, schema_str, "t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12973 | |
| 12974 | // aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12975 | static C10_NOINLINE c10::TypedOperatorHandle<t_copy_out::schema> create_t_copy_out_typed_handle() { |
| 12976 | return c10::Dispatcher::singleton() |
| 12977 | .findSchemaOrThrow(t_copy_out::name, t_copy_out::overload_name) |
| 12978 | .typed<t_copy_out::schema>(); |
| 12979 | } |
| 12980 | |
| 12981 | // aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12982 | at::Tensor & t_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
| 12983 | |
| 12984 | static auto op = create_t_copy_out_typed_handle(); |
| 12985 | return op.call(self, out); |
| 12986 | } |
| 12987 | |
| 12988 | // aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 12989 | at::Tensor & t_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 12990 | |
| 12991 | static auto op = create_t_copy_out_typed_handle(); |
| 12992 | return op.redispatch(dispatchKeySet, self, out); |
| 12993 | } |
| 12994 | |
| 12995 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices_copy_out, name, "aten::col_indices_copy") |
| 12996 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices_copy_out, overload_name, "out") |
| 12997 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices_copy_out, schema_str, "col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 12998 | |
| 12999 | // aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13000 | static C10_NOINLINE c10::TypedOperatorHandle<col_indices_copy_out::schema> create_col_indices_copy_out_typed_handle() { |
| 13001 | return c10::Dispatcher::singleton() |
| 13002 | .findSchemaOrThrow(col_indices_copy_out::name, col_indices_copy_out::overload_name) |
| 13003 | .typed<col_indices_copy_out::schema>(); |
| 13004 | } |
| 13005 | |
| 13006 | // aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13007 | at::Tensor & col_indices_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
| 13008 | |
| 13009 | static auto op = create_col_indices_copy_out_typed_handle(); |
| 13010 | return op.call(self, out); |
| 13011 | } |
| 13012 | |
| 13013 | // aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13014 | at::Tensor & col_indices_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 13015 | |
| 13016 | static auto op = create_col_indices_copy_out_typed_handle(); |
| 13017 | return op.redispatch(dispatchKeySet, self, out); |
| 13018 | } |
| 13019 | |
| 13020 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alias_copy_out, name, "aten::alias_copy") |
| 13021 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alias_copy_out, overload_name, "out") |
| 13022 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(alias_copy_out, schema_str, "alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)") |
| 13023 | |
| 13024 | // aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13025 | static C10_NOINLINE c10::TypedOperatorHandle<alias_copy_out::schema> create_alias_copy_out_typed_handle() { |
| 13026 | return c10::Dispatcher::singleton() |
| 13027 | .findSchemaOrThrow(alias_copy_out::name, alias_copy_out::overload_name) |
| 13028 | .typed<alias_copy_out::schema>(); |
| 13029 | } |
| 13030 | |
| 13031 | // aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13032 | at::Tensor & alias_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
| 13033 | |
| 13034 | static auto op = create_alias_copy_out_typed_handle(); |
| 13035 | return op.call(self, out); |
| 13036 | } |
| 13037 | |
| 13038 | // aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
| 13039 | at::Tensor & alias_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
| 13040 | |
| 13041 | static auto op = create_alias_copy_out_typed_handle(); |
| 13042 | return op.redispatch(dispatchKeySet, self, out); |
| 13043 | } |
| 13044 | |
| 13045 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_triton_scaled_dot_attention_out, name, "aten::_triton_scaled_dot_attention") |
| 13046 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_triton_scaled_dot_attention_out, overload_name, "out") |
| 13047 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_triton_scaled_dot_attention_out, schema_str, "_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!)") |
| 13048 | |
| 13049 | // aten::_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!) |
| 13050 | static C10_NOINLINE c10::TypedOperatorHandle<_triton_scaled_dot_attention_out::schema> create__triton_scaled_dot_attention_out_typed_handle() { |
| 13051 | return c10::Dispatcher::singleton() |
| 13052 | .findSchemaOrThrow(_triton_scaled_dot_attention_out::name, _triton_scaled_dot_attention_out::overload_name) |
| 13053 | .typed<_triton_scaled_dot_attention_out::schema>(); |
| 13054 | } |
| 13055 | |
| 13056 | // aten::_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!) |
| 13057 | at::Tensor & _triton_scaled_dot_attention_out::call(const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p, at::Tensor & out) { |
| 13058 | |
| 13059 | static auto op = create__triton_scaled_dot_attention_out_typed_handle(); |
| 13060 | return op.call(q, k, v, dropout_p, out); |
| 13061 | } |
| 13062 | |
| 13063 | // aten::_triton_scaled_dot_attention.out(Tensor q, Tensor k, Tensor v, float dropout_p=0.0, *, Tensor(a!) out) -> Tensor(a!) |
| 13064 | at::Tensor & _triton_scaled_dot_attention_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & q, const at::Tensor & k, const at::Tensor & v, double dropout_p, at::Tensor & out) { |
| 13065 | |
| 13066 | static auto op = create__triton_scaled_dot_attention_out_typed_handle(); |
| 13067 | return op.redispatch(dispatchKeySet, q, k, v, dropout_p, out); |
| 13068 | } |
| 13069 | |
| 13070 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foobar_out, name, "aten::_foobar") |
| 13071 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foobar_out, overload_name, "out") |
| 13072 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foobar_out, schema_str, "_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!)") |
| 13073 | |
| 13074 | // aten::_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!) |
| 13075 | static C10_NOINLINE c10::TypedOperatorHandle<_foobar_out::schema> create__foobar_out_typed_handle() { |
| 13076 | return c10::Dispatcher::singleton() |
| 13077 | .findSchemaOrThrow(_foobar_out::name, _foobar_out::overload_name) |
| 13078 | .typed<_foobar_out::schema>(); |
| 13079 | } |
| 13080 | |
| 13081 | // aten::_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!) |
| 13082 | at::Tensor & _foobar_out::call(const at::Tensor & self, bool arg1, bool arg2, bool arg3, at::Tensor & out) { |
| 13083 | |
| 13084 | static auto op = create__foobar_out_typed_handle(); |
| 13085 | return op.call(self, arg1, arg2, arg3, out); |
| 13086 | } |
| 13087 | |
| 13088 | // aten::_foobar.out(Tensor self, bool arg1=True, bool arg2=True, *, bool arg3=True, Tensor(a!) out) -> Tensor(a!) |
| 13089 | at::Tensor & _foobar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool arg1, bool arg2, bool arg3, at::Tensor & out) { |
| 13090 | |
| 13091 | static auto op = create__foobar_out_typed_handle(); |
| 13092 | return op.redispatch(dispatchKeySet, self, arg1, arg2, arg3, out); |
| 13093 | } |
| 13094 | |
| 13095 | }} // namespace at::_ops |
| 13096 |
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