1 | #include <ATen/Tensor.h> |
2 | #include <ATen/core/dispatch/Dispatcher.h> |
3 | |
4 | // @generated by torchgen/gen.py from Operators.cpp |
5 | // NOTE See [Sharded File] comment in VariableType |
6 | |
7 | #ifndef AT_PER_OPERATOR_HEADERS |
8 | #include <ATen/Operators.h> |
9 | #else |
10 | #include <ATen/ops/_cast_Short.h> |
11 | #include <ATen/ops/output_nr.h> |
12 | #include <ATen/ops/_new_zeros_with_same_feature_meta.h> |
13 | #include <ATen/ops/_cudnn_init_dropout_state.h> |
14 | #include <ATen/ops/native_dropout.h> |
15 | #include <ATen/ops/absolute.h> |
16 | #include <ATen/ops/absolute.h> |
17 | #include <ATen/ops/absolute.h> |
18 | #include <ATen/ops/angle.h> |
19 | #include <ATen/ops/angle.h> |
20 | #include <ATen/ops/add.h> |
21 | #include <ATen/ops/add.h> |
22 | #include <ATen/ops/add.h> |
23 | #include <ATen/ops/add.h> |
24 | #include <ATen/ops/add.h> |
25 | #include <ATen/ops/all.h> |
26 | #include <ATen/ops/all.h> |
27 | #include <ATen/ops/all.h> |
28 | #include <ATen/ops/all.h> |
29 | #include <ATen/ops/asinh.h> |
30 | #include <ATen/ops/asinh.h> |
31 | #include <ATen/ops/asinh.h> |
32 | #include <ATen/ops/atleast_2d.h> |
33 | #include <ATen/ops/atleast_2d.h> |
34 | #include <ATen/ops/baddbmm.h> |
35 | #include <ATen/ops/baddbmm.h> |
36 | #include <ATen/ops/baddbmm.h> |
37 | #include <ATen/ops/batch_norm.h> |
38 | #include <ATen/ops/bernoulli.h> |
39 | #include <ATen/ops/bernoulli.h> |
40 | #include <ATen/ops/bernoulli.h> |
41 | #include <ATen/ops/bernoulli.h> |
42 | #include <ATen/ops/bernoulli.h> |
43 | #include <ATen/ops/bilinear.h> |
44 | #include <ATen/ops/binary_cross_entropy_with_logits.h> |
45 | #include <ATen/ops/bincount.h> |
46 | #include <ATen/ops/logical_and.h> |
47 | #include <ATen/ops/logical_and.h> |
48 | #include <ATen/ops/logical_and.h> |
49 | #include <ATen/ops/block_diag.h> |
50 | #include <ATen/ops/unsafe_chunk.h> |
51 | #include <ATen/ops/chunk.h> |
52 | #include <ATen/ops/tensor_split.h> |
53 | #include <ATen/ops/tensor_split.h> |
54 | #include <ATen/ops/tensor_split.h> |
55 | #include <ATen/ops/clamp.h> |
56 | #include <ATen/ops/clamp.h> |
57 | #include <ATen/ops/clamp.h> |
58 | #include <ATen/ops/clamp.h> |
59 | #include <ATen/ops/clamp.h> |
60 | #include <ATen/ops/clamp.h> |
61 | #include <ATen/ops/clamp_max.h> |
62 | #include <ATen/ops/clamp_max.h> |
63 | #include <ATen/ops/clamp_max.h> |
64 | #include <ATen/ops/clamp_max.h> |
65 | #include <ATen/ops/clamp_max.h> |
66 | #include <ATen/ops/clamp_max.h> |
67 | #include <ATen/ops/clip.h> |
68 | #include <ATen/ops/clip.h> |
69 | #include <ATen/ops/clip.h> |
70 | #include <ATen/ops/clip.h> |
71 | #include <ATen/ops/clip.h> |
72 | #include <ATen/ops/clip.h> |
73 | #include <ATen/ops/cudnn_is_acceptable.h> |
74 | #include <ATen/ops/complex.h> |
75 | #include <ATen/ops/complex.h> |
76 | #include <ATen/ops/polar.h> |
77 | #include <ATen/ops/polar.h> |
78 | #include <ATen/ops/conv_transpose2d.h> |
79 | #include <ATen/ops/count_nonzero.h> |
80 | #include <ATen/ops/count_nonzero.h> |
81 | #include <ATen/ops/cov.h> |
82 | #include <ATen/ops/cudnn_convolution_add_relu.h> |
83 | #include <ATen/ops/cummax.h> |
84 | #include <ATen/ops/cummax.h> |
85 | #include <ATen/ops/cummax.h> |
86 | #include <ATen/ops/cummax.h> |
87 | #include <ATen/ops/_cummax_helper.h> |
88 | #include <ATen/ops/_ctc_loss_backward.h> |
89 | #include <ATen/ops/_ctc_loss_backward.h> |
90 | #include <ATen/ops/diagonal_backward.h> |
91 | #include <ATen/ops/diff.h> |
92 | #include <ATen/ops/diff.h> |
93 | #include <ATen/ops/gradient.h> |
94 | #include <ATen/ops/gradient.h> |
95 | #include <ATen/ops/gradient.h> |
96 | #include <ATen/ops/gradient.h> |
97 | #include <ATen/ops/gradient.h> |
98 | #include <ATen/ops/gradient.h> |
99 | #include <ATen/ops/gradient.h> |
100 | #include <ATen/ops/dot.h> |
101 | #include <ATen/ops/dot.h> |
102 | #include <ATen/ops/einsum.h> |
103 | #include <ATen/ops/embedding_renorm.h> |
104 | #include <ATen/ops/embedding_sparse_backward.h> |
105 | #include <ATen/ops/_embedding_bag_per_sample_weights_backward.h> |
106 | #include <ATen/ops/empty.h> |
107 | #include <ATen/ops/empty.h> |
108 | #include <ATen/ops/new_empty_strided.h> |
109 | #include <ATen/ops/new_full.h> |
110 | #include <ATen/ops/new_ones.h> |
111 | #include <ATen/ops/_empty_per_channel_affine_quantized.h> |
112 | #include <ATen/ops/empty_quantized.h> |
113 | #include <ATen/ops/empty.h> |
114 | #include <ATen/ops/empty_strided.h> |
115 | #include <ATen/ops/exp.h> |
116 | #include <ATen/ops/exp.h> |
117 | #include <ATen/ops/exp.h> |
118 | #include <ATen/ops/exp2.h> |
119 | #include <ATen/ops/exp2.h> |
120 | #include <ATen/ops/exp2.h> |
121 | #include <ATen/ops/eye.h> |
122 | #include <ATen/ops/eye.h> |
123 | #include <ATen/ops/eye.h> |
124 | #include <ATen/ops/eye.h> |
125 | #include <ATen/ops/frac.h> |
126 | #include <ATen/ops/frac.h> |
127 | #include <ATen/ops/frac.h> |
128 | #include <ATen/ops/from_file.h> |
129 | #include <ATen/ops/gcd.h> |
130 | #include <ATen/ops/gcd.h> |
131 | #include <ATen/ops/gcd.h> |
132 | #include <ATen/ops/_cufft_clear_plan_cache.h> |
133 | #include <ATen/ops/isin.h> |
134 | #include <ATen/ops/isin.h> |
135 | #include <ATen/ops/isin.h> |
136 | #include <ATen/ops/isin.h> |
137 | #include <ATen/ops/isin.h> |
138 | #include <ATen/ops/isin.h> |
139 | #include <ATen/ops/is_conj.h> |
140 | #include <ATen/ops/_is_zerotensor.h> |
141 | #include <ATen/ops/is_nonzero.h> |
142 | #include <ATen/ops/is_signed.h> |
143 | #include <ATen/ops/layer_norm.h> |
144 | #include <ATen/ops/native_layer_norm_backward.h> |
145 | #include <ATen/ops/fbgemm_linear_fp16_weight.h> |
146 | #include <ATen/ops/fbgemm_pack_quantized_matrix.h> |
147 | #include <ATen/ops/fbgemm_pack_quantized_matrix.h> |
148 | #include <ATen/ops/ldexp.h> |
149 | #include <ATen/ops/ldexp.h> |
150 | #include <ATen/ops/ldexp.h> |
151 | #include <ATen/ops/log.h> |
152 | #include <ATen/ops/log.h> |
153 | #include <ATen/ops/log.h> |
154 | #include <ATen/ops/log2.h> |
155 | #include <ATen/ops/log2.h> |
156 | #include <ATen/ops/log2.h> |
157 | #include <ATen/ops/logaddexp.h> |
158 | #include <ATen/ops/logaddexp.h> |
159 | #include <ATen/ops/logspace.h> |
160 | #include <ATen/ops/logspace.h> |
161 | #include <ATen/ops/log_softmax.h> |
162 | #include <ATen/ops/log_softmax.h> |
163 | #include <ATen/ops/log_softmax.h> |
164 | #include <ATen/ops/matrix_power.h> |
165 | #include <ATen/ops/matrix_power.h> |
166 | #include <ATen/ops/mps_max_pool2d_backward.h> |
167 | #include <ATen/ops/mkldnn_max_pool3d.h> |
168 | #include <ATen/ops/mps_convolution_backward.h> |
169 | #include <ATen/ops/mkldnn_rnn_layer.h> |
170 | #include <ATen/ops/miopen_convolution.h> |
171 | #include <ATen/ops/miopen_rnn.h> |
172 | #include <ATen/ops/_sparse_mm.h> |
173 | #include <ATen/ops/_sparse_mm.h> |
174 | #include <ATen/ops/_sparse_sparse_matmul.h> |
175 | #include <ATen/ops/_native_batch_norm_legit.h> |
176 | #include <ATen/ops/_native_batch_norm_legit.h> |
177 | #include <ATen/ops/_native_batch_norm_legit.h> |
178 | #include <ATen/ops/_native_batch_norm_legit.h> |
179 | #include <ATen/ops/batch_norm_update_stats.h> |
180 | #include <ATen/ops/_nnpack_available.h> |
181 | #include <ATen/ops/ones_like.h> |
182 | #include <ATen/ops/_euclidean_dist.h> |
183 | #include <ATen/ops/_cdist_backward.h> |
184 | #include <ATen/ops/_pdist_forward.h> |
185 | #include <ATen/ops/native_channel_shuffle.h> |
186 | #include <ATen/ops/rad2deg.h> |
187 | #include <ATen/ops/rad2deg.h> |
188 | #include <ATen/ops/rad2deg.h> |
189 | #include <ATen/ops/scalar_tensor.h> |
190 | #include <ATen/ops/rand.h> |
191 | #include <ATen/ops/rand.h> |
192 | #include <ATen/ops/rand.h> |
193 | #include <ATen/ops/rand.h> |
194 | #include <ATen/ops/rand.h> |
195 | #include <ATen/ops/rand.h> |
196 | #include <ATen/ops/randint.h> |
197 | #include <ATen/ops/randint.h> |
198 | #include <ATen/ops/randint.h> |
199 | #include <ATen/ops/randint.h> |
200 | #include <ATen/ops/randint.h> |
201 | #include <ATen/ops/randint.h> |
202 | #include <ATen/ops/randint.h> |
203 | #include <ATen/ops/randint.h> |
204 | #include <ATen/ops/randn_like.h> |
205 | #include <ATen/ops/repeat.h> |
206 | #include <ATen/ops/repeat_interleave.h> |
207 | #include <ATen/ops/repeat_interleave.h> |
208 | #include <ATen/ops/repeat_interleave.h> |
209 | #include <ATen/ops/_mkldnn_reshape.h> |
210 | #include <ATen/ops/_prelu_kernel.h> |
211 | #include <ATen/ops/rsqrt.h> |
212 | #include <ATen/ops/rsqrt.h> |
213 | #include <ATen/ops/rsqrt.h> |
214 | #include <ATen/ops/_nested_select_backward.h> |
215 | #include <ATen/ops/vsplit.h> |
216 | #include <ATen/ops/vsplit.h> |
217 | #include <ATen/ops/hstack.h> |
218 | #include <ATen/ops/hstack.h> |
219 | #include <ATen/ops/istft.h> |
220 | #include <ATen/ops/sum.h> |
221 | #include <ATen/ops/sum.h> |
222 | #include <ATen/ops/sum.h> |
223 | #include <ATen/ops/sum.h> |
224 | #include <ATen/ops/sum.h> |
225 | #include <ATen/ops/nansum.h> |
226 | #include <ATen/ops/nansum.h> |
227 | #include <ATen/ops/flipud.h> |
228 | #include <ATen/ops/rot90.h> |
229 | #include <ATen/ops/trapz.h> |
230 | #include <ATen/ops/trapz.h> |
231 | #include <ATen/ops/_nested_tensor_strides.h> |
232 | #include <ATen/ops/_nested_tensor_offsets.h> |
233 | #include <ATen/ops/triplet_margin_loss.h> |
234 | #include <ATen/ops/trunc.h> |
235 | #include <ATen/ops/trunc.h> |
236 | #include <ATen/ops/trunc.h> |
237 | #include <ATen/ops/var.h> |
238 | #include <ATen/ops/var.h> |
239 | #include <ATen/ops/var.h> |
240 | #include <ATen/ops/var.h> |
241 | #include <ATen/ops/var.h> |
242 | #include <ATen/ops/var.h> |
243 | #include <ATen/ops/var.h> |
244 | #include <ATen/ops/var.h> |
245 | #include <ATen/ops/var.h> |
246 | #include <ATen/ops/var_mean.h> |
247 | #include <ATen/ops/var_mean.h> |
248 | #include <ATen/ops/var_mean.h> |
249 | #include <ATen/ops/var_mean.h> |
250 | #include <ATen/ops/var_mean.h> |
251 | #include <ATen/ops/norm_except_dim.h> |
252 | #include <ATen/ops/_standard_gamma_grad.h> |
253 | #include <ATen/ops/native_norm.h> |
254 | #include <ATen/ops/native_norm.h> |
255 | #include <ATen/ops/_sparse_sum_backward.h> |
256 | #include <ATen/ops/_sparse_csr_sum.h> |
257 | #include <ATen/ops/_sparse_softmax.h> |
258 | #include <ATen/ops/_sparse_softmax.h> |
259 | #include <ATen/ops/_sparse_softmax.h> |
260 | #include <ATen/ops/norm.h> |
261 | #include <ATen/ops/norm.h> |
262 | #include <ATen/ops/norm.h> |
263 | #include <ATen/ops/norm.h> |
264 | #include <ATen/ops/norm.h> |
265 | #include <ATen/ops/norm.h> |
266 | #include <ATen/ops/norm.h> |
267 | #include <ATen/ops/norm.h> |
268 | #include <ATen/ops/norm.h> |
269 | #include <ATen/ops/norm.h> |
270 | #include <ATen/ops/nuclear_norm.h> |
271 | #include <ATen/ops/nuclear_norm.h> |
272 | #include <ATen/ops/nuclear_norm.h> |
273 | #include <ATen/ops/nuclear_norm.h> |
274 | #include <ATen/ops/_sparse_csc_tensor_unsafe.h> |
275 | #include <ATen/ops/_validate_sparse_coo_tensor_args.h> |
276 | #include <ATen/ops/_sparse_coo_tensor_with_dims_and_tensors.h> |
277 | #include <ATen/ops/_to_dense.h> |
278 | #include <ATen/ops/is_coalesced.h> |
279 | #include <ATen/ops/_coalesced.h> |
280 | #include <ATen/ops/indices.h> |
281 | #include <ATen/ops/col_indices.h> |
282 | #include <ATen/ops/hspmm.h> |
283 | #include <ATen/ops/hspmm.h> |
284 | #include <ATen/ops/to_sparse_bsc.h> |
285 | #include <ATen/ops/quantize_per_tensor_dynamic.h> |
286 | #include <ATen/ops/quantize_per_tensor.h> |
287 | #include <ATen/ops/quantize_per_tensor.h> |
288 | #include <ATen/ops/quantize_per_tensor.h> |
289 | #include <ATen/ops/fake_quantize_per_tensor_affine_cachemask.h> |
290 | #include <ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.h> |
291 | #include <ATen/ops/_fake_quantize_learnable_per_tensor_affine.h> |
292 | #include <ATen/ops/choose_qparams_optimized.h> |
293 | #include <ATen/ops/cartesian_prod.h> |
294 | #include <ATen/ops/promote_types.h> |
295 | #include <ATen/ops/_local_scalar_dense.h> |
296 | #include <ATen/ops/_thnn_fused_gru_cell_backward.h> |
297 | #include <ATen/ops/rnn_relu.h> |
298 | #include <ATen/ops/rnn_relu.h> |
299 | #include <ATen/ops/gru_cell.h> |
300 | #include <ATen/ops/quantized_lstm_cell.h> |
301 | #include <ATen/ops/set.h> |
302 | #include <ATen/ops/set.h> |
303 | #include <ATen/ops/set.h> |
304 | #include <ATen/ops/set.h> |
305 | #include <ATen/ops/set.h> |
306 | #include <ATen/ops/put.h> |
307 | #include <ATen/ops/put.h> |
308 | #include <ATen/ops/scatter.h> |
309 | #include <ATen/ops/scatter.h> |
310 | #include <ATen/ops/scatter.h> |
311 | #include <ATen/ops/scatter.h> |
312 | #include <ATen/ops/scatter.h> |
313 | #include <ATen/ops/scatter.h> |
314 | #include <ATen/ops/scatter.h> |
315 | #include <ATen/ops/scatter.h> |
316 | #include <ATen/ops/scatter.h> |
317 | #include <ATen/ops/scatter.h> |
318 | #include <ATen/ops/scatter.h> |
319 | #include <ATen/ops/scatter.h> |
320 | #include <ATen/ops/scatter.h> |
321 | #include <ATen/ops/scatter.h> |
322 | #include <ATen/ops/scatter_reduce.h> |
323 | #include <ATen/ops/scatter_reduce.h> |
324 | #include <ATen/ops/scatter_reduce.h> |
325 | #include <ATen/ops/and.h> |
326 | #include <ATen/ops/and.h> |
327 | #include <ATen/ops/and.h> |
328 | #include <ATen/ops/and.h> |
329 | #include <ATen/ops/tril.h> |
330 | #include <ATen/ops/uniform.h> |
331 | #include <ATen/ops/tril.h> |
332 | #include <ATen/ops/tril.h> |
333 | #include <ATen/ops/tril_indices.h> |
334 | #include <ATen/ops/less_equal.h> |
335 | #include <ATen/ops/less_equal.h> |
336 | #include <ATen/ops/less_equal.h> |
337 | #include <ATen/ops/less_equal.h> |
338 | #include <ATen/ops/less_equal.h> |
339 | #include <ATen/ops/less_equal.h> |
340 | #include <ATen/ops/gt.h> |
341 | #include <ATen/ops/gt.h> |
342 | #include <ATen/ops/gt.h> |
343 | #include <ATen/ops/gt.h> |
344 | #include <ATen/ops/gt.h> |
345 | #include <ATen/ops/gt.h> |
346 | #include <ATen/ops/lt.h> |
347 | #include <ATen/ops/lt.h> |
348 | #include <ATen/ops/lt.h> |
349 | #include <ATen/ops/lt.h> |
350 | #include <ATen/ops/lt.h> |
351 | #include <ATen/ops/lt.h> |
352 | #include <ATen/ops/less.h> |
353 | #include <ATen/ops/less.h> |
354 | #include <ATen/ops/less.h> |
355 | #include <ATen/ops/less.h> |
356 | #include <ATen/ops/less.h> |
357 | #include <ATen/ops/less.h> |
358 | #include <ATen/ops/masked_select.h> |
359 | #include <ATen/ops/masked_select.h> |
360 | #include <ATen/ops/addcdiv.h> |
361 | #include <ATen/ops/addcdiv.h> |
362 | #include <ATen/ops/addcdiv.h> |
363 | #include <ATen/ops/_cholesky_solve_helper.h> |
364 | #include <ATen/ops/cholesky_inverse.h> |
365 | #include <ATen/ops/cholesky_inverse.h> |
366 | #include <ATen/ops/_lu_with_info.h> |
367 | #include <ATen/ops/atan2.h> |
368 | #include <ATen/ops/atan2.h> |
369 | #include <ATen/ops/atan2.h> |
370 | #include <ATen/ops/histogramdd.h> |
371 | #include <ATen/ops/histogramdd.h> |
372 | #include <ATen/ops/histogramdd.h> |
373 | #include <ATen/ops/hypot.h> |
374 | #include <ATen/ops/hypot.h> |
375 | #include <ATen/ops/hypot.h> |
376 | #include <ATen/ops/igammac.h> |
377 | #include <ATen/ops/igammac.h> |
378 | #include <ATen/ops/igammac.h> |
379 | #include <ATen/ops/fmax.h> |
380 | #include <ATen/ops/fmax.h> |
381 | #include <ATen/ops/sort.h> |
382 | #include <ATen/ops/sort.h> |
383 | #include <ATen/ops/sort.h> |
384 | #include <ATen/ops/sort.h> |
385 | #include <ATen/ops/sort.h> |
386 | #include <ATen/ops/sort.h> |
387 | #include <ATen/ops/sort.h> |
388 | #include <ATen/ops/sort.h> |
389 | #include <ATen/ops/all.h> |
390 | #include <ATen/ops/all.h> |
391 | #include <ATen/ops/_amp_update_scale.h> |
392 | #include <ATen/ops/_foreach_exp.h> |
393 | #include <ATen/ops/_foreach_exp.h> |
394 | #include <ATen/ops/_foreach_sqrt.h> |
395 | #include <ATen/ops/_foreach_sqrt.h> |
396 | #include <ATen/ops/_foreach_log.h> |
397 | #include <ATen/ops/_foreach_log.h> |
398 | #include <ATen/ops/_foreach_log1p.h> |
399 | #include <ATen/ops/_foreach_log1p.h> |
400 | #include <ATen/ops/_foreach_neg.h> |
401 | #include <ATen/ops/_foreach_neg.h> |
402 | #include <ATen/ops/_foreach_sin.h> |
403 | #include <ATen/ops/_foreach_sin.h> |
404 | #include <ATen/ops/_foreach_reciprocal.h> |
405 | #include <ATen/ops/_foreach_reciprocal.h> |
406 | #include <ATen/ops/_foreach_sigmoid.h> |
407 | #include <ATen/ops/_foreach_sigmoid.h> |
408 | #include <ATen/ops/_foreach_addcdiv.h> |
409 | #include <ATen/ops/_foreach_addcdiv.h> |
410 | #include <ATen/ops/_foreach_addcdiv.h> |
411 | #include <ATen/ops/_foreach_addcdiv.h> |
412 | #include <ATen/ops/_foreach_addcdiv.h> |
413 | #include <ATen/ops/_foreach_addcdiv.h> |
414 | #include <ATen/ops/_foreach_norm.h> |
415 | #include <ATen/ops/_convert_indices_from_coo_to_csr.h> |
416 | #include <ATen/ops/_convert_indices_from_coo_to_csr.h> |
417 | #include <ATen/ops/multi_margin_loss.h> |
418 | #include <ATen/ops/multi_margin_loss.h> |
419 | #include <ATen/ops/multilabel_margin_loss.h> |
420 | #include <ATen/ops/multilabel_margin_loss.h> |
421 | #include <ATen/ops/multilabel_margin_loss_forward.h> |
422 | #include <ATen/ops/multilabel_margin_loss_forward.h> |
423 | #include <ATen/ops/nll_loss_forward.h> |
424 | #include <ATen/ops/nll_loss_forward.h> |
425 | #include <ATen/ops/soft_margin_loss_backward.h> |
426 | #include <ATen/ops/soft_margin_loss_backward.h> |
427 | #include <ATen/ops/glu_jvp.h> |
428 | #include <ATen/ops/hardswish.h> |
429 | #include <ATen/ops/hardswish.h> |
430 | #include <ATen/ops/hardswish.h> |
431 | #include <ATen/ops/rrelu_with_noise.h> |
432 | #include <ATen/ops/rrelu_with_noise.h> |
433 | #include <ATen/ops/rrelu_with_noise.h> |
434 | #include <ATen/ops/softshrink_backward.h> |
435 | #include <ATen/ops/softshrink_backward.h> |
436 | #include <ATen/ops/_adaptive_avg_pool2d_backward.h> |
437 | #include <ATen/ops/avg_pool2d.h> |
438 | #include <ATen/ops/avg_pool2d.h> |
439 | #include <ATen/ops/fractional_max_pool2d_backward.h> |
440 | #include <ATen/ops/fractional_max_pool2d_backward.h> |
441 | #include <ATen/ops/max_pool3d_with_indices_backward.h> |
442 | #include <ATen/ops/max_pool3d_with_indices_backward.h> |
443 | #include <ATen/ops/reflection_pad1d_backward.h> |
444 | #include <ATen/ops/reflection_pad1d_backward.h> |
445 | #include <ATen/ops/reflection_pad2d_backward.h> |
446 | #include <ATen/ops/reflection_pad2d_backward.h> |
447 | #include <ATen/ops/replication_pad1d_backward.h> |
448 | #include <ATen/ops/replication_pad1d_backward.h> |
449 | #include <ATen/ops/replication_pad3d_backward.h> |
450 | #include <ATen/ops/replication_pad3d_backward.h> |
451 | #include <ATen/ops/_upsample_nearest_exact2d.h> |
452 | #include <ATen/ops/_upsample_nearest_exact3d.h> |
453 | #include <ATen/ops/upsample_bilinear2d_backward.h> |
454 | #include <ATen/ops/upsample_bilinear2d_backward.h> |
455 | #include <ATen/ops/_upsample_bicubic2d_aa_backward.h> |
456 | #include <ATen/ops/_upsample_bicubic2d_aa_backward.h> |
457 | #include <ATen/ops/_upsample_nearest_exact1d_backward.h> |
458 | #include <ATen/ops/_upsample_nearest_exact1d_backward.h> |
459 | #include <ATen/ops/_upsample_nearest_exact2d.h> |
460 | #include <ATen/ops/_upsample_nearest_exact2d.h> |
461 | #include <ATen/ops/_upsample_nearest_exact2d_backward.h> |
462 | #include <ATen/ops/_upsample_nearest_exact2d_backward.h> |
463 | #include <ATen/ops/_upsample_nearest_exact3d.h> |
464 | #include <ATen/ops/_upsample_nearest_exact3d.h> |
465 | #include <ATen/ops/slow_conv_dilated3d.h> |
466 | #include <ATen/ops/isinf.h> |
467 | #include <ATen/ops/special_digamma.h> |
468 | #include <ATen/ops/special_digamma.h> |
469 | #include <ATen/ops/special_ndtr.h> |
470 | #include <ATen/ops/special_ndtr.h> |
471 | #include <ATen/ops/special_zeta.h> |
472 | #include <ATen/ops/special_zeta.h> |
473 | #include <ATen/ops/special_zeta.h> |
474 | #include <ATen/ops/special_zeta.h> |
475 | #include <ATen/ops/special_zeta.h> |
476 | #include <ATen/ops/special_zeta.h> |
477 | #include <ATen/ops/special_round.h> |
478 | #include <ATen/ops/special_round.h> |
479 | #include <ATen/ops/fft_ifft.h> |
480 | #include <ATen/ops/fft_ifft.h> |
481 | #include <ATen/ops/fft_hfft.h> |
482 | #include <ATen/ops/fft_hfft.h> |
483 | #include <ATen/ops/fft_ihfft.h> |
484 | #include <ATen/ops/fft_ihfft.h> |
485 | #include <ATen/ops/fft_ihfft2.h> |
486 | #include <ATen/ops/fft_ihfft2.h> |
487 | #include <ATen/ops/fft_irfftn.h> |
488 | #include <ATen/ops/fft_irfftn.h> |
489 | #include <ATen/ops/fft_ifftshift.h> |
490 | #include <ATen/ops/slogdet.h> |
491 | #include <ATen/ops/slogdet.h> |
492 | #include <ATen/ops/linalg_eig.h> |
493 | #include <ATen/ops/linalg_eig.h> |
494 | #include <ATen/ops/linalg_eigh.h> |
495 | #include <ATen/ops/linalg_eigh.h> |
496 | #include <ATen/ops/linalg_eigvalsh.h> |
497 | #include <ATen/ops/linalg_eigvalsh.h> |
498 | #include <ATen/ops/linalg_householder_product.h> |
499 | #include <ATen/ops/linalg_householder_product.h> |
500 | #include <ATen/ops/linalg_matrix_norm.h> |
501 | #include <ATen/ops/linalg_matrix_norm.h> |
502 | #include <ATen/ops/linalg_matrix_norm.h> |
503 | #include <ATen/ops/linalg_matrix_norm.h> |
504 | #include <ATen/ops/linalg_svd.h> |
505 | #include <ATen/ops/linalg_svd.h> |
506 | #include <ATen/ops/_test_optional_floatlist.h> |
507 | #include <ATen/ops/unflatten_dense_tensors.h> |
508 | #include <ATen/ops/_nested_tensor_from_tensor_list.h> |
509 | #include <ATen/ops/_sparse_broadcast_to_copy.h> |
510 | #include <ATen/ops/transpose_copy.h> |
511 | #include <ATen/ops/_indices_copy.h> |
512 | #include <ATen/ops/_values_copy.h> |
513 | #include <ATen/ops/values_copy.h> |
514 | #include <ATen/ops/view_copy.h> |
515 | #include <ATen/ops/view_copy.h> |
516 | #include <ATen/ops/unfold_copy.h> |
517 | #include <ATen/ops/scaled_dot_product_attention.h> |
518 | #include <ATen/ops/_native_decoder_only_multi_head_attention.h> |
519 | #include <ATen/ops/special_bessel_y1.h> |
520 | #include <ATen/ops/special_bessel_y1.h> |
521 | #include <ATen/ops/special_laguerre_polynomial_l.h> |
522 | #include <ATen/ops/special_laguerre_polynomial_l.h> |
523 | #include <ATen/ops/special_laguerre_polynomial_l.h> |
524 | #include <ATen/ops/special_laguerre_polynomial_l.h> |
525 | #include <ATen/ops/special_laguerre_polynomial_l.h> |
526 | #include <ATen/ops/special_laguerre_polynomial_l.h> |
527 | #include <ATen/ops/special_legendre_polynomial_p.h> |
528 | #include <ATen/ops/special_legendre_polynomial_p.h> |
529 | #include <ATen/ops/special_legendre_polynomial_p.h> |
530 | #include <ATen/ops/special_legendre_polynomial_p.h> |
531 | #include <ATen/ops/special_legendre_polynomial_p.h> |
532 | #include <ATen/ops/special_legendre_polynomial_p.h> |
533 | #include <ATen/ops/special_scaled_modified_bessel_k0.h> |
534 | #include <ATen/ops/special_scaled_modified_bessel_k0.h> |
535 | #include <ATen/ops/special_shifted_chebyshev_polynomial_u.h> |
536 | #include <ATen/ops/special_shifted_chebyshev_polynomial_u.h> |
537 | #include <ATen/ops/special_shifted_chebyshev_polynomial_u.h> |
538 | #include <ATen/ops/special_shifted_chebyshev_polynomial_u.h> |
539 | #include <ATen/ops/special_shifted_chebyshev_polynomial_u.h> |
540 | #include <ATen/ops/special_shifted_chebyshev_polynomial_u.h> |
541 | #include <ATen/ops/_fused_adam.h> |
542 | #include <ATen/ops/_new_zeros_with_same_feature_meta.h> |
543 | #include <ATen/ops/_cudnn_init_dropout_state.h> |
544 | #include <ATen/ops/native_dropout.h> |
545 | #include <ATen/ops/add.h> |
546 | #include <ATen/ops/bernoulli.h> |
547 | #include <ATen/ops/bernoulli.h> |
548 | #include <ATen/ops/bernoulli.h> |
549 | #include <ATen/ops/binary_cross_entropy_with_logits.h> |
550 | #include <ATen/ops/bincount.h> |
551 | #include <ATen/ops/block_diag.h> |
552 | #include <ATen/ops/count_nonzero.h> |
553 | #include <ATen/ops/count_nonzero.h> |
554 | #include <ATen/ops/cudnn_convolution_add_relu.h> |
555 | #include <ATen/ops/_ctc_loss_backward.h> |
556 | #include <ATen/ops/diagonal_backward.h> |
557 | #include <ATen/ops/embedding_renorm.h> |
558 | #include <ATen/ops/embedding_renorm.h> |
559 | #include <ATen/ops/_embedding_bag_per_sample_weights_backward.h> |
560 | #include <ATen/ops/empty.h> |
561 | #include <ATen/ops/new_empty_strided.h> |
562 | #include <ATen/ops/new_full.h> |
563 | #include <ATen/ops/new_ones.h> |
564 | #include <ATen/ops/_empty_per_channel_affine_quantized.h> |
565 | #include <ATen/ops/empty_quantized.h> |
566 | #include <ATen/ops/empty_strided.h> |
567 | #include <ATen/ops/from_file.h> |
568 | #include <ATen/ops/native_layer_norm_backward.h> |
569 | #include <ATen/ops/mps_max_pool2d_backward.h> |
570 | #include <ATen/ops/mkldnn_max_pool3d.h> |
571 | #include <ATen/ops/mps_convolution_backward.h> |
572 | #include <ATen/ops/mkldnn_rnn_layer.h> |
573 | #include <ATen/ops/miopen_convolution.h> |
574 | #include <ATen/ops/miopen_rnn.h> |
575 | #include <ATen/ops/_sparse_sparse_matmul.h> |
576 | #include <ATen/ops/_native_batch_norm_legit.h> |
577 | #include <ATen/ops/batch_norm_update_stats.h> |
578 | #include <ATen/ops/ones_like.h> |
579 | #include <ATen/ops/_euclidean_dist.h> |
580 | #include <ATen/ops/_cdist_backward.h> |
581 | #include <ATen/ops/_pdist_forward.h> |
582 | #include <ATen/ops/scalar_tensor.h> |
583 | #include <ATen/ops/rand.h> |
584 | #include <ATen/ops/rand.h> |
585 | #include <ATen/ops/randn_like.h> |
586 | #include <ATen/ops/repeat.h> |
587 | #include <ATen/ops/repeat_interleave.h> |
588 | #include <ATen/ops/_mkldnn_reshape.h> |
589 | #include <ATen/ops/sum.h> |
590 | #include <ATen/ops/rot90.h> |
591 | #include <ATen/ops/_nested_tensor_strides.h> |
592 | #include <ATen/ops/var_mean.h> |
593 | #include <ATen/ops/_standard_gamma_grad.h> |
594 | #include <ATen/ops/native_norm.h> |
595 | #include <ATen/ops/native_norm.h> |
596 | #include <ATen/ops/_sparse_sum_backward.h> |
597 | #include <ATen/ops/_sparse_csr_sum.h> |
598 | #include <ATen/ops/_sparse_softmax.h> |
599 | #include <ATen/ops/norm.h> |
600 | #include <ATen/ops/norm.h> |
601 | #include <ATen/ops/_sparse_coo_tensor_with_dims_and_tensors.h> |
602 | #include <ATen/ops/_to_dense.h> |
603 | #include <ATen/ops/_coalesced.h> |
604 | #include <ATen/ops/_coalesced.h> |
605 | #include <ATen/ops/to_sparse_bsc.h> |
606 | #include <ATen/ops/quantize_per_tensor_dynamic.h> |
607 | #include <ATen/ops/quantize_per_tensor.h> |
608 | #include <ATen/ops/quantize_per_tensor.h> |
609 | #include <ATen/ops/quantize_per_tensor.h> |
610 | #include <ATen/ops/fake_quantize_per_tensor_affine_cachemask.h> |
611 | #include <ATen/ops/_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.h> |
612 | #include <ATen/ops/_fake_quantize_learnable_per_tensor_affine.h> |
613 | #include <ATen/ops/_thnn_fused_gru_cell_backward.h> |
614 | #include <ATen/ops/set.h> |
615 | #include <ATen/ops/set.h> |
616 | #include <ATen/ops/set.h> |
617 | #include <ATen/ops/set.h> |
618 | #include <ATen/ops/set.h> |
619 | #include <ATen/ops/set.h> |
620 | #include <ATen/ops/set.h> |
621 | #include <ATen/ops/set.h> |
622 | #include <ATen/ops/put.h> |
623 | #include <ATen/ops/uniform.h> |
624 | #include <ATen/ops/uniform.h> |
625 | #include <ATen/ops/tril_indices.h> |
626 | #include <ATen/ops/_cholesky_solve_helper.h> |
627 | #include <ATen/ops/_amp_update_scale.h> |
628 | #include <ATen/ops/_amp_update_scale.h> |
629 | #include <ATen/ops/_foreach_exp.h> |
630 | #include <ATen/ops/_foreach_sqrt.h> |
631 | #include <ATen/ops/_foreach_log.h> |
632 | #include <ATen/ops/_foreach_log1p.h> |
633 | #include <ATen/ops/_foreach_neg.h> |
634 | #include <ATen/ops/_foreach_sin.h> |
635 | #include <ATen/ops/_foreach_reciprocal.h> |
636 | #include <ATen/ops/_foreach_sigmoid.h> |
637 | #include <ATen/ops/_foreach_addcdiv.h> |
638 | #include <ATen/ops/_foreach_addcdiv.h> |
639 | #include <ATen/ops/_foreach_addcdiv.h> |
640 | #include <ATen/ops/_foreach_norm.h> |
641 | #include <ATen/ops/glu_jvp.h> |
642 | #include <ATen/ops/_adaptive_avg_pool2d_backward.h> |
643 | #include <ATen/ops/slow_conv_dilated3d.h> |
644 | #include <ATen/ops/isinf.h> |
645 | #include <ATen/ops/_test_optional_floatlist.h> |
646 | #include <ATen/ops/_nested_tensor_from_tensor_list.h> |
647 | #include <ATen/ops/_sparse_broadcast_to_copy.h> |
648 | #include <ATen/ops/transpose_copy.h> |
649 | #include <ATen/ops/_indices_copy.h> |
650 | #include <ATen/ops/_values_copy.h> |
651 | #include <ATen/ops/values_copy.h> |
652 | #include <ATen/ops/view_copy.h> |
653 | #include <ATen/ops/view_copy.h> |
654 | #include <ATen/ops/unfold_copy.h> |
655 | #include <ATen/ops/_native_decoder_only_multi_head_attention.h> |
656 | #include <ATen/ops/_fused_adam.h> |
657 | #include <ATen/ops/_fused_adam.h> |
658 | #endif |
659 | |
660 | |
661 | |
662 | namespace at { namespace _ops { |
663 | |
664 | |
665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Short, name, "aten::_cast_Short" ) |
666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Short, overload_name, "" ) |
667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cast_Short, schema_str, "_cast_Short(Tensor self, bool non_blocking=False) -> Tensor" ) |
668 | |
669 | // aten::_cast_Short(Tensor self, bool non_blocking=False) -> Tensor |
670 | static C10_NOINLINE c10::TypedOperatorHandle<_cast_Short::schema> create__cast_Short_typed_handle() { |
671 | return c10::Dispatcher::singleton() |
672 | .findSchemaOrThrow(_cast_Short::name, _cast_Short::overload_name) |
673 | .typed<_cast_Short::schema>(); |
674 | } |
675 | |
676 | // aten::_cast_Short(Tensor self, bool non_blocking=False) -> Tensor |
677 | at::Tensor _cast_Short::call(const at::Tensor & self, bool non_blocking) { |
678 | |
679 | static auto op = create__cast_Short_typed_handle(); |
680 | return op.call(self, non_blocking); |
681 | } |
682 | |
683 | // aten::_cast_Short(Tensor self, bool non_blocking=False) -> Tensor |
684 | at::Tensor _cast_Short::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool non_blocking) { |
685 | |
686 | static auto op = create__cast_Short_typed_handle(); |
687 | return op.redispatch(dispatchKeySet, self, non_blocking); |
688 | } |
689 | |
690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(output_nr, name, "aten::output_nr" ) |
691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(output_nr, overload_name, "" ) |
692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(output_nr, schema_str, "output_nr(Tensor self) -> int" ) |
693 | |
694 | // aten::output_nr(Tensor self) -> int |
695 | static C10_NOINLINE c10::TypedOperatorHandle<output_nr::schema> create_output_nr_typed_handle() { |
696 | return c10::Dispatcher::singleton() |
697 | .findSchemaOrThrow(output_nr::name, output_nr::overload_name) |
698 | .typed<output_nr::schema>(); |
699 | } |
700 | |
701 | // aten::output_nr(Tensor self) -> int |
702 | int64_t output_nr::call(const at::Tensor & self) { |
703 | |
704 | static auto op = create_output_nr_typed_handle(); |
705 | return op.call(self); |
706 | } |
707 | |
708 | // aten::output_nr(Tensor self) -> int |
709 | int64_t output_nr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
710 | |
711 | static auto op = create_output_nr_typed_handle(); |
712 | return op.redispatch(dispatchKeySet, self); |
713 | } |
714 | |
715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_new_zeros_with_same_feature_meta, name, "aten::_new_zeros_with_same_feature_meta" ) |
716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_new_zeros_with_same_feature_meta, overload_name, "" ) |
717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_new_zeros_with_same_feature_meta, schema_str, "_new_zeros_with_same_feature_meta(Tensor self, Tensor other, *, int self_num_batch_dims=0) -> Tensor" ) |
718 | |
719 | // aten::_new_zeros_with_same_feature_meta(Tensor self, Tensor other, *, int self_num_batch_dims=0) -> Tensor |
720 | static C10_NOINLINE c10::TypedOperatorHandle<_new_zeros_with_same_feature_meta::schema> create__new_zeros_with_same_feature_meta_typed_handle() { |
721 | return c10::Dispatcher::singleton() |
722 | .findSchemaOrThrow(_new_zeros_with_same_feature_meta::name, _new_zeros_with_same_feature_meta::overload_name) |
723 | .typed<_new_zeros_with_same_feature_meta::schema>(); |
724 | } |
725 | |
726 | // aten::_new_zeros_with_same_feature_meta(Tensor self, Tensor other, *, int self_num_batch_dims=0) -> Tensor |
727 | at::Tensor _new_zeros_with_same_feature_meta::call(const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims) { |
728 | |
729 | static auto op = create__new_zeros_with_same_feature_meta_typed_handle(); |
730 | return op.call(self, other, self_num_batch_dims); |
731 | } |
732 | |
733 | // aten::_new_zeros_with_same_feature_meta(Tensor self, Tensor other, *, int self_num_batch_dims=0) -> Tensor |
734 | at::Tensor _new_zeros_with_same_feature_meta::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims) { |
735 | |
736 | static auto op = create__new_zeros_with_same_feature_meta_typed_handle(); |
737 | return op.redispatch(dispatchKeySet, self, other, self_num_batch_dims); |
738 | } |
739 | |
740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_init_dropout_state, name, "aten::_cudnn_init_dropout_state" ) |
741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_init_dropout_state, overload_name, "" ) |
742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_init_dropout_state, schema_str, "_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor" ) |
743 | |
744 | // aten::_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
745 | static C10_NOINLINE c10::TypedOperatorHandle<_cudnn_init_dropout_state::schema> create__cudnn_init_dropout_state_typed_handle() { |
746 | return c10::Dispatcher::singleton() |
747 | .findSchemaOrThrow(_cudnn_init_dropout_state::name, _cudnn_init_dropout_state::overload_name) |
748 | .typed<_cudnn_init_dropout_state::schema>(); |
749 | } |
750 | |
751 | // aten::_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
752 | at::Tensor _cudnn_init_dropout_state::call(double dropout, bool train, int64_t dropout_seed, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
753 | |
754 | static auto op = create__cudnn_init_dropout_state_typed_handle(); |
755 | return op.call(dropout, train, dropout_seed, dtype, layout, device, pin_memory); |
756 | } |
757 | |
758 | // aten::_cudnn_init_dropout_state(float dropout, bool train, int dropout_seed, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
759 | at::Tensor _cudnn_init_dropout_state::redispatch(c10::DispatchKeySet dispatchKeySet, double dropout, bool train, int64_t dropout_seed, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
760 | |
761 | static auto op = create__cudnn_init_dropout_state_typed_handle(); |
762 | return op.redispatch(dispatchKeySet, dropout, train, dropout_seed, dtype, layout, device, pin_memory); |
763 | } |
764 | |
765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_dropout, name, "aten::native_dropout" ) |
766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_dropout, overload_name, "" ) |
767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_dropout, schema_str, "native_dropout(Tensor input, float p, bool? train) -> (Tensor, Tensor)" ) |
768 | |
769 | // aten::native_dropout(Tensor input, float p, bool? train) -> (Tensor, Tensor) |
770 | static C10_NOINLINE c10::TypedOperatorHandle<native_dropout::schema> create_native_dropout_typed_handle() { |
771 | return c10::Dispatcher::singleton() |
772 | .findSchemaOrThrow(native_dropout::name, native_dropout::overload_name) |
773 | .typed<native_dropout::schema>(); |
774 | } |
775 | |
776 | // aten::native_dropout(Tensor input, float p, bool? train) -> (Tensor, Tensor) |
777 | ::std::tuple<at::Tensor,at::Tensor> native_dropout::call(const at::Tensor & input, double p, c10::optional<bool> train) { |
778 | |
779 | static auto op = create_native_dropout_typed_handle(); |
780 | return op.call(input, p, train); |
781 | } |
782 | |
783 | // aten::native_dropout(Tensor input, float p, bool? train) -> (Tensor, Tensor) |
784 | ::std::tuple<at::Tensor,at::Tensor> native_dropout::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, c10::optional<bool> train) { |
785 | |
786 | static auto op = create_native_dropout_typed_handle(); |
787 | return op.redispatch(dispatchKeySet, input, p, train); |
788 | } |
789 | |
790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute, name, "aten::absolute" ) |
791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute, overload_name, "" ) |
792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute, schema_str, "absolute(Tensor self) -> Tensor" ) |
793 | |
794 | // aten::absolute(Tensor self) -> Tensor |
795 | static C10_NOINLINE c10::TypedOperatorHandle<absolute::schema> create_absolute_typed_handle() { |
796 | return c10::Dispatcher::singleton() |
797 | .findSchemaOrThrow(absolute::name, absolute::overload_name) |
798 | .typed<absolute::schema>(); |
799 | } |
800 | |
801 | // aten::absolute(Tensor self) -> Tensor |
802 | at::Tensor absolute::call(const at::Tensor & self) { |
803 | |
804 | static auto op = create_absolute_typed_handle(); |
805 | return op.call(self); |
806 | } |
807 | |
808 | // aten::absolute(Tensor self) -> Tensor |
809 | at::Tensor absolute::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
810 | |
811 | static auto op = create_absolute_typed_handle(); |
812 | return op.redispatch(dispatchKeySet, self); |
813 | } |
814 | |
815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute_, name, "aten::absolute_" ) |
816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute_, overload_name, "" ) |
817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute_, schema_str, "absolute_(Tensor(a!) self) -> Tensor(a!)" ) |
818 | |
819 | // aten::absolute_(Tensor(a!) self) -> Tensor(a!) |
820 | static C10_NOINLINE c10::TypedOperatorHandle<absolute_::schema> create_absolute__typed_handle() { |
821 | return c10::Dispatcher::singleton() |
822 | .findSchemaOrThrow(absolute_::name, absolute_::overload_name) |
823 | .typed<absolute_::schema>(); |
824 | } |
825 | |
826 | // aten::absolute_(Tensor(a!) self) -> Tensor(a!) |
827 | at::Tensor & absolute_::call(at::Tensor & self) { |
828 | |
829 | static auto op = create_absolute__typed_handle(); |
830 | return op.call(self); |
831 | } |
832 | |
833 | // aten::absolute_(Tensor(a!) self) -> Tensor(a!) |
834 | at::Tensor & absolute_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
835 | |
836 | static auto op = create_absolute__typed_handle(); |
837 | return op.redispatch(dispatchKeySet, self); |
838 | } |
839 | |
840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute_out, name, "aten::absolute" ) |
841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute_out, overload_name, "out" ) |
842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(absolute_out, schema_str, "absolute.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
843 | |
844 | // aten::absolute.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
845 | static C10_NOINLINE c10::TypedOperatorHandle<absolute_out::schema> create_absolute_out_typed_handle() { |
846 | return c10::Dispatcher::singleton() |
847 | .findSchemaOrThrow(absolute_out::name, absolute_out::overload_name) |
848 | .typed<absolute_out::schema>(); |
849 | } |
850 | |
851 | // aten::absolute.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
852 | at::Tensor & absolute_out::call(const at::Tensor & self, at::Tensor & out) { |
853 | |
854 | static auto op = create_absolute_out_typed_handle(); |
855 | return op.call(self, out); |
856 | } |
857 | |
858 | // aten::absolute.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
859 | at::Tensor & absolute_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
860 | |
861 | static auto op = create_absolute_out_typed_handle(); |
862 | return op.redispatch(dispatchKeySet, self, out); |
863 | } |
864 | |
865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(angle, name, "aten::angle" ) |
866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(angle, overload_name, "" ) |
867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(angle, schema_str, "angle(Tensor self) -> Tensor" ) |
868 | |
869 | // aten::angle(Tensor self) -> Tensor |
870 | static C10_NOINLINE c10::TypedOperatorHandle<angle::schema> create_angle_typed_handle() { |
871 | return c10::Dispatcher::singleton() |
872 | .findSchemaOrThrow(angle::name, angle::overload_name) |
873 | .typed<angle::schema>(); |
874 | } |
875 | |
876 | // aten::angle(Tensor self) -> Tensor |
877 | at::Tensor angle::call(const at::Tensor & self) { |
878 | |
879 | static auto op = create_angle_typed_handle(); |
880 | return op.call(self); |
881 | } |
882 | |
883 | // aten::angle(Tensor self) -> Tensor |
884 | at::Tensor angle::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
885 | |
886 | static auto op = create_angle_typed_handle(); |
887 | return op.redispatch(dispatchKeySet, self); |
888 | } |
889 | |
890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(angle_out, name, "aten::angle" ) |
891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(angle_out, overload_name, "out" ) |
892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(angle_out, schema_str, "angle.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
893 | |
894 | // aten::angle.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
895 | static C10_NOINLINE c10::TypedOperatorHandle<angle_out::schema> create_angle_out_typed_handle() { |
896 | return c10::Dispatcher::singleton() |
897 | .findSchemaOrThrow(angle_out::name, angle_out::overload_name) |
898 | .typed<angle_out::schema>(); |
899 | } |
900 | |
901 | // aten::angle.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
902 | at::Tensor & angle_out::call(const at::Tensor & self, at::Tensor & out) { |
903 | |
904 | static auto op = create_angle_out_typed_handle(); |
905 | return op.call(self, out); |
906 | } |
907 | |
908 | // aten::angle.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
909 | at::Tensor & angle_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
910 | |
911 | static auto op = create_angle_out_typed_handle(); |
912 | return op.redispatch(dispatchKeySet, self, out); |
913 | } |
914 | |
915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Tensor, name, "aten::add" ) |
916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Tensor, overload_name, "Tensor" ) |
917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Tensor, schema_str, "add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor" ) |
918 | |
919 | // aten::add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
920 | static C10_NOINLINE c10::TypedOperatorHandle<add_Tensor::schema> create_add_Tensor_typed_handle() { |
921 | return c10::Dispatcher::singleton() |
922 | .findSchemaOrThrow(add_Tensor::name, add_Tensor::overload_name) |
923 | .typed<add_Tensor::schema>(); |
924 | } |
925 | |
926 | // aten::add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
927 | at::Tensor add_Tensor::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
928 | |
929 | static auto op = create_add_Tensor_typed_handle(); |
930 | return op.call(self, other, alpha); |
931 | } |
932 | |
933 | // aten::add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor |
934 | at::Tensor add_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
935 | |
936 | static auto op = create_add_Tensor_typed_handle(); |
937 | return op.redispatch(dispatchKeySet, self, other, alpha); |
938 | } |
939 | |
940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add__Tensor, name, "aten::add_" ) |
941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add__Tensor, overload_name, "Tensor" ) |
942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add__Tensor, schema_str, "add_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!)" ) |
943 | |
944 | // aten::add_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
945 | static C10_NOINLINE c10::TypedOperatorHandle<add__Tensor::schema> create_add__Tensor_typed_handle() { |
946 | return c10::Dispatcher::singleton() |
947 | .findSchemaOrThrow(add__Tensor::name, add__Tensor::overload_name) |
948 | .typed<add__Tensor::schema>(); |
949 | } |
950 | |
951 | // aten::add_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
952 | at::Tensor & add__Tensor::call(at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
953 | |
954 | static auto op = create_add__Tensor_typed_handle(); |
955 | return op.call(self, other, alpha); |
956 | } |
957 | |
958 | // aten::add_.Tensor(Tensor(a!) self, Tensor other, *, Scalar alpha=1) -> Tensor(a!) |
959 | at::Tensor & add__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) { |
960 | |
961 | static auto op = create_add__Tensor_typed_handle(); |
962 | return op.redispatch(dispatchKeySet, self, other, alpha); |
963 | } |
964 | |
965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_out, name, "aten::add" ) |
966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_out, overload_name, "out" ) |
967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_out, schema_str, "add.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)" ) |
968 | |
969 | // aten::add.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
970 | static C10_NOINLINE c10::TypedOperatorHandle<add_out::schema> create_add_out_typed_handle() { |
971 | return c10::Dispatcher::singleton() |
972 | .findSchemaOrThrow(add_out::name, add_out::overload_name) |
973 | .typed<add_out::schema>(); |
974 | } |
975 | |
976 | // aten::add.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
977 | at::Tensor & add_out::call(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out) { |
978 | |
979 | static auto op = create_add_out_typed_handle(); |
980 | return op.call(self, other, alpha, out); |
981 | } |
982 | |
983 | // aten::add.out(Tensor self, Tensor other, *, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
984 | at::Tensor & add_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha, at::Tensor & out) { |
985 | |
986 | static auto op = create_add_out_typed_handle(); |
987 | return op.redispatch(dispatchKeySet, self, other, alpha, out); |
988 | } |
989 | |
990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Scalar, name, "aten::add" ) |
991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Scalar, overload_name, "Scalar" ) |
992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Scalar, schema_str, "add.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor" ) |
993 | |
994 | // aten::add.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
995 | static C10_NOINLINE c10::TypedOperatorHandle<add_Scalar::schema> create_add_Scalar_typed_handle() { |
996 | return c10::Dispatcher::singleton() |
997 | .findSchemaOrThrow(add_Scalar::name, add_Scalar::overload_name) |
998 | .typed<add_Scalar::schema>(); |
999 | } |
1000 | |
1001 | // aten::add.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
1002 | at::Tensor add_Scalar::call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
1003 | |
1004 | static auto op = create_add_Scalar_typed_handle(); |
1005 | return op.call(self, other, alpha); |
1006 | } |
1007 | |
1008 | // aten::add.Scalar(Tensor self, Scalar other, Scalar alpha=1) -> Tensor |
1009 | at::Tensor add_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
1010 | |
1011 | static auto op = create_add_Scalar_typed_handle(); |
1012 | return op.redispatch(dispatchKeySet, self, other, alpha); |
1013 | } |
1014 | |
1015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add__Scalar, name, "aten::add_" ) |
1016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add__Scalar, overload_name, "Scalar" ) |
1017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add__Scalar, schema_str, "add_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!)" ) |
1018 | |
1019 | // aten::add_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
1020 | static C10_NOINLINE c10::TypedOperatorHandle<add__Scalar::schema> create_add__Scalar_typed_handle() { |
1021 | return c10::Dispatcher::singleton() |
1022 | .findSchemaOrThrow(add__Scalar::name, add__Scalar::overload_name) |
1023 | .typed<add__Scalar::schema>(); |
1024 | } |
1025 | |
1026 | // aten::add_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
1027 | at::Tensor & add__Scalar::call(at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
1028 | |
1029 | static auto op = create_add__Scalar_typed_handle(); |
1030 | return op.call(self, other, alpha); |
1031 | } |
1032 | |
1033 | // aten::add_.Scalar(Tensor(a!) self, Scalar other, Scalar alpha=1) -> Tensor(a!) |
1034 | at::Tensor & add__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha) { |
1035 | |
1036 | static auto op = create_add__Scalar_typed_handle(); |
1037 | return op.redispatch(dispatchKeySet, self, other, alpha); |
1038 | } |
1039 | |
1040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dim, name, "aten::all" ) |
1041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dim, overload_name, "dim" ) |
1042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dim, schema_str, "all.dim(Tensor self, int dim, bool keepdim=False) -> Tensor" ) |
1043 | |
1044 | // aten::all.dim(Tensor self, int dim, bool keepdim=False) -> Tensor |
1045 | static C10_NOINLINE c10::TypedOperatorHandle<all_dim::schema> create_all_dim_typed_handle() { |
1046 | return c10::Dispatcher::singleton() |
1047 | .findSchemaOrThrow(all_dim::name, all_dim::overload_name) |
1048 | .typed<all_dim::schema>(); |
1049 | } |
1050 | |
1051 | // aten::all.dim(Tensor self, int dim, bool keepdim=False) -> Tensor |
1052 | at::Tensor all_dim::call(const at::Tensor & self, int64_t dim, bool keepdim) { |
1053 | |
1054 | static auto op = create_all_dim_typed_handle(); |
1055 | return op.call(self, dim, keepdim); |
1056 | } |
1057 | |
1058 | // aten::all.dim(Tensor self, int dim, bool keepdim=False) -> Tensor |
1059 | at::Tensor all_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim) { |
1060 | |
1061 | static auto op = create_all_dim_typed_handle(); |
1062 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
1063 | } |
1064 | |
1065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_out, name, "aten::all" ) |
1066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_out, overload_name, "out" ) |
1067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_out, schema_str, "all.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
1068 | |
1069 | // aten::all.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
1070 | static C10_NOINLINE c10::TypedOperatorHandle<all_out::schema> create_all_out_typed_handle() { |
1071 | return c10::Dispatcher::singleton() |
1072 | .findSchemaOrThrow(all_out::name, all_out::overload_name) |
1073 | .typed<all_out::schema>(); |
1074 | } |
1075 | |
1076 | // aten::all.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
1077 | at::Tensor & all_out::call(const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out) { |
1078 | |
1079 | static auto op = create_all_out_typed_handle(); |
1080 | return op.call(self, dim, keepdim, out); |
1081 | } |
1082 | |
1083 | // aten::all.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
1084 | at::Tensor & all_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool keepdim, at::Tensor & out) { |
1085 | |
1086 | static auto op = create_all_out_typed_handle(); |
1087 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
1088 | } |
1089 | |
1090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dimname, name, "aten::all" ) |
1091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dimname, overload_name, "dimname" ) |
1092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dimname, schema_str, "all.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor" ) |
1093 | |
1094 | // aten::all.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor |
1095 | static C10_NOINLINE c10::TypedOperatorHandle<all_dimname::schema> create_all_dimname_typed_handle() { |
1096 | return c10::Dispatcher::singleton() |
1097 | .findSchemaOrThrow(all_dimname::name, all_dimname::overload_name) |
1098 | .typed<all_dimname::schema>(); |
1099 | } |
1100 | |
1101 | // aten::all.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor |
1102 | at::Tensor all_dimname::call(const at::Tensor & self, at::Dimname dim, bool keepdim) { |
1103 | |
1104 | static auto op = create_all_dimname_typed_handle(); |
1105 | return op.call(self, dim, keepdim); |
1106 | } |
1107 | |
1108 | // aten::all.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor |
1109 | at::Tensor all_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim) { |
1110 | |
1111 | static auto op = create_all_dimname_typed_handle(); |
1112 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
1113 | } |
1114 | |
1115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dimname_out, name, "aten::all" ) |
1116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dimname_out, overload_name, "dimname_out" ) |
1117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_dimname_out, schema_str, "all.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
1118 | |
1119 | // aten::all.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
1120 | static C10_NOINLINE c10::TypedOperatorHandle<all_dimname_out::schema> create_all_dimname_out_typed_handle() { |
1121 | return c10::Dispatcher::singleton() |
1122 | .findSchemaOrThrow(all_dimname_out::name, all_dimname_out::overload_name) |
1123 | .typed<all_dimname_out::schema>(); |
1124 | } |
1125 | |
1126 | // aten::all.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
1127 | at::Tensor & all_dimname_out::call(const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out) { |
1128 | |
1129 | static auto op = create_all_dimname_out_typed_handle(); |
1130 | return op.call(self, dim, keepdim, out); |
1131 | } |
1132 | |
1133 | // aten::all.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
1134 | at::Tensor & all_dimname_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool keepdim, at::Tensor & out) { |
1135 | |
1136 | static auto op = create_all_dimname_out_typed_handle(); |
1137 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
1138 | } |
1139 | |
1140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh, name, "aten::asinh" ) |
1141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh, overload_name, "" ) |
1142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh, schema_str, "asinh(Tensor self) -> Tensor" ) |
1143 | |
1144 | // aten::asinh(Tensor self) -> Tensor |
1145 | static C10_NOINLINE c10::TypedOperatorHandle<asinh::schema> create_asinh_typed_handle() { |
1146 | return c10::Dispatcher::singleton() |
1147 | .findSchemaOrThrow(asinh::name, asinh::overload_name) |
1148 | .typed<asinh::schema>(); |
1149 | } |
1150 | |
1151 | // aten::asinh(Tensor self) -> Tensor |
1152 | at::Tensor asinh::call(const at::Tensor & self) { |
1153 | |
1154 | static auto op = create_asinh_typed_handle(); |
1155 | return op.call(self); |
1156 | } |
1157 | |
1158 | // aten::asinh(Tensor self) -> Tensor |
1159 | at::Tensor asinh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
1160 | |
1161 | static auto op = create_asinh_typed_handle(); |
1162 | return op.redispatch(dispatchKeySet, self); |
1163 | } |
1164 | |
1165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh_, name, "aten::asinh_" ) |
1166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh_, overload_name, "" ) |
1167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh_, schema_str, "asinh_(Tensor(a!) self) -> Tensor(a!)" ) |
1168 | |
1169 | // aten::asinh_(Tensor(a!) self) -> Tensor(a!) |
1170 | static C10_NOINLINE c10::TypedOperatorHandle<asinh_::schema> create_asinh__typed_handle() { |
1171 | return c10::Dispatcher::singleton() |
1172 | .findSchemaOrThrow(asinh_::name, asinh_::overload_name) |
1173 | .typed<asinh_::schema>(); |
1174 | } |
1175 | |
1176 | // aten::asinh_(Tensor(a!) self) -> Tensor(a!) |
1177 | at::Tensor & asinh_::call(at::Tensor & self) { |
1178 | |
1179 | static auto op = create_asinh__typed_handle(); |
1180 | return op.call(self); |
1181 | } |
1182 | |
1183 | // aten::asinh_(Tensor(a!) self) -> Tensor(a!) |
1184 | at::Tensor & asinh_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
1185 | |
1186 | static auto op = create_asinh__typed_handle(); |
1187 | return op.redispatch(dispatchKeySet, self); |
1188 | } |
1189 | |
1190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh_out, name, "aten::asinh" ) |
1191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh_out, overload_name, "out" ) |
1192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(asinh_out, schema_str, "asinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
1193 | |
1194 | // aten::asinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
1195 | static C10_NOINLINE c10::TypedOperatorHandle<asinh_out::schema> create_asinh_out_typed_handle() { |
1196 | return c10::Dispatcher::singleton() |
1197 | .findSchemaOrThrow(asinh_out::name, asinh_out::overload_name) |
1198 | .typed<asinh_out::schema>(); |
1199 | } |
1200 | |
1201 | // aten::asinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
1202 | at::Tensor & asinh_out::call(const at::Tensor & self, at::Tensor & out) { |
1203 | |
1204 | static auto op = create_asinh_out_typed_handle(); |
1205 | return op.call(self, out); |
1206 | } |
1207 | |
1208 | // aten::asinh.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
1209 | at::Tensor & asinh_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
1210 | |
1211 | static auto op = create_asinh_out_typed_handle(); |
1212 | return op.redispatch(dispatchKeySet, self, out); |
1213 | } |
1214 | |
1215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_2d, name, "aten::atleast_2d" ) |
1216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_2d, overload_name, "" ) |
1217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_2d, schema_str, "atleast_2d(Tensor self) -> Tensor" ) |
1218 | |
1219 | // aten::atleast_2d(Tensor self) -> Tensor |
1220 | static C10_NOINLINE c10::TypedOperatorHandle<atleast_2d::schema> create_atleast_2d_typed_handle() { |
1221 | return c10::Dispatcher::singleton() |
1222 | .findSchemaOrThrow(atleast_2d::name, atleast_2d::overload_name) |
1223 | .typed<atleast_2d::schema>(); |
1224 | } |
1225 | |
1226 | // aten::atleast_2d(Tensor self) -> Tensor |
1227 | at::Tensor atleast_2d::call(const at::Tensor & self) { |
1228 | |
1229 | static auto op = create_atleast_2d_typed_handle(); |
1230 | return op.call(self); |
1231 | } |
1232 | |
1233 | // aten::atleast_2d(Tensor self) -> Tensor |
1234 | at::Tensor atleast_2d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
1235 | |
1236 | static auto op = create_atleast_2d_typed_handle(); |
1237 | return op.redispatch(dispatchKeySet, self); |
1238 | } |
1239 | |
1240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_2d_Sequence, name, "aten::atleast_2d" ) |
1241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_2d_Sequence, overload_name, "Sequence" ) |
1242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atleast_2d_Sequence, schema_str, "atleast_2d.Sequence(Tensor[] tensors) -> Tensor[]" ) |
1243 | |
1244 | // aten::atleast_2d.Sequence(Tensor[] tensors) -> Tensor[] |
1245 | static C10_NOINLINE c10::TypedOperatorHandle<atleast_2d_Sequence::schema> create_atleast_2d_Sequence_typed_handle() { |
1246 | return c10::Dispatcher::singleton() |
1247 | .findSchemaOrThrow(atleast_2d_Sequence::name, atleast_2d_Sequence::overload_name) |
1248 | .typed<atleast_2d_Sequence::schema>(); |
1249 | } |
1250 | |
1251 | // aten::atleast_2d.Sequence(Tensor[] tensors) -> Tensor[] |
1252 | ::std::vector<at::Tensor> atleast_2d_Sequence::call(at::TensorList tensors) { |
1253 | |
1254 | static auto op = create_atleast_2d_Sequence_typed_handle(); |
1255 | return op.call(tensors); |
1256 | } |
1257 | |
1258 | // aten::atleast_2d.Sequence(Tensor[] tensors) -> Tensor[] |
1259 | ::std::vector<at::Tensor> atleast_2d_Sequence::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
1260 | |
1261 | static auto op = create_atleast_2d_Sequence_typed_handle(); |
1262 | return op.redispatch(dispatchKeySet, tensors); |
1263 | } |
1264 | |
1265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm, name, "aten::baddbmm" ) |
1266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm, overload_name, "" ) |
1267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm, schema_str, "baddbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor" ) |
1268 | |
1269 | // aten::baddbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
1270 | static C10_NOINLINE c10::TypedOperatorHandle<baddbmm::schema> create_baddbmm_typed_handle() { |
1271 | return c10::Dispatcher::singleton() |
1272 | .findSchemaOrThrow(baddbmm::name, baddbmm::overload_name) |
1273 | .typed<baddbmm::schema>(); |
1274 | } |
1275 | |
1276 | // aten::baddbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
1277 | at::Tensor baddbmm::call(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha) { |
1278 | |
1279 | static auto op = create_baddbmm_typed_handle(); |
1280 | return op.call(self, batch1, batch2, beta, alpha); |
1281 | } |
1282 | |
1283 | // aten::baddbmm(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor |
1284 | at::Tensor baddbmm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha) { |
1285 | |
1286 | static auto op = create_baddbmm_typed_handle(); |
1287 | return op.redispatch(dispatchKeySet, self, batch1, batch2, beta, alpha); |
1288 | } |
1289 | |
1290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm_, name, "aten::baddbmm_" ) |
1291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm_, overload_name, "" ) |
1292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm_, schema_str, "baddbmm_(Tensor(a!) self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!)" ) |
1293 | |
1294 | // aten::baddbmm_(Tensor(a!) self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!) |
1295 | static C10_NOINLINE c10::TypedOperatorHandle<baddbmm_::schema> create_baddbmm__typed_handle() { |
1296 | return c10::Dispatcher::singleton() |
1297 | .findSchemaOrThrow(baddbmm_::name, baddbmm_::overload_name) |
1298 | .typed<baddbmm_::schema>(); |
1299 | } |
1300 | |
1301 | // aten::baddbmm_(Tensor(a!) self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!) |
1302 | at::Tensor & baddbmm_::call(at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha) { |
1303 | |
1304 | static auto op = create_baddbmm__typed_handle(); |
1305 | return op.call(self, batch1, batch2, beta, alpha); |
1306 | } |
1307 | |
1308 | // aten::baddbmm_(Tensor(a!) self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1) -> Tensor(a!) |
1309 | at::Tensor & baddbmm_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha) { |
1310 | |
1311 | static auto op = create_baddbmm__typed_handle(); |
1312 | return op.redispatch(dispatchKeySet, self, batch1, batch2, beta, alpha); |
1313 | } |
1314 | |
1315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm_out, name, "aten::baddbmm" ) |
1316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm_out, overload_name, "out" ) |
1317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(baddbmm_out, schema_str, "baddbmm.out(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!)" ) |
1318 | |
1319 | // aten::baddbmm.out(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
1320 | static C10_NOINLINE c10::TypedOperatorHandle<baddbmm_out::schema> create_baddbmm_out_typed_handle() { |
1321 | return c10::Dispatcher::singleton() |
1322 | .findSchemaOrThrow(baddbmm_out::name, baddbmm_out::overload_name) |
1323 | .typed<baddbmm_out::schema>(); |
1324 | } |
1325 | |
1326 | // aten::baddbmm.out(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
1327 | at::Tensor & baddbmm_out::call(const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
1328 | |
1329 | static auto op = create_baddbmm_out_typed_handle(); |
1330 | return op.call(self, batch1, batch2, beta, alpha, out); |
1331 | } |
1332 | |
1333 | // aten::baddbmm.out(Tensor self, Tensor batch1, Tensor batch2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) |
1334 | at::Tensor & baddbmm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & batch1, const at::Tensor & batch2, const at::Scalar & beta, const at::Scalar & alpha, at::Tensor & out) { |
1335 | |
1336 | static auto op = create_baddbmm_out_typed_handle(); |
1337 | return op.redispatch(dispatchKeySet, self, batch1, batch2, beta, alpha, out); |
1338 | } |
1339 | |
1340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm, name, "aten::batch_norm" ) |
1341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm, overload_name, "" ) |
1342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm, schema_str, "batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor" ) |
1343 | |
1344 | // aten::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor |
1345 | static C10_NOINLINE c10::TypedOperatorHandle<batch_norm::schema> create_batch_norm_typed_handle() { |
1346 | return c10::Dispatcher::singleton() |
1347 | .findSchemaOrThrow(batch_norm::name, batch_norm::overload_name) |
1348 | .typed<batch_norm::schema>(); |
1349 | } |
1350 | |
1351 | // aten::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor |
1352 | at::Tensor batch_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 training, double momentum, double eps, bool cudnn_enabled) { |
1353 | |
1354 | static auto op = create_batch_norm_typed_handle(); |
1355 | return op.call(input, weight, bias, running_mean, running_var, training, momentum, eps, cudnn_enabled); |
1356 | } |
1357 | |
1358 | // aten::batch_norm(Tensor input, Tensor? weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float momentum, float eps, bool cudnn_enabled) -> Tensor |
1359 | at::Tensor batch_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 training, double momentum, double eps, bool cudnn_enabled) { |
1360 | |
1361 | static auto op = create_batch_norm_typed_handle(); |
1362 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, momentum, eps, cudnn_enabled); |
1363 | } |
1364 | |
1365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli, name, "aten::bernoulli" ) |
1366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli, overload_name, "" ) |
1367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli, schema_str, "bernoulli(Tensor self, *, Generator? generator=None) -> Tensor" ) |
1368 | |
1369 | // aten::bernoulli(Tensor self, *, Generator? generator=None) -> Tensor |
1370 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli::schema> create_bernoulli_typed_handle() { |
1371 | return c10::Dispatcher::singleton() |
1372 | .findSchemaOrThrow(bernoulli::name, bernoulli::overload_name) |
1373 | .typed<bernoulli::schema>(); |
1374 | } |
1375 | |
1376 | // aten::bernoulli(Tensor self, *, Generator? generator=None) -> Tensor |
1377 | at::Tensor bernoulli::call(const at::Tensor & self, c10::optional<at::Generator> generator) { |
1378 | |
1379 | static auto op = create_bernoulli_typed_handle(); |
1380 | return op.call(self, generator); |
1381 | } |
1382 | |
1383 | // aten::bernoulli(Tensor self, *, Generator? generator=None) -> Tensor |
1384 | at::Tensor bernoulli::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator) { |
1385 | |
1386 | static auto op = create_bernoulli_typed_handle(); |
1387 | return op.redispatch(dispatchKeySet, self, generator); |
1388 | } |
1389 | |
1390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_out, name, "aten::bernoulli" ) |
1391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_out, overload_name, "out" ) |
1392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_out, schema_str, "bernoulli.out(Tensor self, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)" ) |
1393 | |
1394 | // aten::bernoulli.out(Tensor self, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
1395 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli_out::schema> create_bernoulli_out_typed_handle() { |
1396 | return c10::Dispatcher::singleton() |
1397 | .findSchemaOrThrow(bernoulli_out::name, bernoulli_out::overload_name) |
1398 | .typed<bernoulli_out::schema>(); |
1399 | } |
1400 | |
1401 | // aten::bernoulli.out(Tensor self, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
1402 | at::Tensor & bernoulli_out::call(const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
1403 | |
1404 | static auto op = create_bernoulli_out_typed_handle(); |
1405 | return op.call(self, generator, out); |
1406 | } |
1407 | |
1408 | // aten::bernoulli.out(Tensor self, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
1409 | at::Tensor & bernoulli_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::Generator> generator, at::Tensor & out) { |
1410 | |
1411 | static auto op = create_bernoulli_out_typed_handle(); |
1412 | return op.redispatch(dispatchKeySet, self, generator, out); |
1413 | } |
1414 | |
1415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli__Tensor, name, "aten::bernoulli_" ) |
1416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli__Tensor, overload_name, "Tensor" ) |
1417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli__Tensor, schema_str, "bernoulli_.Tensor(Tensor(a!) self, Tensor p, *, Generator? generator=None) -> Tensor(a!)" ) |
1418 | |
1419 | // aten::bernoulli_.Tensor(Tensor(a!) self, Tensor p, *, Generator? generator=None) -> Tensor(a!) |
1420 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli__Tensor::schema> create_bernoulli__Tensor_typed_handle() { |
1421 | return c10::Dispatcher::singleton() |
1422 | .findSchemaOrThrow(bernoulli__Tensor::name, bernoulli__Tensor::overload_name) |
1423 | .typed<bernoulli__Tensor::schema>(); |
1424 | } |
1425 | |
1426 | // aten::bernoulli_.Tensor(Tensor(a!) self, Tensor p, *, Generator? generator=None) -> Tensor(a!) |
1427 | at::Tensor & bernoulli__Tensor::call(at::Tensor & self, const at::Tensor & p, c10::optional<at::Generator> generator) { |
1428 | |
1429 | static auto op = create_bernoulli__Tensor_typed_handle(); |
1430 | return op.call(self, p, generator); |
1431 | } |
1432 | |
1433 | // aten::bernoulli_.Tensor(Tensor(a!) self, Tensor p, *, Generator? generator=None) -> Tensor(a!) |
1434 | at::Tensor & bernoulli__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & p, c10::optional<at::Generator> generator) { |
1435 | |
1436 | static auto op = create_bernoulli__Tensor_typed_handle(); |
1437 | return op.redispatch(dispatchKeySet, self, p, generator); |
1438 | } |
1439 | |
1440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli__float, name, "aten::bernoulli_" ) |
1441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli__float, overload_name, "float" ) |
1442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli__float, schema_str, "bernoulli_.float(Tensor(a!) self, float p=0.5, *, Generator? generator=None) -> Tensor(a!)" ) |
1443 | |
1444 | // aten::bernoulli_.float(Tensor(a!) self, float p=0.5, *, Generator? generator=None) -> Tensor(a!) |
1445 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli__float::schema> create_bernoulli__float_typed_handle() { |
1446 | return c10::Dispatcher::singleton() |
1447 | .findSchemaOrThrow(bernoulli__float::name, bernoulli__float::overload_name) |
1448 | .typed<bernoulli__float::schema>(); |
1449 | } |
1450 | |
1451 | // aten::bernoulli_.float(Tensor(a!) self, float p=0.5, *, Generator? generator=None) -> Tensor(a!) |
1452 | at::Tensor & bernoulli__float::call(at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
1453 | |
1454 | static auto op = create_bernoulli__float_typed_handle(); |
1455 | return op.call(self, p, generator); |
1456 | } |
1457 | |
1458 | // aten::bernoulli_.float(Tensor(a!) self, float p=0.5, *, Generator? generator=None) -> Tensor(a!) |
1459 | at::Tensor & bernoulli__float::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
1460 | |
1461 | static auto op = create_bernoulli__float_typed_handle(); |
1462 | return op.redispatch(dispatchKeySet, self, p, generator); |
1463 | } |
1464 | |
1465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_p, name, "aten::bernoulli" ) |
1466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_p, overload_name, "p" ) |
1467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_p, schema_str, "bernoulli.p(Tensor self, float p, *, Generator? generator=None) -> Tensor" ) |
1468 | |
1469 | // aten::bernoulli.p(Tensor self, float p, *, Generator? generator=None) -> Tensor |
1470 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli_p::schema> create_bernoulli_p_typed_handle() { |
1471 | return c10::Dispatcher::singleton() |
1472 | .findSchemaOrThrow(bernoulli_p::name, bernoulli_p::overload_name) |
1473 | .typed<bernoulli_p::schema>(); |
1474 | } |
1475 | |
1476 | // aten::bernoulli.p(Tensor self, float p, *, Generator? generator=None) -> Tensor |
1477 | at::Tensor bernoulli_p::call(const at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
1478 | |
1479 | static auto op = create_bernoulli_p_typed_handle(); |
1480 | return op.call(self, p, generator); |
1481 | } |
1482 | |
1483 | // aten::bernoulli.p(Tensor self, float p, *, Generator? generator=None) -> Tensor |
1484 | at::Tensor bernoulli_p::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional<at::Generator> generator) { |
1485 | |
1486 | static auto op = create_bernoulli_p_typed_handle(); |
1487 | return op.redispatch(dispatchKeySet, self, p, generator); |
1488 | } |
1489 | |
1490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bilinear, name, "aten::bilinear" ) |
1491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bilinear, overload_name, "" ) |
1492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bilinear, schema_str, "bilinear(Tensor input1, Tensor input2, Tensor weight, Tensor? bias=None) -> Tensor" ) |
1493 | |
1494 | // aten::bilinear(Tensor input1, Tensor input2, Tensor weight, Tensor? bias=None) -> Tensor |
1495 | static C10_NOINLINE c10::TypedOperatorHandle<bilinear::schema> create_bilinear_typed_handle() { |
1496 | return c10::Dispatcher::singleton() |
1497 | .findSchemaOrThrow(bilinear::name, bilinear::overload_name) |
1498 | .typed<bilinear::schema>(); |
1499 | } |
1500 | |
1501 | // aten::bilinear(Tensor input1, Tensor input2, Tensor weight, Tensor? bias=None) -> Tensor |
1502 | at::Tensor bilinear::call(const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const c10::optional<at::Tensor> & bias) { |
1503 | |
1504 | static auto op = create_bilinear_typed_handle(); |
1505 | return op.call(input1, input2, weight, bias); |
1506 | } |
1507 | |
1508 | // aten::bilinear(Tensor input1, Tensor input2, Tensor weight, Tensor? bias=None) -> Tensor |
1509 | at::Tensor bilinear::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input1, const at::Tensor & input2, const at::Tensor & weight, const c10::optional<at::Tensor> & bias) { |
1510 | |
1511 | static auto op = create_bilinear_typed_handle(); |
1512 | return op.redispatch(dispatchKeySet, input1, input2, weight, bias); |
1513 | } |
1514 | |
1515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binary_cross_entropy_with_logits, name, "aten::binary_cross_entropy_with_logits" ) |
1516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binary_cross_entropy_with_logits, overload_name, "" ) |
1517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binary_cross_entropy_with_logits, schema_str, "binary_cross_entropy_with_logits(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean) -> Tensor" ) |
1518 | |
1519 | // aten::binary_cross_entropy_with_logits(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean) -> Tensor |
1520 | static C10_NOINLINE c10::TypedOperatorHandle<binary_cross_entropy_with_logits::schema> create_binary_cross_entropy_with_logits_typed_handle() { |
1521 | return c10::Dispatcher::singleton() |
1522 | .findSchemaOrThrow(binary_cross_entropy_with_logits::name, binary_cross_entropy_with_logits::overload_name) |
1523 | .typed<binary_cross_entropy_with_logits::schema>(); |
1524 | } |
1525 | |
1526 | // aten::binary_cross_entropy_with_logits(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean) -> Tensor |
1527 | at::Tensor binary_cross_entropy_with_logits::call(const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & pos_weight, int64_t reduction) { |
1528 | |
1529 | static auto op = create_binary_cross_entropy_with_logits_typed_handle(); |
1530 | return op.call(self, target, weight, pos_weight, reduction); |
1531 | } |
1532 | |
1533 | // aten::binary_cross_entropy_with_logits(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean) -> Tensor |
1534 | at::Tensor binary_cross_entropy_with_logits::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & pos_weight, int64_t reduction) { |
1535 | |
1536 | static auto op = create_binary_cross_entropy_with_logits_typed_handle(); |
1537 | return op.redispatch(dispatchKeySet, self, target, weight, pos_weight, reduction); |
1538 | } |
1539 | |
1540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bincount, name, "aten::bincount" ) |
1541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bincount, overload_name, "" ) |
1542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bincount, schema_str, "bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor" ) |
1543 | |
1544 | // aten::bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor |
1545 | static C10_NOINLINE c10::TypedOperatorHandle<bincount::schema> create_bincount_typed_handle() { |
1546 | return c10::Dispatcher::singleton() |
1547 | .findSchemaOrThrow(bincount::name, bincount::overload_name) |
1548 | .typed<bincount::schema>(); |
1549 | } |
1550 | |
1551 | // aten::bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor |
1552 | at::Tensor bincount::call(const at::Tensor & self, const c10::optional<at::Tensor> & weights, int64_t minlength) { |
1553 | |
1554 | static auto op = create_bincount_typed_handle(); |
1555 | return op.call(self, weights, minlength); |
1556 | } |
1557 | |
1558 | // aten::bincount(Tensor self, Tensor? weights=None, int minlength=0) -> Tensor |
1559 | at::Tensor bincount::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Tensor> & weights, int64_t minlength) { |
1560 | |
1561 | static auto op = create_bincount_typed_handle(); |
1562 | return op.redispatch(dispatchKeySet, self, weights, minlength); |
1563 | } |
1564 | |
1565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and, name, "aten::logical_and" ) |
1566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and, overload_name, "" ) |
1567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and, schema_str, "logical_and(Tensor self, Tensor other) -> Tensor" ) |
1568 | |
1569 | // aten::logical_and(Tensor self, Tensor other) -> Tensor |
1570 | static C10_NOINLINE c10::TypedOperatorHandle<logical_and::schema> create_logical_and_typed_handle() { |
1571 | return c10::Dispatcher::singleton() |
1572 | .findSchemaOrThrow(logical_and::name, logical_and::overload_name) |
1573 | .typed<logical_and::schema>(); |
1574 | } |
1575 | |
1576 | // aten::logical_and(Tensor self, Tensor other) -> Tensor |
1577 | at::Tensor logical_and::call(const at::Tensor & self, const at::Tensor & other) { |
1578 | |
1579 | static auto op = create_logical_and_typed_handle(); |
1580 | return op.call(self, other); |
1581 | } |
1582 | |
1583 | // aten::logical_and(Tensor self, Tensor other) -> Tensor |
1584 | at::Tensor logical_and::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
1585 | |
1586 | static auto op = create_logical_and_typed_handle(); |
1587 | return op.redispatch(dispatchKeySet, self, other); |
1588 | } |
1589 | |
1590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and_, name, "aten::logical_and_" ) |
1591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and_, overload_name, "" ) |
1592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and_, schema_str, "logical_and_(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
1593 | |
1594 | // aten::logical_and_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
1595 | static C10_NOINLINE c10::TypedOperatorHandle<logical_and_::schema> create_logical_and__typed_handle() { |
1596 | return c10::Dispatcher::singleton() |
1597 | .findSchemaOrThrow(logical_and_::name, logical_and_::overload_name) |
1598 | .typed<logical_and_::schema>(); |
1599 | } |
1600 | |
1601 | // aten::logical_and_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
1602 | at::Tensor & logical_and_::call(at::Tensor & self, const at::Tensor & other) { |
1603 | |
1604 | static auto op = create_logical_and__typed_handle(); |
1605 | return op.call(self, other); |
1606 | } |
1607 | |
1608 | // aten::logical_and_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
1609 | at::Tensor & logical_and_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
1610 | |
1611 | static auto op = create_logical_and__typed_handle(); |
1612 | return op.redispatch(dispatchKeySet, self, other); |
1613 | } |
1614 | |
1615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and_out, name, "aten::logical_and" ) |
1616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and_out, overload_name, "out" ) |
1617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logical_and_out, schema_str, "logical_and.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
1618 | |
1619 | // aten::logical_and.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
1620 | static C10_NOINLINE c10::TypedOperatorHandle<logical_and_out::schema> create_logical_and_out_typed_handle() { |
1621 | return c10::Dispatcher::singleton() |
1622 | .findSchemaOrThrow(logical_and_out::name, logical_and_out::overload_name) |
1623 | .typed<logical_and_out::schema>(); |
1624 | } |
1625 | |
1626 | // aten::logical_and.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
1627 | at::Tensor & logical_and_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
1628 | |
1629 | static auto op = create_logical_and_out_typed_handle(); |
1630 | return op.call(self, other, out); |
1631 | } |
1632 | |
1633 | // aten::logical_and.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
1634 | at::Tensor & logical_and_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
1635 | |
1636 | static auto op = create_logical_and_out_typed_handle(); |
1637 | return op.redispatch(dispatchKeySet, self, other, out); |
1638 | } |
1639 | |
1640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(block_diag, name, "aten::block_diag" ) |
1641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(block_diag, overload_name, "" ) |
1642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(block_diag, schema_str, "block_diag(Tensor[] tensors) -> Tensor" ) |
1643 | |
1644 | // aten::block_diag(Tensor[] tensors) -> Tensor |
1645 | static C10_NOINLINE c10::TypedOperatorHandle<block_diag::schema> create_block_diag_typed_handle() { |
1646 | return c10::Dispatcher::singleton() |
1647 | .findSchemaOrThrow(block_diag::name, block_diag::overload_name) |
1648 | .typed<block_diag::schema>(); |
1649 | } |
1650 | |
1651 | // aten::block_diag(Tensor[] tensors) -> Tensor |
1652 | at::Tensor block_diag::call(at::TensorList tensors) { |
1653 | |
1654 | static auto op = create_block_diag_typed_handle(); |
1655 | return op.call(tensors); |
1656 | } |
1657 | |
1658 | // aten::block_diag(Tensor[] tensors) -> Tensor |
1659 | at::Tensor block_diag::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
1660 | |
1661 | static auto op = create_block_diag_typed_handle(); |
1662 | return op.redispatch(dispatchKeySet, tensors); |
1663 | } |
1664 | |
1665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_chunk, name, "aten::unsafe_chunk" ) |
1666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_chunk, overload_name, "" ) |
1667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unsafe_chunk, schema_str, "unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[]" ) |
1668 | |
1669 | // aten::unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[] |
1670 | static C10_NOINLINE c10::TypedOperatorHandle<unsafe_chunk::schema> create_unsafe_chunk_typed_handle() { |
1671 | return c10::Dispatcher::singleton() |
1672 | .findSchemaOrThrow(unsafe_chunk::name, unsafe_chunk::overload_name) |
1673 | .typed<unsafe_chunk::schema>(); |
1674 | } |
1675 | |
1676 | // aten::unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[] |
1677 | ::std::vector<at::Tensor> unsafe_chunk::call(const at::Tensor & self, int64_t chunks, int64_t dim) { |
1678 | |
1679 | static auto op = create_unsafe_chunk_typed_handle(); |
1680 | return op.call(self, chunks, dim); |
1681 | } |
1682 | |
1683 | // aten::unsafe_chunk(Tensor self, int chunks, int dim=0) -> Tensor[] |
1684 | ::std::vector<at::Tensor> unsafe_chunk::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t chunks, int64_t dim) { |
1685 | |
1686 | static auto op = create_unsafe_chunk_typed_handle(); |
1687 | return op.redispatch(dispatchKeySet, self, chunks, dim); |
1688 | } |
1689 | |
1690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(chunk, name, "aten::chunk" ) |
1691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(chunk, overload_name, "" ) |
1692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(chunk, schema_str, "chunk(Tensor(a -> *) self, int chunks, int dim=0) -> Tensor(a)[]" ) |
1693 | |
1694 | // aten::chunk(Tensor(a -> *) self, int chunks, int dim=0) -> Tensor(a)[] |
1695 | static C10_NOINLINE c10::TypedOperatorHandle<chunk::schema> create_chunk_typed_handle() { |
1696 | return c10::Dispatcher::singleton() |
1697 | .findSchemaOrThrow(chunk::name, chunk::overload_name) |
1698 | .typed<chunk::schema>(); |
1699 | } |
1700 | |
1701 | // aten::chunk(Tensor(a -> *) self, int chunks, int dim=0) -> Tensor(a)[] |
1702 | ::std::vector<at::Tensor> chunk::call(const at::Tensor & self, int64_t chunks, int64_t dim) { |
1703 | |
1704 | static auto op = create_chunk_typed_handle(); |
1705 | return op.call(self, chunks, dim); |
1706 | } |
1707 | |
1708 | // aten::chunk(Tensor(a -> *) self, int chunks, int dim=0) -> Tensor(a)[] |
1709 | ::std::vector<at::Tensor> chunk::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t chunks, int64_t dim) { |
1710 | |
1711 | static auto op = create_chunk_typed_handle(); |
1712 | return op.redispatch(dispatchKeySet, self, chunks, dim); |
1713 | } |
1714 | |
1715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_sections, name, "aten::tensor_split" ) |
1716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_sections, overload_name, "sections" ) |
1717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_sections, schema_str, "tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[]" ) |
1718 | |
1719 | // aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] |
1720 | static C10_NOINLINE c10::TypedOperatorHandle<tensor_split_sections::schema> create_tensor_split_sections_typed_handle() { |
1721 | return c10::Dispatcher::singleton() |
1722 | .findSchemaOrThrow(tensor_split_sections::name, tensor_split_sections::overload_name) |
1723 | .typed<tensor_split_sections::schema>(); |
1724 | } |
1725 | |
1726 | // aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] |
1727 | ::std::vector<at::Tensor> tensor_split_sections::call(const at::Tensor & self, c10::SymInt sections, int64_t dim) { |
1728 | |
1729 | static auto op = create_tensor_split_sections_typed_handle(); |
1730 | return op.call(self, sections, dim); |
1731 | } |
1732 | |
1733 | // aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] |
1734 | ::std::vector<at::Tensor> tensor_split_sections::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt sections, int64_t dim) { |
1735 | |
1736 | static auto op = create_tensor_split_sections_typed_handle(); |
1737 | return op.redispatch(dispatchKeySet, self, sections, dim); |
1738 | } |
1739 | |
1740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_indices, name, "aten::tensor_split" ) |
1741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_indices, overload_name, "indices" ) |
1742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_indices, schema_str, "tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[]" ) |
1743 | |
1744 | // aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] |
1745 | static C10_NOINLINE c10::TypedOperatorHandle<tensor_split_indices::schema> create_tensor_split_indices_typed_handle() { |
1746 | return c10::Dispatcher::singleton() |
1747 | .findSchemaOrThrow(tensor_split_indices::name, tensor_split_indices::overload_name) |
1748 | .typed<tensor_split_indices::schema>(); |
1749 | } |
1750 | |
1751 | // aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] |
1752 | ::std::vector<at::Tensor> tensor_split_indices::call(const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim) { |
1753 | |
1754 | static auto op = create_tensor_split_indices_typed_handle(); |
1755 | return op.call(self, indices, dim); |
1756 | } |
1757 | |
1758 | // aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] |
1759 | ::std::vector<at::Tensor> tensor_split_indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef indices, int64_t dim) { |
1760 | |
1761 | static auto op = create_tensor_split_indices_typed_handle(); |
1762 | return op.redispatch(dispatchKeySet, self, indices, dim); |
1763 | } |
1764 | |
1765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_tensor_indices_or_sections, name, "aten::tensor_split" ) |
1766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_tensor_indices_or_sections, overload_name, "tensor_indices_or_sections" ) |
1767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tensor_split_tensor_indices_or_sections, schema_str, "tensor_split.tensor_indices_or_sections(Tensor(a -> *) self, Tensor tensor_indices_or_sections, int dim=0) -> Tensor(a)[]" ) |
1768 | |
1769 | // aten::tensor_split.tensor_indices_or_sections(Tensor(a -> *) self, Tensor tensor_indices_or_sections, int dim=0) -> Tensor(a)[] |
1770 | static C10_NOINLINE c10::TypedOperatorHandle<tensor_split_tensor_indices_or_sections::schema> create_tensor_split_tensor_indices_or_sections_typed_handle() { |
1771 | return c10::Dispatcher::singleton() |
1772 | .findSchemaOrThrow(tensor_split_tensor_indices_or_sections::name, tensor_split_tensor_indices_or_sections::overload_name) |
1773 | .typed<tensor_split_tensor_indices_or_sections::schema>(); |
1774 | } |
1775 | |
1776 | // aten::tensor_split.tensor_indices_or_sections(Tensor(a -> *) self, Tensor tensor_indices_or_sections, int dim=0) -> Tensor(a)[] |
1777 | ::std::vector<at::Tensor> tensor_split_tensor_indices_or_sections::call(const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim) { |
1778 | |
1779 | static auto op = create_tensor_split_tensor_indices_or_sections_typed_handle(); |
1780 | return op.call(self, tensor_indices_or_sections, dim); |
1781 | } |
1782 | |
1783 | // aten::tensor_split.tensor_indices_or_sections(Tensor(a -> *) self, Tensor tensor_indices_or_sections, int dim=0) -> Tensor(a)[] |
1784 | ::std::vector<at::Tensor> tensor_split_tensor_indices_or_sections::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor_indices_or_sections, int64_t dim) { |
1785 | |
1786 | static auto op = create_tensor_split_tensor_indices_or_sections_typed_handle(); |
1787 | return op.redispatch(dispatchKeySet, self, tensor_indices_or_sections, dim); |
1788 | } |
1789 | |
1790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp, name, "aten::clamp" ) |
1791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp, overload_name, "" ) |
1792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp, schema_str, "clamp(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor" ) |
1793 | |
1794 | // aten::clamp(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor |
1795 | static C10_NOINLINE c10::TypedOperatorHandle<clamp::schema> create_clamp_typed_handle() { |
1796 | return c10::Dispatcher::singleton() |
1797 | .findSchemaOrThrow(clamp::name, clamp::overload_name) |
1798 | .typed<clamp::schema>(); |
1799 | } |
1800 | |
1801 | // aten::clamp(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor |
1802 | at::Tensor clamp::call(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
1803 | |
1804 | static auto op = create_clamp_typed_handle(); |
1805 | return op.call(self, min, max); |
1806 | } |
1807 | |
1808 | // aten::clamp(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor |
1809 | at::Tensor clamp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
1810 | |
1811 | static auto op = create_clamp_typed_handle(); |
1812 | return op.redispatch(dispatchKeySet, self, min, max); |
1813 | } |
1814 | |
1815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_Tensor, name, "aten::clamp" ) |
1816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_Tensor, overload_name, "Tensor" ) |
1817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_Tensor, schema_str, "clamp.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor" ) |
1818 | |
1819 | // aten::clamp.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor |
1820 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_Tensor::schema> create_clamp_Tensor_typed_handle() { |
1821 | return c10::Dispatcher::singleton() |
1822 | .findSchemaOrThrow(clamp_Tensor::name, clamp_Tensor::overload_name) |
1823 | .typed<clamp_Tensor::schema>(); |
1824 | } |
1825 | |
1826 | // aten::clamp.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor |
1827 | at::Tensor clamp_Tensor::call(const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
1828 | |
1829 | static auto op = create_clamp_Tensor_typed_handle(); |
1830 | return op.call(self, min, max); |
1831 | } |
1832 | |
1833 | // aten::clamp.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor |
1834 | at::Tensor clamp_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
1835 | |
1836 | static auto op = create_clamp_Tensor_typed_handle(); |
1837 | return op.redispatch(dispatchKeySet, self, min, max); |
1838 | } |
1839 | |
1840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_, name, "aten::clamp_" ) |
1841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_, overload_name, "" ) |
1842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_, schema_str, "clamp_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!)" ) |
1843 | |
1844 | // aten::clamp_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!) |
1845 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_::schema> create_clamp__typed_handle() { |
1846 | return c10::Dispatcher::singleton() |
1847 | .findSchemaOrThrow(clamp_::name, clamp_::overload_name) |
1848 | .typed<clamp_::schema>(); |
1849 | } |
1850 | |
1851 | // aten::clamp_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!) |
1852 | at::Tensor & clamp_::call(at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
1853 | |
1854 | static auto op = create_clamp__typed_handle(); |
1855 | return op.call(self, min, max); |
1856 | } |
1857 | |
1858 | // aten::clamp_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!) |
1859 | at::Tensor & clamp_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
1860 | |
1861 | static auto op = create_clamp__typed_handle(); |
1862 | return op.redispatch(dispatchKeySet, self, min, max); |
1863 | } |
1864 | |
1865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp__Tensor, name, "aten::clamp_" ) |
1866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp__Tensor, overload_name, "Tensor" ) |
1867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp__Tensor, schema_str, "clamp_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!)" ) |
1868 | |
1869 | // aten::clamp_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!) |
1870 | static C10_NOINLINE c10::TypedOperatorHandle<clamp__Tensor::schema> create_clamp__Tensor_typed_handle() { |
1871 | return c10::Dispatcher::singleton() |
1872 | .findSchemaOrThrow(clamp__Tensor::name, clamp__Tensor::overload_name) |
1873 | .typed<clamp__Tensor::schema>(); |
1874 | } |
1875 | |
1876 | // aten::clamp_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!) |
1877 | at::Tensor & clamp__Tensor::call(at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
1878 | |
1879 | static auto op = create_clamp__Tensor_typed_handle(); |
1880 | return op.call(self, min, max); |
1881 | } |
1882 | |
1883 | // aten::clamp_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!) |
1884 | at::Tensor & clamp__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
1885 | |
1886 | static auto op = create_clamp__Tensor_typed_handle(); |
1887 | return op.redispatch(dispatchKeySet, self, min, max); |
1888 | } |
1889 | |
1890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_out, name, "aten::clamp" ) |
1891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_out, overload_name, "out" ) |
1892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_out, schema_str, "clamp.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
1893 | |
1894 | // aten::clamp.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) |
1895 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_out::schema> create_clamp_out_typed_handle() { |
1896 | return c10::Dispatcher::singleton() |
1897 | .findSchemaOrThrow(clamp_out::name, clamp_out::overload_name) |
1898 | .typed<clamp_out::schema>(); |
1899 | } |
1900 | |
1901 | // aten::clamp.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) |
1902 | at::Tensor & clamp_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max, at::Tensor & out) { |
1903 | |
1904 | static auto op = create_clamp_out_typed_handle(); |
1905 | return op.call(self, min, max, out); |
1906 | } |
1907 | |
1908 | // aten::clamp.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) |
1909 | at::Tensor & clamp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max, at::Tensor & out) { |
1910 | |
1911 | static auto op = create_clamp_out_typed_handle(); |
1912 | return op.redispatch(dispatchKeySet, self, min, max, out); |
1913 | } |
1914 | |
1915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_Tensor_out, name, "aten::clamp" ) |
1916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_Tensor_out, overload_name, "Tensor_out" ) |
1917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_Tensor_out, schema_str, "clamp.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
1918 | |
1919 | // aten::clamp.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) |
1920 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_Tensor_out::schema> create_clamp_Tensor_out_typed_handle() { |
1921 | return c10::Dispatcher::singleton() |
1922 | .findSchemaOrThrow(clamp_Tensor_out::name, clamp_Tensor_out::overload_name) |
1923 | .typed<clamp_Tensor_out::schema>(); |
1924 | } |
1925 | |
1926 | // aten::clamp.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) |
1927 | at::Tensor & clamp_Tensor_out::call(const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max, at::Tensor & out) { |
1928 | |
1929 | static auto op = create_clamp_Tensor_out_typed_handle(); |
1930 | return op.call(self, min, max, out); |
1931 | } |
1932 | |
1933 | // aten::clamp.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) |
1934 | at::Tensor & clamp_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max, at::Tensor & out) { |
1935 | |
1936 | static auto op = create_clamp_Tensor_out_typed_handle(); |
1937 | return op.redispatch(dispatchKeySet, self, min, max, out); |
1938 | } |
1939 | |
1940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max, name, "aten::clamp_max" ) |
1941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max, overload_name, "" ) |
1942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max, schema_str, "clamp_max(Tensor self, Scalar max) -> Tensor" ) |
1943 | |
1944 | // aten::clamp_max(Tensor self, Scalar max) -> Tensor |
1945 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_max::schema> create_clamp_max_typed_handle() { |
1946 | return c10::Dispatcher::singleton() |
1947 | .findSchemaOrThrow(clamp_max::name, clamp_max::overload_name) |
1948 | .typed<clamp_max::schema>(); |
1949 | } |
1950 | |
1951 | // aten::clamp_max(Tensor self, Scalar max) -> Tensor |
1952 | at::Tensor clamp_max::call(const at::Tensor & self, const at::Scalar & max) { |
1953 | |
1954 | static auto op = create_clamp_max_typed_handle(); |
1955 | return op.call(self, max); |
1956 | } |
1957 | |
1958 | // aten::clamp_max(Tensor self, Scalar max) -> Tensor |
1959 | at::Tensor clamp_max::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & max) { |
1960 | |
1961 | static auto op = create_clamp_max_typed_handle(); |
1962 | return op.redispatch(dispatchKeySet, self, max); |
1963 | } |
1964 | |
1965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_Tensor, name, "aten::clamp_max" ) |
1966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_Tensor, overload_name, "Tensor" ) |
1967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_Tensor, schema_str, "clamp_max.Tensor(Tensor self, Tensor max) -> Tensor" ) |
1968 | |
1969 | // aten::clamp_max.Tensor(Tensor self, Tensor max) -> Tensor |
1970 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_max_Tensor::schema> create_clamp_max_Tensor_typed_handle() { |
1971 | return c10::Dispatcher::singleton() |
1972 | .findSchemaOrThrow(clamp_max_Tensor::name, clamp_max_Tensor::overload_name) |
1973 | .typed<clamp_max_Tensor::schema>(); |
1974 | } |
1975 | |
1976 | // aten::clamp_max.Tensor(Tensor self, Tensor max) -> Tensor |
1977 | at::Tensor clamp_max_Tensor::call(const at::Tensor & self, const at::Tensor & max) { |
1978 | |
1979 | static auto op = create_clamp_max_Tensor_typed_handle(); |
1980 | return op.call(self, max); |
1981 | } |
1982 | |
1983 | // aten::clamp_max.Tensor(Tensor self, Tensor max) -> Tensor |
1984 | at::Tensor clamp_max_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & max) { |
1985 | |
1986 | static auto op = create_clamp_max_Tensor_typed_handle(); |
1987 | return op.redispatch(dispatchKeySet, self, max); |
1988 | } |
1989 | |
1990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_, name, "aten::clamp_max_" ) |
1991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_, overload_name, "" ) |
1992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_, schema_str, "clamp_max_(Tensor(a!) self, Scalar max) -> Tensor(a!)" ) |
1993 | |
1994 | // aten::clamp_max_(Tensor(a!) self, Scalar max) -> Tensor(a!) |
1995 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_max_::schema> create_clamp_max__typed_handle() { |
1996 | return c10::Dispatcher::singleton() |
1997 | .findSchemaOrThrow(clamp_max_::name, clamp_max_::overload_name) |
1998 | .typed<clamp_max_::schema>(); |
1999 | } |
2000 | |
2001 | // aten::clamp_max_(Tensor(a!) self, Scalar max) -> Tensor(a!) |
2002 | at::Tensor & clamp_max_::call(at::Tensor & self, const at::Scalar & max) { |
2003 | |
2004 | static auto op = create_clamp_max__typed_handle(); |
2005 | return op.call(self, max); |
2006 | } |
2007 | |
2008 | // aten::clamp_max_(Tensor(a!) self, Scalar max) -> Tensor(a!) |
2009 | at::Tensor & clamp_max_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & max) { |
2010 | |
2011 | static auto op = create_clamp_max__typed_handle(); |
2012 | return op.redispatch(dispatchKeySet, self, max); |
2013 | } |
2014 | |
2015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max__Tensor, name, "aten::clamp_max_" ) |
2016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max__Tensor, overload_name, "Tensor" ) |
2017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max__Tensor, schema_str, "clamp_max_.Tensor(Tensor(a!) self, Tensor max) -> Tensor(a!)" ) |
2018 | |
2019 | // aten::clamp_max_.Tensor(Tensor(a!) self, Tensor max) -> Tensor(a!) |
2020 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_max__Tensor::schema> create_clamp_max__Tensor_typed_handle() { |
2021 | return c10::Dispatcher::singleton() |
2022 | .findSchemaOrThrow(clamp_max__Tensor::name, clamp_max__Tensor::overload_name) |
2023 | .typed<clamp_max__Tensor::schema>(); |
2024 | } |
2025 | |
2026 | // aten::clamp_max_.Tensor(Tensor(a!) self, Tensor max) -> Tensor(a!) |
2027 | at::Tensor & clamp_max__Tensor::call(at::Tensor & self, const at::Tensor & max) { |
2028 | |
2029 | static auto op = create_clamp_max__Tensor_typed_handle(); |
2030 | return op.call(self, max); |
2031 | } |
2032 | |
2033 | // aten::clamp_max_.Tensor(Tensor(a!) self, Tensor max) -> Tensor(a!) |
2034 | at::Tensor & clamp_max__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & max) { |
2035 | |
2036 | static auto op = create_clamp_max__Tensor_typed_handle(); |
2037 | return op.redispatch(dispatchKeySet, self, max); |
2038 | } |
2039 | |
2040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_out, name, "aten::clamp_max" ) |
2041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_out, overload_name, "out" ) |
2042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_out, schema_str, "clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!)" ) |
2043 | |
2044 | // aten::clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!) |
2045 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_max_out::schema> create_clamp_max_out_typed_handle() { |
2046 | return c10::Dispatcher::singleton() |
2047 | .findSchemaOrThrow(clamp_max_out::name, clamp_max_out::overload_name) |
2048 | .typed<clamp_max_out::schema>(); |
2049 | } |
2050 | |
2051 | // aten::clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!) |
2052 | at::Tensor & clamp_max_out::call(const at::Tensor & self, const at::Scalar & max, at::Tensor & out) { |
2053 | |
2054 | static auto op = create_clamp_max_out_typed_handle(); |
2055 | return op.call(self, max, out); |
2056 | } |
2057 | |
2058 | // aten::clamp_max.out(Tensor self, Scalar max, *, Tensor(a!) out) -> Tensor(a!) |
2059 | at::Tensor & clamp_max_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & max, at::Tensor & out) { |
2060 | |
2061 | static auto op = create_clamp_max_out_typed_handle(); |
2062 | return op.redispatch(dispatchKeySet, self, max, out); |
2063 | } |
2064 | |
2065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_Tensor_out, name, "aten::clamp_max" ) |
2066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_Tensor_out, overload_name, "Tensor_out" ) |
2067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clamp_max_Tensor_out, schema_str, "clamp_max.Tensor_out(Tensor self, Tensor max, *, Tensor(a!) out) -> Tensor(a!)" ) |
2068 | |
2069 | // aten::clamp_max.Tensor_out(Tensor self, Tensor max, *, Tensor(a!) out) -> Tensor(a!) |
2070 | static C10_NOINLINE c10::TypedOperatorHandle<clamp_max_Tensor_out::schema> create_clamp_max_Tensor_out_typed_handle() { |
2071 | return c10::Dispatcher::singleton() |
2072 | .findSchemaOrThrow(clamp_max_Tensor_out::name, clamp_max_Tensor_out::overload_name) |
2073 | .typed<clamp_max_Tensor_out::schema>(); |
2074 | } |
2075 | |
2076 | // aten::clamp_max.Tensor_out(Tensor self, Tensor max, *, Tensor(a!) out) -> Tensor(a!) |
2077 | at::Tensor & clamp_max_Tensor_out::call(const at::Tensor & self, const at::Tensor & max, at::Tensor & out) { |
2078 | |
2079 | static auto op = create_clamp_max_Tensor_out_typed_handle(); |
2080 | return op.call(self, max, out); |
2081 | } |
2082 | |
2083 | // aten::clamp_max.Tensor_out(Tensor self, Tensor max, *, Tensor(a!) out) -> Tensor(a!) |
2084 | at::Tensor & clamp_max_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & max, at::Tensor & out) { |
2085 | |
2086 | static auto op = create_clamp_max_Tensor_out_typed_handle(); |
2087 | return op.redispatch(dispatchKeySet, self, max, out); |
2088 | } |
2089 | |
2090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip, name, "aten::clip" ) |
2091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip, overload_name, "" ) |
2092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip, schema_str, "clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor" ) |
2093 | |
2094 | // aten::clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor |
2095 | static C10_NOINLINE c10::TypedOperatorHandle<clip::schema> create_clip_typed_handle() { |
2096 | return c10::Dispatcher::singleton() |
2097 | .findSchemaOrThrow(clip::name, clip::overload_name) |
2098 | .typed<clip::schema>(); |
2099 | } |
2100 | |
2101 | // aten::clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor |
2102 | at::Tensor clip::call(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
2103 | |
2104 | static auto op = create_clip_typed_handle(); |
2105 | return op.call(self, min, max); |
2106 | } |
2107 | |
2108 | // aten::clip(Tensor self, Scalar? min=None, Scalar? max=None) -> Tensor |
2109 | at::Tensor clip::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
2110 | |
2111 | static auto op = create_clip_typed_handle(); |
2112 | return op.redispatch(dispatchKeySet, self, min, max); |
2113 | } |
2114 | |
2115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_Tensor, name, "aten::clip" ) |
2116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_Tensor, overload_name, "Tensor" ) |
2117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_Tensor, schema_str, "clip.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor" ) |
2118 | |
2119 | // aten::clip.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor |
2120 | static C10_NOINLINE c10::TypedOperatorHandle<clip_Tensor::schema> create_clip_Tensor_typed_handle() { |
2121 | return c10::Dispatcher::singleton() |
2122 | .findSchemaOrThrow(clip_Tensor::name, clip_Tensor::overload_name) |
2123 | .typed<clip_Tensor::schema>(); |
2124 | } |
2125 | |
2126 | // aten::clip.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor |
2127 | at::Tensor clip_Tensor::call(const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
2128 | |
2129 | static auto op = create_clip_Tensor_typed_handle(); |
2130 | return op.call(self, min, max); |
2131 | } |
2132 | |
2133 | // aten::clip.Tensor(Tensor self, Tensor? min=None, Tensor? max=None) -> Tensor |
2134 | at::Tensor clip_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
2135 | |
2136 | static auto op = create_clip_Tensor_typed_handle(); |
2137 | return op.redispatch(dispatchKeySet, self, min, max); |
2138 | } |
2139 | |
2140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_, name, "aten::clip_" ) |
2141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_, overload_name, "" ) |
2142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_, schema_str, "clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!)" ) |
2143 | |
2144 | // aten::clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!) |
2145 | static C10_NOINLINE c10::TypedOperatorHandle<clip_::schema> create_clip__typed_handle() { |
2146 | return c10::Dispatcher::singleton() |
2147 | .findSchemaOrThrow(clip_::name, clip_::overload_name) |
2148 | .typed<clip_::schema>(); |
2149 | } |
2150 | |
2151 | // aten::clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!) |
2152 | at::Tensor & clip_::call(at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
2153 | |
2154 | static auto op = create_clip__typed_handle(); |
2155 | return op.call(self, min, max); |
2156 | } |
2157 | |
2158 | // aten::clip_(Tensor(a!) self, Scalar? min=None, Scalar? max=None) -> Tensor(a!) |
2159 | at::Tensor & clip_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max) { |
2160 | |
2161 | static auto op = create_clip__typed_handle(); |
2162 | return op.redispatch(dispatchKeySet, self, min, max); |
2163 | } |
2164 | |
2165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip__Tensor, name, "aten::clip_" ) |
2166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip__Tensor, overload_name, "Tensor" ) |
2167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip__Tensor, schema_str, "clip_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!)" ) |
2168 | |
2169 | // aten::clip_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!) |
2170 | static C10_NOINLINE c10::TypedOperatorHandle<clip__Tensor::schema> create_clip__Tensor_typed_handle() { |
2171 | return c10::Dispatcher::singleton() |
2172 | .findSchemaOrThrow(clip__Tensor::name, clip__Tensor::overload_name) |
2173 | .typed<clip__Tensor::schema>(); |
2174 | } |
2175 | |
2176 | // aten::clip_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!) |
2177 | at::Tensor & clip__Tensor::call(at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
2178 | |
2179 | static auto op = create_clip__Tensor_typed_handle(); |
2180 | return op.call(self, min, max); |
2181 | } |
2182 | |
2183 | // aten::clip_.Tensor(Tensor(a!) self, Tensor? min=None, Tensor? max=None) -> Tensor(a!) |
2184 | at::Tensor & clip__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max) { |
2185 | |
2186 | static auto op = create_clip__Tensor_typed_handle(); |
2187 | return op.redispatch(dispatchKeySet, self, min, max); |
2188 | } |
2189 | |
2190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_out, name, "aten::clip" ) |
2191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_out, overload_name, "out" ) |
2192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_out, schema_str, "clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
2193 | |
2194 | // aten::clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) |
2195 | static C10_NOINLINE c10::TypedOperatorHandle<clip_out::schema> create_clip_out_typed_handle() { |
2196 | return c10::Dispatcher::singleton() |
2197 | .findSchemaOrThrow(clip_out::name, clip_out::overload_name) |
2198 | .typed<clip_out::schema>(); |
2199 | } |
2200 | |
2201 | // aten::clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) |
2202 | at::Tensor & clip_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max, at::Tensor & out) { |
2203 | |
2204 | static auto op = create_clip_out_typed_handle(); |
2205 | return op.call(self, min, max, out); |
2206 | } |
2207 | |
2208 | // aten::clip.out(Tensor self, Scalar? min=None, Scalar? max=None, *, Tensor(a!) out) -> Tensor(a!) |
2209 | at::Tensor & clip_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & min, const c10::optional<at::Scalar> & max, at::Tensor & out) { |
2210 | |
2211 | static auto op = create_clip_out_typed_handle(); |
2212 | return op.redispatch(dispatchKeySet, self, min, max, out); |
2213 | } |
2214 | |
2215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_Tensor_out, name, "aten::clip" ) |
2216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_Tensor_out, overload_name, "Tensor_out" ) |
2217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(clip_Tensor_out, schema_str, "clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
2218 | |
2219 | // aten::clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) |
2220 | static C10_NOINLINE c10::TypedOperatorHandle<clip_Tensor_out::schema> create_clip_Tensor_out_typed_handle() { |
2221 | return c10::Dispatcher::singleton() |
2222 | .findSchemaOrThrow(clip_Tensor_out::name, clip_Tensor_out::overload_name) |
2223 | .typed<clip_Tensor_out::schema>(); |
2224 | } |
2225 | |
2226 | // aten::clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) |
2227 | at::Tensor & clip_Tensor_out::call(const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max, at::Tensor & out) { |
2228 | |
2229 | static auto op = create_clip_Tensor_out_typed_handle(); |
2230 | return op.call(self, min, max, out); |
2231 | } |
2232 | |
2233 | // aten::clip.Tensor_out(Tensor self, Tensor? min=None, Tensor? max=None, *, Tensor(a!) out) -> Tensor(a!) |
2234 | at::Tensor & clip_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Tensor> & min, const c10::optional<at::Tensor> & max, at::Tensor & out) { |
2235 | |
2236 | static auto op = create_clip_Tensor_out_typed_handle(); |
2237 | return op.redispatch(dispatchKeySet, self, min, max, out); |
2238 | } |
2239 | |
2240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_is_acceptable, name, "aten::cudnn_is_acceptable" ) |
2241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_is_acceptable, overload_name, "" ) |
2242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_is_acceptable, schema_str, "cudnn_is_acceptable(Tensor self) -> bool" ) |
2243 | |
2244 | // aten::cudnn_is_acceptable(Tensor self) -> bool |
2245 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_is_acceptable::schema> create_cudnn_is_acceptable_typed_handle() { |
2246 | return c10::Dispatcher::singleton() |
2247 | .findSchemaOrThrow(cudnn_is_acceptable::name, cudnn_is_acceptable::overload_name) |
2248 | .typed<cudnn_is_acceptable::schema>(); |
2249 | } |
2250 | |
2251 | // aten::cudnn_is_acceptable(Tensor self) -> bool |
2252 | bool cudnn_is_acceptable::call(const at::Tensor & self) { |
2253 | |
2254 | static auto op = create_cudnn_is_acceptable_typed_handle(); |
2255 | return op.call(self); |
2256 | } |
2257 | |
2258 | // aten::cudnn_is_acceptable(Tensor self) -> bool |
2259 | bool cudnn_is_acceptable::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
2260 | |
2261 | static auto op = create_cudnn_is_acceptable_typed_handle(); |
2262 | return op.redispatch(dispatchKeySet, self); |
2263 | } |
2264 | |
2265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(complex, name, "aten::complex" ) |
2266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(complex, overload_name, "" ) |
2267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(complex, schema_str, "complex(Tensor real, Tensor imag) -> Tensor" ) |
2268 | |
2269 | // aten::complex(Tensor real, Tensor imag) -> Tensor |
2270 | static C10_NOINLINE c10::TypedOperatorHandle<complex::schema> create_complex_typed_handle() { |
2271 | return c10::Dispatcher::singleton() |
2272 | .findSchemaOrThrow(complex::name, complex::overload_name) |
2273 | .typed<complex::schema>(); |
2274 | } |
2275 | |
2276 | // aten::complex(Tensor real, Tensor imag) -> Tensor |
2277 | at::Tensor complex::call(const at::Tensor & real, const at::Tensor & imag) { |
2278 | |
2279 | static auto op = create_complex_typed_handle(); |
2280 | return op.call(real, imag); |
2281 | } |
2282 | |
2283 | // aten::complex(Tensor real, Tensor imag) -> Tensor |
2284 | at::Tensor complex::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & real, const at::Tensor & imag) { |
2285 | |
2286 | static auto op = create_complex_typed_handle(); |
2287 | return op.redispatch(dispatchKeySet, real, imag); |
2288 | } |
2289 | |
2290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(complex_out, name, "aten::complex" ) |
2291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(complex_out, overload_name, "out" ) |
2292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(complex_out, schema_str, "complex.out(Tensor real, Tensor imag, *, Tensor(a!) out) -> Tensor(a!)" ) |
2293 | |
2294 | // aten::complex.out(Tensor real, Tensor imag, *, Tensor(a!) out) -> Tensor(a!) |
2295 | static C10_NOINLINE c10::TypedOperatorHandle<complex_out::schema> create_complex_out_typed_handle() { |
2296 | return c10::Dispatcher::singleton() |
2297 | .findSchemaOrThrow(complex_out::name, complex_out::overload_name) |
2298 | .typed<complex_out::schema>(); |
2299 | } |
2300 | |
2301 | // aten::complex.out(Tensor real, Tensor imag, *, Tensor(a!) out) -> Tensor(a!) |
2302 | at::Tensor & complex_out::call(const at::Tensor & real, const at::Tensor & imag, at::Tensor & out) { |
2303 | |
2304 | static auto op = create_complex_out_typed_handle(); |
2305 | return op.call(real, imag, out); |
2306 | } |
2307 | |
2308 | // aten::complex.out(Tensor real, Tensor imag, *, Tensor(a!) out) -> Tensor(a!) |
2309 | at::Tensor & complex_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & real, const at::Tensor & imag, at::Tensor & out) { |
2310 | |
2311 | static auto op = create_complex_out_typed_handle(); |
2312 | return op.redispatch(dispatchKeySet, real, imag, out); |
2313 | } |
2314 | |
2315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(polar, name, "aten::polar" ) |
2316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(polar, overload_name, "" ) |
2317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(polar, schema_str, "polar(Tensor abs, Tensor angle) -> Tensor" ) |
2318 | |
2319 | // aten::polar(Tensor abs, Tensor angle) -> Tensor |
2320 | static C10_NOINLINE c10::TypedOperatorHandle<polar::schema> create_polar_typed_handle() { |
2321 | return c10::Dispatcher::singleton() |
2322 | .findSchemaOrThrow(polar::name, polar::overload_name) |
2323 | .typed<polar::schema>(); |
2324 | } |
2325 | |
2326 | // aten::polar(Tensor abs, Tensor angle) -> Tensor |
2327 | at::Tensor polar::call(const at::Tensor & abs, const at::Tensor & angle) { |
2328 | |
2329 | static auto op = create_polar_typed_handle(); |
2330 | return op.call(abs, angle); |
2331 | } |
2332 | |
2333 | // aten::polar(Tensor abs, Tensor angle) -> Tensor |
2334 | at::Tensor polar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & abs, const at::Tensor & angle) { |
2335 | |
2336 | static auto op = create_polar_typed_handle(); |
2337 | return op.redispatch(dispatchKeySet, abs, angle); |
2338 | } |
2339 | |
2340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(polar_out, name, "aten::polar" ) |
2341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(polar_out, overload_name, "out" ) |
2342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(polar_out, schema_str, "polar.out(Tensor abs, Tensor angle, *, Tensor(a!) out) -> Tensor(a!)" ) |
2343 | |
2344 | // aten::polar.out(Tensor abs, Tensor angle, *, Tensor(a!) out) -> Tensor(a!) |
2345 | static C10_NOINLINE c10::TypedOperatorHandle<polar_out::schema> create_polar_out_typed_handle() { |
2346 | return c10::Dispatcher::singleton() |
2347 | .findSchemaOrThrow(polar_out::name, polar_out::overload_name) |
2348 | .typed<polar_out::schema>(); |
2349 | } |
2350 | |
2351 | // aten::polar.out(Tensor abs, Tensor angle, *, Tensor(a!) out) -> Tensor(a!) |
2352 | at::Tensor & polar_out::call(const at::Tensor & abs, const at::Tensor & angle, at::Tensor & out) { |
2353 | |
2354 | static auto op = create_polar_out_typed_handle(); |
2355 | return op.call(abs, angle, out); |
2356 | } |
2357 | |
2358 | // aten::polar.out(Tensor abs, Tensor angle, *, Tensor(a!) out) -> Tensor(a!) |
2359 | at::Tensor & polar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & abs, const at::Tensor & angle, at::Tensor & out) { |
2360 | |
2361 | static auto op = create_polar_out_typed_handle(); |
2362 | return op.redispatch(dispatchKeySet, abs, angle, out); |
2363 | } |
2364 | |
2365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv_transpose2d_input, name, "aten::conv_transpose2d" ) |
2366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv_transpose2d_input, overload_name, "input" ) |
2367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(conv_transpose2d_input, schema_str, "conv_transpose2d.input(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int groups=1, int[2] dilation=1) -> Tensor" ) |
2368 | |
2369 | // aten::conv_transpose2d.input(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int groups=1, int[2] dilation=1) -> Tensor |
2370 | static C10_NOINLINE c10::TypedOperatorHandle<conv_transpose2d_input::schema> create_conv_transpose2d_input_typed_handle() { |
2371 | return c10::Dispatcher::singleton() |
2372 | .findSchemaOrThrow(conv_transpose2d_input::name, conv_transpose2d_input::overload_name) |
2373 | .typed<conv_transpose2d_input::schema>(); |
2374 | } |
2375 | |
2376 | // aten::conv_transpose2d.input(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int groups=1, int[2] dilation=1) -> Tensor |
2377 | at::Tensor conv_transpose2d_input::call(const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, int64_t groups, at::IntArrayRef dilation) { |
2378 | |
2379 | static auto op = create_conv_transpose2d_input_typed_handle(); |
2380 | return op.call(input, weight, bias, stride, padding, output_padding, groups, dilation); |
2381 | } |
2382 | |
2383 | // aten::conv_transpose2d.input(Tensor input, Tensor weight, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int groups=1, int[2] dilation=1) -> Tensor |
2384 | at::Tensor conv_transpose2d_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef output_padding, int64_t groups, at::IntArrayRef dilation) { |
2385 | |
2386 | static auto op = create_conv_transpose2d_input_typed_handle(); |
2387 | return op.redispatch(dispatchKeySet, input, weight, bias, stride, padding, output_padding, groups, dilation); |
2388 | } |
2389 | |
2390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_dim_IntList, name, "aten::count_nonzero" ) |
2391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_dim_IntList, overload_name, "dim_IntList" ) |
2392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_dim_IntList, schema_str, "count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor" ) |
2393 | |
2394 | // aten::count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor |
2395 | static C10_NOINLINE c10::TypedOperatorHandle<count_nonzero_dim_IntList::schema> create_count_nonzero_dim_IntList_typed_handle() { |
2396 | return c10::Dispatcher::singleton() |
2397 | .findSchemaOrThrow(count_nonzero_dim_IntList::name, count_nonzero_dim_IntList::overload_name) |
2398 | .typed<count_nonzero_dim_IntList::schema>(); |
2399 | } |
2400 | |
2401 | // aten::count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor |
2402 | at::Tensor count_nonzero_dim_IntList::call(const at::Tensor & self, at::IntArrayRef dim) { |
2403 | |
2404 | static auto op = create_count_nonzero_dim_IntList_typed_handle(); |
2405 | return op.call(self, dim); |
2406 | } |
2407 | |
2408 | // aten::count_nonzero.dim_IntList(Tensor self, int[] dim) -> Tensor |
2409 | at::Tensor count_nonzero_dim_IntList::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim) { |
2410 | |
2411 | static auto op = create_count_nonzero_dim_IntList_typed_handle(); |
2412 | return op.redispatch(dispatchKeySet, self, dim); |
2413 | } |
2414 | |
2415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero, name, "aten::count_nonzero" ) |
2416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero, overload_name, "" ) |
2417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero, schema_str, "count_nonzero(Tensor self, int? dim=None) -> Tensor" ) |
2418 | |
2419 | // aten::count_nonzero(Tensor self, int? dim=None) -> Tensor |
2420 | static C10_NOINLINE c10::TypedOperatorHandle<count_nonzero::schema> create_count_nonzero_typed_handle() { |
2421 | return c10::Dispatcher::singleton() |
2422 | .findSchemaOrThrow(count_nonzero::name, count_nonzero::overload_name) |
2423 | .typed<count_nonzero::schema>(); |
2424 | } |
2425 | |
2426 | // aten::count_nonzero(Tensor self, int? dim=None) -> Tensor |
2427 | at::Tensor count_nonzero::call(const at::Tensor & self, c10::optional<int64_t> dim) { |
2428 | |
2429 | static auto op = create_count_nonzero_typed_handle(); |
2430 | return op.call(self, dim); |
2431 | } |
2432 | |
2433 | // aten::count_nonzero(Tensor self, int? dim=None) -> Tensor |
2434 | at::Tensor count_nonzero::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dim) { |
2435 | |
2436 | static auto op = create_count_nonzero_typed_handle(); |
2437 | return op.redispatch(dispatchKeySet, self, dim); |
2438 | } |
2439 | |
2440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cov, name, "aten::cov" ) |
2441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cov, overload_name, "" ) |
2442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cov, schema_str, "cov(Tensor self, *, int correction=1, Tensor? fweights=None, Tensor? aweights=None) -> Tensor" ) |
2443 | |
2444 | // aten::cov(Tensor self, *, int correction=1, Tensor? fweights=None, Tensor? aweights=None) -> Tensor |
2445 | static C10_NOINLINE c10::TypedOperatorHandle<cov::schema> create_cov_typed_handle() { |
2446 | return c10::Dispatcher::singleton() |
2447 | .findSchemaOrThrow(cov::name, cov::overload_name) |
2448 | .typed<cov::schema>(); |
2449 | } |
2450 | |
2451 | // aten::cov(Tensor self, *, int correction=1, Tensor? fweights=None, Tensor? aweights=None) -> Tensor |
2452 | at::Tensor cov::call(const at::Tensor & self, int64_t correction, const c10::optional<at::Tensor> & fweights, const c10::optional<at::Tensor> & aweights) { |
2453 | |
2454 | static auto op = create_cov_typed_handle(); |
2455 | return op.call(self, correction, fweights, aweights); |
2456 | } |
2457 | |
2458 | // aten::cov(Tensor self, *, int correction=1, Tensor? fweights=None, Tensor? aweights=None) -> Tensor |
2459 | at::Tensor cov::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t correction, const c10::optional<at::Tensor> & fweights, const c10::optional<at::Tensor> & aweights) { |
2460 | |
2461 | static auto op = create_cov_typed_handle(); |
2462 | return op.redispatch(dispatchKeySet, self, correction, fweights, aweights); |
2463 | } |
2464 | |
2465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_add_relu, name, "aten::cudnn_convolution_add_relu" ) |
2466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_add_relu, overload_name, "" ) |
2467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_add_relu, schema_str, "cudnn_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor" ) |
2468 | |
2469 | // aten::cudnn_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
2470 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_convolution_add_relu::schema> create_cudnn_convolution_add_relu_typed_handle() { |
2471 | return c10::Dispatcher::singleton() |
2472 | .findSchemaOrThrow(cudnn_convolution_add_relu::name, cudnn_convolution_add_relu::overload_name) |
2473 | .typed<cudnn_convolution_add_relu::schema>(); |
2474 | } |
2475 | |
2476 | // aten::cudnn_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
2477 | at::Tensor cudnn_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) { |
2478 | |
2479 | static auto op = create_cudnn_convolution_add_relu_typed_handle(); |
2480 | return op.call(self, weight, z, alpha, bias, stride, padding, dilation, groups); |
2481 | } |
2482 | |
2483 | // aten::cudnn_convolution_add_relu(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups) -> Tensor |
2484 | at::Tensor cudnn_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) { |
2485 | |
2486 | static auto op = create_cudnn_convolution_add_relu_typed_handle(); |
2487 | return op.redispatch(dispatchKeySet, self, weight, z, alpha, bias, stride, padding, dilation, groups); |
2488 | } |
2489 | |
2490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax, name, "aten::cummax" ) |
2491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax, overload_name, "" ) |
2492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax, schema_str, "cummax(Tensor self, int dim) -> (Tensor values, Tensor indices)" ) |
2493 | |
2494 | // aten::cummax(Tensor self, int dim) -> (Tensor values, Tensor indices) |
2495 | static C10_NOINLINE c10::TypedOperatorHandle<cummax::schema> create_cummax_typed_handle() { |
2496 | return c10::Dispatcher::singleton() |
2497 | .findSchemaOrThrow(cummax::name, cummax::overload_name) |
2498 | .typed<cummax::schema>(); |
2499 | } |
2500 | |
2501 | // aten::cummax(Tensor self, int dim) -> (Tensor values, Tensor indices) |
2502 | ::std::tuple<at::Tensor,at::Tensor> cummax::call(const at::Tensor & self, int64_t dim) { |
2503 | |
2504 | static auto op = create_cummax_typed_handle(); |
2505 | return op.call(self, dim); |
2506 | } |
2507 | |
2508 | // aten::cummax(Tensor self, int dim) -> (Tensor values, Tensor indices) |
2509 | ::std::tuple<at::Tensor,at::Tensor> cummax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim) { |
2510 | |
2511 | static auto op = create_cummax_typed_handle(); |
2512 | return op.redispatch(dispatchKeySet, self, dim); |
2513 | } |
2514 | |
2515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_out, name, "aten::cummax" ) |
2516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_out, overload_name, "out" ) |
2517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_out, schema_str, "cummax.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)" ) |
2518 | |
2519 | // aten::cummax.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
2520 | static C10_NOINLINE c10::TypedOperatorHandle<cummax_out::schema> create_cummax_out_typed_handle() { |
2521 | return c10::Dispatcher::singleton() |
2522 | .findSchemaOrThrow(cummax_out::name, cummax_out::overload_name) |
2523 | .typed<cummax_out::schema>(); |
2524 | } |
2525 | |
2526 | // aten::cummax.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
2527 | ::std::tuple<at::Tensor &,at::Tensor &> cummax_out::call(const at::Tensor & self, int64_t dim, at::Tensor & values, at::Tensor & indices) { |
2528 | |
2529 | static auto op = create_cummax_out_typed_handle(); |
2530 | return op.call(self, dim, values, indices); |
2531 | } |
2532 | |
2533 | // aten::cummax.out(Tensor self, int dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
2534 | ::std::tuple<at::Tensor &,at::Tensor &> cummax_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, at::Tensor & values, at::Tensor & indices) { |
2535 | |
2536 | static auto op = create_cummax_out_typed_handle(); |
2537 | return op.redispatch(dispatchKeySet, self, dim, values, indices); |
2538 | } |
2539 | |
2540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_dimname, name, "aten::cummax" ) |
2541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_dimname, overload_name, "dimname" ) |
2542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_dimname, schema_str, "cummax.dimname(Tensor self, Dimname dim) -> (Tensor values, Tensor indices)" ) |
2543 | |
2544 | // aten::cummax.dimname(Tensor self, Dimname dim) -> (Tensor values, Tensor indices) |
2545 | static C10_NOINLINE c10::TypedOperatorHandle<cummax_dimname::schema> create_cummax_dimname_typed_handle() { |
2546 | return c10::Dispatcher::singleton() |
2547 | .findSchemaOrThrow(cummax_dimname::name, cummax_dimname::overload_name) |
2548 | .typed<cummax_dimname::schema>(); |
2549 | } |
2550 | |
2551 | // aten::cummax.dimname(Tensor self, Dimname dim) -> (Tensor values, Tensor indices) |
2552 | ::std::tuple<at::Tensor,at::Tensor> cummax_dimname::call(const at::Tensor & self, at::Dimname dim) { |
2553 | |
2554 | static auto op = create_cummax_dimname_typed_handle(); |
2555 | return op.call(self, dim); |
2556 | } |
2557 | |
2558 | // aten::cummax.dimname(Tensor self, Dimname dim) -> (Tensor values, Tensor indices) |
2559 | ::std::tuple<at::Tensor,at::Tensor> cummax_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim) { |
2560 | |
2561 | static auto op = create_cummax_dimname_typed_handle(); |
2562 | return op.redispatch(dispatchKeySet, self, dim); |
2563 | } |
2564 | |
2565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_dimname_out, name, "aten::cummax" ) |
2566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_dimname_out, overload_name, "dimname_out" ) |
2567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cummax_dimname_out, schema_str, "cummax.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)" ) |
2568 | |
2569 | // aten::cummax.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
2570 | static C10_NOINLINE c10::TypedOperatorHandle<cummax_dimname_out::schema> create_cummax_dimname_out_typed_handle() { |
2571 | return c10::Dispatcher::singleton() |
2572 | .findSchemaOrThrow(cummax_dimname_out::name, cummax_dimname_out::overload_name) |
2573 | .typed<cummax_dimname_out::schema>(); |
2574 | } |
2575 | |
2576 | // aten::cummax.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
2577 | ::std::tuple<at::Tensor &,at::Tensor &> cummax_dimname_out::call(const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices) { |
2578 | |
2579 | static auto op = create_cummax_dimname_out_typed_handle(); |
2580 | return op.call(self, dim, values, indices); |
2581 | } |
2582 | |
2583 | // aten::cummax.dimname_out(Tensor self, Dimname dim, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
2584 | ::std::tuple<at::Tensor &,at::Tensor &> cummax_dimname_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, at::Tensor & values, at::Tensor & indices) { |
2585 | |
2586 | static auto op = create_cummax_dimname_out_typed_handle(); |
2587 | return op.redispatch(dispatchKeySet, self, dim, values, indices); |
2588 | } |
2589 | |
2590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cummax_helper, name, "aten::_cummax_helper" ) |
2591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cummax_helper, overload_name, "" ) |
2592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cummax_helper, schema_str, "_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> ()" ) |
2593 | |
2594 | // aten::_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> () |
2595 | static C10_NOINLINE c10::TypedOperatorHandle<_cummax_helper::schema> create__cummax_helper_typed_handle() { |
2596 | return c10::Dispatcher::singleton() |
2597 | .findSchemaOrThrow(_cummax_helper::name, _cummax_helper::overload_name) |
2598 | .typed<_cummax_helper::schema>(); |
2599 | } |
2600 | |
2601 | // aten::_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> () |
2602 | void _cummax_helper::call(const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim) { |
2603 | |
2604 | static auto op = create__cummax_helper_typed_handle(); |
2605 | return op.call(self, values, indices, dim); |
2606 | } |
2607 | |
2608 | // aten::_cummax_helper(Tensor self, Tensor(a!) values, Tensor(b!) indices, int dim) -> () |
2609 | void _cummax_helper::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & values, at::Tensor & indices, int64_t dim) { |
2610 | |
2611 | static auto op = create__cummax_helper_typed_handle(); |
2612 | return op.redispatch(dispatchKeySet, self, values, indices, dim); |
2613 | } |
2614 | |
2615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward, name, "aten::_ctc_loss_backward" ) |
2616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward, overload_name, "" ) |
2617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward, schema_str, "_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor" ) |
2618 | |
2619 | // aten::_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor |
2620 | static C10_NOINLINE c10::TypedOperatorHandle<_ctc_loss_backward::schema> create__ctc_loss_backward_typed_handle() { |
2621 | return c10::Dispatcher::singleton() |
2622 | .findSchemaOrThrow(_ctc_loss_backward::name, _ctc_loss_backward::overload_name) |
2623 | .typed<_ctc_loss_backward::schema>(); |
2624 | } |
2625 | |
2626 | // aten::_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor |
2627 | at::Tensor _ctc_loss_backward::call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity) { |
2628 | |
2629 | static auto op = create__ctc_loss_backward_typed_handle(); |
2630 | return op.call(grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); |
2631 | } |
2632 | |
2633 | // aten::_ctc_loss_backward(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor |
2634 | at::Tensor _ctc_loss_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity) { |
2635 | |
2636 | static auto op = create__ctc_loss_backward_typed_handle(); |
2637 | return op.redispatch(dispatchKeySet, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); |
2638 | } |
2639 | |
2640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward_Tensor, name, "aten::_ctc_loss_backward" ) |
2641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward_Tensor, overload_name, "Tensor" ) |
2642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward_Tensor, schema_str, "_ctc_loss_backward.Tensor(Tensor grad, Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor" ) |
2643 | |
2644 | // aten::_ctc_loss_backward.Tensor(Tensor grad, Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor |
2645 | static C10_NOINLINE c10::TypedOperatorHandle<_ctc_loss_backward_Tensor::schema> create__ctc_loss_backward_Tensor_typed_handle() { |
2646 | return c10::Dispatcher::singleton() |
2647 | .findSchemaOrThrow(_ctc_loss_backward_Tensor::name, _ctc_loss_backward_Tensor::overload_name) |
2648 | .typed<_ctc_loss_backward_Tensor::schema>(); |
2649 | } |
2650 | |
2651 | // aten::_ctc_loss_backward.Tensor(Tensor grad, Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor |
2652 | at::Tensor _ctc_loss_backward_Tensor::call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity) { |
2653 | |
2654 | static auto op = create__ctc_loss_backward_Tensor_typed_handle(); |
2655 | return op.call(grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); |
2656 | } |
2657 | |
2658 | // aten::_ctc_loss_backward.Tensor(Tensor grad, Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False) -> Tensor |
2659 | at::Tensor _ctc_loss_backward_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, const at::Tensor & input_lengths, const at::Tensor & target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity) { |
2660 | |
2661 | static auto op = create__ctc_loss_backward_Tensor_typed_handle(); |
2662 | return op.redispatch(dispatchKeySet, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); |
2663 | } |
2664 | |
2665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_backward, name, "aten::diagonal_backward" ) |
2666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_backward, overload_name, "" ) |
2667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_backward, schema_str, "diagonal_backward(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2) -> Tensor" ) |
2668 | |
2669 | // aten::diagonal_backward(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2) -> Tensor |
2670 | static C10_NOINLINE c10::TypedOperatorHandle<diagonal_backward::schema> create_diagonal_backward_typed_handle() { |
2671 | return c10::Dispatcher::singleton() |
2672 | .findSchemaOrThrow(diagonal_backward::name, diagonal_backward::overload_name) |
2673 | .typed<diagonal_backward::schema>(); |
2674 | } |
2675 | |
2676 | // aten::diagonal_backward(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2) -> Tensor |
2677 | at::Tensor diagonal_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2) { |
2678 | |
2679 | static auto op = create_diagonal_backward_typed_handle(); |
2680 | return op.call(grad_output, input_sizes, offset, dim1, dim2); |
2681 | } |
2682 | |
2683 | // aten::diagonal_backward(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2) -> Tensor |
2684 | at::Tensor diagonal_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2) { |
2685 | |
2686 | static auto op = create_diagonal_backward_typed_handle(); |
2687 | return op.redispatch(dispatchKeySet, grad_output, input_sizes, offset, dim1, dim2); |
2688 | } |
2689 | |
2690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diff, name, "aten::diff" ) |
2691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diff, overload_name, "" ) |
2692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diff, schema_str, "diff(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None) -> Tensor" ) |
2693 | |
2694 | // aten::diff(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None) -> Tensor |
2695 | static C10_NOINLINE c10::TypedOperatorHandle<diff::schema> create_diff_typed_handle() { |
2696 | return c10::Dispatcher::singleton() |
2697 | .findSchemaOrThrow(diff::name, diff::overload_name) |
2698 | .typed<diff::schema>(); |
2699 | } |
2700 | |
2701 | // aten::diff(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None) -> Tensor |
2702 | at::Tensor diff::call(const at::Tensor & self, int64_t n, int64_t dim, const c10::optional<at::Tensor> & prepend, const c10::optional<at::Tensor> & append) { |
2703 | |
2704 | static auto op = create_diff_typed_handle(); |
2705 | return op.call(self, n, dim, prepend, append); |
2706 | } |
2707 | |
2708 | // aten::diff(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None) -> Tensor |
2709 | at::Tensor diff::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n, int64_t dim, const c10::optional<at::Tensor> & prepend, const c10::optional<at::Tensor> & append) { |
2710 | |
2711 | static auto op = create_diff_typed_handle(); |
2712 | return op.redispatch(dispatchKeySet, self, n, dim, prepend, append); |
2713 | } |
2714 | |
2715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diff_out, name, "aten::diff" ) |
2716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diff_out, overload_name, "out" ) |
2717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diff_out, schema_str, "diff.out(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
2718 | |
2719 | // aten::diff.out(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None, *, Tensor(a!) out) -> Tensor(a!) |
2720 | static C10_NOINLINE c10::TypedOperatorHandle<diff_out::schema> create_diff_out_typed_handle() { |
2721 | return c10::Dispatcher::singleton() |
2722 | .findSchemaOrThrow(diff_out::name, diff_out::overload_name) |
2723 | .typed<diff_out::schema>(); |
2724 | } |
2725 | |
2726 | // aten::diff.out(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None, *, Tensor(a!) out) -> Tensor(a!) |
2727 | at::Tensor & diff_out::call(const at::Tensor & self, int64_t n, int64_t dim, const c10::optional<at::Tensor> & prepend, const c10::optional<at::Tensor> & append, at::Tensor & out) { |
2728 | |
2729 | static auto op = create_diff_out_typed_handle(); |
2730 | return op.call(self, n, dim, prepend, append, out); |
2731 | } |
2732 | |
2733 | // aten::diff.out(Tensor self, int n=1, int dim=-1, Tensor? prepend=None, Tensor? append=None, *, Tensor(a!) out) -> Tensor(a!) |
2734 | at::Tensor & diff_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n, int64_t dim, const c10::optional<at::Tensor> & prepend, const c10::optional<at::Tensor> & append, at::Tensor & out) { |
2735 | |
2736 | static auto op = create_diff_out_typed_handle(); |
2737 | return op.redispatch(dispatchKeySet, self, n, dim, prepend, append, out); |
2738 | } |
2739 | |
2740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarint, name, "aten::gradient" ) |
2741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarint, overload_name, "scalarint" ) |
2742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarint, schema_str, "gradient.scalarint(Tensor self, *, Scalar? spacing=None, int? dim=None, int edge_order=1) -> Tensor[]" ) |
2743 | |
2744 | // aten::gradient.scalarint(Tensor self, *, Scalar? spacing=None, int? dim=None, int edge_order=1) -> Tensor[] |
2745 | static C10_NOINLINE c10::TypedOperatorHandle<gradient_scalarint::schema> create_gradient_scalarint_typed_handle() { |
2746 | return c10::Dispatcher::singleton() |
2747 | .findSchemaOrThrow(gradient_scalarint::name, gradient_scalarint::overload_name) |
2748 | .typed<gradient_scalarint::schema>(); |
2749 | } |
2750 | |
2751 | // aten::gradient.scalarint(Tensor self, *, Scalar? spacing=None, int? dim=None, int edge_order=1) -> Tensor[] |
2752 | ::std::vector<at::Tensor> gradient_scalarint::call(const at::Tensor & self, const c10::optional<at::Scalar> & spacing, c10::optional<int64_t> dim, int64_t edge_order) { |
2753 | |
2754 | static auto op = create_gradient_scalarint_typed_handle(); |
2755 | return op.call(self, spacing, dim, edge_order); |
2756 | } |
2757 | |
2758 | // aten::gradient.scalarint(Tensor self, *, Scalar? spacing=None, int? dim=None, int edge_order=1) -> Tensor[] |
2759 | ::std::vector<at::Tensor> gradient_scalarint::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & spacing, c10::optional<int64_t> dim, int64_t edge_order) { |
2760 | |
2761 | static auto op = create_gradient_scalarint_typed_handle(); |
2762 | return op.redispatch(dispatchKeySet, self, spacing, dim, edge_order); |
2763 | } |
2764 | |
2765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalararray, name, "aten::gradient" ) |
2766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalararray, overload_name, "scalararray" ) |
2767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalararray, schema_str, "gradient.scalararray(Tensor self, *, Scalar spacing, int[] dim, int edge_order=1) -> Tensor[]" ) |
2768 | |
2769 | // aten::gradient.scalararray(Tensor self, *, Scalar spacing, int[] dim, int edge_order=1) -> Tensor[] |
2770 | static C10_NOINLINE c10::TypedOperatorHandle<gradient_scalararray::schema> create_gradient_scalararray_typed_handle() { |
2771 | return c10::Dispatcher::singleton() |
2772 | .findSchemaOrThrow(gradient_scalararray::name, gradient_scalararray::overload_name) |
2773 | .typed<gradient_scalararray::schema>(); |
2774 | } |
2775 | |
2776 | // aten::gradient.scalararray(Tensor self, *, Scalar spacing, int[] dim, int edge_order=1) -> Tensor[] |
2777 | ::std::vector<at::Tensor> gradient_scalararray::call(const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order) { |
2778 | |
2779 | static auto op = create_gradient_scalararray_typed_handle(); |
2780 | return op.call(self, spacing, dim, edge_order); |
2781 | } |
2782 | |
2783 | // aten::gradient.scalararray(Tensor self, *, Scalar spacing, int[] dim, int edge_order=1) -> Tensor[] |
2784 | ::std::vector<at::Tensor> gradient_scalararray::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & spacing, at::IntArrayRef dim, int64_t edge_order) { |
2785 | |
2786 | static auto op = create_gradient_scalararray_typed_handle(); |
2787 | return op.redispatch(dispatchKeySet, self, spacing, dim, edge_order); |
2788 | } |
2789 | |
2790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_array, name, "aten::gradient" ) |
2791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_array, overload_name, "array" ) |
2792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_array, schema_str, "gradient.array(Tensor self, *, int[] dim, int edge_order=1) -> Tensor[]" ) |
2793 | |
2794 | // aten::gradient.array(Tensor self, *, int[] dim, int edge_order=1) -> Tensor[] |
2795 | static C10_NOINLINE c10::TypedOperatorHandle<gradient_array::schema> create_gradient_array_typed_handle() { |
2796 | return c10::Dispatcher::singleton() |
2797 | .findSchemaOrThrow(gradient_array::name, gradient_array::overload_name) |
2798 | .typed<gradient_array::schema>(); |
2799 | } |
2800 | |
2801 | // aten::gradient.array(Tensor self, *, int[] dim, int edge_order=1) -> Tensor[] |
2802 | ::std::vector<at::Tensor> gradient_array::call(const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order) { |
2803 | |
2804 | static auto op = create_gradient_array_typed_handle(); |
2805 | return op.call(self, dim, edge_order); |
2806 | } |
2807 | |
2808 | // aten::gradient.array(Tensor self, *, int[] dim, int edge_order=1) -> Tensor[] |
2809 | ::std::vector<at::Tensor> gradient_array::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, int64_t edge_order) { |
2810 | |
2811 | static auto op = create_gradient_array_typed_handle(); |
2812 | return op.redispatch(dispatchKeySet, self, dim, edge_order); |
2813 | } |
2814 | |
2815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarrayint, name, "aten::gradient" ) |
2816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarrayint, overload_name, "scalarrayint" ) |
2817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarrayint, schema_str, "gradient.scalarrayint(Tensor self, *, Scalar[] spacing, int? dim=None, int edge_order=1) -> Tensor[]" ) |
2818 | |
2819 | // aten::gradient.scalarrayint(Tensor self, *, Scalar[] spacing, int? dim=None, int edge_order=1) -> Tensor[] |
2820 | static C10_NOINLINE c10::TypedOperatorHandle<gradient_scalarrayint::schema> create_gradient_scalarrayint_typed_handle() { |
2821 | return c10::Dispatcher::singleton() |
2822 | .findSchemaOrThrow(gradient_scalarrayint::name, gradient_scalarrayint::overload_name) |
2823 | .typed<gradient_scalarrayint::schema>(); |
2824 | } |
2825 | |
2826 | // aten::gradient.scalarrayint(Tensor self, *, Scalar[] spacing, int? dim=None, int edge_order=1) -> Tensor[] |
2827 | ::std::vector<at::Tensor> gradient_scalarrayint::call(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, c10::optional<int64_t> dim, int64_t edge_order) { |
2828 | |
2829 | static auto op = create_gradient_scalarrayint_typed_handle(); |
2830 | return op.call(self, spacing, dim, edge_order); |
2831 | } |
2832 | |
2833 | // aten::gradient.scalarrayint(Tensor self, *, Scalar[] spacing, int? dim=None, int edge_order=1) -> Tensor[] |
2834 | ::std::vector<at::Tensor> gradient_scalarrayint::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, c10::optional<int64_t> dim, int64_t edge_order) { |
2835 | |
2836 | static auto op = create_gradient_scalarrayint_typed_handle(); |
2837 | return op.redispatch(dispatchKeySet, self, spacing, dim, edge_order); |
2838 | } |
2839 | |
2840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarrayarray, name, "aten::gradient" ) |
2841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarrayarray, overload_name, "scalarrayarray" ) |
2842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_scalarrayarray, schema_str, "gradient.scalarrayarray(Tensor self, *, Scalar[] spacing, int[] dim, int edge_order=1) -> Tensor[]" ) |
2843 | |
2844 | // aten::gradient.scalarrayarray(Tensor self, *, Scalar[] spacing, int[] dim, int edge_order=1) -> Tensor[] |
2845 | static C10_NOINLINE c10::TypedOperatorHandle<gradient_scalarrayarray::schema> create_gradient_scalarrayarray_typed_handle() { |
2846 | return c10::Dispatcher::singleton() |
2847 | .findSchemaOrThrow(gradient_scalarrayarray::name, gradient_scalarrayarray::overload_name) |
2848 | .typed<gradient_scalarrayarray::schema>(); |
2849 | } |
2850 | |
2851 | // aten::gradient.scalarrayarray(Tensor self, *, Scalar[] spacing, int[] dim, int edge_order=1) -> Tensor[] |
2852 | ::std::vector<at::Tensor> gradient_scalarrayarray::call(const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order) { |
2853 | |
2854 | static auto op = create_gradient_scalarrayarray_typed_handle(); |
2855 | return op.call(self, spacing, dim, edge_order); |
2856 | } |
2857 | |
2858 | // aten::gradient.scalarrayarray(Tensor self, *, Scalar[] spacing, int[] dim, int edge_order=1) -> Tensor[] |
2859 | ::std::vector<at::Tensor> gradient_scalarrayarray::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ArrayRef<at::Scalar> spacing, at::IntArrayRef dim, int64_t edge_order) { |
2860 | |
2861 | static auto op = create_gradient_scalarrayarray_typed_handle(); |
2862 | return op.redispatch(dispatchKeySet, self, spacing, dim, edge_order); |
2863 | } |
2864 | |
2865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_tensorarrayint, name, "aten::gradient" ) |
2866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_tensorarrayint, overload_name, "tensorarrayint" ) |
2867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_tensorarrayint, schema_str, "gradient.tensorarrayint(Tensor self, *, Tensor[] spacing, int? dim=None, int edge_order=1) -> Tensor[]" ) |
2868 | |
2869 | // aten::gradient.tensorarrayint(Tensor self, *, Tensor[] spacing, int? dim=None, int edge_order=1) -> Tensor[] |
2870 | static C10_NOINLINE c10::TypedOperatorHandle<gradient_tensorarrayint::schema> create_gradient_tensorarrayint_typed_handle() { |
2871 | return c10::Dispatcher::singleton() |
2872 | .findSchemaOrThrow(gradient_tensorarrayint::name, gradient_tensorarrayint::overload_name) |
2873 | .typed<gradient_tensorarrayint::schema>(); |
2874 | } |
2875 | |
2876 | // aten::gradient.tensorarrayint(Tensor self, *, Tensor[] spacing, int? dim=None, int edge_order=1) -> Tensor[] |
2877 | ::std::vector<at::Tensor> gradient_tensorarrayint::call(const at::Tensor & self, at::TensorList spacing, c10::optional<int64_t> dim, int64_t edge_order) { |
2878 | |
2879 | static auto op = create_gradient_tensorarrayint_typed_handle(); |
2880 | return op.call(self, spacing, dim, edge_order); |
2881 | } |
2882 | |
2883 | // aten::gradient.tensorarrayint(Tensor self, *, Tensor[] spacing, int? dim=None, int edge_order=1) -> Tensor[] |
2884 | ::std::vector<at::Tensor> gradient_tensorarrayint::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList spacing, c10::optional<int64_t> dim, int64_t edge_order) { |
2885 | |
2886 | static auto op = create_gradient_tensorarrayint_typed_handle(); |
2887 | return op.redispatch(dispatchKeySet, self, spacing, dim, edge_order); |
2888 | } |
2889 | |
2890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_tensorarray, name, "aten::gradient" ) |
2891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_tensorarray, overload_name, "tensorarray" ) |
2892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gradient_tensorarray, schema_str, "gradient.tensorarray(Tensor self, *, Tensor[] spacing, int[] dim, int edge_order=1) -> Tensor[]" ) |
2893 | |
2894 | // aten::gradient.tensorarray(Tensor self, *, Tensor[] spacing, int[] dim, int edge_order=1) -> Tensor[] |
2895 | static C10_NOINLINE c10::TypedOperatorHandle<gradient_tensorarray::schema> create_gradient_tensorarray_typed_handle() { |
2896 | return c10::Dispatcher::singleton() |
2897 | .findSchemaOrThrow(gradient_tensorarray::name, gradient_tensorarray::overload_name) |
2898 | .typed<gradient_tensorarray::schema>(); |
2899 | } |
2900 | |
2901 | // aten::gradient.tensorarray(Tensor self, *, Tensor[] spacing, int[] dim, int edge_order=1) -> Tensor[] |
2902 | ::std::vector<at::Tensor> gradient_tensorarray::call(const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order) { |
2903 | |
2904 | static auto op = create_gradient_tensorarray_typed_handle(); |
2905 | return op.call(self, spacing, dim, edge_order); |
2906 | } |
2907 | |
2908 | // aten::gradient.tensorarray(Tensor self, *, Tensor[] spacing, int[] dim, int edge_order=1) -> Tensor[] |
2909 | ::std::vector<at::Tensor> gradient_tensorarray::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList spacing, at::IntArrayRef dim, int64_t edge_order) { |
2910 | |
2911 | static auto op = create_gradient_tensorarray_typed_handle(); |
2912 | return op.redispatch(dispatchKeySet, self, spacing, dim, edge_order); |
2913 | } |
2914 | |
2915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dot, name, "aten::dot" ) |
2916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dot, overload_name, "" ) |
2917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dot, schema_str, "dot(Tensor self, Tensor tensor) -> Tensor" ) |
2918 | |
2919 | // aten::dot(Tensor self, Tensor tensor) -> Tensor |
2920 | static C10_NOINLINE c10::TypedOperatorHandle<dot::schema> create_dot_typed_handle() { |
2921 | return c10::Dispatcher::singleton() |
2922 | .findSchemaOrThrow(dot::name, dot::overload_name) |
2923 | .typed<dot::schema>(); |
2924 | } |
2925 | |
2926 | // aten::dot(Tensor self, Tensor tensor) -> Tensor |
2927 | at::Tensor dot::call(const at::Tensor & self, const at::Tensor & tensor) { |
2928 | |
2929 | static auto op = create_dot_typed_handle(); |
2930 | return op.call(self, tensor); |
2931 | } |
2932 | |
2933 | // aten::dot(Tensor self, Tensor tensor) -> Tensor |
2934 | at::Tensor dot::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor) { |
2935 | |
2936 | static auto op = create_dot_typed_handle(); |
2937 | return op.redispatch(dispatchKeySet, self, tensor); |
2938 | } |
2939 | |
2940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dot_out, name, "aten::dot" ) |
2941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dot_out, overload_name, "out" ) |
2942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(dot_out, schema_str, "dot.out(Tensor self, Tensor tensor, *, Tensor(a!) out) -> Tensor(a!)" ) |
2943 | |
2944 | // aten::dot.out(Tensor self, Tensor tensor, *, Tensor(a!) out) -> Tensor(a!) |
2945 | static C10_NOINLINE c10::TypedOperatorHandle<dot_out::schema> create_dot_out_typed_handle() { |
2946 | return c10::Dispatcher::singleton() |
2947 | .findSchemaOrThrow(dot_out::name, dot_out::overload_name) |
2948 | .typed<dot_out::schema>(); |
2949 | } |
2950 | |
2951 | // aten::dot.out(Tensor self, Tensor tensor, *, Tensor(a!) out) -> Tensor(a!) |
2952 | at::Tensor & dot_out::call(const at::Tensor & self, const at::Tensor & tensor, at::Tensor & out) { |
2953 | |
2954 | static auto op = create_dot_out_typed_handle(); |
2955 | return op.call(self, tensor, out); |
2956 | } |
2957 | |
2958 | // aten::dot.out(Tensor self, Tensor tensor, *, Tensor(a!) out) -> Tensor(a!) |
2959 | at::Tensor & dot_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor, at::Tensor & out) { |
2960 | |
2961 | static auto op = create_dot_out_typed_handle(); |
2962 | return op.redispatch(dispatchKeySet, self, tensor, out); |
2963 | } |
2964 | |
2965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(einsum, name, "aten::einsum" ) |
2966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(einsum, overload_name, "" ) |
2967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(einsum, schema_str, "einsum(str equation, Tensor[] tensors, *, int[]? path=None) -> Tensor" ) |
2968 | |
2969 | // aten::einsum(str equation, Tensor[] tensors, *, int[]? path=None) -> Tensor |
2970 | static C10_NOINLINE c10::TypedOperatorHandle<einsum::schema> create_einsum_typed_handle() { |
2971 | return c10::Dispatcher::singleton() |
2972 | .findSchemaOrThrow(einsum::name, einsum::overload_name) |
2973 | .typed<einsum::schema>(); |
2974 | } |
2975 | |
2976 | // aten::einsum(str equation, Tensor[] tensors, *, int[]? path=None) -> Tensor |
2977 | at::Tensor einsum::call(c10::string_view equation, at::TensorList tensors, at::OptionalIntArrayRef path) { |
2978 | |
2979 | static auto op = create_einsum_typed_handle(); |
2980 | return op.call(equation, tensors, path); |
2981 | } |
2982 | |
2983 | // aten::einsum(str equation, Tensor[] tensors, *, int[]? path=None) -> Tensor |
2984 | at::Tensor einsum::redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view equation, at::TensorList tensors, at::OptionalIntArrayRef path) { |
2985 | |
2986 | static auto op = create_einsum_typed_handle(); |
2987 | return op.redispatch(dispatchKeySet, equation, tensors, path); |
2988 | } |
2989 | |
2990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm_, name, "aten::embedding_renorm_" ) |
2991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm_, overload_name, "" ) |
2992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm_, schema_str, "embedding_renorm_(Tensor(a!) self, Tensor indices, float max_norm, float norm_type) -> Tensor(a!)" ) |
2993 | |
2994 | // aten::embedding_renorm_(Tensor(a!) self, Tensor indices, float max_norm, float norm_type) -> Tensor(a!) |
2995 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_renorm_::schema> create_embedding_renorm__typed_handle() { |
2996 | return c10::Dispatcher::singleton() |
2997 | .findSchemaOrThrow(embedding_renorm_::name, embedding_renorm_::overload_name) |
2998 | .typed<embedding_renorm_::schema>(); |
2999 | } |
3000 | |
3001 | // aten::embedding_renorm_(Tensor(a!) self, Tensor indices, float max_norm, float norm_type) -> Tensor(a!) |
3002 | at::Tensor & embedding_renorm_::call(at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type) { |
3003 | |
3004 | static auto op = create_embedding_renorm__typed_handle(); |
3005 | return op.call(self, indices, max_norm, norm_type); |
3006 | } |
3007 | |
3008 | // aten::embedding_renorm_(Tensor(a!) self, Tensor indices, float max_norm, float norm_type) -> Tensor(a!) |
3009 | at::Tensor & embedding_renorm_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type) { |
3010 | |
3011 | static auto op = create_embedding_renorm__typed_handle(); |
3012 | return op.redispatch(dispatchKeySet, self, indices, max_norm, norm_type); |
3013 | } |
3014 | |
3015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_sparse_backward, name, "aten::embedding_sparse_backward" ) |
3016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_sparse_backward, overload_name, "" ) |
3017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_sparse_backward, schema_str, "embedding_sparse_backward(Tensor grad, Tensor indices, int num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor" ) |
3018 | |
3019 | // aten::embedding_sparse_backward(Tensor grad, Tensor indices, int num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor |
3020 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_sparse_backward::schema> create_embedding_sparse_backward_typed_handle() { |
3021 | return c10::Dispatcher::singleton() |
3022 | .findSchemaOrThrow(embedding_sparse_backward::name, embedding_sparse_backward::overload_name) |
3023 | .typed<embedding_sparse_backward::schema>(); |
3024 | } |
3025 | |
3026 | // aten::embedding_sparse_backward(Tensor grad, Tensor indices, int num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor |
3027 | at::Tensor embedding_sparse_backward::call(const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq) { |
3028 | |
3029 | static auto op = create_embedding_sparse_backward_typed_handle(); |
3030 | return op.call(grad, indices, num_weights, padding_idx, scale_grad_by_freq); |
3031 | } |
3032 | |
3033 | // aten::embedding_sparse_backward(Tensor grad, Tensor indices, int num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor |
3034 | at::Tensor embedding_sparse_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & indices, int64_t num_weights, int64_t padding_idx, bool scale_grad_by_freq) { |
3035 | |
3036 | static auto op = create_embedding_sparse_backward_typed_handle(); |
3037 | return op.redispatch(dispatchKeySet, grad, indices, num_weights, padding_idx, scale_grad_by_freq); |
3038 | } |
3039 | |
3040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_per_sample_weights_backward, name, "aten::_embedding_bag_per_sample_weights_backward" ) |
3041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_per_sample_weights_backward, overload_name, "" ) |
3042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_per_sample_weights_backward, schema_str, "_embedding_bag_per_sample_weights_backward(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1) -> Tensor" ) |
3043 | |
3044 | // aten::_embedding_bag_per_sample_weights_backward(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1) -> Tensor |
3045 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag_per_sample_weights_backward::schema> create__embedding_bag_per_sample_weights_backward_typed_handle() { |
3046 | return c10::Dispatcher::singleton() |
3047 | .findSchemaOrThrow(_embedding_bag_per_sample_weights_backward::name, _embedding_bag_per_sample_weights_backward::overload_name) |
3048 | .typed<_embedding_bag_per_sample_weights_backward::schema>(); |
3049 | } |
3050 | |
3051 | // aten::_embedding_bag_per_sample_weights_backward(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1) -> Tensor |
3052 | at::Tensor _embedding_bag_per_sample_weights_backward::call(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx) { |
3053 | |
3054 | static auto op = create__embedding_bag_per_sample_weights_backward_typed_handle(); |
3055 | return op.call(grad, weight, indices, offsets, offset2bag, mode, padding_idx); |
3056 | } |
3057 | |
3058 | // aten::_embedding_bag_per_sample_weights_backward(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1) -> Tensor |
3059 | at::Tensor _embedding_bag_per_sample_weights_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx) { |
3060 | |
3061 | static auto op = create__embedding_bag_per_sample_weights_backward_typed_handle(); |
3062 | return op.redispatch(dispatchKeySet, grad, weight, indices, offsets, offset2bag, mode, padding_idx); |
3063 | } |
3064 | |
3065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_names, name, "aten::empty" ) |
3066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_names, overload_name, "names" ) |
3067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_names, schema_str, "empty.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor" ) |
3068 | |
3069 | // aten::empty.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3070 | static C10_NOINLINE c10::TypedOperatorHandle<empty_names::schema> create_empty_names_typed_handle() { |
3071 | return c10::Dispatcher::singleton() |
3072 | .findSchemaOrThrow(empty_names::name, empty_names::overload_name) |
3073 | .typed<empty_names::schema>(); |
3074 | } |
3075 | |
3076 | // aten::empty.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3077 | at::Tensor empty_names::call(at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
3078 | |
3079 | static auto op = create_empty_names_typed_handle(); |
3080 | return op.call(size, names, dtype, layout, device, pin_memory, memory_format); |
3081 | } |
3082 | |
3083 | // aten::empty.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3084 | at::Tensor empty_names::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
3085 | |
3086 | static auto op = create_empty_names_typed_handle(); |
3087 | return op.redispatch(dispatchKeySet, size, names, dtype, layout, device, pin_memory, memory_format); |
3088 | } |
3089 | |
3090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_memory_format, name, "aten::empty" ) |
3091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_memory_format, overload_name, "memory_format" ) |
3092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_memory_format, schema_str, "empty.memory_format(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor" ) |
3093 | |
3094 | // aten::empty.memory_format(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3095 | static C10_NOINLINE c10::TypedOperatorHandle<empty_memory_format::schema> create_empty_memory_format_typed_handle() { |
3096 | return c10::Dispatcher::singleton() |
3097 | .findSchemaOrThrow(empty_memory_format::name, empty_memory_format::overload_name) |
3098 | .typed<empty_memory_format::schema>(); |
3099 | } |
3100 | |
3101 | // aten::empty.memory_format(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3102 | at::Tensor empty_memory_format::call(c10::SymIntArrayRef size, 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) { |
3103 | |
3104 | static auto op = create_empty_memory_format_typed_handle(); |
3105 | return op.call(size, dtype, layout, device, pin_memory, memory_format); |
3106 | } |
3107 | |
3108 | // aten::empty.memory_format(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3109 | at::Tensor empty_memory_format::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
3110 | |
3111 | static auto op = create_empty_memory_format_typed_handle(); |
3112 | return op.redispatch(dispatchKeySet, size, dtype, layout, device, pin_memory, memory_format); |
3113 | } |
3114 | |
3115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_strided, name, "aten::new_empty_strided" ) |
3116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_strided, overload_name, "" ) |
3117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_strided, schema_str, "new_empty_strided(Tensor self, SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
3118 | |
3119 | // aten::new_empty_strided(Tensor self, SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3120 | static C10_NOINLINE c10::TypedOperatorHandle<new_empty_strided::schema> create_new_empty_strided_typed_handle() { |
3121 | return c10::Dispatcher::singleton() |
3122 | .findSchemaOrThrow(new_empty_strided::name, new_empty_strided::overload_name) |
3123 | .typed<new_empty_strided::schema>(); |
3124 | } |
3125 | |
3126 | // aten::new_empty_strided(Tensor self, SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3127 | at::Tensor new_empty_strided::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3128 | |
3129 | static auto op = create_new_empty_strided_typed_handle(); |
3130 | return op.call(self, size, stride, dtype, layout, device, pin_memory); |
3131 | } |
3132 | |
3133 | // aten::new_empty_strided(Tensor self, SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3134 | at::Tensor new_empty_strided::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3135 | |
3136 | static auto op = create_new_empty_strided_typed_handle(); |
3137 | return op.redispatch(dispatchKeySet, self, size, stride, dtype, layout, device, pin_memory); |
3138 | } |
3139 | |
3140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_full, name, "aten::new_full" ) |
3141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_full, overload_name, "" ) |
3142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_full, schema_str, "new_full(Tensor self, SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
3143 | |
3144 | // aten::new_full(Tensor self, SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3145 | static C10_NOINLINE c10::TypedOperatorHandle<new_full::schema> create_new_full_typed_handle() { |
3146 | return c10::Dispatcher::singleton() |
3147 | .findSchemaOrThrow(new_full::name, new_full::overload_name) |
3148 | .typed<new_full::schema>(); |
3149 | } |
3150 | |
3151 | // aten::new_full(Tensor self, SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3152 | at::Tensor new_full::call(const at::Tensor & self, 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) { |
3153 | |
3154 | static auto op = create_new_full_typed_handle(); |
3155 | return op.call(self, size, fill_value, dtype, layout, device, pin_memory); |
3156 | } |
3157 | |
3158 | // aten::new_full(Tensor self, SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3159 | at::Tensor new_full::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, 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) { |
3160 | |
3161 | static auto op = create_new_full_typed_handle(); |
3162 | return op.redispatch(dispatchKeySet, self, size, fill_value, dtype, layout, device, pin_memory); |
3163 | } |
3164 | |
3165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_ones, name, "aten::new_ones" ) |
3166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_ones, overload_name, "" ) |
3167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_ones, schema_str, "new_ones(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
3168 | |
3169 | // aten::new_ones(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3170 | static C10_NOINLINE c10::TypedOperatorHandle<new_ones::schema> create_new_ones_typed_handle() { |
3171 | return c10::Dispatcher::singleton() |
3172 | .findSchemaOrThrow(new_ones::name, new_ones::overload_name) |
3173 | .typed<new_ones::schema>(); |
3174 | } |
3175 | |
3176 | // aten::new_ones(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3177 | at::Tensor new_ones::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3178 | |
3179 | static auto op = create_new_ones_typed_handle(); |
3180 | return op.call(self, size, dtype, layout, device, pin_memory); |
3181 | } |
3182 | |
3183 | // aten::new_ones(Tensor self, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3184 | at::Tensor new_ones::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3185 | |
3186 | static auto op = create_new_ones_typed_handle(); |
3187 | return op.redispatch(dispatchKeySet, self, size, dtype, layout, device, pin_memory); |
3188 | } |
3189 | |
3190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_empty_per_channel_affine_quantized, name, "aten::_empty_per_channel_affine_quantized" ) |
3191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_empty_per_channel_affine_quantized, overload_name, "" ) |
3192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_empty_per_channel_affine_quantized, schema_str, "_empty_per_channel_affine_quantized(int[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor" ) |
3193 | |
3194 | // aten::_empty_per_channel_affine_quantized(int[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor |
3195 | static C10_NOINLINE c10::TypedOperatorHandle<_empty_per_channel_affine_quantized::schema> create__empty_per_channel_affine_quantized_typed_handle() { |
3196 | return c10::Dispatcher::singleton() |
3197 | .findSchemaOrThrow(_empty_per_channel_affine_quantized::name, _empty_per_channel_affine_quantized::overload_name) |
3198 | .typed<_empty_per_channel_affine_quantized::schema>(); |
3199 | } |
3200 | |
3201 | // aten::_empty_per_channel_affine_quantized(int[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor |
3202 | at::Tensor _empty_per_channel_affine_quantized::call(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, 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) { |
3203 | |
3204 | static auto op = create__empty_per_channel_affine_quantized_typed_handle(); |
3205 | return op.call(size, scales, zero_points, axis, dtype, layout, device, pin_memory, memory_format); |
3206 | } |
3207 | |
3208 | // aten::_empty_per_channel_affine_quantized(int[] size, *, Tensor scales, Tensor zero_points, int axis, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=contiguous_format) -> Tensor |
3209 | at::Tensor _empty_per_channel_affine_quantized::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, 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) { |
3210 | |
3211 | static auto op = create__empty_per_channel_affine_quantized_typed_handle(); |
3212 | return op.redispatch(dispatchKeySet, size, scales, zero_points, axis, dtype, layout, device, pin_memory, memory_format); |
3213 | } |
3214 | |
3215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_quantized, name, "aten::empty_quantized" ) |
3216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_quantized, overload_name, "" ) |
3217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_quantized, schema_str, "empty_quantized(int[] size, Tensor qtensor, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor" ) |
3218 | |
3219 | // aten::empty_quantized(int[] size, Tensor qtensor, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3220 | static C10_NOINLINE c10::TypedOperatorHandle<empty_quantized::schema> create_empty_quantized_typed_handle() { |
3221 | return c10::Dispatcher::singleton() |
3222 | .findSchemaOrThrow(empty_quantized::name, empty_quantized::overload_name) |
3223 | .typed<empty_quantized::schema>(); |
3224 | } |
3225 | |
3226 | // aten::empty_quantized(int[] size, Tensor qtensor, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3227 | at::Tensor empty_quantized::call(at::IntArrayRef size, const at::Tensor & qtensor, 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) { |
3228 | |
3229 | static auto op = create_empty_quantized_typed_handle(); |
3230 | return op.call(size, qtensor, dtype, layout, device, pin_memory, memory_format); |
3231 | } |
3232 | |
3233 | // aten::empty_quantized(int[] size, Tensor qtensor, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
3234 | at::Tensor empty_quantized::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Tensor & qtensor, 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) { |
3235 | |
3236 | static auto op = create_empty_quantized_typed_handle(); |
3237 | return op.redispatch(dispatchKeySet, size, qtensor, dtype, layout, device, pin_memory, memory_format); |
3238 | } |
3239 | |
3240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_out, name, "aten::empty" ) |
3241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_out, overload_name, "out" ) |
3242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_out, schema_str, "empty.out(SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)" ) |
3243 | |
3244 | // aten::empty.out(SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
3245 | static C10_NOINLINE c10::TypedOperatorHandle<empty_out::schema> create_empty_out_typed_handle() { |
3246 | return c10::Dispatcher::singleton() |
3247 | .findSchemaOrThrow(empty_out::name, empty_out::overload_name) |
3248 | .typed<empty_out::schema>(); |
3249 | } |
3250 | |
3251 | // aten::empty.out(SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
3252 | at::Tensor & empty_out::call(c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
3253 | |
3254 | static auto op = create_empty_out_typed_handle(); |
3255 | return op.call(size, memory_format, out); |
3256 | } |
3257 | |
3258 | // aten::empty.out(SymInt[] size, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
3259 | at::Tensor & empty_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
3260 | |
3261 | static auto op = create_empty_out_typed_handle(); |
3262 | return op.redispatch(dispatchKeySet, size, memory_format, out); |
3263 | } |
3264 | |
3265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_strided, name, "aten::empty_strided" ) |
3266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_strided, overload_name, "" ) |
3267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_strided, schema_str, "empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
3268 | |
3269 | // aten::empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3270 | static C10_NOINLINE c10::TypedOperatorHandle<empty_strided::schema> create_empty_strided_typed_handle() { |
3271 | return c10::Dispatcher::singleton() |
3272 | .findSchemaOrThrow(empty_strided::name, empty_strided::overload_name) |
3273 | .typed<empty_strided::schema>(); |
3274 | } |
3275 | |
3276 | // aten::empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3277 | at::Tensor empty_strided::call(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3278 | |
3279 | static auto op = create_empty_strided_typed_handle(); |
3280 | return op.call(size, stride, dtype, layout, device, pin_memory); |
3281 | } |
3282 | |
3283 | // aten::empty_strided(SymInt[] size, SymInt[] stride, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3284 | at::Tensor empty_strided::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3285 | |
3286 | static auto op = create_empty_strided_typed_handle(); |
3287 | return op.redispatch(dispatchKeySet, size, stride, dtype, layout, device, pin_memory); |
3288 | } |
3289 | |
3290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp, name, "aten::exp" ) |
3291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp, overload_name, "" ) |
3292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp, schema_str, "exp(Tensor self) -> Tensor" ) |
3293 | |
3294 | // aten::exp(Tensor self) -> Tensor |
3295 | static C10_NOINLINE c10::TypedOperatorHandle<exp::schema> create_exp_typed_handle() { |
3296 | return c10::Dispatcher::singleton() |
3297 | .findSchemaOrThrow(exp::name, exp::overload_name) |
3298 | .typed<exp::schema>(); |
3299 | } |
3300 | |
3301 | // aten::exp(Tensor self) -> Tensor |
3302 | at::Tensor exp::call(const at::Tensor & self) { |
3303 | |
3304 | static auto op = create_exp_typed_handle(); |
3305 | return op.call(self); |
3306 | } |
3307 | |
3308 | // aten::exp(Tensor self) -> Tensor |
3309 | at::Tensor exp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
3310 | |
3311 | static auto op = create_exp_typed_handle(); |
3312 | return op.redispatch(dispatchKeySet, self); |
3313 | } |
3314 | |
3315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp_, name, "aten::exp_" ) |
3316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp_, overload_name, "" ) |
3317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp_, schema_str, "exp_(Tensor(a!) self) -> Tensor(a!)" ) |
3318 | |
3319 | // aten::exp_(Tensor(a!) self) -> Tensor(a!) |
3320 | static C10_NOINLINE c10::TypedOperatorHandle<exp_::schema> create_exp__typed_handle() { |
3321 | return c10::Dispatcher::singleton() |
3322 | .findSchemaOrThrow(exp_::name, exp_::overload_name) |
3323 | .typed<exp_::schema>(); |
3324 | } |
3325 | |
3326 | // aten::exp_(Tensor(a!) self) -> Tensor(a!) |
3327 | at::Tensor & exp_::call(at::Tensor & self) { |
3328 | |
3329 | static auto op = create_exp__typed_handle(); |
3330 | return op.call(self); |
3331 | } |
3332 | |
3333 | // aten::exp_(Tensor(a!) self) -> Tensor(a!) |
3334 | at::Tensor & exp_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
3335 | |
3336 | static auto op = create_exp__typed_handle(); |
3337 | return op.redispatch(dispatchKeySet, self); |
3338 | } |
3339 | |
3340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp_out, name, "aten::exp" ) |
3341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp_out, overload_name, "out" ) |
3342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp_out, schema_str, "exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
3343 | |
3344 | // aten::exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3345 | static C10_NOINLINE c10::TypedOperatorHandle<exp_out::schema> create_exp_out_typed_handle() { |
3346 | return c10::Dispatcher::singleton() |
3347 | .findSchemaOrThrow(exp_out::name, exp_out::overload_name) |
3348 | .typed<exp_out::schema>(); |
3349 | } |
3350 | |
3351 | // aten::exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3352 | at::Tensor & exp_out::call(const at::Tensor & self, at::Tensor & out) { |
3353 | |
3354 | static auto op = create_exp_out_typed_handle(); |
3355 | return op.call(self, out); |
3356 | } |
3357 | |
3358 | // aten::exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3359 | at::Tensor & exp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
3360 | |
3361 | static auto op = create_exp_out_typed_handle(); |
3362 | return op.redispatch(dispatchKeySet, self, out); |
3363 | } |
3364 | |
3365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2, name, "aten::exp2" ) |
3366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2, overload_name, "" ) |
3367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2, schema_str, "exp2(Tensor self) -> Tensor" ) |
3368 | |
3369 | // aten::exp2(Tensor self) -> Tensor |
3370 | static C10_NOINLINE c10::TypedOperatorHandle<exp2::schema> create_exp2_typed_handle() { |
3371 | return c10::Dispatcher::singleton() |
3372 | .findSchemaOrThrow(exp2::name, exp2::overload_name) |
3373 | .typed<exp2::schema>(); |
3374 | } |
3375 | |
3376 | // aten::exp2(Tensor self) -> Tensor |
3377 | at::Tensor exp2::call(const at::Tensor & self) { |
3378 | |
3379 | static auto op = create_exp2_typed_handle(); |
3380 | return op.call(self); |
3381 | } |
3382 | |
3383 | // aten::exp2(Tensor self) -> Tensor |
3384 | at::Tensor exp2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
3385 | |
3386 | static auto op = create_exp2_typed_handle(); |
3387 | return op.redispatch(dispatchKeySet, self); |
3388 | } |
3389 | |
3390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2_, name, "aten::exp2_" ) |
3391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2_, overload_name, "" ) |
3392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2_, schema_str, "exp2_(Tensor(a!) self) -> Tensor(a!)" ) |
3393 | |
3394 | // aten::exp2_(Tensor(a!) self) -> Tensor(a!) |
3395 | static C10_NOINLINE c10::TypedOperatorHandle<exp2_::schema> create_exp2__typed_handle() { |
3396 | return c10::Dispatcher::singleton() |
3397 | .findSchemaOrThrow(exp2_::name, exp2_::overload_name) |
3398 | .typed<exp2_::schema>(); |
3399 | } |
3400 | |
3401 | // aten::exp2_(Tensor(a!) self) -> Tensor(a!) |
3402 | at::Tensor & exp2_::call(at::Tensor & self) { |
3403 | |
3404 | static auto op = create_exp2__typed_handle(); |
3405 | return op.call(self); |
3406 | } |
3407 | |
3408 | // aten::exp2_(Tensor(a!) self) -> Tensor(a!) |
3409 | at::Tensor & exp2_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
3410 | |
3411 | static auto op = create_exp2__typed_handle(); |
3412 | return op.redispatch(dispatchKeySet, self); |
3413 | } |
3414 | |
3415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2_out, name, "aten::exp2" ) |
3416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2_out, overload_name, "out" ) |
3417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(exp2_out, schema_str, "exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
3418 | |
3419 | // aten::exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3420 | static C10_NOINLINE c10::TypedOperatorHandle<exp2_out::schema> create_exp2_out_typed_handle() { |
3421 | return c10::Dispatcher::singleton() |
3422 | .findSchemaOrThrow(exp2_out::name, exp2_out::overload_name) |
3423 | .typed<exp2_out::schema>(); |
3424 | } |
3425 | |
3426 | // aten::exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3427 | at::Tensor & exp2_out::call(const at::Tensor & self, at::Tensor & out) { |
3428 | |
3429 | static auto op = create_exp2_out_typed_handle(); |
3430 | return op.call(self, out); |
3431 | } |
3432 | |
3433 | // aten::exp2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3434 | at::Tensor & exp2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
3435 | |
3436 | static auto op = create_exp2_out_typed_handle(); |
3437 | return op.redispatch(dispatchKeySet, self, out); |
3438 | } |
3439 | |
3440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye, name, "aten::eye" ) |
3441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye, overload_name, "" ) |
3442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye, schema_str, "eye(int n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
3443 | |
3444 | // aten::eye(int n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3445 | static C10_NOINLINE c10::TypedOperatorHandle<eye::schema> create_eye_typed_handle() { |
3446 | return c10::Dispatcher::singleton() |
3447 | .findSchemaOrThrow(eye::name, eye::overload_name) |
3448 | .typed<eye::schema>(); |
3449 | } |
3450 | |
3451 | // aten::eye(int n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3452 | at::Tensor eye::call(int64_t n, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3453 | |
3454 | static auto op = create_eye_typed_handle(); |
3455 | return op.call(n, dtype, layout, device, pin_memory); |
3456 | } |
3457 | |
3458 | // aten::eye(int n, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3459 | at::Tensor eye::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) { |
3460 | |
3461 | static auto op = create_eye_typed_handle(); |
3462 | return op.redispatch(dispatchKeySet, n, dtype, layout, device, pin_memory); |
3463 | } |
3464 | |
3465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_m, name, "aten::eye" ) |
3466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_m, overload_name, "m" ) |
3467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_m, schema_str, "eye.m(int n, int m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
3468 | |
3469 | // aten::eye.m(int n, int m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3470 | static C10_NOINLINE c10::TypedOperatorHandle<eye_m::schema> create_eye_m_typed_handle() { |
3471 | return c10::Dispatcher::singleton() |
3472 | .findSchemaOrThrow(eye_m::name, eye_m::overload_name) |
3473 | .typed<eye_m::schema>(); |
3474 | } |
3475 | |
3476 | // aten::eye.m(int n, int m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3477 | at::Tensor eye_m::call(int64_t n, int64_t m, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3478 | |
3479 | static auto op = create_eye_m_typed_handle(); |
3480 | return op.call(n, m, dtype, layout, device, pin_memory); |
3481 | } |
3482 | |
3483 | // aten::eye.m(int n, int m, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3484 | at::Tensor eye_m::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, int64_t m, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3485 | |
3486 | static auto op = create_eye_m_typed_handle(); |
3487 | return op.redispatch(dispatchKeySet, n, m, dtype, layout, device, pin_memory); |
3488 | } |
3489 | |
3490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_out, name, "aten::eye" ) |
3491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_out, overload_name, "out" ) |
3492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_out, schema_str, "eye.out(int n, *, Tensor(a!) out) -> Tensor(a!)" ) |
3493 | |
3494 | // aten::eye.out(int n, *, Tensor(a!) out) -> Tensor(a!) |
3495 | static C10_NOINLINE c10::TypedOperatorHandle<eye_out::schema> create_eye_out_typed_handle() { |
3496 | return c10::Dispatcher::singleton() |
3497 | .findSchemaOrThrow(eye_out::name, eye_out::overload_name) |
3498 | .typed<eye_out::schema>(); |
3499 | } |
3500 | |
3501 | // aten::eye.out(int n, *, Tensor(a!) out) -> Tensor(a!) |
3502 | at::Tensor & eye_out::call(int64_t n, at::Tensor & out) { |
3503 | |
3504 | static auto op = create_eye_out_typed_handle(); |
3505 | return op.call(n, out); |
3506 | } |
3507 | |
3508 | // aten::eye.out(int n, *, Tensor(a!) out) -> Tensor(a!) |
3509 | at::Tensor & eye_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, at::Tensor & out) { |
3510 | |
3511 | static auto op = create_eye_out_typed_handle(); |
3512 | return op.redispatch(dispatchKeySet, n, out); |
3513 | } |
3514 | |
3515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_m_out, name, "aten::eye" ) |
3516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_m_out, overload_name, "m_out" ) |
3517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(eye_m_out, schema_str, "eye.m_out(int n, int m, *, Tensor(a!) out) -> Tensor(a!)" ) |
3518 | |
3519 | // aten::eye.m_out(int n, int m, *, Tensor(a!) out) -> Tensor(a!) |
3520 | static C10_NOINLINE c10::TypedOperatorHandle<eye_m_out::schema> create_eye_m_out_typed_handle() { |
3521 | return c10::Dispatcher::singleton() |
3522 | .findSchemaOrThrow(eye_m_out::name, eye_m_out::overload_name) |
3523 | .typed<eye_m_out::schema>(); |
3524 | } |
3525 | |
3526 | // aten::eye.m_out(int n, int m, *, Tensor(a!) out) -> Tensor(a!) |
3527 | at::Tensor & eye_m_out::call(int64_t n, int64_t m, at::Tensor & out) { |
3528 | |
3529 | static auto op = create_eye_m_out_typed_handle(); |
3530 | return op.call(n, m, out); |
3531 | } |
3532 | |
3533 | // aten::eye.m_out(int n, int m, *, Tensor(a!) out) -> Tensor(a!) |
3534 | at::Tensor & eye_m_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t n, int64_t m, at::Tensor & out) { |
3535 | |
3536 | static auto op = create_eye_m_out_typed_handle(); |
3537 | return op.redispatch(dispatchKeySet, n, m, out); |
3538 | } |
3539 | |
3540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac, name, "aten::frac" ) |
3541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac, overload_name, "" ) |
3542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac, schema_str, "frac(Tensor self) -> Tensor" ) |
3543 | |
3544 | // aten::frac(Tensor self) -> Tensor |
3545 | static C10_NOINLINE c10::TypedOperatorHandle<frac::schema> create_frac_typed_handle() { |
3546 | return c10::Dispatcher::singleton() |
3547 | .findSchemaOrThrow(frac::name, frac::overload_name) |
3548 | .typed<frac::schema>(); |
3549 | } |
3550 | |
3551 | // aten::frac(Tensor self) -> Tensor |
3552 | at::Tensor frac::call(const at::Tensor & self) { |
3553 | |
3554 | static auto op = create_frac_typed_handle(); |
3555 | return op.call(self); |
3556 | } |
3557 | |
3558 | // aten::frac(Tensor self) -> Tensor |
3559 | at::Tensor frac::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
3560 | |
3561 | static auto op = create_frac_typed_handle(); |
3562 | return op.redispatch(dispatchKeySet, self); |
3563 | } |
3564 | |
3565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac_, name, "aten::frac_" ) |
3566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac_, overload_name, "" ) |
3567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac_, schema_str, "frac_(Tensor(a!) self) -> Tensor(a!)" ) |
3568 | |
3569 | // aten::frac_(Tensor(a!) self) -> Tensor(a!) |
3570 | static C10_NOINLINE c10::TypedOperatorHandle<frac_::schema> create_frac__typed_handle() { |
3571 | return c10::Dispatcher::singleton() |
3572 | .findSchemaOrThrow(frac_::name, frac_::overload_name) |
3573 | .typed<frac_::schema>(); |
3574 | } |
3575 | |
3576 | // aten::frac_(Tensor(a!) self) -> Tensor(a!) |
3577 | at::Tensor & frac_::call(at::Tensor & self) { |
3578 | |
3579 | static auto op = create_frac__typed_handle(); |
3580 | return op.call(self); |
3581 | } |
3582 | |
3583 | // aten::frac_(Tensor(a!) self) -> Tensor(a!) |
3584 | at::Tensor & frac_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
3585 | |
3586 | static auto op = create_frac__typed_handle(); |
3587 | return op.redispatch(dispatchKeySet, self); |
3588 | } |
3589 | |
3590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac_out, name, "aten::frac" ) |
3591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac_out, overload_name, "out" ) |
3592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(frac_out, schema_str, "frac.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
3593 | |
3594 | // aten::frac.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3595 | static C10_NOINLINE c10::TypedOperatorHandle<frac_out::schema> create_frac_out_typed_handle() { |
3596 | return c10::Dispatcher::singleton() |
3597 | .findSchemaOrThrow(frac_out::name, frac_out::overload_name) |
3598 | .typed<frac_out::schema>(); |
3599 | } |
3600 | |
3601 | // aten::frac.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3602 | at::Tensor & frac_out::call(const at::Tensor & self, at::Tensor & out) { |
3603 | |
3604 | static auto op = create_frac_out_typed_handle(); |
3605 | return op.call(self, out); |
3606 | } |
3607 | |
3608 | // aten::frac.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
3609 | at::Tensor & frac_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
3610 | |
3611 | static auto op = create_frac_out_typed_handle(); |
3612 | return op.redispatch(dispatchKeySet, self, out); |
3613 | } |
3614 | |
3615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(from_file, name, "aten::from_file" ) |
3616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(from_file, overload_name, "" ) |
3617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(from_file, schema_str, "from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
3618 | |
3619 | // aten::from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3620 | static C10_NOINLINE c10::TypedOperatorHandle<from_file::schema> create_from_file_typed_handle() { |
3621 | return c10::Dispatcher::singleton() |
3622 | .findSchemaOrThrow(from_file::name, from_file::overload_name) |
3623 | .typed<from_file::schema>(); |
3624 | } |
3625 | |
3626 | // aten::from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3627 | at::Tensor from_file::call(c10::string_view filename, c10::optional<bool> shared, c10::optional<int64_t> size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3628 | |
3629 | static auto op = create_from_file_typed_handle(); |
3630 | return op.call(filename, shared, size, dtype, layout, device, pin_memory); |
3631 | } |
3632 | |
3633 | // aten::from_file(str filename, bool? shared=None, int? size=0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
3634 | at::Tensor from_file::redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, c10::optional<bool> shared, c10::optional<int64_t> size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
3635 | |
3636 | static auto op = create_from_file_typed_handle(); |
3637 | return op.redispatch(dispatchKeySet, filename, shared, size, dtype, layout, device, pin_memory); |
3638 | } |
3639 | |
3640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd_out, name, "aten::gcd" ) |
3641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd_out, overload_name, "out" ) |
3642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd_out, schema_str, "gcd.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
3643 | |
3644 | // aten::gcd.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
3645 | static C10_NOINLINE c10::TypedOperatorHandle<gcd_out::schema> create_gcd_out_typed_handle() { |
3646 | return c10::Dispatcher::singleton() |
3647 | .findSchemaOrThrow(gcd_out::name, gcd_out::overload_name) |
3648 | .typed<gcd_out::schema>(); |
3649 | } |
3650 | |
3651 | // aten::gcd.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
3652 | at::Tensor & gcd_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
3653 | |
3654 | static auto op = create_gcd_out_typed_handle(); |
3655 | return op.call(self, other, out); |
3656 | } |
3657 | |
3658 | // aten::gcd.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
3659 | at::Tensor & gcd_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
3660 | |
3661 | static auto op = create_gcd_out_typed_handle(); |
3662 | return op.redispatch(dispatchKeySet, self, other, out); |
3663 | } |
3664 | |
3665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd, name, "aten::gcd" ) |
3666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd, overload_name, "" ) |
3667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd, schema_str, "gcd(Tensor self, Tensor other) -> Tensor" ) |
3668 | |
3669 | // aten::gcd(Tensor self, Tensor other) -> Tensor |
3670 | static C10_NOINLINE c10::TypedOperatorHandle<gcd::schema> create_gcd_typed_handle() { |
3671 | return c10::Dispatcher::singleton() |
3672 | .findSchemaOrThrow(gcd::name, gcd::overload_name) |
3673 | .typed<gcd::schema>(); |
3674 | } |
3675 | |
3676 | // aten::gcd(Tensor self, Tensor other) -> Tensor |
3677 | at::Tensor gcd::call(const at::Tensor & self, const at::Tensor & other) { |
3678 | |
3679 | static auto op = create_gcd_typed_handle(); |
3680 | return op.call(self, other); |
3681 | } |
3682 | |
3683 | // aten::gcd(Tensor self, Tensor other) -> Tensor |
3684 | at::Tensor gcd::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
3685 | |
3686 | static auto op = create_gcd_typed_handle(); |
3687 | return op.redispatch(dispatchKeySet, self, other); |
3688 | } |
3689 | |
3690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd_, name, "aten::gcd_" ) |
3691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd_, overload_name, "" ) |
3692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gcd_, schema_str, "gcd_(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
3693 | |
3694 | // aten::gcd_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
3695 | static C10_NOINLINE c10::TypedOperatorHandle<gcd_::schema> create_gcd__typed_handle() { |
3696 | return c10::Dispatcher::singleton() |
3697 | .findSchemaOrThrow(gcd_::name, gcd_::overload_name) |
3698 | .typed<gcd_::schema>(); |
3699 | } |
3700 | |
3701 | // aten::gcd_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
3702 | at::Tensor & gcd_::call(at::Tensor & self, const at::Tensor & other) { |
3703 | |
3704 | static auto op = create_gcd__typed_handle(); |
3705 | return op.call(self, other); |
3706 | } |
3707 | |
3708 | // aten::gcd_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
3709 | at::Tensor & gcd_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
3710 | |
3711 | static auto op = create_gcd__typed_handle(); |
3712 | return op.redispatch(dispatchKeySet, self, other); |
3713 | } |
3714 | |
3715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cufft_clear_plan_cache, name, "aten::_cufft_clear_plan_cache" ) |
3716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cufft_clear_plan_cache, overload_name, "" ) |
3717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cufft_clear_plan_cache, schema_str, "_cufft_clear_plan_cache(int device_index) -> ()" ) |
3718 | |
3719 | // aten::_cufft_clear_plan_cache(int device_index) -> () |
3720 | static C10_NOINLINE c10::TypedOperatorHandle<_cufft_clear_plan_cache::schema> create__cufft_clear_plan_cache_typed_handle() { |
3721 | return c10::Dispatcher::singleton() |
3722 | .findSchemaOrThrow(_cufft_clear_plan_cache::name, _cufft_clear_plan_cache::overload_name) |
3723 | .typed<_cufft_clear_plan_cache::schema>(); |
3724 | } |
3725 | |
3726 | // aten::_cufft_clear_plan_cache(int device_index) -> () |
3727 | void _cufft_clear_plan_cache::call(int64_t device_index) { |
3728 | |
3729 | static auto op = create__cufft_clear_plan_cache_typed_handle(); |
3730 | return op.call(device_index); |
3731 | } |
3732 | |
3733 | // aten::_cufft_clear_plan_cache(int device_index) -> () |
3734 | void _cufft_clear_plan_cache::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t device_index) { |
3735 | |
3736 | static auto op = create__cufft_clear_plan_cache_typed_handle(); |
3737 | return op.redispatch(dispatchKeySet, device_index); |
3738 | } |
3739 | |
3740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Tensor_out, name, "aten::isin" ) |
3741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Tensor_out, overload_name, "Tensor_Tensor_out" ) |
3742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Tensor_out, schema_str, "isin.Tensor_Tensor_out(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!)" ) |
3743 | |
3744 | // aten::isin.Tensor_Tensor_out(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3745 | static C10_NOINLINE c10::TypedOperatorHandle<isin_Tensor_Tensor_out::schema> create_isin_Tensor_Tensor_out_typed_handle() { |
3746 | return c10::Dispatcher::singleton() |
3747 | .findSchemaOrThrow(isin_Tensor_Tensor_out::name, isin_Tensor_Tensor_out::overload_name) |
3748 | .typed<isin_Tensor_Tensor_out::schema>(); |
3749 | } |
3750 | |
3751 | // aten::isin.Tensor_Tensor_out(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3752 | at::Tensor & isin_Tensor_Tensor_out::call(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out) { |
3753 | |
3754 | static auto op = create_isin_Tensor_Tensor_out_typed_handle(); |
3755 | return op.call(elements, test_elements, assume_unique, invert, out); |
3756 | } |
3757 | |
3758 | // aten::isin.Tensor_Tensor_out(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3759 | at::Tensor & isin_Tensor_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out) { |
3760 | |
3761 | static auto op = create_isin_Tensor_Tensor_out_typed_handle(); |
3762 | return op.redispatch(dispatchKeySet, elements, test_elements, assume_unique, invert, out); |
3763 | } |
3764 | |
3765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Tensor, name, "aten::isin" ) |
3766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Tensor, overload_name, "Tensor_Tensor" ) |
3767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Tensor, schema_str, "isin.Tensor_Tensor(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor" ) |
3768 | |
3769 | // aten::isin.Tensor_Tensor(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor |
3770 | static C10_NOINLINE c10::TypedOperatorHandle<isin_Tensor_Tensor::schema> create_isin_Tensor_Tensor_typed_handle() { |
3771 | return c10::Dispatcher::singleton() |
3772 | .findSchemaOrThrow(isin_Tensor_Tensor::name, isin_Tensor_Tensor::overload_name) |
3773 | .typed<isin_Tensor_Tensor::schema>(); |
3774 | } |
3775 | |
3776 | // aten::isin.Tensor_Tensor(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor |
3777 | at::Tensor isin_Tensor_Tensor::call(const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique, bool invert) { |
3778 | |
3779 | static auto op = create_isin_Tensor_Tensor_typed_handle(); |
3780 | return op.call(elements, test_elements, assume_unique, invert); |
3781 | } |
3782 | |
3783 | // aten::isin.Tensor_Tensor(Tensor elements, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor |
3784 | at::Tensor isin_Tensor_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & elements, const at::Tensor & test_elements, bool assume_unique, bool invert) { |
3785 | |
3786 | static auto op = create_isin_Tensor_Tensor_typed_handle(); |
3787 | return op.redispatch(dispatchKeySet, elements, test_elements, assume_unique, invert); |
3788 | } |
3789 | |
3790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Scalar_out, name, "aten::isin" ) |
3791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Scalar_out, overload_name, "Tensor_Scalar_out" ) |
3792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Scalar_out, schema_str, "isin.Tensor_Scalar_out(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!)" ) |
3793 | |
3794 | // aten::isin.Tensor_Scalar_out(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3795 | static C10_NOINLINE c10::TypedOperatorHandle<isin_Tensor_Scalar_out::schema> create_isin_Tensor_Scalar_out_typed_handle() { |
3796 | return c10::Dispatcher::singleton() |
3797 | .findSchemaOrThrow(isin_Tensor_Scalar_out::name, isin_Tensor_Scalar_out::overload_name) |
3798 | .typed<isin_Tensor_Scalar_out::schema>(); |
3799 | } |
3800 | |
3801 | // aten::isin.Tensor_Scalar_out(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3802 | at::Tensor & isin_Tensor_Scalar_out::call(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique, bool invert, at::Tensor & out) { |
3803 | |
3804 | static auto op = create_isin_Tensor_Scalar_out_typed_handle(); |
3805 | return op.call(elements, test_element, assume_unique, invert, out); |
3806 | } |
3807 | |
3808 | // aten::isin.Tensor_Scalar_out(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3809 | at::Tensor & isin_Tensor_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique, bool invert, at::Tensor & out) { |
3810 | |
3811 | static auto op = create_isin_Tensor_Scalar_out_typed_handle(); |
3812 | return op.redispatch(dispatchKeySet, elements, test_element, assume_unique, invert, out); |
3813 | } |
3814 | |
3815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Scalar, name, "aten::isin" ) |
3816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Scalar, overload_name, "Tensor_Scalar" ) |
3817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Tensor_Scalar, schema_str, "isin.Tensor_Scalar(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False) -> Tensor" ) |
3818 | |
3819 | // aten::isin.Tensor_Scalar(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False) -> Tensor |
3820 | static C10_NOINLINE c10::TypedOperatorHandle<isin_Tensor_Scalar::schema> create_isin_Tensor_Scalar_typed_handle() { |
3821 | return c10::Dispatcher::singleton() |
3822 | .findSchemaOrThrow(isin_Tensor_Scalar::name, isin_Tensor_Scalar::overload_name) |
3823 | .typed<isin_Tensor_Scalar::schema>(); |
3824 | } |
3825 | |
3826 | // aten::isin.Tensor_Scalar(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False) -> Tensor |
3827 | at::Tensor isin_Tensor_Scalar::call(const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique, bool invert) { |
3828 | |
3829 | static auto op = create_isin_Tensor_Scalar_typed_handle(); |
3830 | return op.call(elements, test_element, assume_unique, invert); |
3831 | } |
3832 | |
3833 | // aten::isin.Tensor_Scalar(Tensor elements, Scalar test_element, *, bool assume_unique=False, bool invert=False) -> Tensor |
3834 | at::Tensor isin_Tensor_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & elements, const at::Scalar & test_element, bool assume_unique, bool invert) { |
3835 | |
3836 | static auto op = create_isin_Tensor_Scalar_typed_handle(); |
3837 | return op.redispatch(dispatchKeySet, elements, test_element, assume_unique, invert); |
3838 | } |
3839 | |
3840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Scalar_Tensor_out, name, "aten::isin" ) |
3841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Scalar_Tensor_out, overload_name, "Scalar_Tensor_out" ) |
3842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Scalar_Tensor_out, schema_str, "isin.Scalar_Tensor_out(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!)" ) |
3843 | |
3844 | // aten::isin.Scalar_Tensor_out(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3845 | static C10_NOINLINE c10::TypedOperatorHandle<isin_Scalar_Tensor_out::schema> create_isin_Scalar_Tensor_out_typed_handle() { |
3846 | return c10::Dispatcher::singleton() |
3847 | .findSchemaOrThrow(isin_Scalar_Tensor_out::name, isin_Scalar_Tensor_out::overload_name) |
3848 | .typed<isin_Scalar_Tensor_out::schema>(); |
3849 | } |
3850 | |
3851 | // aten::isin.Scalar_Tensor_out(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3852 | at::Tensor & isin_Scalar_Tensor_out::call(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out) { |
3853 | |
3854 | static auto op = create_isin_Scalar_Tensor_out_typed_handle(); |
3855 | return op.call(element, test_elements, assume_unique, invert, out); |
3856 | } |
3857 | |
3858 | // aten::isin.Scalar_Tensor_out(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False, Tensor(a!) out) -> Tensor(a!) |
3859 | at::Tensor & isin_Scalar_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique, bool invert, at::Tensor & out) { |
3860 | |
3861 | static auto op = create_isin_Scalar_Tensor_out_typed_handle(); |
3862 | return op.redispatch(dispatchKeySet, element, test_elements, assume_unique, invert, out); |
3863 | } |
3864 | |
3865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Scalar_Tensor, name, "aten::isin" ) |
3866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Scalar_Tensor, overload_name, "Scalar_Tensor" ) |
3867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isin_Scalar_Tensor, schema_str, "isin.Scalar_Tensor(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor" ) |
3868 | |
3869 | // aten::isin.Scalar_Tensor(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor |
3870 | static C10_NOINLINE c10::TypedOperatorHandle<isin_Scalar_Tensor::schema> create_isin_Scalar_Tensor_typed_handle() { |
3871 | return c10::Dispatcher::singleton() |
3872 | .findSchemaOrThrow(isin_Scalar_Tensor::name, isin_Scalar_Tensor::overload_name) |
3873 | .typed<isin_Scalar_Tensor::schema>(); |
3874 | } |
3875 | |
3876 | // aten::isin.Scalar_Tensor(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor |
3877 | at::Tensor isin_Scalar_Tensor::call(const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique, bool invert) { |
3878 | |
3879 | static auto op = create_isin_Scalar_Tensor_typed_handle(); |
3880 | return op.call(element, test_elements, assume_unique, invert); |
3881 | } |
3882 | |
3883 | // aten::isin.Scalar_Tensor(Scalar element, Tensor test_elements, *, bool assume_unique=False, bool invert=False) -> Tensor |
3884 | at::Tensor isin_Scalar_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & element, const at::Tensor & test_elements, bool assume_unique, bool invert) { |
3885 | |
3886 | static auto op = create_isin_Scalar_Tensor_typed_handle(); |
3887 | return op.redispatch(dispatchKeySet, element, test_elements, assume_unique, invert); |
3888 | } |
3889 | |
3890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_conj, name, "aten::is_conj" ) |
3891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_conj, overload_name, "" ) |
3892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_conj, schema_str, "is_conj(Tensor self) -> bool" ) |
3893 | |
3894 | // aten::is_conj(Tensor self) -> bool |
3895 | static C10_NOINLINE c10::TypedOperatorHandle<is_conj::schema> create_is_conj_typed_handle() { |
3896 | return c10::Dispatcher::singleton() |
3897 | .findSchemaOrThrow(is_conj::name, is_conj::overload_name) |
3898 | .typed<is_conj::schema>(); |
3899 | } |
3900 | |
3901 | // aten::is_conj(Tensor self) -> bool |
3902 | bool is_conj::call(const at::Tensor & self) { |
3903 | |
3904 | static auto op = create_is_conj_typed_handle(); |
3905 | return op.call(self); |
3906 | } |
3907 | |
3908 | // aten::is_conj(Tensor self) -> bool |
3909 | bool is_conj::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
3910 | |
3911 | static auto op = create_is_conj_typed_handle(); |
3912 | return op.redispatch(dispatchKeySet, self); |
3913 | } |
3914 | |
3915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_is_zerotensor, name, "aten::_is_zerotensor" ) |
3916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_is_zerotensor, overload_name, "" ) |
3917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_is_zerotensor, schema_str, "_is_zerotensor(Tensor self) -> bool" ) |
3918 | |
3919 | // aten::_is_zerotensor(Tensor self) -> bool |
3920 | static C10_NOINLINE c10::TypedOperatorHandle<_is_zerotensor::schema> create__is_zerotensor_typed_handle() { |
3921 | return c10::Dispatcher::singleton() |
3922 | .findSchemaOrThrow(_is_zerotensor::name, _is_zerotensor::overload_name) |
3923 | .typed<_is_zerotensor::schema>(); |
3924 | } |
3925 | |
3926 | // aten::_is_zerotensor(Tensor self) -> bool |
3927 | bool _is_zerotensor::call(const at::Tensor & self) { |
3928 | |
3929 | static auto op = create__is_zerotensor_typed_handle(); |
3930 | return op.call(self); |
3931 | } |
3932 | |
3933 | // aten::_is_zerotensor(Tensor self) -> bool |
3934 | bool _is_zerotensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
3935 | |
3936 | static auto op = create__is_zerotensor_typed_handle(); |
3937 | return op.redispatch(dispatchKeySet, self); |
3938 | } |
3939 | |
3940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_nonzero, name, "aten::is_nonzero" ) |
3941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_nonzero, overload_name, "" ) |
3942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_nonzero, schema_str, "is_nonzero(Tensor self) -> bool" ) |
3943 | |
3944 | // aten::is_nonzero(Tensor self) -> bool |
3945 | static C10_NOINLINE c10::TypedOperatorHandle<is_nonzero::schema> create_is_nonzero_typed_handle() { |
3946 | return c10::Dispatcher::singleton() |
3947 | .findSchemaOrThrow(is_nonzero::name, is_nonzero::overload_name) |
3948 | .typed<is_nonzero::schema>(); |
3949 | } |
3950 | |
3951 | // aten::is_nonzero(Tensor self) -> bool |
3952 | bool is_nonzero::call(const at::Tensor & self) { |
3953 | |
3954 | static auto op = create_is_nonzero_typed_handle(); |
3955 | return op.call(self); |
3956 | } |
3957 | |
3958 | // aten::is_nonzero(Tensor self) -> bool |
3959 | bool is_nonzero::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
3960 | |
3961 | static auto op = create_is_nonzero_typed_handle(); |
3962 | return op.redispatch(dispatchKeySet, self); |
3963 | } |
3964 | |
3965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_signed, name, "aten::is_signed" ) |
3966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_signed, overload_name, "" ) |
3967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_signed, schema_str, "is_signed(Tensor self) -> bool" ) |
3968 | |
3969 | // aten::is_signed(Tensor self) -> bool |
3970 | static C10_NOINLINE c10::TypedOperatorHandle<is_signed::schema> create_is_signed_typed_handle() { |
3971 | return c10::Dispatcher::singleton() |
3972 | .findSchemaOrThrow(is_signed::name, is_signed::overload_name) |
3973 | .typed<is_signed::schema>(); |
3974 | } |
3975 | |
3976 | // aten::is_signed(Tensor self) -> bool |
3977 | bool is_signed::call(const at::Tensor & self) { |
3978 | |
3979 | static auto op = create_is_signed_typed_handle(); |
3980 | return op.call(self); |
3981 | } |
3982 | |
3983 | // aten::is_signed(Tensor self) -> bool |
3984 | bool is_signed::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
3985 | |
3986 | static auto op = create_is_signed_typed_handle(); |
3987 | return op.redispatch(dispatchKeySet, self); |
3988 | } |
3989 | |
3990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(layer_norm, name, "aten::layer_norm" ) |
3991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(layer_norm, overload_name, "" ) |
3992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(layer_norm, schema_str, "layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor" ) |
3993 | |
3994 | // aten::layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor |
3995 | static C10_NOINLINE c10::TypedOperatorHandle<layer_norm::schema> create_layer_norm_typed_handle() { |
3996 | return c10::Dispatcher::singleton() |
3997 | .findSchemaOrThrow(layer_norm::name, layer_norm::overload_name) |
3998 | .typed<layer_norm::schema>(); |
3999 | } |
4000 | |
4001 | // aten::layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor |
4002 | at::Tensor layer_norm::call(const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, double eps, bool cudnn_enable) { |
4003 | |
4004 | static auto op = create_layer_norm_typed_handle(); |
4005 | return op.call(input, normalized_shape, weight, bias, eps, cudnn_enable); |
4006 | } |
4007 | |
4008 | // aten::layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor |
4009 | at::Tensor layer_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, double eps, bool cudnn_enable) { |
4010 | |
4011 | static auto op = create_layer_norm_typed_handle(); |
4012 | return op.redispatch(dispatchKeySet, input, normalized_shape, weight, bias, eps, cudnn_enable); |
4013 | } |
4014 | |
4015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_layer_norm_backward, name, "aten::native_layer_norm_backward" ) |
4016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_layer_norm_backward, overload_name, "" ) |
4017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_layer_norm_backward, schema_str, "native_layer_norm_backward(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask) -> (Tensor, Tensor, Tensor)" ) |
4018 | |
4019 | // aten::native_layer_norm_backward(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
4020 | static C10_NOINLINE c10::TypedOperatorHandle<native_layer_norm_backward::schema> create_native_layer_norm_backward_typed_handle() { |
4021 | return c10::Dispatcher::singleton() |
4022 | .findSchemaOrThrow(native_layer_norm_backward::name, native_layer_norm_backward::overload_name) |
4023 | .typed<native_layer_norm_backward::schema>(); |
4024 | } |
4025 | |
4026 | // aten::native_layer_norm_backward(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
4027 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> native_layer_norm_backward::call(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, ::std::array<bool,3> output_mask) { |
4028 | |
4029 | static auto op = create_native_layer_norm_backward_typed_handle(); |
4030 | return op.call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask); |
4031 | } |
4032 | |
4033 | // aten::native_layer_norm_backward(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
4034 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> native_layer_norm_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, ::std::array<bool,3> output_mask) { |
4035 | |
4036 | static auto op = create_native_layer_norm_backward_typed_handle(); |
4037 | return op.redispatch(dispatchKeySet, grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask); |
4038 | } |
4039 | |
4040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_linear_fp16_weight, name, "aten::fbgemm_linear_fp16_weight" ) |
4041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_linear_fp16_weight, overload_name, "" ) |
4042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_linear_fp16_weight, schema_str, "fbgemm_linear_fp16_weight(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor" ) |
4043 | |
4044 | // aten::fbgemm_linear_fp16_weight(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor |
4045 | static C10_NOINLINE c10::TypedOperatorHandle<fbgemm_linear_fp16_weight::schema> create_fbgemm_linear_fp16_weight_typed_handle() { |
4046 | return c10::Dispatcher::singleton() |
4047 | .findSchemaOrThrow(fbgemm_linear_fp16_weight::name, fbgemm_linear_fp16_weight::overload_name) |
4048 | .typed<fbgemm_linear_fp16_weight::schema>(); |
4049 | } |
4050 | |
4051 | // aten::fbgemm_linear_fp16_weight(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor |
4052 | at::Tensor fbgemm_linear_fp16_weight::call(const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias) { |
4053 | |
4054 | static auto op = create_fbgemm_linear_fp16_weight_typed_handle(); |
4055 | return op.call(input, packed_weight, bias); |
4056 | } |
4057 | |
4058 | // aten::fbgemm_linear_fp16_weight(Tensor input, Tensor packed_weight, Tensor bias) -> Tensor |
4059 | at::Tensor fbgemm_linear_fp16_weight::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & packed_weight, const at::Tensor & bias) { |
4060 | |
4061 | static auto op = create_fbgemm_linear_fp16_weight_typed_handle(); |
4062 | return op.redispatch(dispatchKeySet, input, packed_weight, bias); |
4063 | } |
4064 | |
4065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_quantized_matrix, name, "aten::fbgemm_pack_quantized_matrix" ) |
4066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_quantized_matrix, overload_name, "" ) |
4067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_quantized_matrix, schema_str, "fbgemm_pack_quantized_matrix(Tensor input) -> Tensor" ) |
4068 | |
4069 | // aten::fbgemm_pack_quantized_matrix(Tensor input) -> Tensor |
4070 | static C10_NOINLINE c10::TypedOperatorHandle<fbgemm_pack_quantized_matrix::schema> create_fbgemm_pack_quantized_matrix_typed_handle() { |
4071 | return c10::Dispatcher::singleton() |
4072 | .findSchemaOrThrow(fbgemm_pack_quantized_matrix::name, fbgemm_pack_quantized_matrix::overload_name) |
4073 | .typed<fbgemm_pack_quantized_matrix::schema>(); |
4074 | } |
4075 | |
4076 | // aten::fbgemm_pack_quantized_matrix(Tensor input) -> Tensor |
4077 | at::Tensor fbgemm_pack_quantized_matrix::call(const at::Tensor & input) { |
4078 | |
4079 | static auto op = create_fbgemm_pack_quantized_matrix_typed_handle(); |
4080 | return op.call(input); |
4081 | } |
4082 | |
4083 | // aten::fbgemm_pack_quantized_matrix(Tensor input) -> Tensor |
4084 | at::Tensor fbgemm_pack_quantized_matrix::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input) { |
4085 | |
4086 | static auto op = create_fbgemm_pack_quantized_matrix_typed_handle(); |
4087 | return op.redispatch(dispatchKeySet, input); |
4088 | } |
4089 | |
4090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_quantized_matrix_KN, name, "aten::fbgemm_pack_quantized_matrix" ) |
4091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_quantized_matrix_KN, overload_name, "KN" ) |
4092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fbgemm_pack_quantized_matrix_KN, schema_str, "fbgemm_pack_quantized_matrix.KN(Tensor input, int K, int N) -> Tensor" ) |
4093 | |
4094 | // aten::fbgemm_pack_quantized_matrix.KN(Tensor input, int K, int N) -> Tensor |
4095 | static C10_NOINLINE c10::TypedOperatorHandle<fbgemm_pack_quantized_matrix_KN::schema> create_fbgemm_pack_quantized_matrix_KN_typed_handle() { |
4096 | return c10::Dispatcher::singleton() |
4097 | .findSchemaOrThrow(fbgemm_pack_quantized_matrix_KN::name, fbgemm_pack_quantized_matrix_KN::overload_name) |
4098 | .typed<fbgemm_pack_quantized_matrix_KN::schema>(); |
4099 | } |
4100 | |
4101 | // aten::fbgemm_pack_quantized_matrix.KN(Tensor input, int K, int N) -> Tensor |
4102 | at::Tensor fbgemm_pack_quantized_matrix_KN::call(const at::Tensor & input, int64_t K, int64_t N) { |
4103 | |
4104 | static auto op = create_fbgemm_pack_quantized_matrix_KN_typed_handle(); |
4105 | return op.call(input, K, N); |
4106 | } |
4107 | |
4108 | // aten::fbgemm_pack_quantized_matrix.KN(Tensor input, int K, int N) -> Tensor |
4109 | at::Tensor fbgemm_pack_quantized_matrix_KN::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, int64_t K, int64_t N) { |
4110 | |
4111 | static auto op = create_fbgemm_pack_quantized_matrix_KN_typed_handle(); |
4112 | return op.redispatch(dispatchKeySet, input, K, N); |
4113 | } |
4114 | |
4115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_Tensor, name, "aten::ldexp" ) |
4116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_Tensor, overload_name, "Tensor" ) |
4117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_Tensor, schema_str, "ldexp.Tensor(Tensor self, Tensor other) -> Tensor" ) |
4118 | |
4119 | // aten::ldexp.Tensor(Tensor self, Tensor other) -> Tensor |
4120 | static C10_NOINLINE c10::TypedOperatorHandle<ldexp_Tensor::schema> create_ldexp_Tensor_typed_handle() { |
4121 | return c10::Dispatcher::singleton() |
4122 | .findSchemaOrThrow(ldexp_Tensor::name, ldexp_Tensor::overload_name) |
4123 | .typed<ldexp_Tensor::schema>(); |
4124 | } |
4125 | |
4126 | // aten::ldexp.Tensor(Tensor self, Tensor other) -> Tensor |
4127 | at::Tensor ldexp_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
4128 | |
4129 | static auto op = create_ldexp_Tensor_typed_handle(); |
4130 | return op.call(self, other); |
4131 | } |
4132 | |
4133 | // aten::ldexp.Tensor(Tensor self, Tensor other) -> Tensor |
4134 | at::Tensor ldexp_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
4135 | |
4136 | static auto op = create_ldexp_Tensor_typed_handle(); |
4137 | return op.redispatch(dispatchKeySet, self, other); |
4138 | } |
4139 | |
4140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_, name, "aten::ldexp_" ) |
4141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_, overload_name, "" ) |
4142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_, schema_str, "ldexp_(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
4143 | |
4144 | // aten::ldexp_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
4145 | static C10_NOINLINE c10::TypedOperatorHandle<ldexp_::schema> create_ldexp__typed_handle() { |
4146 | return c10::Dispatcher::singleton() |
4147 | .findSchemaOrThrow(ldexp_::name, ldexp_::overload_name) |
4148 | .typed<ldexp_::schema>(); |
4149 | } |
4150 | |
4151 | // aten::ldexp_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
4152 | at::Tensor & ldexp_::call(at::Tensor & self, const at::Tensor & other) { |
4153 | |
4154 | static auto op = create_ldexp__typed_handle(); |
4155 | return op.call(self, other); |
4156 | } |
4157 | |
4158 | // aten::ldexp_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
4159 | at::Tensor & ldexp_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
4160 | |
4161 | static auto op = create_ldexp__typed_handle(); |
4162 | return op.redispatch(dispatchKeySet, self, other); |
4163 | } |
4164 | |
4165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_out, name, "aten::ldexp" ) |
4166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_out, overload_name, "out" ) |
4167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ldexp_out, schema_str, "ldexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
4168 | |
4169 | // aten::ldexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
4170 | static C10_NOINLINE c10::TypedOperatorHandle<ldexp_out::schema> create_ldexp_out_typed_handle() { |
4171 | return c10::Dispatcher::singleton() |
4172 | .findSchemaOrThrow(ldexp_out::name, ldexp_out::overload_name) |
4173 | .typed<ldexp_out::schema>(); |
4174 | } |
4175 | |
4176 | // aten::ldexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
4177 | at::Tensor & ldexp_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
4178 | |
4179 | static auto op = create_ldexp_out_typed_handle(); |
4180 | return op.call(self, other, out); |
4181 | } |
4182 | |
4183 | // aten::ldexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
4184 | at::Tensor & ldexp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
4185 | |
4186 | static auto op = create_ldexp_out_typed_handle(); |
4187 | return op.redispatch(dispatchKeySet, self, other, out); |
4188 | } |
4189 | |
4190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log, name, "aten::log" ) |
4191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log, overload_name, "" ) |
4192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log, schema_str, "log(Tensor self) -> Tensor" ) |
4193 | |
4194 | // aten::log(Tensor self) -> Tensor |
4195 | static C10_NOINLINE c10::TypedOperatorHandle<log::schema> create_log_typed_handle() { |
4196 | return c10::Dispatcher::singleton() |
4197 | .findSchemaOrThrow(log::name, log::overload_name) |
4198 | .typed<log::schema>(); |
4199 | } |
4200 | |
4201 | // aten::log(Tensor self) -> Tensor |
4202 | at::Tensor log::call(const at::Tensor & self) { |
4203 | |
4204 | static auto op = create_log_typed_handle(); |
4205 | return op.call(self); |
4206 | } |
4207 | |
4208 | // aten::log(Tensor self) -> Tensor |
4209 | at::Tensor log::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
4210 | |
4211 | static auto op = create_log_typed_handle(); |
4212 | return op.redispatch(dispatchKeySet, self); |
4213 | } |
4214 | |
4215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_, name, "aten::log_" ) |
4216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_, overload_name, "" ) |
4217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_, schema_str, "log_(Tensor(a!) self) -> Tensor(a!)" ) |
4218 | |
4219 | // aten::log_(Tensor(a!) self) -> Tensor(a!) |
4220 | static C10_NOINLINE c10::TypedOperatorHandle<log_::schema> create_log__typed_handle() { |
4221 | return c10::Dispatcher::singleton() |
4222 | .findSchemaOrThrow(log_::name, log_::overload_name) |
4223 | .typed<log_::schema>(); |
4224 | } |
4225 | |
4226 | // aten::log_(Tensor(a!) self) -> Tensor(a!) |
4227 | at::Tensor & log_::call(at::Tensor & self) { |
4228 | |
4229 | static auto op = create_log__typed_handle(); |
4230 | return op.call(self); |
4231 | } |
4232 | |
4233 | // aten::log_(Tensor(a!) self) -> Tensor(a!) |
4234 | at::Tensor & log_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
4235 | |
4236 | static auto op = create_log__typed_handle(); |
4237 | return op.redispatch(dispatchKeySet, self); |
4238 | } |
4239 | |
4240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_out, name, "aten::log" ) |
4241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_out, overload_name, "out" ) |
4242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_out, schema_str, "log.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
4243 | |
4244 | // aten::log.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
4245 | static C10_NOINLINE c10::TypedOperatorHandle<log_out::schema> create_log_out_typed_handle() { |
4246 | return c10::Dispatcher::singleton() |
4247 | .findSchemaOrThrow(log_out::name, log_out::overload_name) |
4248 | .typed<log_out::schema>(); |
4249 | } |
4250 | |
4251 | // aten::log.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
4252 | at::Tensor & log_out::call(const at::Tensor & self, at::Tensor & out) { |
4253 | |
4254 | static auto op = create_log_out_typed_handle(); |
4255 | return op.call(self, out); |
4256 | } |
4257 | |
4258 | // aten::log.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
4259 | at::Tensor & log_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
4260 | |
4261 | static auto op = create_log_out_typed_handle(); |
4262 | return op.redispatch(dispatchKeySet, self, out); |
4263 | } |
4264 | |
4265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2, name, "aten::log2" ) |
4266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2, overload_name, "" ) |
4267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2, schema_str, "log2(Tensor self) -> Tensor" ) |
4268 | |
4269 | // aten::log2(Tensor self) -> Tensor |
4270 | static C10_NOINLINE c10::TypedOperatorHandle<log2::schema> create_log2_typed_handle() { |
4271 | return c10::Dispatcher::singleton() |
4272 | .findSchemaOrThrow(log2::name, log2::overload_name) |
4273 | .typed<log2::schema>(); |
4274 | } |
4275 | |
4276 | // aten::log2(Tensor self) -> Tensor |
4277 | at::Tensor log2::call(const at::Tensor & self) { |
4278 | |
4279 | static auto op = create_log2_typed_handle(); |
4280 | return op.call(self); |
4281 | } |
4282 | |
4283 | // aten::log2(Tensor self) -> Tensor |
4284 | at::Tensor log2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
4285 | |
4286 | static auto op = create_log2_typed_handle(); |
4287 | return op.redispatch(dispatchKeySet, self); |
4288 | } |
4289 | |
4290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2_, name, "aten::log2_" ) |
4291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2_, overload_name, "" ) |
4292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2_, schema_str, "log2_(Tensor(a!) self) -> Tensor(a!)" ) |
4293 | |
4294 | // aten::log2_(Tensor(a!) self) -> Tensor(a!) |
4295 | static C10_NOINLINE c10::TypedOperatorHandle<log2_::schema> create_log2__typed_handle() { |
4296 | return c10::Dispatcher::singleton() |
4297 | .findSchemaOrThrow(log2_::name, log2_::overload_name) |
4298 | .typed<log2_::schema>(); |
4299 | } |
4300 | |
4301 | // aten::log2_(Tensor(a!) self) -> Tensor(a!) |
4302 | at::Tensor & log2_::call(at::Tensor & self) { |
4303 | |
4304 | static auto op = create_log2__typed_handle(); |
4305 | return op.call(self); |
4306 | } |
4307 | |
4308 | // aten::log2_(Tensor(a!) self) -> Tensor(a!) |
4309 | at::Tensor & log2_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
4310 | |
4311 | static auto op = create_log2__typed_handle(); |
4312 | return op.redispatch(dispatchKeySet, self); |
4313 | } |
4314 | |
4315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2_out, name, "aten::log2" ) |
4316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2_out, overload_name, "out" ) |
4317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log2_out, schema_str, "log2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
4318 | |
4319 | // aten::log2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
4320 | static C10_NOINLINE c10::TypedOperatorHandle<log2_out::schema> create_log2_out_typed_handle() { |
4321 | return c10::Dispatcher::singleton() |
4322 | .findSchemaOrThrow(log2_out::name, log2_out::overload_name) |
4323 | .typed<log2_out::schema>(); |
4324 | } |
4325 | |
4326 | // aten::log2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
4327 | at::Tensor & log2_out::call(const at::Tensor & self, at::Tensor & out) { |
4328 | |
4329 | static auto op = create_log2_out_typed_handle(); |
4330 | return op.call(self, out); |
4331 | } |
4332 | |
4333 | // aten::log2.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
4334 | at::Tensor & log2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
4335 | |
4336 | static auto op = create_log2_out_typed_handle(); |
4337 | return op.redispatch(dispatchKeySet, self, out); |
4338 | } |
4339 | |
4340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp_out, name, "aten::logaddexp" ) |
4341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp_out, overload_name, "out" ) |
4342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp_out, schema_str, "logaddexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
4343 | |
4344 | // aten::logaddexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
4345 | static C10_NOINLINE c10::TypedOperatorHandle<logaddexp_out::schema> create_logaddexp_out_typed_handle() { |
4346 | return c10::Dispatcher::singleton() |
4347 | .findSchemaOrThrow(logaddexp_out::name, logaddexp_out::overload_name) |
4348 | .typed<logaddexp_out::schema>(); |
4349 | } |
4350 | |
4351 | // aten::logaddexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
4352 | at::Tensor & logaddexp_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
4353 | |
4354 | static auto op = create_logaddexp_out_typed_handle(); |
4355 | return op.call(self, other, out); |
4356 | } |
4357 | |
4358 | // aten::logaddexp.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
4359 | at::Tensor & logaddexp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
4360 | |
4361 | static auto op = create_logaddexp_out_typed_handle(); |
4362 | return op.redispatch(dispatchKeySet, self, other, out); |
4363 | } |
4364 | |
4365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp, name, "aten::logaddexp" ) |
4366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp, overload_name, "" ) |
4367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logaddexp, schema_str, "logaddexp(Tensor self, Tensor other) -> Tensor" ) |
4368 | |
4369 | // aten::logaddexp(Tensor self, Tensor other) -> Tensor |
4370 | static C10_NOINLINE c10::TypedOperatorHandle<logaddexp::schema> create_logaddexp_typed_handle() { |
4371 | return c10::Dispatcher::singleton() |
4372 | .findSchemaOrThrow(logaddexp::name, logaddexp::overload_name) |
4373 | .typed<logaddexp::schema>(); |
4374 | } |
4375 | |
4376 | // aten::logaddexp(Tensor self, Tensor other) -> Tensor |
4377 | at::Tensor logaddexp::call(const at::Tensor & self, const at::Tensor & other) { |
4378 | |
4379 | static auto op = create_logaddexp_typed_handle(); |
4380 | return op.call(self, other); |
4381 | } |
4382 | |
4383 | // aten::logaddexp(Tensor self, Tensor other) -> Tensor |
4384 | at::Tensor logaddexp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
4385 | |
4386 | static auto op = create_logaddexp_typed_handle(); |
4387 | return op.redispatch(dispatchKeySet, self, other); |
4388 | } |
4389 | |
4390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logspace, name, "aten::logspace" ) |
4391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logspace, overload_name, "" ) |
4392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logspace, schema_str, "logspace(Scalar start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
4393 | |
4394 | // aten::logspace(Scalar start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
4395 | static C10_NOINLINE c10::TypedOperatorHandle<logspace::schema> create_logspace_typed_handle() { |
4396 | return c10::Dispatcher::singleton() |
4397 | .findSchemaOrThrow(logspace::name, logspace::overload_name) |
4398 | .typed<logspace::schema>(); |
4399 | } |
4400 | |
4401 | // aten::logspace(Scalar start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
4402 | at::Tensor logspace::call(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
4403 | |
4404 | static auto op = create_logspace_typed_handle(); |
4405 | return op.call(start, end, steps, base, dtype, layout, device, pin_memory); |
4406 | } |
4407 | |
4408 | // aten::logspace(Scalar start, Scalar end, int steps, float base=10.0, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
4409 | at::Tensor logspace::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
4410 | |
4411 | static auto op = create_logspace_typed_handle(); |
4412 | return op.redispatch(dispatchKeySet, start, end, steps, base, dtype, layout, device, pin_memory); |
4413 | } |
4414 | |
4415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logspace_out, name, "aten::logspace" ) |
4416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logspace_out, overload_name, "out" ) |
4417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(logspace_out, schema_str, "logspace.out(Scalar start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!)" ) |
4418 | |
4419 | // aten::logspace.out(Scalar start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!) |
4420 | static C10_NOINLINE c10::TypedOperatorHandle<logspace_out::schema> create_logspace_out_typed_handle() { |
4421 | return c10::Dispatcher::singleton() |
4422 | .findSchemaOrThrow(logspace_out::name, logspace_out::overload_name) |
4423 | .typed<logspace_out::schema>(); |
4424 | } |
4425 | |
4426 | // aten::logspace.out(Scalar start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!) |
4427 | at::Tensor & logspace_out::call(const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out) { |
4428 | |
4429 | static auto op = create_logspace_out_typed_handle(); |
4430 | return op.call(start, end, steps, base, out); |
4431 | } |
4432 | |
4433 | // aten::logspace.out(Scalar start, Scalar end, int steps, float base=10.0, *, Tensor(a!) out) -> Tensor(a!) |
4434 | at::Tensor & logspace_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & start, const at::Scalar & end, int64_t steps, double base, at::Tensor & out) { |
4435 | |
4436 | static auto op = create_logspace_out_typed_handle(); |
4437 | return op.redispatch(dispatchKeySet, start, end, steps, base, out); |
4438 | } |
4439 | |
4440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_int, name, "aten::log_softmax" ) |
4441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_int, overload_name, "int" ) |
4442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_int, schema_str, "log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor" ) |
4443 | |
4444 | // aten::log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor |
4445 | static C10_NOINLINE c10::TypedOperatorHandle<log_softmax_int::schema> create_log_softmax_int_typed_handle() { |
4446 | return c10::Dispatcher::singleton() |
4447 | .findSchemaOrThrow(log_softmax_int::name, log_softmax_int::overload_name) |
4448 | .typed<log_softmax_int::schema>(); |
4449 | } |
4450 | |
4451 | // aten::log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor |
4452 | at::Tensor log_softmax_int::call(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
4453 | |
4454 | static auto op = create_log_softmax_int_typed_handle(); |
4455 | return op.call(self, dim, dtype); |
4456 | } |
4457 | |
4458 | // aten::log_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor |
4459 | at::Tensor log_softmax_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
4460 | |
4461 | static auto op = create_log_softmax_int_typed_handle(); |
4462 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
4463 | } |
4464 | |
4465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_int_out, name, "aten::log_softmax" ) |
4466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_int_out, overload_name, "int_out" ) |
4467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_int_out, schema_str, "log_softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
4468 | |
4469 | // aten::log_softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
4470 | static C10_NOINLINE c10::TypedOperatorHandle<log_softmax_int_out::schema> create_log_softmax_int_out_typed_handle() { |
4471 | return c10::Dispatcher::singleton() |
4472 | .findSchemaOrThrow(log_softmax_int_out::name, log_softmax_int_out::overload_name) |
4473 | .typed<log_softmax_int_out::schema>(); |
4474 | } |
4475 | |
4476 | // aten::log_softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
4477 | at::Tensor & log_softmax_int_out::call(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
4478 | |
4479 | static auto op = create_log_softmax_int_out_typed_handle(); |
4480 | return op.call(self, dim, dtype, out); |
4481 | } |
4482 | |
4483 | // aten::log_softmax.int_out(Tensor self, int dim, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
4484 | at::Tensor & log_softmax_int_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
4485 | |
4486 | static auto op = create_log_softmax_int_out_typed_handle(); |
4487 | return op.redispatch(dispatchKeySet, self, dim, dtype, out); |
4488 | } |
4489 | |
4490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_Dimname, name, "aten::log_softmax" ) |
4491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_Dimname, overload_name, "Dimname" ) |
4492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(log_softmax_Dimname, schema_str, "log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor" ) |
4493 | |
4494 | // aten::log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
4495 | static C10_NOINLINE c10::TypedOperatorHandle<log_softmax_Dimname::schema> create_log_softmax_Dimname_typed_handle() { |
4496 | return c10::Dispatcher::singleton() |
4497 | .findSchemaOrThrow(log_softmax_Dimname::name, log_softmax_Dimname::overload_name) |
4498 | .typed<log_softmax_Dimname::schema>(); |
4499 | } |
4500 | |
4501 | // aten::log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
4502 | at::Tensor log_softmax_Dimname::call(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
4503 | |
4504 | static auto op = create_log_softmax_Dimname_typed_handle(); |
4505 | return op.call(self, dim, dtype); |
4506 | } |
4507 | |
4508 | // aten::log_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
4509 | at::Tensor log_softmax_Dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
4510 | |
4511 | static auto op = create_log_softmax_Dimname_typed_handle(); |
4512 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
4513 | } |
4514 | |
4515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_power, name, "aten::matrix_power" ) |
4516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_power, overload_name, "" ) |
4517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_power, schema_str, "matrix_power(Tensor self, int n) -> Tensor" ) |
4518 | |
4519 | // aten::matrix_power(Tensor self, int n) -> Tensor |
4520 | static C10_NOINLINE c10::TypedOperatorHandle<matrix_power::schema> create_matrix_power_typed_handle() { |
4521 | return c10::Dispatcher::singleton() |
4522 | .findSchemaOrThrow(matrix_power::name, matrix_power::overload_name) |
4523 | .typed<matrix_power::schema>(); |
4524 | } |
4525 | |
4526 | // aten::matrix_power(Tensor self, int n) -> Tensor |
4527 | at::Tensor matrix_power::call(const at::Tensor & self, int64_t n) { |
4528 | |
4529 | static auto op = create_matrix_power_typed_handle(); |
4530 | return op.call(self, n); |
4531 | } |
4532 | |
4533 | // aten::matrix_power(Tensor self, int n) -> Tensor |
4534 | at::Tensor matrix_power::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n) { |
4535 | |
4536 | static auto op = create_matrix_power_typed_handle(); |
4537 | return op.redispatch(dispatchKeySet, self, n); |
4538 | } |
4539 | |
4540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_power_out, name, "aten::matrix_power" ) |
4541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_power_out, overload_name, "out" ) |
4542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(matrix_power_out, schema_str, "matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!)" ) |
4543 | |
4544 | // aten::matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) |
4545 | static C10_NOINLINE c10::TypedOperatorHandle<matrix_power_out::schema> create_matrix_power_out_typed_handle() { |
4546 | return c10::Dispatcher::singleton() |
4547 | .findSchemaOrThrow(matrix_power_out::name, matrix_power_out::overload_name) |
4548 | .typed<matrix_power_out::schema>(); |
4549 | } |
4550 | |
4551 | // aten::matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) |
4552 | at::Tensor & matrix_power_out::call(const at::Tensor & self, int64_t n, at::Tensor & out) { |
4553 | |
4554 | static auto op = create_matrix_power_out_typed_handle(); |
4555 | return op.call(self, n, out); |
4556 | } |
4557 | |
4558 | // aten::matrix_power.out(Tensor self, int n, *, Tensor(a!) out) -> Tensor(a!) |
4559 | at::Tensor & matrix_power_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n, at::Tensor & out) { |
4560 | |
4561 | static auto op = create_matrix_power_out_typed_handle(); |
4562 | return op.redispatch(dispatchKeySet, self, n, out); |
4563 | } |
4564 | |
4565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_max_pool2d_backward, name, "aten::mps_max_pool2d_backward" ) |
4566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_max_pool2d_backward, overload_name, "" ) |
4567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_max_pool2d_backward, schema_str, "mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor" ) |
4568 | |
4569 | // aten::mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor |
4570 | static C10_NOINLINE c10::TypedOperatorHandle<mps_max_pool2d_backward::schema> create_mps_max_pool2d_backward_typed_handle() { |
4571 | return c10::Dispatcher::singleton() |
4572 | .findSchemaOrThrow(mps_max_pool2d_backward::name, mps_max_pool2d_backward::overload_name) |
4573 | .typed<mps_max_pool2d_backward::schema>(); |
4574 | } |
4575 | |
4576 | // aten::mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor |
4577 | at::Tensor mps_max_pool2d_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) { |
4578 | |
4579 | static auto op = create_mps_max_pool2d_backward_typed_handle(); |
4580 | return op.call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); |
4581 | } |
4582 | |
4583 | // aten::mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor |
4584 | at::Tensor mps_max_pool2d_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) { |
4585 | |
4586 | static auto op = create_mps_max_pool2d_backward_typed_handle(); |
4587 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); |
4588 | } |
4589 | |
4590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d, name, "aten::mkldnn_max_pool3d" ) |
4591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d, overload_name, "" ) |
4592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d, schema_str, "mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor" ) |
4593 | |
4594 | // aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
4595 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_max_pool3d::schema> create_mkldnn_max_pool3d_typed_handle() { |
4596 | return c10::Dispatcher::singleton() |
4597 | .findSchemaOrThrow(mkldnn_max_pool3d::name, mkldnn_max_pool3d::overload_name) |
4598 | .typed<mkldnn_max_pool3d::schema>(); |
4599 | } |
4600 | |
4601 | // aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
4602 | at::Tensor mkldnn_max_pool3d::call(const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef stride, at::IntArrayRef padding, at::IntArrayRef dilation, bool ceil_mode) { |
4603 | |
4604 | static auto op = create_mkldnn_max_pool3d_typed_handle(); |
4605 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode); |
4606 | } |
4607 | |
4608 | // aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor |
4609 | at::Tensor mkldnn_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) { |
4610 | |
4611 | static auto op = create_mkldnn_max_pool3d_typed_handle(); |
4612 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode); |
4613 | } |
4614 | |
4615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_backward, name, "aten::mps_convolution_backward" ) |
4616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_backward, overload_name, "" ) |
4617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_backward, schema_str, "mps_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor)" ) |
4618 | |
4619 | // aten::mps_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
4620 | static C10_NOINLINE c10::TypedOperatorHandle<mps_convolution_backward::schema> create_mps_convolution_backward_typed_handle() { |
4621 | return c10::Dispatcher::singleton() |
4622 | .findSchemaOrThrow(mps_convolution_backward::name, mps_convolution_backward::overload_name) |
4623 | .typed<mps_convolution_backward::schema>(); |
4624 | } |
4625 | |
4626 | // aten::mps_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
4627 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> mps_convolution_backward::call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,3> output_mask) { |
4628 | |
4629 | static auto op = create_mps_convolution_backward_typed_handle(); |
4630 | return op.call(self, grad_output, weight, padding, stride, dilation, groups, output_mask); |
4631 | } |
4632 | |
4633 | // aten::mps_convolution_backward(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) |
4634 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> mps_convolution_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,3> output_mask) { |
4635 | |
4636 | static auto op = create_mps_convolution_backward_typed_handle(); |
4637 | return op.redispatch(dispatchKeySet, self, grad_output, weight, padding, stride, dilation, groups, output_mask); |
4638 | } |
4639 | |
4640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_rnn_layer, name, "aten::mkldnn_rnn_layer" ) |
4641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_rnn_layer, overload_name, "" ) |
4642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_rnn_layer, schema_str, "mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor)" ) |
4643 | |
4644 | // aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) |
4645 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_rnn_layer::schema> create_mkldnn_rnn_layer_typed_handle() { |
4646 | return c10::Dispatcher::singleton() |
4647 | .findSchemaOrThrow(mkldnn_rnn_layer::name, mkldnn_rnn_layer::overload_name) |
4648 | .typed<mkldnn_rnn_layer::schema>(); |
4649 | } |
4650 | |
4651 | // aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) |
4652 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> mkldnn_rnn_layer::call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) { |
4653 | |
4654 | static auto op = create_mkldnn_rnn_layer_typed_handle(); |
4655 | return op.call(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); |
4656 | } |
4657 | |
4658 | // aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) |
4659 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> mkldnn_rnn_layer::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) { |
4660 | |
4661 | static auto op = create_mkldnn_rnn_layer_typed_handle(); |
4662 | return op.redispatch(dispatchKeySet, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); |
4663 | } |
4664 | |
4665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution, name, "aten::miopen_convolution" ) |
4666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution, overload_name, "" ) |
4667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution, schema_str, "miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor" ) |
4668 | |
4669 | // aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor |
4670 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_convolution::schema> create_miopen_convolution_typed_handle() { |
4671 | return c10::Dispatcher::singleton() |
4672 | .findSchemaOrThrow(miopen_convolution::name, miopen_convolution::overload_name) |
4673 | .typed<miopen_convolution::schema>(); |
4674 | } |
4675 | |
4676 | // aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor |
4677 | at::Tensor miopen_convolution::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { |
4678 | |
4679 | static auto op = create_miopen_convolution_typed_handle(); |
4680 | return op.call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); |
4681 | } |
4682 | |
4683 | // aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor |
4684 | at::Tensor miopen_convolution::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic) { |
4685 | |
4686 | static auto op = create_miopen_convolution_typed_handle(); |
4687 | return op.redispatch(dispatchKeySet, self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic); |
4688 | } |
4689 | |
4690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn, name, "aten::miopen_rnn" ) |
4691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn, overload_name, "" ) |
4692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn, schema_str, "miopen_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor)" ) |
4693 | |
4694 | // aten::miopen_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
4695 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_rnn::schema> create_miopen_rnn_typed_handle() { |
4696 | return c10::Dispatcher::singleton() |
4697 | .findSchemaOrThrow(miopen_rnn::name, miopen_rnn::overload_name) |
4698 | .typed<miopen_rnn::schema>(); |
4699 | } |
4700 | |
4701 | // aten::miopen_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
4702 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> miopen_rnn::call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, 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) { |
4703 | |
4704 | static auto op = create_miopen_rnn_typed_handle(); |
4705 | return op.call(input, weight, weight_stride0, hx, cx, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); |
4706 | } |
4707 | |
4708 | // aten::miopen_rnn(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
4709 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> miopen_rnn::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, 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) { |
4710 | |
4711 | static auto op = create_miopen_rnn_typed_handle(); |
4712 | return op.redispatch(dispatchKeySet, input, weight, weight_stride0, hx, cx, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state); |
4713 | } |
4714 | |
4715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm, name, "aten::_sparse_mm" ) |
4716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm, overload_name, "" ) |
4717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm, schema_str, "_sparse_mm(Tensor sparse, Tensor dense) -> Tensor" ) |
4718 | |
4719 | // aten::_sparse_mm(Tensor sparse, Tensor dense) -> Tensor |
4720 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_mm::schema> create__sparse_mm_typed_handle() { |
4721 | return c10::Dispatcher::singleton() |
4722 | .findSchemaOrThrow(_sparse_mm::name, _sparse_mm::overload_name) |
4723 | .typed<_sparse_mm::schema>(); |
4724 | } |
4725 | |
4726 | // aten::_sparse_mm(Tensor sparse, Tensor dense) -> Tensor |
4727 | at::Tensor _sparse_mm::call(const at::Tensor & sparse, const at::Tensor & dense) { |
4728 | |
4729 | static auto op = create__sparse_mm_typed_handle(); |
4730 | return op.call(sparse, dense); |
4731 | } |
4732 | |
4733 | // aten::_sparse_mm(Tensor sparse, Tensor dense) -> Tensor |
4734 | at::Tensor _sparse_mm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sparse, const at::Tensor & dense) { |
4735 | |
4736 | static auto op = create__sparse_mm_typed_handle(); |
4737 | return op.redispatch(dispatchKeySet, sparse, dense); |
4738 | } |
4739 | |
4740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm_reduce, name, "aten::_sparse_mm" ) |
4741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm_reduce, overload_name, "reduce" ) |
4742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_mm_reduce, schema_str, "_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor" ) |
4743 | |
4744 | // aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor |
4745 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_mm_reduce::schema> create__sparse_mm_reduce_typed_handle() { |
4746 | return c10::Dispatcher::singleton() |
4747 | .findSchemaOrThrow(_sparse_mm_reduce::name, _sparse_mm_reduce::overload_name) |
4748 | .typed<_sparse_mm_reduce::schema>(); |
4749 | } |
4750 | |
4751 | // aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor |
4752 | at::Tensor _sparse_mm_reduce::call(const at::Tensor & sparse, const at::Tensor & dense, c10::string_view reduce) { |
4753 | |
4754 | static auto op = create__sparse_mm_reduce_typed_handle(); |
4755 | return op.call(sparse, dense, reduce); |
4756 | } |
4757 | |
4758 | // aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor |
4759 | at::Tensor _sparse_mm_reduce::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & sparse, const at::Tensor & dense, c10::string_view reduce) { |
4760 | |
4761 | static auto op = create__sparse_mm_reduce_typed_handle(); |
4762 | return op.redispatch(dispatchKeySet, sparse, dense, reduce); |
4763 | } |
4764 | |
4765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sparse_matmul, name, "aten::_sparse_sparse_matmul" ) |
4766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sparse_matmul, overload_name, "" ) |
4767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sparse_matmul, schema_str, "_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor" ) |
4768 | |
4769 | // aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor |
4770 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sparse_matmul::schema> create__sparse_sparse_matmul_typed_handle() { |
4771 | return c10::Dispatcher::singleton() |
4772 | .findSchemaOrThrow(_sparse_sparse_matmul::name, _sparse_sparse_matmul::overload_name) |
4773 | .typed<_sparse_sparse_matmul::schema>(); |
4774 | } |
4775 | |
4776 | // aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor |
4777 | at::Tensor _sparse_sparse_matmul::call(const at::Tensor & self, const at::Tensor & other) { |
4778 | |
4779 | static auto op = create__sparse_sparse_matmul_typed_handle(); |
4780 | return op.call(self, other); |
4781 | } |
4782 | |
4783 | // aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor |
4784 | at::Tensor _sparse_sparse_matmul::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
4785 | |
4786 | static auto op = create__sparse_sparse_matmul_typed_handle(); |
4787 | return op.redispatch(dispatchKeySet, self, other); |
4788 | } |
4789 | |
4790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit, name, "aten::_native_batch_norm_legit" ) |
4791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit, overload_name, "" ) |
4792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit, schema_str, "_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)" ) |
4793 | |
4794 | // aten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) |
4795 | static C10_NOINLINE c10::TypedOperatorHandle<_native_batch_norm_legit::schema> create__native_batch_norm_legit_typed_handle() { |
4796 | return c10::Dispatcher::singleton() |
4797 | .findSchemaOrThrow(_native_batch_norm_legit::name, _native_batch_norm_legit::overload_name) |
4798 | .typed<_native_batch_norm_legit::schema>(); |
4799 | } |
4800 | |
4801 | // aten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) |
4802 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _native_batch_norm_legit::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps) { |
4803 | |
4804 | static auto op = create__native_batch_norm_legit_typed_handle(); |
4805 | return op.call(input, weight, bias, running_mean, running_var, training, momentum, eps); |
4806 | } |
4807 | |
4808 | // aten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) |
4809 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _native_batch_norm_legit::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps) { |
4810 | |
4811 | static auto op = create__native_batch_norm_legit_typed_handle(); |
4812 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, momentum, eps); |
4813 | } |
4814 | |
4815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_out, name, "aten::_native_batch_norm_legit" ) |
4816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_out, overload_name, "out" ) |
4817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_out, schema_str, "_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!))" ) |
4818 | |
4819 | // aten::_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!)) |
4820 | static C10_NOINLINE c10::TypedOperatorHandle<_native_batch_norm_legit_out::schema> create__native_batch_norm_legit_out_typed_handle() { |
4821 | return c10::Dispatcher::singleton() |
4822 | .findSchemaOrThrow(_native_batch_norm_legit_out::name, _native_batch_norm_legit_out::overload_name) |
4823 | .typed<_native_batch_norm_legit_out::schema>(); |
4824 | } |
4825 | |
4826 | // aten::_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!)) |
4827 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _native_batch_norm_legit_out::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd) { |
4828 | |
4829 | static auto op = create__native_batch_norm_legit_out_typed_handle(); |
4830 | return op.call(input, weight, bias, running_mean, running_var, training, momentum, eps, out, save_mean, save_invstd); |
4831 | } |
4832 | |
4833 | // aten::_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!)) |
4834 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _native_batch_norm_legit_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, at::Tensor & running_mean, at::Tensor & running_var, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd) { |
4835 | |
4836 | static auto op = create__native_batch_norm_legit_out_typed_handle(); |
4837 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, momentum, eps, out, save_mean, save_invstd); |
4838 | } |
4839 | |
4840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_no_stats, name, "aten::_native_batch_norm_legit" ) |
4841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_no_stats, overload_name, "no_stats" ) |
4842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_no_stats, schema_str, "_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor)" ) |
4843 | |
4844 | // aten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) |
4845 | static C10_NOINLINE c10::TypedOperatorHandle<_native_batch_norm_legit_no_stats::schema> create__native_batch_norm_legit_no_stats_typed_handle() { |
4846 | return c10::Dispatcher::singleton() |
4847 | .findSchemaOrThrow(_native_batch_norm_legit_no_stats::name, _native_batch_norm_legit_no_stats::overload_name) |
4848 | .typed<_native_batch_norm_legit_no_stats::schema>(); |
4849 | } |
4850 | |
4851 | // aten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) |
4852 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _native_batch_norm_legit_no_stats::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, bool training, double momentum, double eps) { |
4853 | |
4854 | static auto op = create__native_batch_norm_legit_no_stats_typed_handle(); |
4855 | return op.call(input, weight, bias, training, momentum, eps); |
4856 | } |
4857 | |
4858 | // aten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) |
4859 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _native_batch_norm_legit_no_stats::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, bool training, double momentum, double eps) { |
4860 | |
4861 | static auto op = create__native_batch_norm_legit_no_stats_typed_handle(); |
4862 | return op.redispatch(dispatchKeySet, input, weight, bias, training, momentum, eps); |
4863 | } |
4864 | |
4865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_no_stats_out, name, "aten::_native_batch_norm_legit" ) |
4866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_no_stats_out, overload_name, "no_stats_out" ) |
4867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_no_stats_out, schema_str, "_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!))" ) |
4868 | |
4869 | // aten::_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
4870 | static C10_NOINLINE c10::TypedOperatorHandle<_native_batch_norm_legit_no_stats_out::schema> create__native_batch_norm_legit_no_stats_out_typed_handle() { |
4871 | return c10::Dispatcher::singleton() |
4872 | .findSchemaOrThrow(_native_batch_norm_legit_no_stats_out::name, _native_batch_norm_legit_no_stats_out::overload_name) |
4873 | .typed<_native_batch_norm_legit_no_stats_out::schema>(); |
4874 | } |
4875 | |
4876 | // aten::_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
4877 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _native_batch_norm_legit_no_stats_out::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd) { |
4878 | |
4879 | static auto op = create__native_batch_norm_legit_no_stats_out_typed_handle(); |
4880 | return op.call(input, weight, bias, training, momentum, eps, out, save_mean, save_invstd); |
4881 | } |
4882 | |
4883 | // aten::_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
4884 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> _native_batch_norm_legit_no_stats_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, bool training, double momentum, double eps, at::Tensor & out, at::Tensor & save_mean, at::Tensor & save_invstd) { |
4885 | |
4886 | static auto op = create__native_batch_norm_legit_no_stats_out_typed_handle(); |
4887 | return op.redispatch(dispatchKeySet, input, weight, bias, training, momentum, eps, out, save_mean, save_invstd); |
4888 | } |
4889 | |
4890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_update_stats, name, "aten::batch_norm_update_stats" ) |
4891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_update_stats, overload_name, "" ) |
4892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_update_stats, schema_str, "batch_norm_update_stats(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum) -> (Tensor, Tensor)" ) |
4893 | |
4894 | // aten::batch_norm_update_stats(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum) -> (Tensor, Tensor) |
4895 | static C10_NOINLINE c10::TypedOperatorHandle<batch_norm_update_stats::schema> create_batch_norm_update_stats_typed_handle() { |
4896 | return c10::Dispatcher::singleton() |
4897 | .findSchemaOrThrow(batch_norm_update_stats::name, batch_norm_update_stats::overload_name) |
4898 | .typed<batch_norm_update_stats::schema>(); |
4899 | } |
4900 | |
4901 | // aten::batch_norm_update_stats(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum) -> (Tensor, Tensor) |
4902 | ::std::tuple<at::Tensor,at::Tensor> batch_norm_update_stats::call(const at::Tensor & input, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, double momentum) { |
4903 | |
4904 | static auto op = create_batch_norm_update_stats_typed_handle(); |
4905 | return op.call(input, running_mean, running_var, momentum); |
4906 | } |
4907 | |
4908 | // aten::batch_norm_update_stats(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum) -> (Tensor, Tensor) |
4909 | ::std::tuple<at::Tensor,at::Tensor> batch_norm_update_stats::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, double momentum) { |
4910 | |
4911 | static auto op = create_batch_norm_update_stats_typed_handle(); |
4912 | return op.redispatch(dispatchKeySet, input, running_mean, running_var, momentum); |
4913 | } |
4914 | |
4915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nnpack_available, name, "aten::_nnpack_available" ) |
4916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nnpack_available, overload_name, "" ) |
4917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nnpack_available, schema_str, "_nnpack_available() -> bool" ) |
4918 | |
4919 | // aten::_nnpack_available() -> bool |
4920 | static C10_NOINLINE c10::TypedOperatorHandle<_nnpack_available::schema> create__nnpack_available_typed_handle() { |
4921 | return c10::Dispatcher::singleton() |
4922 | .findSchemaOrThrow(_nnpack_available::name, _nnpack_available::overload_name) |
4923 | .typed<_nnpack_available::schema>(); |
4924 | } |
4925 | |
4926 | // aten::_nnpack_available() -> bool |
4927 | bool _nnpack_available::call() { |
4928 | |
4929 | static auto op = create__nnpack_available_typed_handle(); |
4930 | return op.call(); |
4931 | } |
4932 | |
4933 | // aten::_nnpack_available() -> bool |
4934 | bool _nnpack_available::redispatch(c10::DispatchKeySet dispatchKeySet) { |
4935 | |
4936 | static auto op = create__nnpack_available_typed_handle(); |
4937 | return op.redispatch(dispatchKeySet); |
4938 | } |
4939 | |
4940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ones_like, name, "aten::ones_like" ) |
4941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ones_like, overload_name, "" ) |
4942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ones_like, schema_str, "ones_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor" ) |
4943 | |
4944 | // aten::ones_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
4945 | static C10_NOINLINE c10::TypedOperatorHandle<ones_like::schema> create_ones_like_typed_handle() { |
4946 | return c10::Dispatcher::singleton() |
4947 | .findSchemaOrThrow(ones_like::name, ones_like::overload_name) |
4948 | .typed<ones_like::schema>(); |
4949 | } |
4950 | |
4951 | // aten::ones_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
4952 | at::Tensor ones_like::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
4953 | |
4954 | static auto op = create_ones_like_typed_handle(); |
4955 | return op.call(self, dtype, layout, device, pin_memory, memory_format); |
4956 | } |
4957 | |
4958 | // aten::ones_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
4959 | at::Tensor ones_like::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
4960 | |
4961 | static auto op = create_ones_like_typed_handle(); |
4962 | return op.redispatch(dispatchKeySet, self, dtype, layout, device, pin_memory, memory_format); |
4963 | } |
4964 | |
4965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_euclidean_dist, name, "aten::_euclidean_dist" ) |
4966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_euclidean_dist, overload_name, "" ) |
4967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_euclidean_dist, schema_str, "_euclidean_dist(Tensor x1, Tensor x2) -> Tensor" ) |
4968 | |
4969 | // aten::_euclidean_dist(Tensor x1, Tensor x2) -> Tensor |
4970 | static C10_NOINLINE c10::TypedOperatorHandle<_euclidean_dist::schema> create__euclidean_dist_typed_handle() { |
4971 | return c10::Dispatcher::singleton() |
4972 | .findSchemaOrThrow(_euclidean_dist::name, _euclidean_dist::overload_name) |
4973 | .typed<_euclidean_dist::schema>(); |
4974 | } |
4975 | |
4976 | // aten::_euclidean_dist(Tensor x1, Tensor x2) -> Tensor |
4977 | at::Tensor _euclidean_dist::call(const at::Tensor & x1, const at::Tensor & x2) { |
4978 | |
4979 | static auto op = create__euclidean_dist_typed_handle(); |
4980 | return op.call(x1, x2); |
4981 | } |
4982 | |
4983 | // aten::_euclidean_dist(Tensor x1, Tensor x2) -> Tensor |
4984 | at::Tensor _euclidean_dist::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2) { |
4985 | |
4986 | static auto op = create__euclidean_dist_typed_handle(); |
4987 | return op.redispatch(dispatchKeySet, x1, x2); |
4988 | } |
4989 | |
4990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cdist_backward, name, "aten::_cdist_backward" ) |
4991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cdist_backward, overload_name, "" ) |
4992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cdist_backward, schema_str, "_cdist_backward(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist) -> Tensor" ) |
4993 | |
4994 | // aten::_cdist_backward(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist) -> Tensor |
4995 | static C10_NOINLINE c10::TypedOperatorHandle<_cdist_backward::schema> create__cdist_backward_typed_handle() { |
4996 | return c10::Dispatcher::singleton() |
4997 | .findSchemaOrThrow(_cdist_backward::name, _cdist_backward::overload_name) |
4998 | .typed<_cdist_backward::schema>(); |
4999 | } |
5000 | |
5001 | // aten::_cdist_backward(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist) -> Tensor |
5002 | at::Tensor _cdist_backward::call(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist) { |
5003 | |
5004 | static auto op = create__cdist_backward_typed_handle(); |
5005 | return op.call(grad, x1, x2, p, cdist); |
5006 | } |
5007 | |
5008 | // aten::_cdist_backward(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist) -> Tensor |
5009 | at::Tensor _cdist_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist) { |
5010 | |
5011 | static auto op = create__cdist_backward_typed_handle(); |
5012 | return op.redispatch(dispatchKeySet, grad, x1, x2, p, cdist); |
5013 | } |
5014 | |
5015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pdist_forward, name, "aten::_pdist_forward" ) |
5016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pdist_forward, overload_name, "" ) |
5017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pdist_forward, schema_str, "_pdist_forward(Tensor self, float p=2) -> Tensor" ) |
5018 | |
5019 | // aten::_pdist_forward(Tensor self, float p=2) -> Tensor |
5020 | static C10_NOINLINE c10::TypedOperatorHandle<_pdist_forward::schema> create__pdist_forward_typed_handle() { |
5021 | return c10::Dispatcher::singleton() |
5022 | .findSchemaOrThrow(_pdist_forward::name, _pdist_forward::overload_name) |
5023 | .typed<_pdist_forward::schema>(); |
5024 | } |
5025 | |
5026 | // aten::_pdist_forward(Tensor self, float p=2) -> Tensor |
5027 | at::Tensor _pdist_forward::call(const at::Tensor & self, double p) { |
5028 | |
5029 | static auto op = create__pdist_forward_typed_handle(); |
5030 | return op.call(self, p); |
5031 | } |
5032 | |
5033 | // aten::_pdist_forward(Tensor self, float p=2) -> Tensor |
5034 | at::Tensor _pdist_forward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p) { |
5035 | |
5036 | static auto op = create__pdist_forward_typed_handle(); |
5037 | return op.redispatch(dispatchKeySet, self, p); |
5038 | } |
5039 | |
5040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_channel_shuffle, name, "aten::native_channel_shuffle" ) |
5041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_channel_shuffle, overload_name, "" ) |
5042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_channel_shuffle, schema_str, "native_channel_shuffle(Tensor self, int groups) -> Tensor" ) |
5043 | |
5044 | // aten::native_channel_shuffle(Tensor self, int groups) -> Tensor |
5045 | static C10_NOINLINE c10::TypedOperatorHandle<native_channel_shuffle::schema> create_native_channel_shuffle_typed_handle() { |
5046 | return c10::Dispatcher::singleton() |
5047 | .findSchemaOrThrow(native_channel_shuffle::name, native_channel_shuffle::overload_name) |
5048 | .typed<native_channel_shuffle::schema>(); |
5049 | } |
5050 | |
5051 | // aten::native_channel_shuffle(Tensor self, int groups) -> Tensor |
5052 | at::Tensor native_channel_shuffle::call(const at::Tensor & self, int64_t groups) { |
5053 | |
5054 | static auto op = create_native_channel_shuffle_typed_handle(); |
5055 | return op.call(self, groups); |
5056 | } |
5057 | |
5058 | // aten::native_channel_shuffle(Tensor self, int groups) -> Tensor |
5059 | at::Tensor native_channel_shuffle::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t groups) { |
5060 | |
5061 | static auto op = create_native_channel_shuffle_typed_handle(); |
5062 | return op.redispatch(dispatchKeySet, self, groups); |
5063 | } |
5064 | |
5065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg, name, "aten::rad2deg" ) |
5066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg, overload_name, "" ) |
5067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg, schema_str, "rad2deg(Tensor self) -> Tensor" ) |
5068 | |
5069 | // aten::rad2deg(Tensor self) -> Tensor |
5070 | static C10_NOINLINE c10::TypedOperatorHandle<rad2deg::schema> create_rad2deg_typed_handle() { |
5071 | return c10::Dispatcher::singleton() |
5072 | .findSchemaOrThrow(rad2deg::name, rad2deg::overload_name) |
5073 | .typed<rad2deg::schema>(); |
5074 | } |
5075 | |
5076 | // aten::rad2deg(Tensor self) -> Tensor |
5077 | at::Tensor rad2deg::call(const at::Tensor & self) { |
5078 | |
5079 | static auto op = create_rad2deg_typed_handle(); |
5080 | return op.call(self); |
5081 | } |
5082 | |
5083 | // aten::rad2deg(Tensor self) -> Tensor |
5084 | at::Tensor rad2deg::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
5085 | |
5086 | static auto op = create_rad2deg_typed_handle(); |
5087 | return op.redispatch(dispatchKeySet, self); |
5088 | } |
5089 | |
5090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg_, name, "aten::rad2deg_" ) |
5091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg_, overload_name, "" ) |
5092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg_, schema_str, "rad2deg_(Tensor(a!) self) -> Tensor(a!)" ) |
5093 | |
5094 | // aten::rad2deg_(Tensor(a!) self) -> Tensor(a!) |
5095 | static C10_NOINLINE c10::TypedOperatorHandle<rad2deg_::schema> create_rad2deg__typed_handle() { |
5096 | return c10::Dispatcher::singleton() |
5097 | .findSchemaOrThrow(rad2deg_::name, rad2deg_::overload_name) |
5098 | .typed<rad2deg_::schema>(); |
5099 | } |
5100 | |
5101 | // aten::rad2deg_(Tensor(a!) self) -> Tensor(a!) |
5102 | at::Tensor & rad2deg_::call(at::Tensor & self) { |
5103 | |
5104 | static auto op = create_rad2deg__typed_handle(); |
5105 | return op.call(self); |
5106 | } |
5107 | |
5108 | // aten::rad2deg_(Tensor(a!) self) -> Tensor(a!) |
5109 | at::Tensor & rad2deg_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
5110 | |
5111 | static auto op = create_rad2deg__typed_handle(); |
5112 | return op.redispatch(dispatchKeySet, self); |
5113 | } |
5114 | |
5115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg_out, name, "aten::rad2deg" ) |
5116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg_out, overload_name, "out" ) |
5117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rad2deg_out, schema_str, "rad2deg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
5118 | |
5119 | // aten::rad2deg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
5120 | static C10_NOINLINE c10::TypedOperatorHandle<rad2deg_out::schema> create_rad2deg_out_typed_handle() { |
5121 | return c10::Dispatcher::singleton() |
5122 | .findSchemaOrThrow(rad2deg_out::name, rad2deg_out::overload_name) |
5123 | .typed<rad2deg_out::schema>(); |
5124 | } |
5125 | |
5126 | // aten::rad2deg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
5127 | at::Tensor & rad2deg_out::call(const at::Tensor & self, at::Tensor & out) { |
5128 | |
5129 | static auto op = create_rad2deg_out_typed_handle(); |
5130 | return op.call(self, out); |
5131 | } |
5132 | |
5133 | // aten::rad2deg.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
5134 | at::Tensor & rad2deg_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
5135 | |
5136 | static auto op = create_rad2deg_out_typed_handle(); |
5137 | return op.redispatch(dispatchKeySet, self, out); |
5138 | } |
5139 | |
5140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scalar_tensor, name, "aten::scalar_tensor" ) |
5141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scalar_tensor, overload_name, "" ) |
5142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scalar_tensor, schema_str, "scalar_tensor(Scalar s, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5143 | |
5144 | // aten::scalar_tensor(Scalar s, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5145 | static C10_NOINLINE c10::TypedOperatorHandle<scalar_tensor::schema> create_scalar_tensor_typed_handle() { |
5146 | return c10::Dispatcher::singleton() |
5147 | .findSchemaOrThrow(scalar_tensor::name, scalar_tensor::overload_name) |
5148 | .typed<scalar_tensor::schema>(); |
5149 | } |
5150 | |
5151 | // aten::scalar_tensor(Scalar s, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5152 | at::Tensor scalar_tensor::call(const at::Scalar & s, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5153 | |
5154 | static auto op = create_scalar_tensor_typed_handle(); |
5155 | return op.call(s, dtype, layout, device, pin_memory); |
5156 | } |
5157 | |
5158 | // aten::scalar_tensor(Scalar s, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5159 | at::Tensor scalar_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & s, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5160 | |
5161 | static auto op = create_scalar_tensor_typed_handle(); |
5162 | return op.redispatch(dispatchKeySet, s, dtype, layout, device, pin_memory); |
5163 | } |
5164 | |
5165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_names, name, "aten::rand" ) |
5166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_names, overload_name, "names" ) |
5167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_names, schema_str, "rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5168 | |
5169 | // aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5170 | static C10_NOINLINE c10::TypedOperatorHandle<rand_names::schema> create_rand_names_typed_handle() { |
5171 | return c10::Dispatcher::singleton() |
5172 | .findSchemaOrThrow(rand_names::name, rand_names::overload_name) |
5173 | .typed<rand_names::schema>(); |
5174 | } |
5175 | |
5176 | // aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5177 | at::Tensor rand_names::call(c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5178 | |
5179 | static auto op = create_rand_names_typed_handle(); |
5180 | return op.call(size, names, dtype, layout, device, pin_memory); |
5181 | } |
5182 | |
5183 | // aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5184 | at::Tensor rand_names::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5185 | |
5186 | static auto op = create_rand_names_typed_handle(); |
5187 | return op.redispatch(dispatchKeySet, size, names, dtype, layout, device, pin_memory); |
5188 | } |
5189 | |
5190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_with_names, name, "aten::rand" ) |
5191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_with_names, overload_name, "generator_with_names" ) |
5192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_with_names, schema_str, "rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5193 | |
5194 | // aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5195 | static C10_NOINLINE c10::TypedOperatorHandle<rand_generator_with_names::schema> create_rand_generator_with_names_typed_handle() { |
5196 | return c10::Dispatcher::singleton() |
5197 | .findSchemaOrThrow(rand_generator_with_names::name, rand_generator_with_names::overload_name) |
5198 | .typed<rand_generator_with_names::schema>(); |
5199 | } |
5200 | |
5201 | // aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5202 | at::Tensor rand_generator_with_names::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5203 | |
5204 | static auto op = create_rand_generator_with_names_typed_handle(); |
5205 | return op.call(size, generator, names, dtype, layout, device, pin_memory); |
5206 | } |
5207 | |
5208 | // aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5209 | at::Tensor rand_generator_with_names::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5210 | |
5211 | static auto op = create_rand_generator_with_names_typed_handle(); |
5212 | return op.redispatch(dispatchKeySet, size, generator, names, dtype, layout, device, pin_memory); |
5213 | } |
5214 | |
5215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand, name, "aten::rand" ) |
5216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand, overload_name, "" ) |
5217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand, schema_str, "rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5218 | |
5219 | // aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5220 | static C10_NOINLINE c10::TypedOperatorHandle<rand::schema> create_rand_typed_handle() { |
5221 | return c10::Dispatcher::singleton() |
5222 | .findSchemaOrThrow(rand::name, rand::overload_name) |
5223 | .typed<rand::schema>(); |
5224 | } |
5225 | |
5226 | // aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5227 | at::Tensor rand::call(c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5228 | |
5229 | static auto op = create_rand_typed_handle(); |
5230 | return op.call(size, dtype, layout, device, pin_memory); |
5231 | } |
5232 | |
5233 | // aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5234 | at::Tensor rand::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5235 | |
5236 | static auto op = create_rand_typed_handle(); |
5237 | return op.redispatch(dispatchKeySet, size, dtype, layout, device, pin_memory); |
5238 | } |
5239 | |
5240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator, name, "aten::rand" ) |
5241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator, overload_name, "generator" ) |
5242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator, schema_str, "rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5243 | |
5244 | // aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5245 | static C10_NOINLINE c10::TypedOperatorHandle<rand_generator::schema> create_rand_generator_typed_handle() { |
5246 | return c10::Dispatcher::singleton() |
5247 | .findSchemaOrThrow(rand_generator::name, rand_generator::overload_name) |
5248 | .typed<rand_generator::schema>(); |
5249 | } |
5250 | |
5251 | // aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5252 | at::Tensor rand_generator::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5253 | |
5254 | static auto op = create_rand_generator_typed_handle(); |
5255 | return op.call(size, generator, dtype, layout, device, pin_memory); |
5256 | } |
5257 | |
5258 | // aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5259 | at::Tensor rand_generator::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5260 | |
5261 | static auto op = create_rand_generator_typed_handle(); |
5262 | return op.redispatch(dispatchKeySet, size, generator, dtype, layout, device, pin_memory); |
5263 | } |
5264 | |
5265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_out, name, "aten::rand" ) |
5266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_out, overload_name, "out" ) |
5267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_out, schema_str, "rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)" ) |
5268 | |
5269 | // aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5270 | static C10_NOINLINE c10::TypedOperatorHandle<rand_out::schema> create_rand_out_typed_handle() { |
5271 | return c10::Dispatcher::singleton() |
5272 | .findSchemaOrThrow(rand_out::name, rand_out::overload_name) |
5273 | .typed<rand_out::schema>(); |
5274 | } |
5275 | |
5276 | // aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5277 | at::Tensor & rand_out::call(c10::SymIntArrayRef size, at::Tensor & out) { |
5278 | |
5279 | static auto op = create_rand_out_typed_handle(); |
5280 | return op.call(size, out); |
5281 | } |
5282 | |
5283 | // aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5284 | at::Tensor & rand_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, at::Tensor & out) { |
5285 | |
5286 | static auto op = create_rand_out_typed_handle(); |
5287 | return op.redispatch(dispatchKeySet, size, out); |
5288 | } |
5289 | |
5290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_out, name, "aten::rand" ) |
5291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_out, overload_name, "generator_out" ) |
5292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_out, schema_str, "rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)" ) |
5293 | |
5294 | // aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5295 | static C10_NOINLINE c10::TypedOperatorHandle<rand_generator_out::schema> create_rand_generator_out_typed_handle() { |
5296 | return c10::Dispatcher::singleton() |
5297 | .findSchemaOrThrow(rand_generator_out::name, rand_generator_out::overload_name) |
5298 | .typed<rand_generator_out::schema>(); |
5299 | } |
5300 | |
5301 | // aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5302 | at::Tensor & rand_generator_out::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
5303 | |
5304 | static auto op = create_rand_generator_out_typed_handle(); |
5305 | return op.call(size, generator, out); |
5306 | } |
5307 | |
5308 | // aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5309 | at::Tensor & rand_generator_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
5310 | |
5311 | static auto op = create_rand_generator_out_typed_handle(); |
5312 | return op.redispatch(dispatchKeySet, size, generator, out); |
5313 | } |
5314 | |
5315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint, name, "aten::randint" ) |
5316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint, overload_name, "" ) |
5317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint, schema_str, "randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5318 | |
5319 | // aten::randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5320 | static C10_NOINLINE c10::TypedOperatorHandle<randint::schema> create_randint_typed_handle() { |
5321 | return c10::Dispatcher::singleton() |
5322 | .findSchemaOrThrow(randint::name, randint::overload_name) |
5323 | .typed<randint::schema>(); |
5324 | } |
5325 | |
5326 | // aten::randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5327 | at::Tensor randint::call(int64_t high, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5328 | |
5329 | static auto op = create_randint_typed_handle(); |
5330 | return op.call(high, size, dtype, layout, device, pin_memory); |
5331 | } |
5332 | |
5333 | // aten::randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5334 | at::Tensor randint::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t high, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5335 | |
5336 | static auto op = create_randint_typed_handle(); |
5337 | return op.redispatch(dispatchKeySet, high, size, dtype, layout, device, pin_memory); |
5338 | } |
5339 | |
5340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_generator, name, "aten::randint" ) |
5341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_generator, overload_name, "generator" ) |
5342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_generator, schema_str, "randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5343 | |
5344 | // aten::randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5345 | static C10_NOINLINE c10::TypedOperatorHandle<randint_generator::schema> create_randint_generator_typed_handle() { |
5346 | return c10::Dispatcher::singleton() |
5347 | .findSchemaOrThrow(randint_generator::name, randint_generator::overload_name) |
5348 | .typed<randint_generator::schema>(); |
5349 | } |
5350 | |
5351 | // aten::randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5352 | at::Tensor randint_generator::call(int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5353 | |
5354 | static auto op = create_randint_generator_typed_handle(); |
5355 | return op.call(high, size, generator, dtype, layout, device, pin_memory); |
5356 | } |
5357 | |
5358 | // aten::randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5359 | at::Tensor randint_generator::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5360 | |
5361 | static auto op = create_randint_generator_typed_handle(); |
5362 | return op.redispatch(dispatchKeySet, high, size, generator, dtype, layout, device, pin_memory); |
5363 | } |
5364 | |
5365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low, name, "aten::randint" ) |
5366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low, overload_name, "low" ) |
5367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low, schema_str, "randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5368 | |
5369 | // aten::randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5370 | static C10_NOINLINE c10::TypedOperatorHandle<randint_low::schema> create_randint_low_typed_handle() { |
5371 | return c10::Dispatcher::singleton() |
5372 | .findSchemaOrThrow(randint_low::name, randint_low::overload_name) |
5373 | .typed<randint_low::schema>(); |
5374 | } |
5375 | |
5376 | // aten::randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5377 | at::Tensor randint_low::call(int64_t low, int64_t high, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5378 | |
5379 | static auto op = create_randint_low_typed_handle(); |
5380 | return op.call(low, high, size, dtype, layout, device, pin_memory); |
5381 | } |
5382 | |
5383 | // aten::randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5384 | at::Tensor randint_low::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t low, int64_t high, c10::SymIntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5385 | |
5386 | static auto op = create_randint_low_typed_handle(); |
5387 | return op.redispatch(dispatchKeySet, low, high, size, dtype, layout, device, pin_memory); |
5388 | } |
5389 | |
5390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_generator, name, "aten::randint" ) |
5391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_generator, overload_name, "low_generator" ) |
5392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_generator, schema_str, "randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
5393 | |
5394 | // aten::randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5395 | static C10_NOINLINE c10::TypedOperatorHandle<randint_low_generator::schema> create_randint_low_generator_typed_handle() { |
5396 | return c10::Dispatcher::singleton() |
5397 | .findSchemaOrThrow(randint_low_generator::name, randint_low_generator::overload_name) |
5398 | .typed<randint_low_generator::schema>(); |
5399 | } |
5400 | |
5401 | // aten::randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5402 | at::Tensor randint_low_generator::call(int64_t low, int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5403 | |
5404 | static auto op = create_randint_low_generator_typed_handle(); |
5405 | return op.call(low, high, size, generator, dtype, layout, device, pin_memory); |
5406 | } |
5407 | |
5408 | // aten::randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
5409 | at::Tensor randint_low_generator::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t low, int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
5410 | |
5411 | static auto op = create_randint_low_generator_typed_handle(); |
5412 | return op.redispatch(dispatchKeySet, low, high, size, generator, dtype, layout, device, pin_memory); |
5413 | } |
5414 | |
5415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_out, name, "aten::randint" ) |
5416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_out, overload_name, "out" ) |
5417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_out, schema_str, "randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)" ) |
5418 | |
5419 | // aten::randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5420 | static C10_NOINLINE c10::TypedOperatorHandle<randint_out::schema> create_randint_out_typed_handle() { |
5421 | return c10::Dispatcher::singleton() |
5422 | .findSchemaOrThrow(randint_out::name, randint_out::overload_name) |
5423 | .typed<randint_out::schema>(); |
5424 | } |
5425 | |
5426 | // aten::randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5427 | at::Tensor & randint_out::call(int64_t high, c10::SymIntArrayRef size, at::Tensor & out) { |
5428 | |
5429 | static auto op = create_randint_out_typed_handle(); |
5430 | return op.call(high, size, out); |
5431 | } |
5432 | |
5433 | // aten::randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5434 | at::Tensor & randint_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t high, c10::SymIntArrayRef size, at::Tensor & out) { |
5435 | |
5436 | static auto op = create_randint_out_typed_handle(); |
5437 | return op.redispatch(dispatchKeySet, high, size, out); |
5438 | } |
5439 | |
5440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_generator_out, name, "aten::randint" ) |
5441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_generator_out, overload_name, "generator_out" ) |
5442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_generator_out, schema_str, "randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)" ) |
5443 | |
5444 | // aten::randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5445 | static C10_NOINLINE c10::TypedOperatorHandle<randint_generator_out::schema> create_randint_generator_out_typed_handle() { |
5446 | return c10::Dispatcher::singleton() |
5447 | .findSchemaOrThrow(randint_generator_out::name, randint_generator_out::overload_name) |
5448 | .typed<randint_generator_out::schema>(); |
5449 | } |
5450 | |
5451 | // aten::randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5452 | at::Tensor & randint_generator_out::call(int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
5453 | |
5454 | static auto op = create_randint_generator_out_typed_handle(); |
5455 | return op.call(high, size, generator, out); |
5456 | } |
5457 | |
5458 | // aten::randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5459 | at::Tensor & randint_generator_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
5460 | |
5461 | static auto op = create_randint_generator_out_typed_handle(); |
5462 | return op.redispatch(dispatchKeySet, high, size, generator, out); |
5463 | } |
5464 | |
5465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_out, name, "aten::randint" ) |
5466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_out, overload_name, "low_out" ) |
5467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_out, schema_str, "randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)" ) |
5468 | |
5469 | // aten::randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5470 | static C10_NOINLINE c10::TypedOperatorHandle<randint_low_out::schema> create_randint_low_out_typed_handle() { |
5471 | return c10::Dispatcher::singleton() |
5472 | .findSchemaOrThrow(randint_low_out::name, randint_low_out::overload_name) |
5473 | .typed<randint_low_out::schema>(); |
5474 | } |
5475 | |
5476 | // aten::randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5477 | at::Tensor & randint_low_out::call(int64_t low, int64_t high, c10::SymIntArrayRef size, at::Tensor & out) { |
5478 | |
5479 | static auto op = create_randint_low_out_typed_handle(); |
5480 | return op.call(low, high, size, out); |
5481 | } |
5482 | |
5483 | // aten::randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
5484 | at::Tensor & randint_low_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t low, int64_t high, c10::SymIntArrayRef size, at::Tensor & out) { |
5485 | |
5486 | static auto op = create_randint_low_out_typed_handle(); |
5487 | return op.redispatch(dispatchKeySet, low, high, size, out); |
5488 | } |
5489 | |
5490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_generator_out, name, "aten::randint" ) |
5491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_generator_out, overload_name, "low_generator_out" ) |
5492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randint_low_generator_out, schema_str, "randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!)" ) |
5493 | |
5494 | // aten::randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5495 | static C10_NOINLINE c10::TypedOperatorHandle<randint_low_generator_out::schema> create_randint_low_generator_out_typed_handle() { |
5496 | return c10::Dispatcher::singleton() |
5497 | .findSchemaOrThrow(randint_low_generator_out::name, randint_low_generator_out::overload_name) |
5498 | .typed<randint_low_generator_out::schema>(); |
5499 | } |
5500 | |
5501 | // aten::randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5502 | at::Tensor & randint_low_generator_out::call(int64_t low, int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
5503 | |
5504 | static auto op = create_randint_low_generator_out_typed_handle(); |
5505 | return op.call(low, high, size, generator, out); |
5506 | } |
5507 | |
5508 | // aten::randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) |
5509 | at::Tensor & randint_low_generator_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t low, int64_t high, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, at::Tensor & out) { |
5510 | |
5511 | static auto op = create_randint_low_generator_out_typed_handle(); |
5512 | return op.redispatch(dispatchKeySet, low, high, size, generator, out); |
5513 | } |
5514 | |
5515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_like, name, "aten::randn_like" ) |
5516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_like, overload_name, "" ) |
5517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_like, schema_str, "randn_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor" ) |
5518 | |
5519 | // aten::randn_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
5520 | static C10_NOINLINE c10::TypedOperatorHandle<randn_like::schema> create_randn_like_typed_handle() { |
5521 | return c10::Dispatcher::singleton() |
5522 | .findSchemaOrThrow(randn_like::name, randn_like::overload_name) |
5523 | .typed<randn_like::schema>(); |
5524 | } |
5525 | |
5526 | // aten::randn_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
5527 | at::Tensor randn_like::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
5528 | |
5529 | static auto op = create_randn_like_typed_handle(); |
5530 | return op.call(self, dtype, layout, device, pin_memory, memory_format); |
5531 | } |
5532 | |
5533 | // aten::randn_like(Tensor self, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor |
5534 | at::Tensor randn_like::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, c10::optional<at::MemoryFormat> memory_format) { |
5535 | |
5536 | static auto op = create_randn_like_typed_handle(); |
5537 | return op.redispatch(dispatchKeySet, self, dtype, layout, device, pin_memory, memory_format); |
5538 | } |
5539 | |
5540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat, name, "aten::repeat" ) |
5541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat, overload_name, "" ) |
5542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat, schema_str, "repeat(Tensor self, SymInt[] repeats) -> Tensor" ) |
5543 | |
5544 | // aten::repeat(Tensor self, SymInt[] repeats) -> Tensor |
5545 | static C10_NOINLINE c10::TypedOperatorHandle<repeat::schema> create_repeat_typed_handle() { |
5546 | return c10::Dispatcher::singleton() |
5547 | .findSchemaOrThrow(repeat::name, repeat::overload_name) |
5548 | .typed<repeat::schema>(); |
5549 | } |
5550 | |
5551 | // aten::repeat(Tensor self, SymInt[] repeats) -> Tensor |
5552 | at::Tensor repeat::call(const at::Tensor & self, c10::SymIntArrayRef repeats) { |
5553 | |
5554 | static auto op = create_repeat_typed_handle(); |
5555 | return op.call(self, repeats); |
5556 | } |
5557 | |
5558 | // aten::repeat(Tensor self, SymInt[] repeats) -> Tensor |
5559 | at::Tensor repeat::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef repeats) { |
5560 | |
5561 | static auto op = create_repeat_typed_handle(); |
5562 | return op.redispatch(dispatchKeySet, self, repeats); |
5563 | } |
5564 | |
5565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_Tensor, name, "aten::repeat_interleave" ) |
5566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_Tensor, overload_name, "Tensor" ) |
5567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_Tensor, schema_str, "repeat_interleave.Tensor(Tensor repeats, *, int? output_size=None) -> Tensor" ) |
5568 | |
5569 | // aten::repeat_interleave.Tensor(Tensor repeats, *, int? output_size=None) -> Tensor |
5570 | static C10_NOINLINE c10::TypedOperatorHandle<repeat_interleave_Tensor::schema> create_repeat_interleave_Tensor_typed_handle() { |
5571 | return c10::Dispatcher::singleton() |
5572 | .findSchemaOrThrow(repeat_interleave_Tensor::name, repeat_interleave_Tensor::overload_name) |
5573 | .typed<repeat_interleave_Tensor::schema>(); |
5574 | } |
5575 | |
5576 | // aten::repeat_interleave.Tensor(Tensor repeats, *, int? output_size=None) -> Tensor |
5577 | at::Tensor repeat_interleave_Tensor::call(const at::Tensor & repeats, c10::optional<int64_t> output_size) { |
5578 | |
5579 | static auto op = create_repeat_interleave_Tensor_typed_handle(); |
5580 | return op.call(repeats, output_size); |
5581 | } |
5582 | |
5583 | // aten::repeat_interleave.Tensor(Tensor repeats, *, int? output_size=None) -> Tensor |
5584 | at::Tensor repeat_interleave_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & repeats, c10::optional<int64_t> output_size) { |
5585 | |
5586 | static auto op = create_repeat_interleave_Tensor_typed_handle(); |
5587 | return op.redispatch(dispatchKeySet, repeats, output_size); |
5588 | } |
5589 | |
5590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_self_Tensor, name, "aten::repeat_interleave" ) |
5591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_self_Tensor, overload_name, "self_Tensor" ) |
5592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_self_Tensor, schema_str, "repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, int? output_size=None) -> Tensor" ) |
5593 | |
5594 | // aten::repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, int? output_size=None) -> Tensor |
5595 | static C10_NOINLINE c10::TypedOperatorHandle<repeat_interleave_self_Tensor::schema> create_repeat_interleave_self_Tensor_typed_handle() { |
5596 | return c10::Dispatcher::singleton() |
5597 | .findSchemaOrThrow(repeat_interleave_self_Tensor::name, repeat_interleave_self_Tensor::overload_name) |
5598 | .typed<repeat_interleave_self_Tensor::schema>(); |
5599 | } |
5600 | |
5601 | // aten::repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, int? output_size=None) -> Tensor |
5602 | at::Tensor repeat_interleave_self_Tensor::call(const at::Tensor & self, const at::Tensor & repeats, c10::optional<int64_t> dim, c10::optional<int64_t> output_size) { |
5603 | |
5604 | static auto op = create_repeat_interleave_self_Tensor_typed_handle(); |
5605 | return op.call(self, repeats, dim, output_size); |
5606 | } |
5607 | |
5608 | // aten::repeat_interleave.self_Tensor(Tensor self, Tensor repeats, int? dim=None, *, int? output_size=None) -> Tensor |
5609 | at::Tensor repeat_interleave_self_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & repeats, c10::optional<int64_t> dim, c10::optional<int64_t> output_size) { |
5610 | |
5611 | static auto op = create_repeat_interleave_self_Tensor_typed_handle(); |
5612 | return op.redispatch(dispatchKeySet, self, repeats, dim, output_size); |
5613 | } |
5614 | |
5615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_self_int, name, "aten::repeat_interleave" ) |
5616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_self_int, overload_name, "self_int" ) |
5617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_self_int, schema_str, "repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor" ) |
5618 | |
5619 | // aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor |
5620 | static C10_NOINLINE c10::TypedOperatorHandle<repeat_interleave_self_int::schema> create_repeat_interleave_self_int_typed_handle() { |
5621 | return c10::Dispatcher::singleton() |
5622 | .findSchemaOrThrow(repeat_interleave_self_int::name, repeat_interleave_self_int::overload_name) |
5623 | .typed<repeat_interleave_self_int::schema>(); |
5624 | } |
5625 | |
5626 | // aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor |
5627 | at::Tensor repeat_interleave_self_int::call(const at::Tensor & self, c10::SymInt repeats, c10::optional<int64_t> dim, c10::optional<int64_t> output_size) { |
5628 | |
5629 | static auto op = create_repeat_interleave_self_int_typed_handle(); |
5630 | return op.call(self, repeats, dim, output_size); |
5631 | } |
5632 | |
5633 | // aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor |
5634 | at::Tensor repeat_interleave_self_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymInt repeats, c10::optional<int64_t> dim, c10::optional<int64_t> output_size) { |
5635 | |
5636 | static auto op = create_repeat_interleave_self_int_typed_handle(); |
5637 | return op.redispatch(dispatchKeySet, self, repeats, dim, output_size); |
5638 | } |
5639 | |
5640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mkldnn_reshape, name, "aten::_mkldnn_reshape" ) |
5641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mkldnn_reshape, overload_name, "" ) |
5642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mkldnn_reshape, schema_str, "_mkldnn_reshape(Tensor self, int[] shape) -> Tensor" ) |
5643 | |
5644 | // aten::_mkldnn_reshape(Tensor self, int[] shape) -> Tensor |
5645 | static C10_NOINLINE c10::TypedOperatorHandle<_mkldnn_reshape::schema> create__mkldnn_reshape_typed_handle() { |
5646 | return c10::Dispatcher::singleton() |
5647 | .findSchemaOrThrow(_mkldnn_reshape::name, _mkldnn_reshape::overload_name) |
5648 | .typed<_mkldnn_reshape::schema>(); |
5649 | } |
5650 | |
5651 | // aten::_mkldnn_reshape(Tensor self, int[] shape) -> Tensor |
5652 | at::Tensor _mkldnn_reshape::call(const at::Tensor & self, at::IntArrayRef shape) { |
5653 | |
5654 | static auto op = create__mkldnn_reshape_typed_handle(); |
5655 | return op.call(self, shape); |
5656 | } |
5657 | |
5658 | // aten::_mkldnn_reshape(Tensor self, int[] shape) -> Tensor |
5659 | at::Tensor _mkldnn_reshape::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef shape) { |
5660 | |
5661 | static auto op = create__mkldnn_reshape_typed_handle(); |
5662 | return op.redispatch(dispatchKeySet, self, shape); |
5663 | } |
5664 | |
5665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_prelu_kernel, name, "aten::_prelu_kernel" ) |
5666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_prelu_kernel, overload_name, "" ) |
5667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_prelu_kernel, schema_str, "_prelu_kernel(Tensor self, Tensor weight) -> Tensor" ) |
5668 | |
5669 | // aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor |
5670 | static C10_NOINLINE c10::TypedOperatorHandle<_prelu_kernel::schema> create__prelu_kernel_typed_handle() { |
5671 | return c10::Dispatcher::singleton() |
5672 | .findSchemaOrThrow(_prelu_kernel::name, _prelu_kernel::overload_name) |
5673 | .typed<_prelu_kernel::schema>(); |
5674 | } |
5675 | |
5676 | // aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor |
5677 | at::Tensor _prelu_kernel::call(const at::Tensor & self, const at::Tensor & weight) { |
5678 | |
5679 | static auto op = create__prelu_kernel_typed_handle(); |
5680 | return op.call(self, weight); |
5681 | } |
5682 | |
5683 | // aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor |
5684 | at::Tensor _prelu_kernel::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight) { |
5685 | |
5686 | static auto op = create__prelu_kernel_typed_handle(); |
5687 | return op.redispatch(dispatchKeySet, self, weight); |
5688 | } |
5689 | |
5690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt, name, "aten::rsqrt" ) |
5691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt, overload_name, "" ) |
5692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt, schema_str, "rsqrt(Tensor self) -> Tensor" ) |
5693 | |
5694 | // aten::rsqrt(Tensor self) -> Tensor |
5695 | static C10_NOINLINE c10::TypedOperatorHandle<rsqrt::schema> create_rsqrt_typed_handle() { |
5696 | return c10::Dispatcher::singleton() |
5697 | .findSchemaOrThrow(rsqrt::name, rsqrt::overload_name) |
5698 | .typed<rsqrt::schema>(); |
5699 | } |
5700 | |
5701 | // aten::rsqrt(Tensor self) -> Tensor |
5702 | at::Tensor rsqrt::call(const at::Tensor & self) { |
5703 | |
5704 | static auto op = create_rsqrt_typed_handle(); |
5705 | return op.call(self); |
5706 | } |
5707 | |
5708 | // aten::rsqrt(Tensor self) -> Tensor |
5709 | at::Tensor rsqrt::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
5710 | |
5711 | static auto op = create_rsqrt_typed_handle(); |
5712 | return op.redispatch(dispatchKeySet, self); |
5713 | } |
5714 | |
5715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt_, name, "aten::rsqrt_" ) |
5716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt_, overload_name, "" ) |
5717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt_, schema_str, "rsqrt_(Tensor(a!) self) -> Tensor(a!)" ) |
5718 | |
5719 | // aten::rsqrt_(Tensor(a!) self) -> Tensor(a!) |
5720 | static C10_NOINLINE c10::TypedOperatorHandle<rsqrt_::schema> create_rsqrt__typed_handle() { |
5721 | return c10::Dispatcher::singleton() |
5722 | .findSchemaOrThrow(rsqrt_::name, rsqrt_::overload_name) |
5723 | .typed<rsqrt_::schema>(); |
5724 | } |
5725 | |
5726 | // aten::rsqrt_(Tensor(a!) self) -> Tensor(a!) |
5727 | at::Tensor & rsqrt_::call(at::Tensor & self) { |
5728 | |
5729 | static auto op = create_rsqrt__typed_handle(); |
5730 | return op.call(self); |
5731 | } |
5732 | |
5733 | // aten::rsqrt_(Tensor(a!) self) -> Tensor(a!) |
5734 | at::Tensor & rsqrt_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
5735 | |
5736 | static auto op = create_rsqrt__typed_handle(); |
5737 | return op.redispatch(dispatchKeySet, self); |
5738 | } |
5739 | |
5740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt_out, name, "aten::rsqrt" ) |
5741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt_out, overload_name, "out" ) |
5742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rsqrt_out, schema_str, "rsqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
5743 | |
5744 | // aten::rsqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
5745 | static C10_NOINLINE c10::TypedOperatorHandle<rsqrt_out::schema> create_rsqrt_out_typed_handle() { |
5746 | return c10::Dispatcher::singleton() |
5747 | .findSchemaOrThrow(rsqrt_out::name, rsqrt_out::overload_name) |
5748 | .typed<rsqrt_out::schema>(); |
5749 | } |
5750 | |
5751 | // aten::rsqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
5752 | at::Tensor & rsqrt_out::call(const at::Tensor & self, at::Tensor & out) { |
5753 | |
5754 | static auto op = create_rsqrt_out_typed_handle(); |
5755 | return op.call(self, out); |
5756 | } |
5757 | |
5758 | // aten::rsqrt.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
5759 | at::Tensor & rsqrt_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
5760 | |
5761 | static auto op = create_rsqrt_out_typed_handle(); |
5762 | return op.redispatch(dispatchKeySet, self, out); |
5763 | } |
5764 | |
5765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_select_backward, name, "aten::_nested_select_backward" ) |
5766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_select_backward, overload_name, "" ) |
5767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_select_backward, schema_str, "_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor" ) |
5768 | |
5769 | // aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor |
5770 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_select_backward::schema> create__nested_select_backward_typed_handle() { |
5771 | return c10::Dispatcher::singleton() |
5772 | .findSchemaOrThrow(_nested_select_backward::name, _nested_select_backward::overload_name) |
5773 | .typed<_nested_select_backward::schema>(); |
5774 | } |
5775 | |
5776 | // aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor |
5777 | at::Tensor _nested_select_backward::call(const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, c10::SymInt index) { |
5778 | |
5779 | static auto op = create__nested_select_backward_typed_handle(); |
5780 | return op.call(grad_output, self, dim, index); |
5781 | } |
5782 | |
5783 | // aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor |
5784 | at::Tensor _nested_select_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, int64_t dim, c10::SymInt index) { |
5785 | |
5786 | static auto op = create__nested_select_backward_typed_handle(); |
5787 | return op.redispatch(dispatchKeySet, grad_output, self, dim, index); |
5788 | } |
5789 | |
5790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vsplit_int, name, "aten::vsplit" ) |
5791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vsplit_int, overload_name, "int" ) |
5792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vsplit_int, schema_str, "vsplit.int(Tensor(a -> *) self, int sections) -> Tensor(a)[]" ) |
5793 | |
5794 | // aten::vsplit.int(Tensor(a -> *) self, int sections) -> Tensor(a)[] |
5795 | static C10_NOINLINE c10::TypedOperatorHandle<vsplit_int::schema> create_vsplit_int_typed_handle() { |
5796 | return c10::Dispatcher::singleton() |
5797 | .findSchemaOrThrow(vsplit_int::name, vsplit_int::overload_name) |
5798 | .typed<vsplit_int::schema>(); |
5799 | } |
5800 | |
5801 | // aten::vsplit.int(Tensor(a -> *) self, int sections) -> Tensor(a)[] |
5802 | ::std::vector<at::Tensor> vsplit_int::call(const at::Tensor & self, int64_t sections) { |
5803 | |
5804 | static auto op = create_vsplit_int_typed_handle(); |
5805 | return op.call(self, sections); |
5806 | } |
5807 | |
5808 | // aten::vsplit.int(Tensor(a -> *) self, int sections) -> Tensor(a)[] |
5809 | ::std::vector<at::Tensor> vsplit_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t sections) { |
5810 | |
5811 | static auto op = create_vsplit_int_typed_handle(); |
5812 | return op.redispatch(dispatchKeySet, self, sections); |
5813 | } |
5814 | |
5815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vsplit_array, name, "aten::vsplit" ) |
5816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vsplit_array, overload_name, "array" ) |
5817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(vsplit_array, schema_str, "vsplit.array(Tensor(a -> *) self, int[] indices) -> Tensor(a)[]" ) |
5818 | |
5819 | // aten::vsplit.array(Tensor(a -> *) self, int[] indices) -> Tensor(a)[] |
5820 | static C10_NOINLINE c10::TypedOperatorHandle<vsplit_array::schema> create_vsplit_array_typed_handle() { |
5821 | return c10::Dispatcher::singleton() |
5822 | .findSchemaOrThrow(vsplit_array::name, vsplit_array::overload_name) |
5823 | .typed<vsplit_array::schema>(); |
5824 | } |
5825 | |
5826 | // aten::vsplit.array(Tensor(a -> *) self, int[] indices) -> Tensor(a)[] |
5827 | ::std::vector<at::Tensor> vsplit_array::call(const at::Tensor & self, at::IntArrayRef indices) { |
5828 | |
5829 | static auto op = create_vsplit_array_typed_handle(); |
5830 | return op.call(self, indices); |
5831 | } |
5832 | |
5833 | // aten::vsplit.array(Tensor(a -> *) self, int[] indices) -> Tensor(a)[] |
5834 | ::std::vector<at::Tensor> vsplit_array::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef indices) { |
5835 | |
5836 | static auto op = create_vsplit_array_typed_handle(); |
5837 | return op.redispatch(dispatchKeySet, self, indices); |
5838 | } |
5839 | |
5840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hstack, name, "aten::hstack" ) |
5841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hstack, overload_name, "" ) |
5842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hstack, schema_str, "hstack(Tensor[] tensors) -> Tensor" ) |
5843 | |
5844 | // aten::hstack(Tensor[] tensors) -> Tensor |
5845 | static C10_NOINLINE c10::TypedOperatorHandle<hstack::schema> create_hstack_typed_handle() { |
5846 | return c10::Dispatcher::singleton() |
5847 | .findSchemaOrThrow(hstack::name, hstack::overload_name) |
5848 | .typed<hstack::schema>(); |
5849 | } |
5850 | |
5851 | // aten::hstack(Tensor[] tensors) -> Tensor |
5852 | at::Tensor hstack::call(at::TensorList tensors) { |
5853 | |
5854 | static auto op = create_hstack_typed_handle(); |
5855 | return op.call(tensors); |
5856 | } |
5857 | |
5858 | // aten::hstack(Tensor[] tensors) -> Tensor |
5859 | at::Tensor hstack::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
5860 | |
5861 | static auto op = create_hstack_typed_handle(); |
5862 | return op.redispatch(dispatchKeySet, tensors); |
5863 | } |
5864 | |
5865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hstack_out, name, "aten::hstack" ) |
5866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hstack_out, overload_name, "out" ) |
5867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hstack_out, schema_str, "hstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)" ) |
5868 | |
5869 | // aten::hstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
5870 | static C10_NOINLINE c10::TypedOperatorHandle<hstack_out::schema> create_hstack_out_typed_handle() { |
5871 | return c10::Dispatcher::singleton() |
5872 | .findSchemaOrThrow(hstack_out::name, hstack_out::overload_name) |
5873 | .typed<hstack_out::schema>(); |
5874 | } |
5875 | |
5876 | // aten::hstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
5877 | at::Tensor & hstack_out::call(at::TensorList tensors, at::Tensor & out) { |
5878 | |
5879 | static auto op = create_hstack_out_typed_handle(); |
5880 | return op.call(tensors, out); |
5881 | } |
5882 | |
5883 | // aten::hstack.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
5884 | at::Tensor & hstack_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out) { |
5885 | |
5886 | static auto op = create_hstack_out_typed_handle(); |
5887 | return op.redispatch(dispatchKeySet, tensors, out); |
5888 | } |
5889 | |
5890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(istft, name, "aten::istft" ) |
5891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(istft, overload_name, "" ) |
5892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(istft, schema_str, "istft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, bool normalized=False, bool? onesided=None, int? length=None, bool return_complex=False) -> Tensor" ) |
5893 | |
5894 | // aten::istft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, bool normalized=False, bool? onesided=None, int? length=None, bool return_complex=False) -> Tensor |
5895 | static C10_NOINLINE c10::TypedOperatorHandle<istft::schema> create_istft_typed_handle() { |
5896 | return c10::Dispatcher::singleton() |
5897 | .findSchemaOrThrow(istft::name, istft::overload_name) |
5898 | .typed<istft::schema>(); |
5899 | } |
5900 | |
5901 | // aten::istft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, bool normalized=False, bool? onesided=None, int? length=None, bool return_complex=False) -> Tensor |
5902 | at::Tensor istft::call(const at::Tensor & self, int64_t n_fft, c10::optional<int64_t> hop_length, c10::optional<int64_t> win_length, const c10::optional<at::Tensor> & window, bool center, bool normalized, c10::optional<bool> onesided, c10::optional<int64_t> length, bool return_complex) { |
5903 | |
5904 | static auto op = create_istft_typed_handle(); |
5905 | return op.call(self, n_fft, hop_length, win_length, window, center, normalized, onesided, length, return_complex); |
5906 | } |
5907 | |
5908 | // aten::istft(Tensor self, int n_fft, int? hop_length=None, int? win_length=None, Tensor? window=None, bool center=True, bool normalized=False, bool? onesided=None, int? length=None, bool return_complex=False) -> Tensor |
5909 | at::Tensor istft::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t n_fft, c10::optional<int64_t> hop_length, c10::optional<int64_t> win_length, const c10::optional<at::Tensor> & window, bool center, bool normalized, c10::optional<bool> onesided, c10::optional<int64_t> length, bool return_complex) { |
5910 | |
5911 | static auto op = create_istft_typed_handle(); |
5912 | return op.redispatch(dispatchKeySet, self, n_fft, hop_length, win_length, window, center, normalized, onesided, length, return_complex); |
5913 | } |
5914 | |
5915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum, name, "aten::sum" ) |
5916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum, overload_name, "" ) |
5917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum, schema_str, "sum(Tensor self, *, ScalarType? dtype=None) -> Tensor" ) |
5918 | |
5919 | // aten::sum(Tensor self, *, ScalarType? dtype=None) -> Tensor |
5920 | static C10_NOINLINE c10::TypedOperatorHandle<sum::schema> create_sum_typed_handle() { |
5921 | return c10::Dispatcher::singleton() |
5922 | .findSchemaOrThrow(sum::name, sum::overload_name) |
5923 | .typed<sum::schema>(); |
5924 | } |
5925 | |
5926 | // aten::sum(Tensor self, *, ScalarType? dtype=None) -> Tensor |
5927 | at::Tensor sum::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
5928 | |
5929 | static auto op = create_sum_typed_handle(); |
5930 | return op.call(self, dtype); |
5931 | } |
5932 | |
5933 | // aten::sum(Tensor self, *, ScalarType? dtype=None) -> Tensor |
5934 | at::Tensor sum::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
5935 | |
5936 | static auto op = create_sum_typed_handle(); |
5937 | return op.redispatch(dispatchKeySet, self, dtype); |
5938 | } |
5939 | |
5940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_dim_IntList, name, "aten::sum" ) |
5941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_dim_IntList, overload_name, "dim_IntList" ) |
5942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_dim_IntList, schema_str, "sum.dim_IntList(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor" ) |
5943 | |
5944 | // aten::sum.dim_IntList(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
5945 | static C10_NOINLINE c10::TypedOperatorHandle<sum_dim_IntList::schema> create_sum_dim_IntList_typed_handle() { |
5946 | return c10::Dispatcher::singleton() |
5947 | .findSchemaOrThrow(sum_dim_IntList::name, sum_dim_IntList::overload_name) |
5948 | .typed<sum_dim_IntList::schema>(); |
5949 | } |
5950 | |
5951 | // aten::sum.dim_IntList(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
5952 | at::Tensor sum_dim_IntList::call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
5953 | |
5954 | static auto op = create_sum_dim_IntList_typed_handle(); |
5955 | return op.call(self, dim, keepdim, dtype); |
5956 | } |
5957 | |
5958 | // aten::sum.dim_IntList(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
5959 | at::Tensor sum_dim_IntList::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
5960 | |
5961 | static auto op = create_sum_dim_IntList_typed_handle(); |
5962 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype); |
5963 | } |
5964 | |
5965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_dim_DimnameList, name, "aten::sum" ) |
5966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_dim_DimnameList, overload_name, "dim_DimnameList" ) |
5967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_dim_DimnameList, schema_str, "sum.dim_DimnameList(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor" ) |
5968 | |
5969 | // aten::sum.dim_DimnameList(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
5970 | static C10_NOINLINE c10::TypedOperatorHandle<sum_dim_DimnameList::schema> create_sum_dim_DimnameList_typed_handle() { |
5971 | return c10::Dispatcher::singleton() |
5972 | .findSchemaOrThrow(sum_dim_DimnameList::name, sum_dim_DimnameList::overload_name) |
5973 | .typed<sum_dim_DimnameList::schema>(); |
5974 | } |
5975 | |
5976 | // aten::sum.dim_DimnameList(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
5977 | at::Tensor sum_dim_DimnameList::call(const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
5978 | |
5979 | static auto op = create_sum_dim_DimnameList_typed_handle(); |
5980 | return op.call(self, dim, keepdim, dtype); |
5981 | } |
5982 | |
5983 | // aten::sum.dim_DimnameList(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
5984 | at::Tensor sum_dim_DimnameList::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
5985 | |
5986 | static auto op = create_sum_dim_DimnameList_typed_handle(); |
5987 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype); |
5988 | } |
5989 | |
5990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_IntList_out, name, "aten::sum" ) |
5991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_IntList_out, overload_name, "IntList_out" ) |
5992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_IntList_out, schema_str, "sum.IntList_out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)" ) |
5993 | |
5994 | // aten::sum.IntList_out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
5995 | static C10_NOINLINE c10::TypedOperatorHandle<sum_IntList_out::schema> create_sum_IntList_out_typed_handle() { |
5996 | return c10::Dispatcher::singleton() |
5997 | .findSchemaOrThrow(sum_IntList_out::name, sum_IntList_out::overload_name) |
5998 | .typed<sum_IntList_out::schema>(); |
5999 | } |
6000 | |
6001 | // aten::sum.IntList_out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6002 | at::Tensor & sum_IntList_out::call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
6003 | |
6004 | static auto op = create_sum_IntList_out_typed_handle(); |
6005 | return op.call(self, dim, keepdim, dtype, out); |
6006 | } |
6007 | |
6008 | // aten::sum.IntList_out(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6009 | at::Tensor & sum_IntList_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
6010 | |
6011 | static auto op = create_sum_IntList_out_typed_handle(); |
6012 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype, out); |
6013 | } |
6014 | |
6015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_DimnameList_out, name, "aten::sum" ) |
6016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_DimnameList_out, overload_name, "DimnameList_out" ) |
6017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_DimnameList_out, schema_str, "sum.DimnameList_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)" ) |
6018 | |
6019 | // aten::sum.DimnameList_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6020 | static C10_NOINLINE c10::TypedOperatorHandle<sum_DimnameList_out::schema> create_sum_DimnameList_out_typed_handle() { |
6021 | return c10::Dispatcher::singleton() |
6022 | .findSchemaOrThrow(sum_DimnameList_out::name, sum_DimnameList_out::overload_name) |
6023 | .typed<sum_DimnameList_out::schema>(); |
6024 | } |
6025 | |
6026 | // aten::sum.DimnameList_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6027 | at::Tensor & sum_DimnameList_out::call(const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
6028 | |
6029 | static auto op = create_sum_DimnameList_out_typed_handle(); |
6030 | return op.call(self, dim, keepdim, dtype, out); |
6031 | } |
6032 | |
6033 | // aten::sum.DimnameList_out(Tensor self, Dimname[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6034 | at::Tensor & sum_DimnameList_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
6035 | |
6036 | static auto op = create_sum_DimnameList_out_typed_handle(); |
6037 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype, out); |
6038 | } |
6039 | |
6040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nansum, name, "aten::nansum" ) |
6041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nansum, overload_name, "" ) |
6042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nansum, schema_str, "nansum(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor" ) |
6043 | |
6044 | // aten::nansum(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
6045 | static C10_NOINLINE c10::TypedOperatorHandle<nansum::schema> create_nansum_typed_handle() { |
6046 | return c10::Dispatcher::singleton() |
6047 | .findSchemaOrThrow(nansum::name, nansum::overload_name) |
6048 | .typed<nansum::schema>(); |
6049 | } |
6050 | |
6051 | // aten::nansum(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
6052 | at::Tensor nansum::call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
6053 | |
6054 | static auto op = create_nansum_typed_handle(); |
6055 | return op.call(self, dim, keepdim, dtype); |
6056 | } |
6057 | |
6058 | // aten::nansum(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
6059 | at::Tensor nansum::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
6060 | |
6061 | static auto op = create_nansum_typed_handle(); |
6062 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype); |
6063 | } |
6064 | |
6065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nansum_out, name, "aten::nansum" ) |
6066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nansum_out, overload_name, "out" ) |
6067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nansum_out, schema_str, "nansum.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)" ) |
6068 | |
6069 | // aten::nansum.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6070 | static C10_NOINLINE c10::TypedOperatorHandle<nansum_out::schema> create_nansum_out_typed_handle() { |
6071 | return c10::Dispatcher::singleton() |
6072 | .findSchemaOrThrow(nansum_out::name, nansum_out::overload_name) |
6073 | .typed<nansum_out::schema>(); |
6074 | } |
6075 | |
6076 | // aten::nansum.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6077 | at::Tensor & nansum_out::call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
6078 | |
6079 | static auto op = create_nansum_out_typed_handle(); |
6080 | return op.call(self, dim, keepdim, dtype, out); |
6081 | } |
6082 | |
6083 | // aten::nansum.out(Tensor self, int[1]? dim=None, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
6084 | at::Tensor & nansum_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
6085 | |
6086 | static auto op = create_nansum_out_typed_handle(); |
6087 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype, out); |
6088 | } |
6089 | |
6090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(flipud, name, "aten::flipud" ) |
6091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(flipud, overload_name, "" ) |
6092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(flipud, schema_str, "flipud(Tensor self) -> Tensor" ) |
6093 | |
6094 | // aten::flipud(Tensor self) -> Tensor |
6095 | static C10_NOINLINE c10::TypedOperatorHandle<flipud::schema> create_flipud_typed_handle() { |
6096 | return c10::Dispatcher::singleton() |
6097 | .findSchemaOrThrow(flipud::name, flipud::overload_name) |
6098 | .typed<flipud::schema>(); |
6099 | } |
6100 | |
6101 | // aten::flipud(Tensor self) -> Tensor |
6102 | at::Tensor flipud::call(const at::Tensor & self) { |
6103 | |
6104 | static auto op = create_flipud_typed_handle(); |
6105 | return op.call(self); |
6106 | } |
6107 | |
6108 | // aten::flipud(Tensor self) -> Tensor |
6109 | at::Tensor flipud::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
6110 | |
6111 | static auto op = create_flipud_typed_handle(); |
6112 | return op.redispatch(dispatchKeySet, self); |
6113 | } |
6114 | |
6115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rot90, name, "aten::rot90" ) |
6116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rot90, overload_name, "" ) |
6117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rot90, schema_str, "rot90(Tensor self, int k=1, int[] dims=[0,1]) -> Tensor" ) |
6118 | |
6119 | // aten::rot90(Tensor self, int k=1, int[] dims=[0,1]) -> Tensor |
6120 | static C10_NOINLINE c10::TypedOperatorHandle<rot90::schema> create_rot90_typed_handle() { |
6121 | return c10::Dispatcher::singleton() |
6122 | .findSchemaOrThrow(rot90::name, rot90::overload_name) |
6123 | .typed<rot90::schema>(); |
6124 | } |
6125 | |
6126 | // aten::rot90(Tensor self, int k=1, int[] dims=[0,1]) -> Tensor |
6127 | at::Tensor rot90::call(const at::Tensor & self, int64_t k, at::IntArrayRef dims) { |
6128 | |
6129 | static auto op = create_rot90_typed_handle(); |
6130 | return op.call(self, k, dims); |
6131 | } |
6132 | |
6133 | // aten::rot90(Tensor self, int k=1, int[] dims=[0,1]) -> Tensor |
6134 | at::Tensor rot90::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t k, at::IntArrayRef dims) { |
6135 | |
6136 | static auto op = create_rot90_typed_handle(); |
6137 | return op.redispatch(dispatchKeySet, self, k, dims); |
6138 | } |
6139 | |
6140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapz_x, name, "aten::trapz" ) |
6141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapz_x, overload_name, "x" ) |
6142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapz_x, schema_str, "trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor" ) |
6143 | |
6144 | // aten::trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor |
6145 | static C10_NOINLINE c10::TypedOperatorHandle<trapz_x::schema> create_trapz_x_typed_handle() { |
6146 | return c10::Dispatcher::singleton() |
6147 | .findSchemaOrThrow(trapz_x::name, trapz_x::overload_name) |
6148 | .typed<trapz_x::schema>(); |
6149 | } |
6150 | |
6151 | // aten::trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor |
6152 | at::Tensor trapz_x::call(const at::Tensor & y, const at::Tensor & x, int64_t dim) { |
6153 | |
6154 | static auto op = create_trapz_x_typed_handle(); |
6155 | return op.call(y, x, dim); |
6156 | } |
6157 | |
6158 | // aten::trapz.x(Tensor y, Tensor x, *, int dim=-1) -> Tensor |
6159 | at::Tensor trapz_x::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, const at::Tensor & x, int64_t dim) { |
6160 | |
6161 | static auto op = create_trapz_x_typed_handle(); |
6162 | return op.redispatch(dispatchKeySet, y, x, dim); |
6163 | } |
6164 | |
6165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapz_dx, name, "aten::trapz" ) |
6166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapz_dx, overload_name, "dx" ) |
6167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trapz_dx, schema_str, "trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor" ) |
6168 | |
6169 | // aten::trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor |
6170 | static C10_NOINLINE c10::TypedOperatorHandle<trapz_dx::schema> create_trapz_dx_typed_handle() { |
6171 | return c10::Dispatcher::singleton() |
6172 | .findSchemaOrThrow(trapz_dx::name, trapz_dx::overload_name) |
6173 | .typed<trapz_dx::schema>(); |
6174 | } |
6175 | |
6176 | // aten::trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor |
6177 | at::Tensor trapz_dx::call(const at::Tensor & y, double dx, int64_t dim) { |
6178 | |
6179 | static auto op = create_trapz_dx_typed_handle(); |
6180 | return op.call(y, dx, dim); |
6181 | } |
6182 | |
6183 | // aten::trapz.dx(Tensor y, *, float dx=1, int dim=-1) -> Tensor |
6184 | at::Tensor trapz_dx::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & y, double dx, int64_t dim) { |
6185 | |
6186 | static auto op = create_trapz_dx_typed_handle(); |
6187 | return op.redispatch(dispatchKeySet, y, dx, dim); |
6188 | } |
6189 | |
6190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_strides, name, "aten::_nested_tensor_strides" ) |
6191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_strides, overload_name, "" ) |
6192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_strides, schema_str, "_nested_tensor_strides(Tensor self) -> Tensor" ) |
6193 | |
6194 | // aten::_nested_tensor_strides(Tensor self) -> Tensor |
6195 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_strides::schema> create__nested_tensor_strides_typed_handle() { |
6196 | return c10::Dispatcher::singleton() |
6197 | .findSchemaOrThrow(_nested_tensor_strides::name, _nested_tensor_strides::overload_name) |
6198 | .typed<_nested_tensor_strides::schema>(); |
6199 | } |
6200 | |
6201 | // aten::_nested_tensor_strides(Tensor self) -> Tensor |
6202 | at::Tensor _nested_tensor_strides::call(const at::Tensor & self) { |
6203 | |
6204 | static auto op = create__nested_tensor_strides_typed_handle(); |
6205 | return op.call(self); |
6206 | } |
6207 | |
6208 | // aten::_nested_tensor_strides(Tensor self) -> Tensor |
6209 | at::Tensor _nested_tensor_strides::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
6210 | |
6211 | static auto op = create__nested_tensor_strides_typed_handle(); |
6212 | return op.redispatch(dispatchKeySet, self); |
6213 | } |
6214 | |
6215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_offsets, name, "aten::_nested_tensor_offsets" ) |
6216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_offsets, overload_name, "" ) |
6217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_offsets, schema_str, "_nested_tensor_offsets(Tensor self) -> int[]" ) |
6218 | |
6219 | // aten::_nested_tensor_offsets(Tensor self) -> int[] |
6220 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_offsets::schema> create__nested_tensor_offsets_typed_handle() { |
6221 | return c10::Dispatcher::singleton() |
6222 | .findSchemaOrThrow(_nested_tensor_offsets::name, _nested_tensor_offsets::overload_name) |
6223 | .typed<_nested_tensor_offsets::schema>(); |
6224 | } |
6225 | |
6226 | // aten::_nested_tensor_offsets(Tensor self) -> int[] |
6227 | ::std::vector<int64_t> _nested_tensor_offsets::call(const at::Tensor & self) { |
6228 | |
6229 | static auto op = create__nested_tensor_offsets_typed_handle(); |
6230 | return op.call(self); |
6231 | } |
6232 | |
6233 | // aten::_nested_tensor_offsets(Tensor self) -> int[] |
6234 | ::std::vector<int64_t> _nested_tensor_offsets::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
6235 | |
6236 | static auto op = create__nested_tensor_offsets_typed_handle(); |
6237 | return op.redispatch(dispatchKeySet, self); |
6238 | } |
6239 | |
6240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triplet_margin_loss, name, "aten::triplet_margin_loss" ) |
6241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triplet_margin_loss, overload_name, "" ) |
6242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(triplet_margin_loss, schema_str, "triplet_margin_loss(Tensor anchor, Tensor positive, Tensor negative, float margin=1.0, float p=2, float eps=1e-06, bool swap=False, int reduction=Mean) -> Tensor" ) |
6243 | |
6244 | // aten::triplet_margin_loss(Tensor anchor, Tensor positive, Tensor negative, float margin=1.0, float p=2, float eps=1e-06, bool swap=False, int reduction=Mean) -> Tensor |
6245 | static C10_NOINLINE c10::TypedOperatorHandle<triplet_margin_loss::schema> create_triplet_margin_loss_typed_handle() { |
6246 | return c10::Dispatcher::singleton() |
6247 | .findSchemaOrThrow(triplet_margin_loss::name, triplet_margin_loss::overload_name) |
6248 | .typed<triplet_margin_loss::schema>(); |
6249 | } |
6250 | |
6251 | // aten::triplet_margin_loss(Tensor anchor, Tensor positive, Tensor negative, float margin=1.0, float p=2, float eps=1e-06, bool swap=False, int reduction=Mean) -> Tensor |
6252 | at::Tensor triplet_margin_loss::call(const at::Tensor & anchor, const at::Tensor & positive, const at::Tensor & negative, double margin, double p, double eps, bool swap, int64_t reduction) { |
6253 | |
6254 | static auto op = create_triplet_margin_loss_typed_handle(); |
6255 | return op.call(anchor, positive, negative, margin, p, eps, swap, reduction); |
6256 | } |
6257 | |
6258 | // aten::triplet_margin_loss(Tensor anchor, Tensor positive, Tensor negative, float margin=1.0, float p=2, float eps=1e-06, bool swap=False, int reduction=Mean) -> Tensor |
6259 | at::Tensor triplet_margin_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & anchor, const at::Tensor & positive, const at::Tensor & negative, double margin, double p, double eps, bool swap, int64_t reduction) { |
6260 | |
6261 | static auto op = create_triplet_margin_loss_typed_handle(); |
6262 | return op.redispatch(dispatchKeySet, anchor, positive, negative, margin, p, eps, swap, reduction); |
6263 | } |
6264 | |
6265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc, name, "aten::trunc" ) |
6266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc, overload_name, "" ) |
6267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc, schema_str, "trunc(Tensor self) -> Tensor" ) |
6268 | |
6269 | // aten::trunc(Tensor self) -> Tensor |
6270 | static C10_NOINLINE c10::TypedOperatorHandle<trunc::schema> create_trunc_typed_handle() { |
6271 | return c10::Dispatcher::singleton() |
6272 | .findSchemaOrThrow(trunc::name, trunc::overload_name) |
6273 | .typed<trunc::schema>(); |
6274 | } |
6275 | |
6276 | // aten::trunc(Tensor self) -> Tensor |
6277 | at::Tensor trunc::call(const at::Tensor & self) { |
6278 | |
6279 | static auto op = create_trunc_typed_handle(); |
6280 | return op.call(self); |
6281 | } |
6282 | |
6283 | // aten::trunc(Tensor self) -> Tensor |
6284 | at::Tensor trunc::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
6285 | |
6286 | static auto op = create_trunc_typed_handle(); |
6287 | return op.redispatch(dispatchKeySet, self); |
6288 | } |
6289 | |
6290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc_, name, "aten::trunc_" ) |
6291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc_, overload_name, "" ) |
6292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc_, schema_str, "trunc_(Tensor(a!) self) -> Tensor(a!)" ) |
6293 | |
6294 | // aten::trunc_(Tensor(a!) self) -> Tensor(a!) |
6295 | static C10_NOINLINE c10::TypedOperatorHandle<trunc_::schema> create_trunc__typed_handle() { |
6296 | return c10::Dispatcher::singleton() |
6297 | .findSchemaOrThrow(trunc_::name, trunc_::overload_name) |
6298 | .typed<trunc_::schema>(); |
6299 | } |
6300 | |
6301 | // aten::trunc_(Tensor(a!) self) -> Tensor(a!) |
6302 | at::Tensor & trunc_::call(at::Tensor & self) { |
6303 | |
6304 | static auto op = create_trunc__typed_handle(); |
6305 | return op.call(self); |
6306 | } |
6307 | |
6308 | // aten::trunc_(Tensor(a!) self) -> Tensor(a!) |
6309 | at::Tensor & trunc_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
6310 | |
6311 | static auto op = create_trunc__typed_handle(); |
6312 | return op.redispatch(dispatchKeySet, self); |
6313 | } |
6314 | |
6315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc_out, name, "aten::trunc" ) |
6316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc_out, overload_name, "out" ) |
6317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(trunc_out, schema_str, "trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
6318 | |
6319 | // aten::trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
6320 | static C10_NOINLINE c10::TypedOperatorHandle<trunc_out::schema> create_trunc_out_typed_handle() { |
6321 | return c10::Dispatcher::singleton() |
6322 | .findSchemaOrThrow(trunc_out::name, trunc_out::overload_name) |
6323 | .typed<trunc_out::schema>(); |
6324 | } |
6325 | |
6326 | // aten::trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
6327 | at::Tensor & trunc_out::call(const at::Tensor & self, at::Tensor & out) { |
6328 | |
6329 | static auto op = create_trunc_out_typed_handle(); |
6330 | return op.call(self, out); |
6331 | } |
6332 | |
6333 | // aten::trunc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
6334 | at::Tensor & trunc_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
6335 | |
6336 | static auto op = create_trunc_out_typed_handle(); |
6337 | return op.redispatch(dispatchKeySet, self, out); |
6338 | } |
6339 | |
6340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var, name, "aten::var" ) |
6341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var, overload_name, "" ) |
6342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var, schema_str, "var(Tensor self, bool unbiased=True) -> Tensor" ) |
6343 | |
6344 | // aten::var(Tensor self, bool unbiased=True) -> Tensor |
6345 | static C10_NOINLINE c10::TypedOperatorHandle<var::schema> create_var_typed_handle() { |
6346 | return c10::Dispatcher::singleton() |
6347 | .findSchemaOrThrow(var::name, var::overload_name) |
6348 | .typed<var::schema>(); |
6349 | } |
6350 | |
6351 | // aten::var(Tensor self, bool unbiased=True) -> Tensor |
6352 | at::Tensor var::call(const at::Tensor & self, bool unbiased) { |
6353 | |
6354 | static auto op = create_var_typed_handle(); |
6355 | return op.call(self, unbiased); |
6356 | } |
6357 | |
6358 | // aten::var(Tensor self, bool unbiased=True) -> Tensor |
6359 | at::Tensor var::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool unbiased) { |
6360 | |
6361 | static auto op = create_var_typed_handle(); |
6362 | return op.redispatch(dispatchKeySet, self, unbiased); |
6363 | } |
6364 | |
6365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_dim, name, "aten::var" ) |
6366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_dim, overload_name, "dim" ) |
6367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_dim, schema_str, "var.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> Tensor" ) |
6368 | |
6369 | // aten::var.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> Tensor |
6370 | static C10_NOINLINE c10::TypedOperatorHandle<var_dim::schema> create_var_dim_typed_handle() { |
6371 | return c10::Dispatcher::singleton() |
6372 | .findSchemaOrThrow(var_dim::name, var_dim::overload_name) |
6373 | .typed<var_dim::schema>(); |
6374 | } |
6375 | |
6376 | // aten::var.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> Tensor |
6377 | at::Tensor var_dim::call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim) { |
6378 | |
6379 | static auto op = create_var_dim_typed_handle(); |
6380 | return op.call(self, dim, unbiased, keepdim); |
6381 | } |
6382 | |
6383 | // aten::var.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> Tensor |
6384 | at::Tensor var_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim) { |
6385 | |
6386 | static auto op = create_var_dim_typed_handle(); |
6387 | return op.redispatch(dispatchKeySet, self, dim, unbiased, keepdim); |
6388 | } |
6389 | |
6390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction, name, "aten::var" ) |
6391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction, overload_name, "correction" ) |
6392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction, schema_str, "var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor" ) |
6393 | |
6394 | // aten::var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor |
6395 | static C10_NOINLINE c10::TypedOperatorHandle<var_correction::schema> create_var_correction_typed_handle() { |
6396 | return c10::Dispatcher::singleton() |
6397 | .findSchemaOrThrow(var_correction::name, var_correction::overload_name) |
6398 | .typed<var_correction::schema>(); |
6399 | } |
6400 | |
6401 | // aten::var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor |
6402 | at::Tensor var_correction::call(const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim) { |
6403 | |
6404 | static auto op = create_var_correction_typed_handle(); |
6405 | return op.call(self, dim, correction, keepdim); |
6406 | } |
6407 | |
6408 | // aten::var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor |
6409 | at::Tensor var_correction::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim) { |
6410 | |
6411 | static auto op = create_var_correction_typed_handle(); |
6412 | return op.redispatch(dispatchKeySet, self, dim, correction, keepdim); |
6413 | } |
6414 | |
6415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_out, name, "aten::var" ) |
6416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_out, overload_name, "out" ) |
6417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_out, schema_str, "var.out(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
6418 | |
6419 | // aten::var.out(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
6420 | static C10_NOINLINE c10::TypedOperatorHandle<var_out::schema> create_var_out_typed_handle() { |
6421 | return c10::Dispatcher::singleton() |
6422 | .findSchemaOrThrow(var_out::name, var_out::overload_name) |
6423 | .typed<var_out::schema>(); |
6424 | } |
6425 | |
6426 | // aten::var.out(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
6427 | at::Tensor & var_out::call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out) { |
6428 | |
6429 | static auto op = create_var_out_typed_handle(); |
6430 | return op.call(self, dim, unbiased, keepdim, out); |
6431 | } |
6432 | |
6433 | // aten::var.out(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
6434 | at::Tensor & var_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim, at::Tensor & out) { |
6435 | |
6436 | static auto op = create_var_out_typed_handle(); |
6437 | return op.redispatch(dispatchKeySet, self, dim, unbiased, keepdim, out); |
6438 | } |
6439 | |
6440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_out, name, "aten::var" ) |
6441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_out, overload_name, "correction_out" ) |
6442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_out, schema_str, "var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!)" ) |
6443 | |
6444 | // aten::var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) |
6445 | static C10_NOINLINE c10::TypedOperatorHandle<var_correction_out::schema> create_var_correction_out_typed_handle() { |
6446 | return c10::Dispatcher::singleton() |
6447 | .findSchemaOrThrow(var_correction_out::name, var_correction_out::overload_name) |
6448 | .typed<var_correction_out::schema>(); |
6449 | } |
6450 | |
6451 | // aten::var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) |
6452 | at::Tensor & var_correction_out::call(const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim, at::Tensor & out) { |
6453 | |
6454 | static auto op = create_var_correction_out_typed_handle(); |
6455 | return op.call(self, dim, correction, keepdim, out); |
6456 | } |
6457 | |
6458 | // aten::var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) |
6459 | at::Tensor & var_correction_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim, at::Tensor & out) { |
6460 | |
6461 | static auto op = create_var_correction_out_typed_handle(); |
6462 | return op.redispatch(dispatchKeySet, self, dim, correction, keepdim, out); |
6463 | } |
6464 | |
6465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_names_dim, name, "aten::var" ) |
6466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_names_dim, overload_name, "names_dim" ) |
6467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_names_dim, schema_str, "var.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> Tensor" ) |
6468 | |
6469 | // aten::var.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> Tensor |
6470 | static C10_NOINLINE c10::TypedOperatorHandle<var_names_dim::schema> create_var_names_dim_typed_handle() { |
6471 | return c10::Dispatcher::singleton() |
6472 | .findSchemaOrThrow(var_names_dim::name, var_names_dim::overload_name) |
6473 | .typed<var_names_dim::schema>(); |
6474 | } |
6475 | |
6476 | // aten::var.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> Tensor |
6477 | at::Tensor var_names_dim::call(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim) { |
6478 | |
6479 | static auto op = create_var_names_dim_typed_handle(); |
6480 | return op.call(self, dim, unbiased, keepdim); |
6481 | } |
6482 | |
6483 | // aten::var.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> Tensor |
6484 | at::Tensor var_names_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim) { |
6485 | |
6486 | static auto op = create_var_names_dim_typed_handle(); |
6487 | return op.redispatch(dispatchKeySet, self, dim, unbiased, keepdim); |
6488 | } |
6489 | |
6490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_names_out, name, "aten::var" ) |
6491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_names_out, overload_name, "names_out" ) |
6492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_names_out, schema_str, "var.names_out(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
6493 | |
6494 | // aten::var.names_out(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
6495 | static C10_NOINLINE c10::TypedOperatorHandle<var_names_out::schema> create_var_names_out_typed_handle() { |
6496 | return c10::Dispatcher::singleton() |
6497 | .findSchemaOrThrow(var_names_out::name, var_names_out::overload_name) |
6498 | .typed<var_names_out::schema>(); |
6499 | } |
6500 | |
6501 | // aten::var.names_out(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
6502 | at::Tensor & var_names_out::call(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out) { |
6503 | |
6504 | static auto op = create_var_names_out_typed_handle(); |
6505 | return op.call(self, dim, unbiased, keepdim, out); |
6506 | } |
6507 | |
6508 | // aten::var.names_out(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
6509 | at::Tensor & var_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim, at::Tensor & out) { |
6510 | |
6511 | static auto op = create_var_names_out_typed_handle(); |
6512 | return op.redispatch(dispatchKeySet, self, dim, unbiased, keepdim, out); |
6513 | } |
6514 | |
6515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_names, name, "aten::var" ) |
6516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_names, overload_name, "correction_names" ) |
6517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_names, schema_str, "var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor" ) |
6518 | |
6519 | // aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor |
6520 | static C10_NOINLINE c10::TypedOperatorHandle<var_correction_names::schema> create_var_correction_names_typed_handle() { |
6521 | return c10::Dispatcher::singleton() |
6522 | .findSchemaOrThrow(var_correction_names::name, var_correction_names::overload_name) |
6523 | .typed<var_correction_names::schema>(); |
6524 | } |
6525 | |
6526 | // aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor |
6527 | at::Tensor var_correction_names::call(const at::Tensor & self, at::DimnameList dim, c10::optional<int64_t> correction, bool keepdim) { |
6528 | |
6529 | static auto op = create_var_correction_names_typed_handle(); |
6530 | return op.call(self, dim, correction, keepdim); |
6531 | } |
6532 | |
6533 | // aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor |
6534 | at::Tensor var_correction_names::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, c10::optional<int64_t> correction, bool keepdim) { |
6535 | |
6536 | static auto op = create_var_correction_names_typed_handle(); |
6537 | return op.redispatch(dispatchKeySet, self, dim, correction, keepdim); |
6538 | } |
6539 | |
6540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_names_out, name, "aten::var" ) |
6541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_names_out, overload_name, "correction_names_out" ) |
6542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_correction_names_out, schema_str, "var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!)" ) |
6543 | |
6544 | // aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) |
6545 | static C10_NOINLINE c10::TypedOperatorHandle<var_correction_names_out::schema> create_var_correction_names_out_typed_handle() { |
6546 | return c10::Dispatcher::singleton() |
6547 | .findSchemaOrThrow(var_correction_names_out::name, var_correction_names_out::overload_name) |
6548 | .typed<var_correction_names_out::schema>(); |
6549 | } |
6550 | |
6551 | // aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) |
6552 | at::Tensor & var_correction_names_out::call(const at::Tensor & self, at::DimnameList dim, c10::optional<int64_t> correction, bool keepdim, at::Tensor & out) { |
6553 | |
6554 | static auto op = create_var_correction_names_out_typed_handle(); |
6555 | return op.call(self, dim, correction, keepdim, out); |
6556 | } |
6557 | |
6558 | // aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) |
6559 | at::Tensor & var_correction_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, c10::optional<int64_t> correction, bool keepdim, at::Tensor & out) { |
6560 | |
6561 | static auto op = create_var_correction_names_out_typed_handle(); |
6562 | return op.redispatch(dispatchKeySet, self, dim, correction, keepdim, out); |
6563 | } |
6564 | |
6565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean, name, "aten::var_mean" ) |
6566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean, overload_name, "" ) |
6567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean, schema_str, "var_mean(Tensor self, bool unbiased=True) -> (Tensor, Tensor)" ) |
6568 | |
6569 | // aten::var_mean(Tensor self, bool unbiased=True) -> (Tensor, Tensor) |
6570 | static C10_NOINLINE c10::TypedOperatorHandle<var_mean::schema> create_var_mean_typed_handle() { |
6571 | return c10::Dispatcher::singleton() |
6572 | .findSchemaOrThrow(var_mean::name, var_mean::overload_name) |
6573 | .typed<var_mean::schema>(); |
6574 | } |
6575 | |
6576 | // aten::var_mean(Tensor self, bool unbiased=True) -> (Tensor, Tensor) |
6577 | ::std::tuple<at::Tensor,at::Tensor> var_mean::call(const at::Tensor & self, bool unbiased) { |
6578 | |
6579 | static auto op = create_var_mean_typed_handle(); |
6580 | return op.call(self, unbiased); |
6581 | } |
6582 | |
6583 | // aten::var_mean(Tensor self, bool unbiased=True) -> (Tensor, Tensor) |
6584 | ::std::tuple<at::Tensor,at::Tensor> var_mean::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool unbiased) { |
6585 | |
6586 | static auto op = create_var_mean_typed_handle(); |
6587 | return op.redispatch(dispatchKeySet, self, unbiased); |
6588 | } |
6589 | |
6590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_dim, name, "aten::var_mean" ) |
6591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_dim, overload_name, "dim" ) |
6592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_dim, schema_str, "var_mean.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor)" ) |
6593 | |
6594 | // aten::var_mean.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor) |
6595 | static C10_NOINLINE c10::TypedOperatorHandle<var_mean_dim::schema> create_var_mean_dim_typed_handle() { |
6596 | return c10::Dispatcher::singleton() |
6597 | .findSchemaOrThrow(var_mean_dim::name, var_mean_dim::overload_name) |
6598 | .typed<var_mean_dim::schema>(); |
6599 | } |
6600 | |
6601 | // aten::var_mean.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor) |
6602 | ::std::tuple<at::Tensor,at::Tensor> var_mean_dim::call(const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim) { |
6603 | |
6604 | static auto op = create_var_mean_dim_typed_handle(); |
6605 | return op.call(self, dim, unbiased, keepdim); |
6606 | } |
6607 | |
6608 | // aten::var_mean.dim(Tensor self, int[1]? dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor) |
6609 | ::std::tuple<at::Tensor,at::Tensor> var_mean_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, bool unbiased, bool keepdim) { |
6610 | |
6611 | static auto op = create_var_mean_dim_typed_handle(); |
6612 | return op.redispatch(dispatchKeySet, self, dim, unbiased, keepdim); |
6613 | } |
6614 | |
6615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction, name, "aten::var_mean" ) |
6616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction, overload_name, "correction" ) |
6617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction, schema_str, "var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor)" ) |
6618 | |
6619 | // aten::var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) |
6620 | static C10_NOINLINE c10::TypedOperatorHandle<var_mean_correction::schema> create_var_mean_correction_typed_handle() { |
6621 | return c10::Dispatcher::singleton() |
6622 | .findSchemaOrThrow(var_mean_correction::name, var_mean_correction::overload_name) |
6623 | .typed<var_mean_correction::schema>(); |
6624 | } |
6625 | |
6626 | // aten::var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) |
6627 | ::std::tuple<at::Tensor,at::Tensor> var_mean_correction::call(const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim) { |
6628 | |
6629 | static auto op = create_var_mean_correction_typed_handle(); |
6630 | return op.call(self, dim, correction, keepdim); |
6631 | } |
6632 | |
6633 | // aten::var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) |
6634 | ::std::tuple<at::Tensor,at::Tensor> var_mean_correction::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim) { |
6635 | |
6636 | static auto op = create_var_mean_correction_typed_handle(); |
6637 | return op.redispatch(dispatchKeySet, self, dim, correction, keepdim); |
6638 | } |
6639 | |
6640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_names_dim, name, "aten::var_mean" ) |
6641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_names_dim, overload_name, "names_dim" ) |
6642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_names_dim, schema_str, "var_mean.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor)" ) |
6643 | |
6644 | // aten::var_mean.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor) |
6645 | static C10_NOINLINE c10::TypedOperatorHandle<var_mean_names_dim::schema> create_var_mean_names_dim_typed_handle() { |
6646 | return c10::Dispatcher::singleton() |
6647 | .findSchemaOrThrow(var_mean_names_dim::name, var_mean_names_dim::overload_name) |
6648 | .typed<var_mean_names_dim::schema>(); |
6649 | } |
6650 | |
6651 | // aten::var_mean.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor) |
6652 | ::std::tuple<at::Tensor,at::Tensor> var_mean_names_dim::call(const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim) { |
6653 | |
6654 | static auto op = create_var_mean_names_dim_typed_handle(); |
6655 | return op.call(self, dim, unbiased, keepdim); |
6656 | } |
6657 | |
6658 | // aten::var_mean.names_dim(Tensor self, Dimname[1] dim, bool unbiased=True, bool keepdim=False) -> (Tensor, Tensor) |
6659 | ::std::tuple<at::Tensor,at::Tensor> var_mean_names_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, bool unbiased, bool keepdim) { |
6660 | |
6661 | static auto op = create_var_mean_names_dim_typed_handle(); |
6662 | return op.redispatch(dispatchKeySet, self, dim, unbiased, keepdim); |
6663 | } |
6664 | |
6665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction_names, name, "aten::var_mean" ) |
6666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction_names, overload_name, "correction_names" ) |
6667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction_names, schema_str, "var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor)" ) |
6668 | |
6669 | // aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) |
6670 | static C10_NOINLINE c10::TypedOperatorHandle<var_mean_correction_names::schema> create_var_mean_correction_names_typed_handle() { |
6671 | return c10::Dispatcher::singleton() |
6672 | .findSchemaOrThrow(var_mean_correction_names::name, var_mean_correction_names::overload_name) |
6673 | .typed<var_mean_correction_names::schema>(); |
6674 | } |
6675 | |
6676 | // aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) |
6677 | ::std::tuple<at::Tensor,at::Tensor> var_mean_correction_names::call(const at::Tensor & self, at::DimnameList dim, c10::optional<int64_t> correction, bool keepdim) { |
6678 | |
6679 | static auto op = create_var_mean_correction_names_typed_handle(); |
6680 | return op.call(self, dim, correction, keepdim); |
6681 | } |
6682 | |
6683 | // aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) |
6684 | ::std::tuple<at::Tensor,at::Tensor> var_mean_correction_names::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::DimnameList dim, c10::optional<int64_t> correction, bool keepdim) { |
6685 | |
6686 | static auto op = create_var_mean_correction_names_typed_handle(); |
6687 | return op.redispatch(dispatchKeySet, self, dim, correction, keepdim); |
6688 | } |
6689 | |
6690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_except_dim, name, "aten::norm_except_dim" ) |
6691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_except_dim, overload_name, "" ) |
6692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_except_dim, schema_str, "norm_except_dim(Tensor v, int pow=2, int dim=0) -> Tensor" ) |
6693 | |
6694 | // aten::norm_except_dim(Tensor v, int pow=2, int dim=0) -> Tensor |
6695 | static C10_NOINLINE c10::TypedOperatorHandle<norm_except_dim::schema> create_norm_except_dim_typed_handle() { |
6696 | return c10::Dispatcher::singleton() |
6697 | .findSchemaOrThrow(norm_except_dim::name, norm_except_dim::overload_name) |
6698 | .typed<norm_except_dim::schema>(); |
6699 | } |
6700 | |
6701 | // aten::norm_except_dim(Tensor v, int pow=2, int dim=0) -> Tensor |
6702 | at::Tensor norm_except_dim::call(const at::Tensor & v, int64_t pow, int64_t dim) { |
6703 | |
6704 | static auto op = create_norm_except_dim_typed_handle(); |
6705 | return op.call(v, pow, dim); |
6706 | } |
6707 | |
6708 | // aten::norm_except_dim(Tensor v, int pow=2, int dim=0) -> Tensor |
6709 | at::Tensor norm_except_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & v, int64_t pow, int64_t dim) { |
6710 | |
6711 | static auto op = create_norm_except_dim_typed_handle(); |
6712 | return op.redispatch(dispatchKeySet, v, pow, dim); |
6713 | } |
6714 | |
6715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_grad, name, "aten::_standard_gamma_grad" ) |
6716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_grad, overload_name, "" ) |
6717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_grad, schema_str, "_standard_gamma_grad(Tensor self, Tensor output) -> Tensor" ) |
6718 | |
6719 | // aten::_standard_gamma_grad(Tensor self, Tensor output) -> Tensor |
6720 | static C10_NOINLINE c10::TypedOperatorHandle<_standard_gamma_grad::schema> create__standard_gamma_grad_typed_handle() { |
6721 | return c10::Dispatcher::singleton() |
6722 | .findSchemaOrThrow(_standard_gamma_grad::name, _standard_gamma_grad::overload_name) |
6723 | .typed<_standard_gamma_grad::schema>(); |
6724 | } |
6725 | |
6726 | // aten::_standard_gamma_grad(Tensor self, Tensor output) -> Tensor |
6727 | at::Tensor _standard_gamma_grad::call(const at::Tensor & self, const at::Tensor & output) { |
6728 | |
6729 | static auto op = create__standard_gamma_grad_typed_handle(); |
6730 | return op.call(self, output); |
6731 | } |
6732 | |
6733 | // aten::_standard_gamma_grad(Tensor self, Tensor output) -> Tensor |
6734 | at::Tensor _standard_gamma_grad::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & output) { |
6735 | |
6736 | static auto op = create__standard_gamma_grad_typed_handle(); |
6737 | return op.redispatch(dispatchKeySet, self, output); |
6738 | } |
6739 | |
6740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm, name, "aten::native_norm" ) |
6741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm, overload_name, "" ) |
6742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm, schema_str, "native_norm(Tensor self, Scalar p=2) -> Tensor" ) |
6743 | |
6744 | // aten::native_norm(Tensor self, Scalar p=2) -> Tensor |
6745 | static C10_NOINLINE c10::TypedOperatorHandle<native_norm::schema> create_native_norm_typed_handle() { |
6746 | return c10::Dispatcher::singleton() |
6747 | .findSchemaOrThrow(native_norm::name, native_norm::overload_name) |
6748 | .typed<native_norm::schema>(); |
6749 | } |
6750 | |
6751 | // aten::native_norm(Tensor self, Scalar p=2) -> Tensor |
6752 | at::Tensor native_norm::call(const at::Tensor & self, const at::Scalar & p) { |
6753 | |
6754 | static auto op = create_native_norm_typed_handle(); |
6755 | return op.call(self, p); |
6756 | } |
6757 | |
6758 | // aten::native_norm(Tensor self, Scalar p=2) -> Tensor |
6759 | at::Tensor native_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p) { |
6760 | |
6761 | static auto op = create_native_norm_typed_handle(); |
6762 | return op.redispatch(dispatchKeySet, self, p); |
6763 | } |
6764 | |
6765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_ScalarOpt_dim_dtype, name, "aten::native_norm" ) |
6766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_ScalarOpt_dim_dtype, overload_name, "ScalarOpt_dim_dtype" ) |
6767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_ScalarOpt_dim_dtype, schema_str, "native_norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype) -> Tensor" ) |
6768 | |
6769 | // aten::native_norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype) -> Tensor |
6770 | static C10_NOINLINE c10::TypedOperatorHandle<native_norm_ScalarOpt_dim_dtype::schema> create_native_norm_ScalarOpt_dim_dtype_typed_handle() { |
6771 | return c10::Dispatcher::singleton() |
6772 | .findSchemaOrThrow(native_norm_ScalarOpt_dim_dtype::name, native_norm_ScalarOpt_dim_dtype::overload_name) |
6773 | .typed<native_norm_ScalarOpt_dim_dtype::schema>(); |
6774 | } |
6775 | |
6776 | // aten::native_norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype) -> Tensor |
6777 | at::Tensor native_norm_ScalarOpt_dim_dtype::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
6778 | |
6779 | static auto op = create_native_norm_ScalarOpt_dim_dtype_typed_handle(); |
6780 | return op.call(self, p, dim, keepdim, dtype); |
6781 | } |
6782 | |
6783 | // aten::native_norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype) -> Tensor |
6784 | at::Tensor native_norm_ScalarOpt_dim_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
6785 | |
6786 | static auto op = create_native_norm_ScalarOpt_dim_dtype_typed_handle(); |
6787 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, dtype); |
6788 | } |
6789 | |
6790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_backward, name, "aten::_sparse_sum_backward" ) |
6791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_backward, overload_name, "" ) |
6792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_backward, schema_str, "_sparse_sum_backward(Tensor grad, Tensor self, int[] dim) -> Tensor" ) |
6793 | |
6794 | // aten::_sparse_sum_backward(Tensor grad, Tensor self, int[] dim) -> Tensor |
6795 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sum_backward::schema> create__sparse_sum_backward_typed_handle() { |
6796 | return c10::Dispatcher::singleton() |
6797 | .findSchemaOrThrow(_sparse_sum_backward::name, _sparse_sum_backward::overload_name) |
6798 | .typed<_sparse_sum_backward::schema>(); |
6799 | } |
6800 | |
6801 | // aten::_sparse_sum_backward(Tensor grad, Tensor self, int[] dim) -> Tensor |
6802 | at::Tensor _sparse_sum_backward::call(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim) { |
6803 | |
6804 | static auto op = create__sparse_sum_backward_typed_handle(); |
6805 | return op.call(grad, self, dim); |
6806 | } |
6807 | |
6808 | // aten::_sparse_sum_backward(Tensor grad, Tensor self, int[] dim) -> Tensor |
6809 | at::Tensor _sparse_sum_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim) { |
6810 | |
6811 | static auto op = create__sparse_sum_backward_typed_handle(); |
6812 | return op.redispatch(dispatchKeySet, grad, self, dim); |
6813 | } |
6814 | |
6815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_sum_dim_dtype, name, "aten::_sparse_csr_sum" ) |
6816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_sum_dim_dtype, overload_name, "dim_dtype" ) |
6817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_sum_dim_dtype, schema_str, "_sparse_csr_sum.dim_dtype(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor" ) |
6818 | |
6819 | // aten::_sparse_csr_sum.dim_dtype(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
6820 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_csr_sum_dim_dtype::schema> create__sparse_csr_sum_dim_dtype_typed_handle() { |
6821 | return c10::Dispatcher::singleton() |
6822 | .findSchemaOrThrow(_sparse_csr_sum_dim_dtype::name, _sparse_csr_sum_dim_dtype::overload_name) |
6823 | .typed<_sparse_csr_sum_dim_dtype::schema>(); |
6824 | } |
6825 | |
6826 | // aten::_sparse_csr_sum.dim_dtype(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
6827 | at::Tensor _sparse_csr_sum_dim_dtype::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
6828 | |
6829 | static auto op = create__sparse_csr_sum_dim_dtype_typed_handle(); |
6830 | return op.call(self, dim, keepdim, dtype); |
6831 | } |
6832 | |
6833 | // aten::_sparse_csr_sum.dim_dtype(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
6834 | at::Tensor _sparse_csr_sum_dim_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
6835 | |
6836 | static auto op = create__sparse_csr_sum_dim_dtype_typed_handle(); |
6837 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype); |
6838 | } |
6839 | |
6840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_int, name, "aten::_sparse_softmax" ) |
6841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_int, overload_name, "int" ) |
6842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_int, schema_str, "_sparse_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor" ) |
6843 | |
6844 | // aten::_sparse_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor |
6845 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_softmax_int::schema> create__sparse_softmax_int_typed_handle() { |
6846 | return c10::Dispatcher::singleton() |
6847 | .findSchemaOrThrow(_sparse_softmax_int::name, _sparse_softmax_int::overload_name) |
6848 | .typed<_sparse_softmax_int::schema>(); |
6849 | } |
6850 | |
6851 | // aten::_sparse_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor |
6852 | at::Tensor _sparse_softmax_int::call(const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
6853 | |
6854 | static auto op = create__sparse_softmax_int_typed_handle(); |
6855 | return op.call(self, dim, dtype); |
6856 | } |
6857 | |
6858 | // aten::_sparse_softmax.int(Tensor self, int dim, ScalarType? dtype=None) -> Tensor |
6859 | at::Tensor _sparse_softmax_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, c10::optional<at::ScalarType> dtype) { |
6860 | |
6861 | static auto op = create__sparse_softmax_int_typed_handle(); |
6862 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
6863 | } |
6864 | |
6865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_Dimname, name, "aten::_sparse_softmax" ) |
6866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_Dimname, overload_name, "Dimname" ) |
6867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_Dimname, schema_str, "_sparse_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor" ) |
6868 | |
6869 | // aten::_sparse_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
6870 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_softmax_Dimname::schema> create__sparse_softmax_Dimname_typed_handle() { |
6871 | return c10::Dispatcher::singleton() |
6872 | .findSchemaOrThrow(_sparse_softmax_Dimname::name, _sparse_softmax_Dimname::overload_name) |
6873 | .typed<_sparse_softmax_Dimname::schema>(); |
6874 | } |
6875 | |
6876 | // aten::_sparse_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
6877 | at::Tensor _sparse_softmax_Dimname::call(const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
6878 | |
6879 | static auto op = create__sparse_softmax_Dimname_typed_handle(); |
6880 | return op.call(self, dim, dtype); |
6881 | } |
6882 | |
6883 | // aten::_sparse_softmax.Dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor |
6884 | at::Tensor _sparse_softmax_Dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, c10::optional<at::ScalarType> dtype) { |
6885 | |
6886 | static auto op = create__sparse_softmax_Dimname_typed_handle(); |
6887 | return op.redispatch(dispatchKeySet, self, dim, dtype); |
6888 | } |
6889 | |
6890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax, name, "aten::_sparse_softmax" ) |
6891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax, overload_name, "" ) |
6892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax, schema_str, "_sparse_softmax(Tensor self, int dim, bool half_to_float) -> Tensor" ) |
6893 | |
6894 | // aten::_sparse_softmax(Tensor self, int dim, bool half_to_float) -> Tensor |
6895 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_softmax::schema> create__sparse_softmax_typed_handle() { |
6896 | return c10::Dispatcher::singleton() |
6897 | .findSchemaOrThrow(_sparse_softmax::name, _sparse_softmax::overload_name) |
6898 | .typed<_sparse_softmax::schema>(); |
6899 | } |
6900 | |
6901 | // aten::_sparse_softmax(Tensor self, int dim, bool half_to_float) -> Tensor |
6902 | at::Tensor _sparse_softmax::call(const at::Tensor & self, int64_t dim, bool half_to_float) { |
6903 | |
6904 | static auto op = create__sparse_softmax_typed_handle(); |
6905 | return op.call(self, dim, half_to_float); |
6906 | } |
6907 | |
6908 | // aten::_sparse_softmax(Tensor self, int dim, bool half_to_float) -> Tensor |
6909 | at::Tensor _sparse_softmax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float) { |
6910 | |
6911 | static auto op = create__sparse_softmax_typed_handle(); |
6912 | return op.redispatch(dispatchKeySet, self, dim, half_to_float); |
6913 | } |
6914 | |
6915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dtype, name, "aten::norm" ) |
6916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dtype, overload_name, "ScalarOpt_dtype" ) |
6917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dtype, schema_str, "norm.ScalarOpt_dtype(Tensor self, Scalar? p, *, ScalarType dtype) -> Tensor" ) |
6918 | |
6919 | // aten::norm.ScalarOpt_dtype(Tensor self, Scalar? p, *, ScalarType dtype) -> Tensor |
6920 | static C10_NOINLINE c10::TypedOperatorHandle<norm_ScalarOpt_dtype::schema> create_norm_ScalarOpt_dtype_typed_handle() { |
6921 | return c10::Dispatcher::singleton() |
6922 | .findSchemaOrThrow(norm_ScalarOpt_dtype::name, norm_ScalarOpt_dtype::overload_name) |
6923 | .typed<norm_ScalarOpt_dtype::schema>(); |
6924 | } |
6925 | |
6926 | // aten::norm.ScalarOpt_dtype(Tensor self, Scalar? p, *, ScalarType dtype) -> Tensor |
6927 | at::Tensor norm_ScalarOpt_dtype::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::ScalarType dtype) { |
6928 | |
6929 | static auto op = create_norm_ScalarOpt_dtype_typed_handle(); |
6930 | return op.call(self, p, dtype); |
6931 | } |
6932 | |
6933 | // aten::norm.ScalarOpt_dtype(Tensor self, Scalar? p, *, ScalarType dtype) -> Tensor |
6934 | at::Tensor norm_ScalarOpt_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::ScalarType dtype) { |
6935 | |
6936 | static auto op = create_norm_ScalarOpt_dtype_typed_handle(); |
6937 | return op.redispatch(dispatchKeySet, self, p, dtype); |
6938 | } |
6939 | |
6940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_Scalar, name, "aten::norm" ) |
6941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_Scalar, overload_name, "Scalar" ) |
6942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_Scalar, schema_str, "norm.Scalar(Tensor self, Scalar p=2) -> Tensor" ) |
6943 | |
6944 | // aten::norm.Scalar(Tensor self, Scalar p=2) -> Tensor |
6945 | static C10_NOINLINE c10::TypedOperatorHandle<norm_Scalar::schema> create_norm_Scalar_typed_handle() { |
6946 | return c10::Dispatcher::singleton() |
6947 | .findSchemaOrThrow(norm_Scalar::name, norm_Scalar::overload_name) |
6948 | .typed<norm_Scalar::schema>(); |
6949 | } |
6950 | |
6951 | // aten::norm.Scalar(Tensor self, Scalar p=2) -> Tensor |
6952 | at::Tensor norm_Scalar::call(const at::Tensor & self, const at::Scalar & p) { |
6953 | |
6954 | static auto op = create_norm_Scalar_typed_handle(); |
6955 | return op.call(self, p); |
6956 | } |
6957 | |
6958 | // aten::norm.Scalar(Tensor self, Scalar p=2) -> Tensor |
6959 | at::Tensor norm_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p) { |
6960 | |
6961 | static auto op = create_norm_Scalar_typed_handle(); |
6962 | return op.redispatch(dispatchKeySet, self, p); |
6963 | } |
6964 | |
6965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dim_dtype, name, "aten::norm" ) |
6966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dim_dtype, overload_name, "ScalarOpt_dim_dtype" ) |
6967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dim_dtype, schema_str, "norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor" ) |
6968 | |
6969 | // aten::norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor |
6970 | static C10_NOINLINE c10::TypedOperatorHandle<norm_ScalarOpt_dim_dtype::schema> create_norm_ScalarOpt_dim_dtype_typed_handle() { |
6971 | return c10::Dispatcher::singleton() |
6972 | .findSchemaOrThrow(norm_ScalarOpt_dim_dtype::name, norm_ScalarOpt_dim_dtype::overload_name) |
6973 | .typed<norm_ScalarOpt_dim_dtype::schema>(); |
6974 | } |
6975 | |
6976 | // aten::norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor |
6977 | at::Tensor norm_ScalarOpt_dim_dtype::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype) { |
6978 | |
6979 | static auto op = create_norm_ScalarOpt_dim_dtype_typed_handle(); |
6980 | return op.call(self, p, dim, keepdim, dtype); |
6981 | } |
6982 | |
6983 | // aten::norm.ScalarOpt_dim_dtype(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor |
6984 | at::Tensor norm_ScalarOpt_dim_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype) { |
6985 | |
6986 | static auto op = create_norm_ScalarOpt_dim_dtype_typed_handle(); |
6987 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, dtype); |
6988 | } |
6989 | |
6990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dim, name, "aten::norm" ) |
6991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dim, overload_name, "ScalarOpt_dim" ) |
6992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dim, schema_str, "norm.ScalarOpt_dim(Tensor self, Scalar? p, int[1] dim, bool keepdim=False) -> Tensor" ) |
6993 | |
6994 | // aten::norm.ScalarOpt_dim(Tensor self, Scalar? p, int[1] dim, bool keepdim=False) -> Tensor |
6995 | static C10_NOINLINE c10::TypedOperatorHandle<norm_ScalarOpt_dim::schema> create_norm_ScalarOpt_dim_typed_handle() { |
6996 | return c10::Dispatcher::singleton() |
6997 | .findSchemaOrThrow(norm_ScalarOpt_dim::name, norm_ScalarOpt_dim::overload_name) |
6998 | .typed<norm_ScalarOpt_dim::schema>(); |
6999 | } |
7000 | |
7001 | // aten::norm.ScalarOpt_dim(Tensor self, Scalar? p, int[1] dim, bool keepdim=False) -> Tensor |
7002 | at::Tensor norm_ScalarOpt_dim::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim) { |
7003 | |
7004 | static auto op = create_norm_ScalarOpt_dim_typed_handle(); |
7005 | return op.call(self, p, dim, keepdim); |
7006 | } |
7007 | |
7008 | // aten::norm.ScalarOpt_dim(Tensor self, Scalar? p, int[1] dim, bool keepdim=False) -> Tensor |
7009 | at::Tensor norm_ScalarOpt_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim) { |
7010 | |
7011 | static auto op = create_norm_ScalarOpt_dim_typed_handle(); |
7012 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim); |
7013 | } |
7014 | |
7015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_dtype_out, name, "aten::norm" ) |
7016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_dtype_out, overload_name, "dtype_out" ) |
7017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_dtype_out, schema_str, "norm.dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!)" ) |
7018 | |
7019 | // aten::norm.dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
7020 | static C10_NOINLINE c10::TypedOperatorHandle<norm_dtype_out::schema> create_norm_dtype_out_typed_handle() { |
7021 | return c10::Dispatcher::singleton() |
7022 | .findSchemaOrThrow(norm_dtype_out::name, norm_dtype_out::overload_name) |
7023 | .typed<norm_dtype_out::schema>(); |
7024 | } |
7025 | |
7026 | // aten::norm.dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
7027 | at::Tensor & norm_dtype_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out) { |
7028 | |
7029 | static auto op = create_norm_dtype_out_typed_handle(); |
7030 | return op.call(self, p, dim, keepdim, dtype, out); |
7031 | } |
7032 | |
7033 | // aten::norm.dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
7034 | at::Tensor & norm_dtype_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, at::ScalarType dtype, at::Tensor & out) { |
7035 | |
7036 | static auto op = create_norm_dtype_out_typed_handle(); |
7037 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, dtype, out); |
7038 | } |
7039 | |
7040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_out, name, "aten::norm" ) |
7041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_out, overload_name, "out" ) |
7042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_out, schema_str, "norm.out(Tensor self, Scalar? p, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
7043 | |
7044 | // aten::norm.out(Tensor self, Scalar? p, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7045 | static C10_NOINLINE c10::TypedOperatorHandle<norm_out::schema> create_norm_out_typed_handle() { |
7046 | return c10::Dispatcher::singleton() |
7047 | .findSchemaOrThrow(norm_out::name, norm_out::overload_name) |
7048 | .typed<norm_out::schema>(); |
7049 | } |
7050 | |
7051 | // aten::norm.out(Tensor self, Scalar? p, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7052 | at::Tensor & norm_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
7053 | |
7054 | static auto op = create_norm_out_typed_handle(); |
7055 | return op.call(self, p, dim, keepdim, out); |
7056 | } |
7057 | |
7058 | // aten::norm.out(Tensor self, Scalar? p, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7059 | at::Tensor & norm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
7060 | |
7061 | static auto op = create_norm_out_typed_handle(); |
7062 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, out); |
7063 | } |
7064 | |
7065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_ScalarOpt_dim_dtype, name, "aten::norm" ) |
7066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_ScalarOpt_dim_dtype, overload_name, "names_ScalarOpt_dim_dtype" ) |
7067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_ScalarOpt_dim_dtype, schema_str, "norm.names_ScalarOpt_dim_dtype(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor" ) |
7068 | |
7069 | // aten::norm.names_ScalarOpt_dim_dtype(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor |
7070 | static C10_NOINLINE c10::TypedOperatorHandle<norm_names_ScalarOpt_dim_dtype::schema> create_norm_names_ScalarOpt_dim_dtype_typed_handle() { |
7071 | return c10::Dispatcher::singleton() |
7072 | .findSchemaOrThrow(norm_names_ScalarOpt_dim_dtype::name, norm_names_ScalarOpt_dim_dtype::overload_name) |
7073 | .typed<norm_names_ScalarOpt_dim_dtype::schema>(); |
7074 | } |
7075 | |
7076 | // aten::norm.names_ScalarOpt_dim_dtype(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor |
7077 | at::Tensor norm_names_ScalarOpt_dim_dtype::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype) { |
7078 | |
7079 | static auto op = create_norm_names_ScalarOpt_dim_dtype_typed_handle(); |
7080 | return op.call(self, p, dim, keepdim, dtype); |
7081 | } |
7082 | |
7083 | // aten::norm.names_ScalarOpt_dim_dtype(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype) -> Tensor |
7084 | at::Tensor norm_names_ScalarOpt_dim_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype) { |
7085 | |
7086 | static auto op = create_norm_names_ScalarOpt_dim_dtype_typed_handle(); |
7087 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, dtype); |
7088 | } |
7089 | |
7090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_ScalarOpt_dim, name, "aten::norm" ) |
7091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_ScalarOpt_dim, overload_name, "names_ScalarOpt_dim" ) |
7092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_ScalarOpt_dim, schema_str, "norm.names_ScalarOpt_dim(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False) -> Tensor" ) |
7093 | |
7094 | // aten::norm.names_ScalarOpt_dim(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False) -> Tensor |
7095 | static C10_NOINLINE c10::TypedOperatorHandle<norm_names_ScalarOpt_dim::schema> create_norm_names_ScalarOpt_dim_typed_handle() { |
7096 | return c10::Dispatcher::singleton() |
7097 | .findSchemaOrThrow(norm_names_ScalarOpt_dim::name, norm_names_ScalarOpt_dim::overload_name) |
7098 | .typed<norm_names_ScalarOpt_dim::schema>(); |
7099 | } |
7100 | |
7101 | // aten::norm.names_ScalarOpt_dim(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False) -> Tensor |
7102 | at::Tensor norm_names_ScalarOpt_dim::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim) { |
7103 | |
7104 | static auto op = create_norm_names_ScalarOpt_dim_typed_handle(); |
7105 | return op.call(self, p, dim, keepdim); |
7106 | } |
7107 | |
7108 | // aten::norm.names_ScalarOpt_dim(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False) -> Tensor |
7109 | at::Tensor norm_names_ScalarOpt_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim) { |
7110 | |
7111 | static auto op = create_norm_names_ScalarOpt_dim_typed_handle(); |
7112 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim); |
7113 | } |
7114 | |
7115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_dtype_out, name, "aten::norm" ) |
7116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_dtype_out, overload_name, "names_dtype_out" ) |
7117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_dtype_out, schema_str, "norm.names_dtype_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!)" ) |
7118 | |
7119 | // aten::norm.names_dtype_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
7120 | static C10_NOINLINE c10::TypedOperatorHandle<norm_names_dtype_out::schema> create_norm_names_dtype_out_typed_handle() { |
7121 | return c10::Dispatcher::singleton() |
7122 | .findSchemaOrThrow(norm_names_dtype_out::name, norm_names_dtype_out::overload_name) |
7123 | .typed<norm_names_dtype_out::schema>(); |
7124 | } |
7125 | |
7126 | // aten::norm.names_dtype_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
7127 | at::Tensor & norm_names_dtype_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype, at::Tensor & out) { |
7128 | |
7129 | static auto op = create_norm_names_dtype_out_typed_handle(); |
7130 | return op.call(self, p, dim, keepdim, dtype, out); |
7131 | } |
7132 | |
7133 | // aten::norm.names_dtype_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
7134 | at::Tensor & norm_names_dtype_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim, at::ScalarType dtype, at::Tensor & out) { |
7135 | |
7136 | static auto op = create_norm_names_dtype_out_typed_handle(); |
7137 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, dtype, out); |
7138 | } |
7139 | |
7140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_out, name, "aten::norm" ) |
7141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_out, overload_name, "names_out" ) |
7142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_names_out, schema_str, "norm.names_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
7143 | |
7144 | // aten::norm.names_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7145 | static C10_NOINLINE c10::TypedOperatorHandle<norm_names_out::schema> create_norm_names_out_typed_handle() { |
7146 | return c10::Dispatcher::singleton() |
7147 | .findSchemaOrThrow(norm_names_out::name, norm_names_out::overload_name) |
7148 | .typed<norm_names_out::schema>(); |
7149 | } |
7150 | |
7151 | // aten::norm.names_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7152 | at::Tensor & norm_names_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim, at::Tensor & out) { |
7153 | |
7154 | static auto op = create_norm_names_out_typed_handle(); |
7155 | return op.call(self, p, dim, keepdim, out); |
7156 | } |
7157 | |
7158 | // aten::norm.names_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7159 | at::Tensor & norm_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::DimnameList dim, bool keepdim, at::Tensor & out) { |
7160 | |
7161 | static auto op = create_norm_names_out_typed_handle(); |
7162 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, out); |
7163 | } |
7164 | |
7165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm, name, "aten::nuclear_norm" ) |
7166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm, overload_name, "" ) |
7167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm, schema_str, "nuclear_norm(Tensor self, bool keepdim=False) -> Tensor" ) |
7168 | |
7169 | // aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor |
7170 | static C10_NOINLINE c10::TypedOperatorHandle<nuclear_norm::schema> create_nuclear_norm_typed_handle() { |
7171 | return c10::Dispatcher::singleton() |
7172 | .findSchemaOrThrow(nuclear_norm::name, nuclear_norm::overload_name) |
7173 | .typed<nuclear_norm::schema>(); |
7174 | } |
7175 | |
7176 | // aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor |
7177 | at::Tensor nuclear_norm::call(const at::Tensor & self, bool keepdim) { |
7178 | |
7179 | static auto op = create_nuclear_norm_typed_handle(); |
7180 | return op.call(self, keepdim); |
7181 | } |
7182 | |
7183 | // aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor |
7184 | at::Tensor nuclear_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool keepdim) { |
7185 | |
7186 | static auto op = create_nuclear_norm_typed_handle(); |
7187 | return op.redispatch(dispatchKeySet, self, keepdim); |
7188 | } |
7189 | |
7190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_out, name, "aten::nuclear_norm" ) |
7191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_out, overload_name, "out" ) |
7192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_out, schema_str, "nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
7193 | |
7194 | // aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7195 | static C10_NOINLINE c10::TypedOperatorHandle<nuclear_norm_out::schema> create_nuclear_norm_out_typed_handle() { |
7196 | return c10::Dispatcher::singleton() |
7197 | .findSchemaOrThrow(nuclear_norm_out::name, nuclear_norm_out::overload_name) |
7198 | .typed<nuclear_norm_out::schema>(); |
7199 | } |
7200 | |
7201 | // aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7202 | at::Tensor & nuclear_norm_out::call(const at::Tensor & self, bool keepdim, at::Tensor & out) { |
7203 | |
7204 | static auto op = create_nuclear_norm_out_typed_handle(); |
7205 | return op.call(self, keepdim, out); |
7206 | } |
7207 | |
7208 | // aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7209 | at::Tensor & nuclear_norm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool keepdim, at::Tensor & out) { |
7210 | |
7211 | static auto op = create_nuclear_norm_out_typed_handle(); |
7212 | return op.redispatch(dispatchKeySet, self, keepdim, out); |
7213 | } |
7214 | |
7215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_dim, name, "aten::nuclear_norm" ) |
7216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_dim, overload_name, "dim" ) |
7217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_dim, schema_str, "nuclear_norm.dim(Tensor self, int[2] dim, bool keepdim=False) -> Tensor" ) |
7218 | |
7219 | // aten::nuclear_norm.dim(Tensor self, int[2] dim, bool keepdim=False) -> Tensor |
7220 | static C10_NOINLINE c10::TypedOperatorHandle<nuclear_norm_dim::schema> create_nuclear_norm_dim_typed_handle() { |
7221 | return c10::Dispatcher::singleton() |
7222 | .findSchemaOrThrow(nuclear_norm_dim::name, nuclear_norm_dim::overload_name) |
7223 | .typed<nuclear_norm_dim::schema>(); |
7224 | } |
7225 | |
7226 | // aten::nuclear_norm.dim(Tensor self, int[2] dim, bool keepdim=False) -> Tensor |
7227 | at::Tensor nuclear_norm_dim::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim) { |
7228 | |
7229 | static auto op = create_nuclear_norm_dim_typed_handle(); |
7230 | return op.call(self, dim, keepdim); |
7231 | } |
7232 | |
7233 | // aten::nuclear_norm.dim(Tensor self, int[2] dim, bool keepdim=False) -> Tensor |
7234 | at::Tensor nuclear_norm_dim::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim) { |
7235 | |
7236 | static auto op = create_nuclear_norm_dim_typed_handle(); |
7237 | return op.redispatch(dispatchKeySet, self, dim, keepdim); |
7238 | } |
7239 | |
7240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_dim_out, name, "aten::nuclear_norm" ) |
7241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_dim_out, overload_name, "dim_out" ) |
7242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nuclear_norm_dim_out, schema_str, "nuclear_norm.dim_out(Tensor self, int[2] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
7243 | |
7244 | // aten::nuclear_norm.dim_out(Tensor self, int[2] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7245 | static C10_NOINLINE c10::TypedOperatorHandle<nuclear_norm_dim_out::schema> create_nuclear_norm_dim_out_typed_handle() { |
7246 | return c10::Dispatcher::singleton() |
7247 | .findSchemaOrThrow(nuclear_norm_dim_out::name, nuclear_norm_dim_out::overload_name) |
7248 | .typed<nuclear_norm_dim_out::schema>(); |
7249 | } |
7250 | |
7251 | // aten::nuclear_norm.dim_out(Tensor self, int[2] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7252 | at::Tensor & nuclear_norm_dim_out::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
7253 | |
7254 | static auto op = create_nuclear_norm_dim_out_typed_handle(); |
7255 | return op.call(self, dim, keepdim, out); |
7256 | } |
7257 | |
7258 | // aten::nuclear_norm.dim_out(Tensor self, int[2] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) |
7259 | at::Tensor & nuclear_norm_dim_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, at::Tensor & out) { |
7260 | |
7261 | static auto op = create_nuclear_norm_dim_out_typed_handle(); |
7262 | return op.redispatch(dispatchKeySet, self, dim, keepdim, out); |
7263 | } |
7264 | |
7265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csc_tensor_unsafe, name, "aten::_sparse_csc_tensor_unsafe" ) |
7266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csc_tensor_unsafe, overload_name, "" ) |
7267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csc_tensor_unsafe, schema_str, "_sparse_csc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
7268 | |
7269 | // aten::_sparse_csc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
7270 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_csc_tensor_unsafe::schema> create__sparse_csc_tensor_unsafe_typed_handle() { |
7271 | return c10::Dispatcher::singleton() |
7272 | .findSchemaOrThrow(_sparse_csc_tensor_unsafe::name, _sparse_csc_tensor_unsafe::overload_name) |
7273 | .typed<_sparse_csc_tensor_unsafe::schema>(); |
7274 | } |
7275 | |
7276 | // aten::_sparse_csc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
7277 | at::Tensor _sparse_csc_tensor_unsafe::call(const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
7278 | |
7279 | static auto op = create__sparse_csc_tensor_unsafe_typed_handle(); |
7280 | return op.call(ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); |
7281 | } |
7282 | |
7283 | // aten::_sparse_csc_tensor_unsafe(Tensor ccol_indices, Tensor row_indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
7284 | at::Tensor _sparse_csc_tensor_unsafe::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & ccol_indices, const at::Tensor & row_indices, const at::Tensor & values, at::IntArrayRef size, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
7285 | |
7286 | static auto op = create__sparse_csc_tensor_unsafe_typed_handle(); |
7287 | return op.redispatch(dispatchKeySet, ccol_indices, row_indices, values, size, dtype, layout, device, pin_memory); |
7288 | } |
7289 | |
7290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_coo_tensor_args, name, "aten::_validate_sparse_coo_tensor_args" ) |
7291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_coo_tensor_args, overload_name, "" ) |
7292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_validate_sparse_coo_tensor_args, schema_str, "_validate_sparse_coo_tensor_args(Tensor indices, Tensor values, int[] size) -> ()" ) |
7293 | |
7294 | // aten::_validate_sparse_coo_tensor_args(Tensor indices, Tensor values, int[] size) -> () |
7295 | static C10_NOINLINE c10::TypedOperatorHandle<_validate_sparse_coo_tensor_args::schema> create__validate_sparse_coo_tensor_args_typed_handle() { |
7296 | return c10::Dispatcher::singleton() |
7297 | .findSchemaOrThrow(_validate_sparse_coo_tensor_args::name, _validate_sparse_coo_tensor_args::overload_name) |
7298 | .typed<_validate_sparse_coo_tensor_args::schema>(); |
7299 | } |
7300 | |
7301 | // aten::_validate_sparse_coo_tensor_args(Tensor indices, Tensor values, int[] size) -> () |
7302 | void _validate_sparse_coo_tensor_args::call(const at::Tensor & indices, const at::Tensor & values, at::IntArrayRef size) { |
7303 | |
7304 | static auto op = create__validate_sparse_coo_tensor_args_typed_handle(); |
7305 | return op.call(indices, values, size); |
7306 | } |
7307 | |
7308 | // aten::_validate_sparse_coo_tensor_args(Tensor indices, Tensor values, int[] size) -> () |
7309 | void _validate_sparse_coo_tensor_args::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & indices, const at::Tensor & values, at::IntArrayRef size) { |
7310 | |
7311 | static auto op = create__validate_sparse_coo_tensor_args_typed_handle(); |
7312 | return op.redispatch(dispatchKeySet, indices, values, size); |
7313 | } |
7314 | |
7315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_with_dims_and_tensors, name, "aten::_sparse_coo_tensor_with_dims_and_tensors" ) |
7316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_with_dims_and_tensors, overload_name, "" ) |
7317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_with_dims_and_tensors, schema_str, "_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor" ) |
7318 | |
7319 | // aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
7320 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_coo_tensor_with_dims_and_tensors::schema> create__sparse_coo_tensor_with_dims_and_tensors_typed_handle() { |
7321 | return c10::Dispatcher::singleton() |
7322 | .findSchemaOrThrow(_sparse_coo_tensor_with_dims_and_tensors::name, _sparse_coo_tensor_with_dims_and_tensors::overload_name) |
7323 | .typed<_sparse_coo_tensor_with_dims_and_tensors::schema>(); |
7324 | } |
7325 | |
7326 | // aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
7327 | at::Tensor _sparse_coo_tensor_with_dims_and_tensors::call(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, 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) { |
7328 | |
7329 | static auto op = create__sparse_coo_tensor_with_dims_and_tensors_typed_handle(); |
7330 | return op.call(sparse_dim, dense_dim, size, indices, values, dtype, layout, device, pin_memory); |
7331 | } |
7332 | |
7333 | // aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor |
7334 | at::Tensor _sparse_coo_tensor_with_dims_and_tensors::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, 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) { |
7335 | |
7336 | static auto op = create__sparse_coo_tensor_with_dims_and_tensors_typed_handle(); |
7337 | return op.redispatch(dispatchKeySet, sparse_dim, dense_dim, size, indices, values, dtype, layout, device, pin_memory); |
7338 | } |
7339 | |
7340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_dense, name, "aten::_to_dense" ) |
7341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_dense, overload_name, "" ) |
7342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_dense, schema_str, "_to_dense(Tensor self, ScalarType? dtype=None) -> Tensor" ) |
7343 | |
7344 | // aten::_to_dense(Tensor self, ScalarType? dtype=None) -> Tensor |
7345 | static C10_NOINLINE c10::TypedOperatorHandle<_to_dense::schema> create__to_dense_typed_handle() { |
7346 | return c10::Dispatcher::singleton() |
7347 | .findSchemaOrThrow(_to_dense::name, _to_dense::overload_name) |
7348 | .typed<_to_dense::schema>(); |
7349 | } |
7350 | |
7351 | // aten::_to_dense(Tensor self, ScalarType? dtype=None) -> Tensor |
7352 | at::Tensor _to_dense::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
7353 | |
7354 | static auto op = create__to_dense_typed_handle(); |
7355 | return op.call(self, dtype); |
7356 | } |
7357 | |
7358 | // aten::_to_dense(Tensor self, ScalarType? dtype=None) -> Tensor |
7359 | at::Tensor _to_dense::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype) { |
7360 | |
7361 | static auto op = create__to_dense_typed_handle(); |
7362 | return op.redispatch(dispatchKeySet, self, dtype); |
7363 | } |
7364 | |
7365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_coalesced, name, "aten::is_coalesced" ) |
7366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_coalesced, overload_name, "" ) |
7367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(is_coalesced, schema_str, "is_coalesced(Tensor self) -> bool" ) |
7368 | |
7369 | // aten::is_coalesced(Tensor self) -> bool |
7370 | static C10_NOINLINE c10::TypedOperatorHandle<is_coalesced::schema> create_is_coalesced_typed_handle() { |
7371 | return c10::Dispatcher::singleton() |
7372 | .findSchemaOrThrow(is_coalesced::name, is_coalesced::overload_name) |
7373 | .typed<is_coalesced::schema>(); |
7374 | } |
7375 | |
7376 | // aten::is_coalesced(Tensor self) -> bool |
7377 | bool is_coalesced::call(const at::Tensor & self) { |
7378 | |
7379 | static auto op = create_is_coalesced_typed_handle(); |
7380 | return op.call(self); |
7381 | } |
7382 | |
7383 | // aten::is_coalesced(Tensor self) -> bool |
7384 | bool is_coalesced::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
7385 | |
7386 | static auto op = create_is_coalesced_typed_handle(); |
7387 | return op.redispatch(dispatchKeySet, self); |
7388 | } |
7389 | |
7390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced_, name, "aten::_coalesced_" ) |
7391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced_, overload_name, "" ) |
7392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced_, schema_str, "_coalesced_(Tensor(a!) self, bool coalesced) -> Tensor(a!)" ) |
7393 | |
7394 | // aten::_coalesced_(Tensor(a!) self, bool coalesced) -> Tensor(a!) |
7395 | static C10_NOINLINE c10::TypedOperatorHandle<_coalesced_::schema> create__coalesced__typed_handle() { |
7396 | return c10::Dispatcher::singleton() |
7397 | .findSchemaOrThrow(_coalesced_::name, _coalesced_::overload_name) |
7398 | .typed<_coalesced_::schema>(); |
7399 | } |
7400 | |
7401 | // aten::_coalesced_(Tensor(a!) self, bool coalesced) -> Tensor(a!) |
7402 | at::Tensor & _coalesced_::call(at::Tensor & self, bool coalesced) { |
7403 | |
7404 | static auto op = create__coalesced__typed_handle(); |
7405 | return op.call(self, coalesced); |
7406 | } |
7407 | |
7408 | // aten::_coalesced_(Tensor(a!) self, bool coalesced) -> Tensor(a!) |
7409 | at::Tensor & _coalesced_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, bool coalesced) { |
7410 | |
7411 | static auto op = create__coalesced__typed_handle(); |
7412 | return op.redispatch(dispatchKeySet, self, coalesced); |
7413 | } |
7414 | |
7415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(indices, name, "aten::indices" ) |
7416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(indices, overload_name, "" ) |
7417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(indices, schema_str, "indices(Tensor(a) self) -> Tensor(a)" ) |
7418 | |
7419 | // aten::indices(Tensor(a) self) -> Tensor(a) |
7420 | static C10_NOINLINE c10::TypedOperatorHandle<indices::schema> create_indices_typed_handle() { |
7421 | return c10::Dispatcher::singleton() |
7422 | .findSchemaOrThrow(indices::name, indices::overload_name) |
7423 | .typed<indices::schema>(); |
7424 | } |
7425 | |
7426 | // aten::indices(Tensor(a) self) -> Tensor(a) |
7427 | at::Tensor indices::call(const at::Tensor & self) { |
7428 | |
7429 | static auto op = create_indices_typed_handle(); |
7430 | return op.call(self); |
7431 | } |
7432 | |
7433 | // aten::indices(Tensor(a) self) -> Tensor(a) |
7434 | at::Tensor indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
7435 | |
7436 | static auto op = create_indices_typed_handle(); |
7437 | return op.redispatch(dispatchKeySet, self); |
7438 | } |
7439 | |
7440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices, name, "aten::col_indices" ) |
7441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices, overload_name, "" ) |
7442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(col_indices, schema_str, "col_indices(Tensor(a) self) -> Tensor(a)" ) |
7443 | |
7444 | // aten::col_indices(Tensor(a) self) -> Tensor(a) |
7445 | static C10_NOINLINE c10::TypedOperatorHandle<col_indices::schema> create_col_indices_typed_handle() { |
7446 | return c10::Dispatcher::singleton() |
7447 | .findSchemaOrThrow(col_indices::name, col_indices::overload_name) |
7448 | .typed<col_indices::schema>(); |
7449 | } |
7450 | |
7451 | // aten::col_indices(Tensor(a) self) -> Tensor(a) |
7452 | at::Tensor col_indices::call(const at::Tensor & self) { |
7453 | |
7454 | static auto op = create_col_indices_typed_handle(); |
7455 | return op.call(self); |
7456 | } |
7457 | |
7458 | // aten::col_indices(Tensor(a) self) -> Tensor(a) |
7459 | at::Tensor col_indices::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
7460 | |
7461 | static auto op = create_col_indices_typed_handle(); |
7462 | return op.redispatch(dispatchKeySet, self); |
7463 | } |
7464 | |
7465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hspmm_out, name, "aten::hspmm" ) |
7466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hspmm_out, overload_name, "out" ) |
7467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hspmm_out, schema_str, "hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)" ) |
7468 | |
7469 | // aten::hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) |
7470 | static C10_NOINLINE c10::TypedOperatorHandle<hspmm_out::schema> create_hspmm_out_typed_handle() { |
7471 | return c10::Dispatcher::singleton() |
7472 | .findSchemaOrThrow(hspmm_out::name, hspmm_out::overload_name) |
7473 | .typed<hspmm_out::schema>(); |
7474 | } |
7475 | |
7476 | // aten::hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) |
7477 | at::Tensor & hspmm_out::call(const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out) { |
7478 | |
7479 | static auto op = create_hspmm_out_typed_handle(); |
7480 | return op.call(mat1, mat2, out); |
7481 | } |
7482 | |
7483 | // aten::hspmm.out(Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!) |
7484 | at::Tensor & hspmm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mat1, const at::Tensor & mat2, at::Tensor & out) { |
7485 | |
7486 | static auto op = create_hspmm_out_typed_handle(); |
7487 | return op.redispatch(dispatchKeySet, mat1, mat2, out); |
7488 | } |
7489 | |
7490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hspmm, name, "aten::hspmm" ) |
7491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hspmm, overload_name, "" ) |
7492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hspmm, schema_str, "hspmm(Tensor mat1, Tensor mat2) -> Tensor" ) |
7493 | |
7494 | // aten::hspmm(Tensor mat1, Tensor mat2) -> Tensor |
7495 | static C10_NOINLINE c10::TypedOperatorHandle<hspmm::schema> create_hspmm_typed_handle() { |
7496 | return c10::Dispatcher::singleton() |
7497 | .findSchemaOrThrow(hspmm::name, hspmm::overload_name) |
7498 | .typed<hspmm::schema>(); |
7499 | } |
7500 | |
7501 | // aten::hspmm(Tensor mat1, Tensor mat2) -> Tensor |
7502 | at::Tensor hspmm::call(const at::Tensor & mat1, const at::Tensor & mat2) { |
7503 | |
7504 | static auto op = create_hspmm_typed_handle(); |
7505 | return op.call(mat1, mat2); |
7506 | } |
7507 | |
7508 | // aten::hspmm(Tensor mat1, Tensor mat2) -> Tensor |
7509 | at::Tensor hspmm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & mat1, const at::Tensor & mat2) { |
7510 | |
7511 | static auto op = create_hspmm_typed_handle(); |
7512 | return op.redispatch(dispatchKeySet, mat1, mat2); |
7513 | } |
7514 | |
7515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsc, name, "aten::to_sparse_bsc" ) |
7516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsc, overload_name, "" ) |
7517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsc, schema_str, "to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor" ) |
7518 | |
7519 | // aten::to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor |
7520 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_bsc::schema> create_to_sparse_bsc_typed_handle() { |
7521 | return c10::Dispatcher::singleton() |
7522 | .findSchemaOrThrow(to_sparse_bsc::name, to_sparse_bsc::overload_name) |
7523 | .typed<to_sparse_bsc::schema>(); |
7524 | } |
7525 | |
7526 | // aten::to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor |
7527 | at::Tensor to_sparse_bsc::call(const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim) { |
7528 | |
7529 | static auto op = create_to_sparse_bsc_typed_handle(); |
7530 | return op.call(self, blocksize, dense_dim); |
7531 | } |
7532 | |
7533 | // aten::to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor |
7534 | at::Tensor to_sparse_bsc::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim) { |
7535 | |
7536 | static auto op = create_to_sparse_bsc_typed_handle(); |
7537 | return op.redispatch(dispatchKeySet, self, blocksize, dense_dim); |
7538 | } |
7539 | |
7540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_dynamic, name, "aten::quantize_per_tensor_dynamic" ) |
7541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_dynamic, overload_name, "" ) |
7542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_dynamic, schema_str, "quantize_per_tensor_dynamic(Tensor self, ScalarType dtype, bool reduce_range) -> Tensor" ) |
7543 | |
7544 | // aten::quantize_per_tensor_dynamic(Tensor self, ScalarType dtype, bool reduce_range) -> Tensor |
7545 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor_dynamic::schema> create_quantize_per_tensor_dynamic_typed_handle() { |
7546 | return c10::Dispatcher::singleton() |
7547 | .findSchemaOrThrow(quantize_per_tensor_dynamic::name, quantize_per_tensor_dynamic::overload_name) |
7548 | .typed<quantize_per_tensor_dynamic::schema>(); |
7549 | } |
7550 | |
7551 | // aten::quantize_per_tensor_dynamic(Tensor self, ScalarType dtype, bool reduce_range) -> Tensor |
7552 | at::Tensor quantize_per_tensor_dynamic::call(const at::Tensor & self, at::ScalarType dtype, bool reduce_range) { |
7553 | |
7554 | static auto op = create_quantize_per_tensor_dynamic_typed_handle(); |
7555 | return op.call(self, dtype, reduce_range); |
7556 | } |
7557 | |
7558 | // aten::quantize_per_tensor_dynamic(Tensor self, ScalarType dtype, bool reduce_range) -> Tensor |
7559 | at::Tensor quantize_per_tensor_dynamic::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype, bool reduce_range) { |
7560 | |
7561 | static auto op = create_quantize_per_tensor_dynamic_typed_handle(); |
7562 | return op.redispatch(dispatchKeySet, self, dtype, reduce_range); |
7563 | } |
7564 | |
7565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor, name, "aten::quantize_per_tensor" ) |
7566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor, overload_name, "" ) |
7567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor, schema_str, "quantize_per_tensor(Tensor self, float scale, int zero_point, ScalarType dtype) -> Tensor" ) |
7568 | |
7569 | // aten::quantize_per_tensor(Tensor self, float scale, int zero_point, ScalarType dtype) -> Tensor |
7570 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor::schema> create_quantize_per_tensor_typed_handle() { |
7571 | return c10::Dispatcher::singleton() |
7572 | .findSchemaOrThrow(quantize_per_tensor::name, quantize_per_tensor::overload_name) |
7573 | .typed<quantize_per_tensor::schema>(); |
7574 | } |
7575 | |
7576 | // aten::quantize_per_tensor(Tensor self, float scale, int zero_point, ScalarType dtype) -> Tensor |
7577 | at::Tensor quantize_per_tensor::call(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype) { |
7578 | |
7579 | static auto op = create_quantize_per_tensor_typed_handle(); |
7580 | return op.call(self, scale, zero_point, dtype); |
7581 | } |
7582 | |
7583 | // aten::quantize_per_tensor(Tensor self, float scale, int zero_point, ScalarType dtype) -> Tensor |
7584 | at::Tensor quantize_per_tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype) { |
7585 | |
7586 | static auto op = create_quantize_per_tensor_typed_handle(); |
7587 | return op.redispatch(dispatchKeySet, self, scale, zero_point, dtype); |
7588 | } |
7589 | |
7590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensor_qparams, name, "aten::quantize_per_tensor" ) |
7591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensor_qparams, overload_name, "tensor_qparams" ) |
7592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensor_qparams, schema_str, "quantize_per_tensor.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype) -> Tensor" ) |
7593 | |
7594 | // aten::quantize_per_tensor.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype) -> Tensor |
7595 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor_tensor_qparams::schema> create_quantize_per_tensor_tensor_qparams_typed_handle() { |
7596 | return c10::Dispatcher::singleton() |
7597 | .findSchemaOrThrow(quantize_per_tensor_tensor_qparams::name, quantize_per_tensor_tensor_qparams::overload_name) |
7598 | .typed<quantize_per_tensor_tensor_qparams::schema>(); |
7599 | } |
7600 | |
7601 | // aten::quantize_per_tensor.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype) -> Tensor |
7602 | at::Tensor quantize_per_tensor_tensor_qparams::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype) { |
7603 | |
7604 | static auto op = create_quantize_per_tensor_tensor_qparams_typed_handle(); |
7605 | return op.call(self, scale, zero_point, dtype); |
7606 | } |
7607 | |
7608 | // aten::quantize_per_tensor.tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype) -> Tensor |
7609 | at::Tensor quantize_per_tensor_tensor_qparams::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype) { |
7610 | |
7611 | static auto op = create_quantize_per_tensor_tensor_qparams_typed_handle(); |
7612 | return op.redispatch(dispatchKeySet, self, scale, zero_point, dtype); |
7613 | } |
7614 | |
7615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensors, name, "aten::quantize_per_tensor" ) |
7616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensors, overload_name, "tensors" ) |
7617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensors, schema_str, "quantize_per_tensor.tensors(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype) -> Tensor[]" ) |
7618 | |
7619 | // aten::quantize_per_tensor.tensors(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype) -> Tensor[] |
7620 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor_tensors::schema> create_quantize_per_tensor_tensors_typed_handle() { |
7621 | return c10::Dispatcher::singleton() |
7622 | .findSchemaOrThrow(quantize_per_tensor_tensors::name, quantize_per_tensor_tensors::overload_name) |
7623 | .typed<quantize_per_tensor_tensors::schema>(); |
7624 | } |
7625 | |
7626 | // aten::quantize_per_tensor.tensors(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype) -> Tensor[] |
7627 | ::std::vector<at::Tensor> quantize_per_tensor_tensors::call(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype) { |
7628 | |
7629 | static auto op = create_quantize_per_tensor_tensors_typed_handle(); |
7630 | return op.call(tensors, scales, zero_points, dtype); |
7631 | } |
7632 | |
7633 | // aten::quantize_per_tensor.tensors(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype) -> Tensor[] |
7634 | ::std::vector<at::Tensor> quantize_per_tensor_tensors::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype) { |
7635 | |
7636 | static auto op = create_quantize_per_tensor_tensors_typed_handle(); |
7637 | return op.redispatch(dispatchKeySet, tensors, scales, zero_points, dtype); |
7638 | } |
7639 | |
7640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask, name, "aten::fake_quantize_per_tensor_affine_cachemask" ) |
7641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask, overload_name, "" ) |
7642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask, schema_str, "fake_quantize_per_tensor_affine_cachemask(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> (Tensor output, Tensor mask)" ) |
7643 | |
7644 | // aten::fake_quantize_per_tensor_affine_cachemask(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
7645 | static C10_NOINLINE c10::TypedOperatorHandle<fake_quantize_per_tensor_affine_cachemask::schema> create_fake_quantize_per_tensor_affine_cachemask_typed_handle() { |
7646 | return c10::Dispatcher::singleton() |
7647 | .findSchemaOrThrow(fake_quantize_per_tensor_affine_cachemask::name, fake_quantize_per_tensor_affine_cachemask::overload_name) |
7648 | .typed<fake_quantize_per_tensor_affine_cachemask::schema>(); |
7649 | } |
7650 | |
7651 | // aten::fake_quantize_per_tensor_affine_cachemask(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
7652 | ::std::tuple<at::Tensor,at::Tensor> fake_quantize_per_tensor_affine_cachemask::call(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max) { |
7653 | |
7654 | static auto op = create_fake_quantize_per_tensor_affine_cachemask_typed_handle(); |
7655 | return op.call(self, scale, zero_point, quant_min, quant_max); |
7656 | } |
7657 | |
7658 | // aten::fake_quantize_per_tensor_affine_cachemask(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
7659 | ::std::tuple<at::Tensor,at::Tensor> fake_quantize_per_tensor_affine_cachemask::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max) { |
7660 | |
7661 | static auto op = create_fake_quantize_per_tensor_affine_cachemask_typed_handle(); |
7662 | return op.redispatch(dispatchKeySet, self, scale, zero_point, quant_min, quant_max); |
7663 | } |
7664 | |
7665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams, name, "aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams" ) |
7666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams, overload_name, "" ) |
7667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams, schema_str, "_fake_quantize_per_tensor_affine_cachemask_tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max) -> (Tensor output, Tensor mask)" ) |
7668 | |
7669 | // aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
7670 | static C10_NOINLINE c10::TypedOperatorHandle<_fake_quantize_per_tensor_affine_cachemask_tensor_qparams::schema> create__fake_quantize_per_tensor_affine_cachemask_tensor_qparams_typed_handle() { |
7671 | return c10::Dispatcher::singleton() |
7672 | .findSchemaOrThrow(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams::name, _fake_quantize_per_tensor_affine_cachemask_tensor_qparams::overload_name) |
7673 | .typed<_fake_quantize_per_tensor_affine_cachemask_tensor_qparams::schema>(); |
7674 | } |
7675 | |
7676 | // aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
7677 | ::std::tuple<at::Tensor,at::Tensor> _fake_quantize_per_tensor_affine_cachemask_tensor_qparams::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max) { |
7678 | |
7679 | static auto op = create__fake_quantize_per_tensor_affine_cachemask_tensor_qparams_typed_handle(); |
7680 | return op.call(self, scale, zero_point, fake_quant_enabled, quant_min, quant_max); |
7681 | } |
7682 | |
7683 | // aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max) -> (Tensor output, Tensor mask) |
7684 | ::std::tuple<at::Tensor,at::Tensor> _fake_quantize_per_tensor_affine_cachemask_tensor_qparams::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max) { |
7685 | |
7686 | static auto op = create__fake_quantize_per_tensor_affine_cachemask_tensor_qparams_typed_handle(); |
7687 | return op.redispatch(dispatchKeySet, self, scale, zero_point, fake_quant_enabled, quant_min, quant_max); |
7688 | } |
7689 | |
7690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_learnable_per_tensor_affine, name, "aten::_fake_quantize_learnable_per_tensor_affine" ) |
7691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_learnable_per_tensor_affine, overload_name, "" ) |
7692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_learnable_per_tensor_affine, schema_str, "_fake_quantize_learnable_per_tensor_affine(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor" ) |
7693 | |
7694 | // aten::_fake_quantize_learnable_per_tensor_affine(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor |
7695 | static C10_NOINLINE c10::TypedOperatorHandle<_fake_quantize_learnable_per_tensor_affine::schema> create__fake_quantize_learnable_per_tensor_affine_typed_handle() { |
7696 | return c10::Dispatcher::singleton() |
7697 | .findSchemaOrThrow(_fake_quantize_learnable_per_tensor_affine::name, _fake_quantize_learnable_per_tensor_affine::overload_name) |
7698 | .typed<_fake_quantize_learnable_per_tensor_affine::schema>(); |
7699 | } |
7700 | |
7701 | // aten::_fake_quantize_learnable_per_tensor_affine(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor |
7702 | at::Tensor _fake_quantize_learnable_per_tensor_affine::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor) { |
7703 | |
7704 | static auto op = create__fake_quantize_learnable_per_tensor_affine_typed_handle(); |
7705 | return op.call(self, scale, zero_point, quant_min, quant_max, grad_factor); |
7706 | } |
7707 | |
7708 | // aten::_fake_quantize_learnable_per_tensor_affine(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0) -> Tensor |
7709 | at::Tensor _fake_quantize_learnable_per_tensor_affine::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor) { |
7710 | |
7711 | static auto op = create__fake_quantize_learnable_per_tensor_affine_typed_handle(); |
7712 | return op.redispatch(dispatchKeySet, self, scale, zero_point, quant_min, quant_max, grad_factor); |
7713 | } |
7714 | |
7715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(choose_qparams_optimized, name, "aten::choose_qparams_optimized" ) |
7716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(choose_qparams_optimized, overload_name, "" ) |
7717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(choose_qparams_optimized, schema_str, "choose_qparams_optimized(Tensor input, int numel, int n_bins, float ratio, int bit_width) -> (Tensor, Tensor)" ) |
7718 | |
7719 | // aten::choose_qparams_optimized(Tensor input, int numel, int n_bins, float ratio, int bit_width) -> (Tensor, Tensor) |
7720 | static C10_NOINLINE c10::TypedOperatorHandle<choose_qparams_optimized::schema> create_choose_qparams_optimized_typed_handle() { |
7721 | return c10::Dispatcher::singleton() |
7722 | .findSchemaOrThrow(choose_qparams_optimized::name, choose_qparams_optimized::overload_name) |
7723 | .typed<choose_qparams_optimized::schema>(); |
7724 | } |
7725 | |
7726 | // aten::choose_qparams_optimized(Tensor input, int numel, int n_bins, float ratio, int bit_width) -> (Tensor, Tensor) |
7727 | ::std::tuple<at::Tensor,at::Tensor> choose_qparams_optimized::call(const at::Tensor & input, int64_t numel, int64_t n_bins, double ratio, int64_t bit_width) { |
7728 | |
7729 | static auto op = create_choose_qparams_optimized_typed_handle(); |
7730 | return op.call(input, numel, n_bins, ratio, bit_width); |
7731 | } |
7732 | |
7733 | // aten::choose_qparams_optimized(Tensor input, int numel, int n_bins, float ratio, int bit_width) -> (Tensor, Tensor) |
7734 | ::std::tuple<at::Tensor,at::Tensor> choose_qparams_optimized::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, int64_t numel, int64_t n_bins, double ratio, int64_t bit_width) { |
7735 | |
7736 | static auto op = create_choose_qparams_optimized_typed_handle(); |
7737 | return op.redispatch(dispatchKeySet, input, numel, n_bins, ratio, bit_width); |
7738 | } |
7739 | |
7740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cartesian_prod, name, "aten::cartesian_prod" ) |
7741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cartesian_prod, overload_name, "" ) |
7742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cartesian_prod, schema_str, "cartesian_prod(Tensor[] tensors) -> Tensor" ) |
7743 | |
7744 | // aten::cartesian_prod(Tensor[] tensors) -> Tensor |
7745 | static C10_NOINLINE c10::TypedOperatorHandle<cartesian_prod::schema> create_cartesian_prod_typed_handle() { |
7746 | return c10::Dispatcher::singleton() |
7747 | .findSchemaOrThrow(cartesian_prod::name, cartesian_prod::overload_name) |
7748 | .typed<cartesian_prod::schema>(); |
7749 | } |
7750 | |
7751 | // aten::cartesian_prod(Tensor[] tensors) -> Tensor |
7752 | at::Tensor cartesian_prod::call(at::TensorList tensors) { |
7753 | |
7754 | static auto op = create_cartesian_prod_typed_handle(); |
7755 | return op.call(tensors); |
7756 | } |
7757 | |
7758 | // aten::cartesian_prod(Tensor[] tensors) -> Tensor |
7759 | at::Tensor cartesian_prod::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors) { |
7760 | |
7761 | static auto op = create_cartesian_prod_typed_handle(); |
7762 | return op.redispatch(dispatchKeySet, tensors); |
7763 | } |
7764 | |
7765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(promote_types, name, "aten::promote_types" ) |
7766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(promote_types, overload_name, "" ) |
7767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(promote_types, schema_str, "promote_types(ScalarType type1, ScalarType type2) -> ScalarType" ) |
7768 | |
7769 | // aten::promote_types(ScalarType type1, ScalarType type2) -> ScalarType |
7770 | static C10_NOINLINE c10::TypedOperatorHandle<promote_types::schema> create_promote_types_typed_handle() { |
7771 | return c10::Dispatcher::singleton() |
7772 | .findSchemaOrThrow(promote_types::name, promote_types::overload_name) |
7773 | .typed<promote_types::schema>(); |
7774 | } |
7775 | |
7776 | // aten::promote_types(ScalarType type1, ScalarType type2) -> ScalarType |
7777 | at::ScalarType promote_types::call(at::ScalarType type1, at::ScalarType type2) { |
7778 | |
7779 | static auto op = create_promote_types_typed_handle(); |
7780 | return op.call(type1, type2); |
7781 | } |
7782 | |
7783 | // aten::promote_types(ScalarType type1, ScalarType type2) -> ScalarType |
7784 | at::ScalarType promote_types::redispatch(c10::DispatchKeySet dispatchKeySet, at::ScalarType type1, at::ScalarType type2) { |
7785 | |
7786 | static auto op = create_promote_types_typed_handle(); |
7787 | return op.redispatch(dispatchKeySet, type1, type2); |
7788 | } |
7789 | |
7790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_local_scalar_dense, name, "aten::_local_scalar_dense" ) |
7791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_local_scalar_dense, overload_name, "" ) |
7792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_local_scalar_dense, schema_str, "_local_scalar_dense(Tensor self) -> Scalar" ) |
7793 | |
7794 | // aten::_local_scalar_dense(Tensor self) -> Scalar |
7795 | static C10_NOINLINE c10::TypedOperatorHandle<_local_scalar_dense::schema> create__local_scalar_dense_typed_handle() { |
7796 | return c10::Dispatcher::singleton() |
7797 | .findSchemaOrThrow(_local_scalar_dense::name, _local_scalar_dense::overload_name) |
7798 | .typed<_local_scalar_dense::schema>(); |
7799 | } |
7800 | |
7801 | // aten::_local_scalar_dense(Tensor self) -> Scalar |
7802 | at::Scalar _local_scalar_dense::call(const at::Tensor & self) { |
7803 | |
7804 | static auto op = create__local_scalar_dense_typed_handle(); |
7805 | return op.call(self); |
7806 | } |
7807 | |
7808 | // aten::_local_scalar_dense(Tensor self) -> Scalar |
7809 | at::Scalar _local_scalar_dense::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
7810 | |
7811 | static auto op = create__local_scalar_dense_typed_handle(); |
7812 | return op.redispatch(dispatchKeySet, self); |
7813 | } |
7814 | |
7815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_gru_cell_backward, name, "aten::_thnn_fused_gru_cell_backward" ) |
7816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_gru_cell_backward, overload_name, "" ) |
7817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_gru_cell_backward, schema_str, "_thnn_fused_gru_cell_backward(Tensor grad_hy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor)" ) |
7818 | |
7819 | // aten::_thnn_fused_gru_cell_backward(Tensor grad_hy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
7820 | static C10_NOINLINE c10::TypedOperatorHandle<_thnn_fused_gru_cell_backward::schema> create__thnn_fused_gru_cell_backward_typed_handle() { |
7821 | return c10::Dispatcher::singleton() |
7822 | .findSchemaOrThrow(_thnn_fused_gru_cell_backward::name, _thnn_fused_gru_cell_backward::overload_name) |
7823 | .typed<_thnn_fused_gru_cell_backward::schema>(); |
7824 | } |
7825 | |
7826 | // aten::_thnn_fused_gru_cell_backward(Tensor grad_hy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
7827 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_fused_gru_cell_backward::call(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias) { |
7828 | |
7829 | static auto op = create__thnn_fused_gru_cell_backward_typed_handle(); |
7830 | return op.call(grad_hy, workspace, has_bias); |
7831 | } |
7832 | |
7833 | // aten::_thnn_fused_gru_cell_backward(Tensor grad_hy, Tensor workspace, bool has_bias) -> (Tensor, Tensor, Tensor, Tensor, Tensor) |
7834 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _thnn_fused_gru_cell_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias) { |
7835 | |
7836 | static auto op = create__thnn_fused_gru_cell_backward_typed_handle(); |
7837 | return op.redispatch(dispatchKeySet, grad_hy, workspace, has_bias); |
7838 | } |
7839 | |
7840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_relu_input, name, "aten::rnn_relu" ) |
7841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_relu_input, overload_name, "input" ) |
7842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_relu_input, schema_str, "rnn_relu.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor)" ) |
7843 | |
7844 | // aten::rnn_relu.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor) |
7845 | static C10_NOINLINE c10::TypedOperatorHandle<rnn_relu_input::schema> create_rnn_relu_input_typed_handle() { |
7846 | return c10::Dispatcher::singleton() |
7847 | .findSchemaOrThrow(rnn_relu_input::name, rnn_relu_input::overload_name) |
7848 | .typed<rnn_relu_input::schema>(); |
7849 | } |
7850 | |
7851 | // aten::rnn_relu.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor) |
7852 | ::std::tuple<at::Tensor,at::Tensor> rnn_relu_input::call(const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first) { |
7853 | |
7854 | static auto op = create_rnn_relu_input_typed_handle(); |
7855 | return op.call(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); |
7856 | } |
7857 | |
7858 | // aten::rnn_relu.input(Tensor input, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor) |
7859 | ::std::tuple<at::Tensor,at::Tensor> rnn_relu_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional, bool batch_first) { |
7860 | |
7861 | static auto op = create_rnn_relu_input_typed_handle(); |
7862 | return op.redispatch(dispatchKeySet, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); |
7863 | } |
7864 | |
7865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_relu_data, name, "aten::rnn_relu" ) |
7866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_relu_data, overload_name, "data" ) |
7867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rnn_relu_data, schema_str, "rnn_relu.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor)" ) |
7868 | |
7869 | // aten::rnn_relu.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor) |
7870 | static C10_NOINLINE c10::TypedOperatorHandle<rnn_relu_data::schema> create_rnn_relu_data_typed_handle() { |
7871 | return c10::Dispatcher::singleton() |
7872 | .findSchemaOrThrow(rnn_relu_data::name, rnn_relu_data::overload_name) |
7873 | .typed<rnn_relu_data::schema>(); |
7874 | } |
7875 | |
7876 | // aten::rnn_relu.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor) |
7877 | ::std::tuple<at::Tensor,at::Tensor> rnn_relu_data::call(const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional) { |
7878 | |
7879 | static auto op = create_rnn_relu_data_typed_handle(); |
7880 | return op.call(data, batch_sizes, hx, params, has_biases, num_layers, dropout, train, bidirectional); |
7881 | } |
7882 | |
7883 | // aten::rnn_relu.data(Tensor data, Tensor batch_sizes, Tensor hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional) -> (Tensor, Tensor) |
7884 | ::std::tuple<at::Tensor,at::Tensor> rnn_relu_data::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & data, const at::Tensor & batch_sizes, const at::Tensor & hx, at::TensorList params, bool has_biases, int64_t num_layers, double dropout, bool train, bool bidirectional) { |
7885 | |
7886 | static auto op = create_rnn_relu_data_typed_handle(); |
7887 | return op.redispatch(dispatchKeySet, data, batch_sizes, hx, params, has_biases, num_layers, dropout, train, bidirectional); |
7888 | } |
7889 | |
7890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gru_cell, name, "aten::gru_cell" ) |
7891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gru_cell, overload_name, "" ) |
7892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gru_cell, schema_str, "gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor" ) |
7893 | |
7894 | // aten::gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor |
7895 | static C10_NOINLINE c10::TypedOperatorHandle<gru_cell::schema> create_gru_cell_typed_handle() { |
7896 | return c10::Dispatcher::singleton() |
7897 | .findSchemaOrThrow(gru_cell::name, gru_cell::overload_name) |
7898 | .typed<gru_cell::schema>(); |
7899 | } |
7900 | |
7901 | // aten::gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor |
7902 | at::Tensor gru_cell::call(const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const c10::optional<at::Tensor> & b_ih, const c10::optional<at::Tensor> & b_hh) { |
7903 | |
7904 | static auto op = create_gru_cell_typed_handle(); |
7905 | return op.call(input, hx, w_ih, w_hh, b_ih, b_hh); |
7906 | } |
7907 | |
7908 | // aten::gru_cell(Tensor input, Tensor hx, Tensor w_ih, Tensor w_hh, Tensor? b_ih=None, Tensor? b_hh=None) -> Tensor |
7909 | at::Tensor gru_cell::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & hx, const at::Tensor & w_ih, const at::Tensor & w_hh, const c10::optional<at::Tensor> & b_ih, const c10::optional<at::Tensor> & b_hh) { |
7910 | |
7911 | static auto op = create_gru_cell_typed_handle(); |
7912 | return op.redispatch(dispatchKeySet, input, hx, w_ih, w_hh, b_ih, b_hh); |
7913 | } |
7914 | |
7915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_lstm_cell, name, "aten::quantized_lstm_cell" ) |
7916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_lstm_cell, overload_name, "" ) |
7917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantized_lstm_cell, schema_str, "quantized_lstm_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, Tensor)" ) |
7918 | |
7919 | // aten::quantized_lstm_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, Tensor) |
7920 | static C10_NOINLINE c10::TypedOperatorHandle<quantized_lstm_cell::schema> create_quantized_lstm_cell_typed_handle() { |
7921 | return c10::Dispatcher::singleton() |
7922 | .findSchemaOrThrow(quantized_lstm_cell::name, quantized_lstm_cell::overload_name) |
7923 | .typed<quantized_lstm_cell::schema>(); |
7924 | } |
7925 | |
7926 | // aten::quantized_lstm_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, Tensor) |
7927 | ::std::tuple<at::Tensor,at::Tensor> quantized_lstm_cell::call(const at::Tensor & input, at::TensorList 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) { |
7928 | |
7929 | static auto op = create_quantized_lstm_cell_typed_handle(); |
7930 | 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); |
7931 | } |
7932 | |
7933 | // aten::quantized_lstm_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, Tensor) |
7934 | ::std::tuple<at::Tensor,at::Tensor> quantized_lstm_cell::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList 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) { |
7935 | |
7936 | static auto op = create_quantized_lstm_cell_typed_handle(); |
7937 | 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); |
7938 | } |
7939 | |
7940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Storage, name, "aten::set_" ) |
7941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Storage, overload_name, "source_Storage" ) |
7942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Storage, schema_str, "set_.source_Storage(Tensor(a!) self, Storage source) -> Tensor(a!)" ) |
7943 | |
7944 | // aten::set_.source_Storage(Tensor(a!) self, Storage source) -> Tensor(a!) |
7945 | static C10_NOINLINE c10::TypedOperatorHandle<set__source_Storage::schema> create_set__source_Storage_typed_handle() { |
7946 | return c10::Dispatcher::singleton() |
7947 | .findSchemaOrThrow(set__source_Storage::name, set__source_Storage::overload_name) |
7948 | .typed<set__source_Storage::schema>(); |
7949 | } |
7950 | |
7951 | // aten::set_.source_Storage(Tensor(a!) self, Storage source) -> Tensor(a!) |
7952 | at::Tensor & set__source_Storage::call(at::Tensor & self, at::Storage source) { |
7953 | |
7954 | static auto op = create_set__source_Storage_typed_handle(); |
7955 | return op.call(self, source); |
7956 | } |
7957 | |
7958 | // aten::set_.source_Storage(Tensor(a!) self, Storage source) -> Tensor(a!) |
7959 | at::Tensor & set__source_Storage::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Storage source) { |
7960 | |
7961 | static auto op = create_set__source_Storage_typed_handle(); |
7962 | return op.redispatch(dispatchKeySet, self, source); |
7963 | } |
7964 | |
7965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Storage_storage_offset, name, "aten::set_" ) |
7966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Storage_storage_offset, overload_name, "source_Storage_storage_offset" ) |
7967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Storage_storage_offset, schema_str, "set_.source_Storage_storage_offset(Tensor(a!) self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!)" ) |
7968 | |
7969 | // aten::set_.source_Storage_storage_offset(Tensor(a!) self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!) |
7970 | static C10_NOINLINE c10::TypedOperatorHandle<set__source_Storage_storage_offset::schema> create_set__source_Storage_storage_offset_typed_handle() { |
7971 | return c10::Dispatcher::singleton() |
7972 | .findSchemaOrThrow(set__source_Storage_storage_offset::name, set__source_Storage_storage_offset::overload_name) |
7973 | .typed<set__source_Storage_storage_offset::schema>(); |
7974 | } |
7975 | |
7976 | // aten::set_.source_Storage_storage_offset(Tensor(a!) self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!) |
7977 | at::Tensor & set__source_Storage_storage_offset::call(at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { |
7978 | |
7979 | static auto op = create_set__source_Storage_storage_offset_typed_handle(); |
7980 | return op.call(self, source, storage_offset, size, stride); |
7981 | } |
7982 | |
7983 | // aten::set_.source_Storage_storage_offset(Tensor(a!) self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!) |
7984 | at::Tensor & set__source_Storage_storage_offset::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { |
7985 | |
7986 | static auto op = create_set__source_Storage_storage_offset_typed_handle(); |
7987 | return op.redispatch(dispatchKeySet, self, source, storage_offset, size, stride); |
7988 | } |
7989 | |
7990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Tensor_storage_offset, name, "aten::set_" ) |
7991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Tensor_storage_offset, overload_name, "source_Tensor_storage_offset" ) |
7992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Tensor_storage_offset, schema_str, "set_.source_Tensor_storage_offset(Tensor(a!) self, Tensor source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!)" ) |
7993 | |
7994 | // aten::set_.source_Tensor_storage_offset(Tensor(a!) self, Tensor source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!) |
7995 | static C10_NOINLINE c10::TypedOperatorHandle<set__source_Tensor_storage_offset::schema> create_set__source_Tensor_storage_offset_typed_handle() { |
7996 | return c10::Dispatcher::singleton() |
7997 | .findSchemaOrThrow(set__source_Tensor_storage_offset::name, set__source_Tensor_storage_offset::overload_name) |
7998 | .typed<set__source_Tensor_storage_offset::schema>(); |
7999 | } |
8000 | |
8001 | // aten::set_.source_Tensor_storage_offset(Tensor(a!) self, Tensor source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!) |
8002 | at::Tensor & set__source_Tensor_storage_offset::call(at::Tensor & self, const at::Tensor & source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { |
8003 | |
8004 | static auto op = create_set__source_Tensor_storage_offset_typed_handle(); |
8005 | return op.call(self, source, storage_offset, size, stride); |
8006 | } |
8007 | |
8008 | // aten::set_.source_Tensor_storage_offset(Tensor(a!) self, Tensor source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor(a!) |
8009 | at::Tensor & set__source_Tensor_storage_offset::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { |
8010 | |
8011 | static auto op = create_set__source_Tensor_storage_offset_typed_handle(); |
8012 | return op.redispatch(dispatchKeySet, self, source, storage_offset, size, stride); |
8013 | } |
8014 | |
8015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Tensor, name, "aten::set_" ) |
8016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Tensor, overload_name, "source_Tensor" ) |
8017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set__source_Tensor, schema_str, "set_.source_Tensor(Tensor(a!) self, Tensor source) -> Tensor(a!)" ) |
8018 | |
8019 | // aten::set_.source_Tensor(Tensor(a!) self, Tensor source) -> Tensor(a!) |
8020 | static C10_NOINLINE c10::TypedOperatorHandle<set__source_Tensor::schema> create_set__source_Tensor_typed_handle() { |
8021 | return c10::Dispatcher::singleton() |
8022 | .findSchemaOrThrow(set__source_Tensor::name, set__source_Tensor::overload_name) |
8023 | .typed<set__source_Tensor::schema>(); |
8024 | } |
8025 | |
8026 | // aten::set_.source_Tensor(Tensor(a!) self, Tensor source) -> Tensor(a!) |
8027 | at::Tensor & set__source_Tensor::call(at::Tensor & self, const at::Tensor & source) { |
8028 | |
8029 | static auto op = create_set__source_Tensor_typed_handle(); |
8030 | return op.call(self, source); |
8031 | } |
8032 | |
8033 | // aten::set_.source_Tensor(Tensor(a!) self, Tensor source) -> Tensor(a!) |
8034 | at::Tensor & set__source_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & source) { |
8035 | |
8036 | static auto op = create_set__source_Tensor_typed_handle(); |
8037 | return op.redispatch(dispatchKeySet, self, source); |
8038 | } |
8039 | |
8040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_, name, "aten::set_" ) |
8041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_, overload_name, "" ) |
8042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_, schema_str, "set_(Tensor(a!) self) -> Tensor(a!)" ) |
8043 | |
8044 | // aten::set_(Tensor(a!) self) -> Tensor(a!) |
8045 | static C10_NOINLINE c10::TypedOperatorHandle<set_::schema> create_set__typed_handle() { |
8046 | return c10::Dispatcher::singleton() |
8047 | .findSchemaOrThrow(set_::name, set_::overload_name) |
8048 | .typed<set_::schema>(); |
8049 | } |
8050 | |
8051 | // aten::set_(Tensor(a!) self) -> Tensor(a!) |
8052 | at::Tensor & set_::call(at::Tensor & self) { |
8053 | |
8054 | static auto op = create_set__typed_handle(); |
8055 | return op.call(self); |
8056 | } |
8057 | |
8058 | // aten::set_(Tensor(a!) self) -> Tensor(a!) |
8059 | at::Tensor & set_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
8060 | |
8061 | static auto op = create_set__typed_handle(); |
8062 | return op.redispatch(dispatchKeySet, self); |
8063 | } |
8064 | |
8065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put_, name, "aten::put_" ) |
8066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put_, overload_name, "" ) |
8067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put_, schema_str, "put_(Tensor(a!) self, Tensor index, Tensor source, bool accumulate=False) -> Tensor(a!)" ) |
8068 | |
8069 | // aten::put_(Tensor(a!) self, Tensor index, Tensor source, bool accumulate=False) -> Tensor(a!) |
8070 | static C10_NOINLINE c10::TypedOperatorHandle<put_::schema> create_put__typed_handle() { |
8071 | return c10::Dispatcher::singleton() |
8072 | .findSchemaOrThrow(put_::name, put_::overload_name) |
8073 | .typed<put_::schema>(); |
8074 | } |
8075 | |
8076 | // aten::put_(Tensor(a!) self, Tensor index, Tensor source, bool accumulate=False) -> Tensor(a!) |
8077 | at::Tensor & put_::call(at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate) { |
8078 | |
8079 | static auto op = create_put__typed_handle(); |
8080 | return op.call(self, index, source, accumulate); |
8081 | } |
8082 | |
8083 | // aten::put_(Tensor(a!) self, Tensor index, Tensor source, bool accumulate=False) -> Tensor(a!) |
8084 | at::Tensor & put_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate) { |
8085 | |
8086 | static auto op = create_put__typed_handle(); |
8087 | return op.redispatch(dispatchKeySet, self, index, source, accumulate); |
8088 | } |
8089 | |
8090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put, name, "aten::put" ) |
8091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put, overload_name, "" ) |
8092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put, schema_str, "put(Tensor self, Tensor index, Tensor source, bool accumulate=False) -> Tensor" ) |
8093 | |
8094 | // aten::put(Tensor self, Tensor index, Tensor source, bool accumulate=False) -> Tensor |
8095 | static C10_NOINLINE c10::TypedOperatorHandle<put::schema> create_put_typed_handle() { |
8096 | return c10::Dispatcher::singleton() |
8097 | .findSchemaOrThrow(put::name, put::overload_name) |
8098 | .typed<put::schema>(); |
8099 | } |
8100 | |
8101 | // aten::put(Tensor self, Tensor index, Tensor source, bool accumulate=False) -> Tensor |
8102 | at::Tensor put::call(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate) { |
8103 | |
8104 | static auto op = create_put_typed_handle(); |
8105 | return op.call(self, index, source, accumulate); |
8106 | } |
8107 | |
8108 | // aten::put(Tensor self, Tensor index, Tensor source, bool accumulate=False) -> Tensor |
8109 | at::Tensor put::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate) { |
8110 | |
8111 | static auto op = create_put_typed_handle(); |
8112 | return op.redispatch(dispatchKeySet, self, index, source, accumulate); |
8113 | } |
8114 | |
8115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_src, name, "aten::scatter" ) |
8116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_src, overload_name, "src" ) |
8117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_src, schema_str, "scatter.src(Tensor self, int dim, Tensor index, Tensor src) -> Tensor" ) |
8118 | |
8119 | // aten::scatter.src(Tensor self, int dim, Tensor index, Tensor src) -> Tensor |
8120 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_src::schema> create_scatter_src_typed_handle() { |
8121 | return c10::Dispatcher::singleton() |
8122 | .findSchemaOrThrow(scatter_src::name, scatter_src::overload_name) |
8123 | .typed<scatter_src::schema>(); |
8124 | } |
8125 | |
8126 | // aten::scatter.src(Tensor self, int dim, Tensor index, Tensor src) -> Tensor |
8127 | at::Tensor scatter_src::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src) { |
8128 | |
8129 | static auto op = create_scatter_src_typed_handle(); |
8130 | return op.call(self, dim, index, src); |
8131 | } |
8132 | |
8133 | // aten::scatter.src(Tensor self, int dim, Tensor index, Tensor src) -> Tensor |
8134 | at::Tensor scatter_src::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src) { |
8135 | |
8136 | static auto op = create_scatter_src_typed_handle(); |
8137 | return op.redispatch(dispatchKeySet, self, dim, index, src); |
8138 | } |
8139 | |
8140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__src, name, "aten::scatter_" ) |
8141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__src, overload_name, "src" ) |
8142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__src, schema_str, "scatter_.src(Tensor(a!) self, int dim, Tensor index, Tensor src) -> Tensor(a!)" ) |
8143 | |
8144 | // aten::scatter_.src(Tensor(a!) self, int dim, Tensor index, Tensor src) -> Tensor(a!) |
8145 | static C10_NOINLINE c10::TypedOperatorHandle<scatter__src::schema> create_scatter__src_typed_handle() { |
8146 | return c10::Dispatcher::singleton() |
8147 | .findSchemaOrThrow(scatter__src::name, scatter__src::overload_name) |
8148 | .typed<scatter__src::schema>(); |
8149 | } |
8150 | |
8151 | // aten::scatter_.src(Tensor(a!) self, int dim, Tensor index, Tensor src) -> Tensor(a!) |
8152 | at::Tensor & scatter__src::call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src) { |
8153 | |
8154 | static auto op = create_scatter__src_typed_handle(); |
8155 | return op.call(self, dim, index, src); |
8156 | } |
8157 | |
8158 | // aten::scatter_.src(Tensor(a!) self, int dim, Tensor index, Tensor src) -> Tensor(a!) |
8159 | at::Tensor & scatter__src::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src) { |
8160 | |
8161 | static auto op = create_scatter__src_typed_handle(); |
8162 | return op.redispatch(dispatchKeySet, self, dim, index, src); |
8163 | } |
8164 | |
8165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_src_out, name, "aten::scatter" ) |
8166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_src_out, overload_name, "src_out" ) |
8167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_src_out, schema_str, "scatter.src_out(Tensor self, int dim, Tensor index, Tensor src, *, Tensor(a!) out) -> Tensor(a!)" ) |
8168 | |
8169 | // aten::scatter.src_out(Tensor self, int dim, Tensor index, Tensor src, *, Tensor(a!) out) -> Tensor(a!) |
8170 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_src_out::schema> create_scatter_src_out_typed_handle() { |
8171 | return c10::Dispatcher::singleton() |
8172 | .findSchemaOrThrow(scatter_src_out::name, scatter_src_out::overload_name) |
8173 | .typed<scatter_src_out::schema>(); |
8174 | } |
8175 | |
8176 | // aten::scatter.src_out(Tensor self, int dim, Tensor index, Tensor src, *, Tensor(a!) out) -> Tensor(a!) |
8177 | at::Tensor & scatter_src_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out) { |
8178 | |
8179 | static auto op = create_scatter_src_out_typed_handle(); |
8180 | return op.call(self, dim, index, src, out); |
8181 | } |
8182 | |
8183 | // aten::scatter.src_out(Tensor self, int dim, Tensor index, Tensor src, *, Tensor(a!) out) -> Tensor(a!) |
8184 | at::Tensor & scatter_src_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, at::Tensor & out) { |
8185 | |
8186 | static auto op = create_scatter_src_out_typed_handle(); |
8187 | return op.redispatch(dispatchKeySet, self, dim, index, src, out); |
8188 | } |
8189 | |
8190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value, name, "aten::scatter" ) |
8191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value, overload_name, "value" ) |
8192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value, schema_str, "scatter.value(Tensor self, int dim, Tensor index, Scalar value) -> Tensor" ) |
8193 | |
8194 | // aten::scatter.value(Tensor self, int dim, Tensor index, Scalar value) -> Tensor |
8195 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_value::schema> create_scatter_value_typed_handle() { |
8196 | return c10::Dispatcher::singleton() |
8197 | .findSchemaOrThrow(scatter_value::name, scatter_value::overload_name) |
8198 | .typed<scatter_value::schema>(); |
8199 | } |
8200 | |
8201 | // aten::scatter.value(Tensor self, int dim, Tensor index, Scalar value) -> Tensor |
8202 | at::Tensor scatter_value::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value) { |
8203 | |
8204 | static auto op = create_scatter_value_typed_handle(); |
8205 | return op.call(self, dim, index, value); |
8206 | } |
8207 | |
8208 | // aten::scatter.value(Tensor self, int dim, Tensor index, Scalar value) -> Tensor |
8209 | at::Tensor scatter_value::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value) { |
8210 | |
8211 | static auto op = create_scatter_value_typed_handle(); |
8212 | return op.redispatch(dispatchKeySet, self, dim, index, value); |
8213 | } |
8214 | |
8215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__value, name, "aten::scatter_" ) |
8216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__value, overload_name, "value" ) |
8217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__value, schema_str, "scatter_.value(Tensor(a!) self, int dim, Tensor index, Scalar value) -> Tensor(a!)" ) |
8218 | |
8219 | // aten::scatter_.value(Tensor(a!) self, int dim, Tensor index, Scalar value) -> Tensor(a!) |
8220 | static C10_NOINLINE c10::TypedOperatorHandle<scatter__value::schema> create_scatter__value_typed_handle() { |
8221 | return c10::Dispatcher::singleton() |
8222 | .findSchemaOrThrow(scatter__value::name, scatter__value::overload_name) |
8223 | .typed<scatter__value::schema>(); |
8224 | } |
8225 | |
8226 | // aten::scatter_.value(Tensor(a!) self, int dim, Tensor index, Scalar value) -> Tensor(a!) |
8227 | at::Tensor & scatter__value::call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value) { |
8228 | |
8229 | static auto op = create_scatter__value_typed_handle(); |
8230 | return op.call(self, dim, index, value); |
8231 | } |
8232 | |
8233 | // aten::scatter_.value(Tensor(a!) self, int dim, Tensor index, Scalar value) -> Tensor(a!) |
8234 | at::Tensor & scatter__value::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value) { |
8235 | |
8236 | static auto op = create_scatter__value_typed_handle(); |
8237 | return op.redispatch(dispatchKeySet, self, dim, index, value); |
8238 | } |
8239 | |
8240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_out, name, "aten::scatter" ) |
8241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_out, overload_name, "value_out" ) |
8242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_out, schema_str, "scatter.value_out(Tensor self, int dim, Tensor index, Scalar value, *, Tensor(a!) out) -> Tensor(a!)" ) |
8243 | |
8244 | // aten::scatter.value_out(Tensor self, int dim, Tensor index, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
8245 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_value_out::schema> create_scatter_value_out_typed_handle() { |
8246 | return c10::Dispatcher::singleton() |
8247 | .findSchemaOrThrow(scatter_value_out::name, scatter_value_out::overload_name) |
8248 | .typed<scatter_value_out::schema>(); |
8249 | } |
8250 | |
8251 | // aten::scatter.value_out(Tensor self, int dim, Tensor index, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
8252 | at::Tensor & scatter_value_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, at::Tensor & out) { |
8253 | |
8254 | static auto op = create_scatter_value_out_typed_handle(); |
8255 | return op.call(self, dim, index, value, out); |
8256 | } |
8257 | |
8258 | // aten::scatter.value_out(Tensor self, int dim, Tensor index, Scalar value, *, Tensor(a!) out) -> Tensor(a!) |
8259 | at::Tensor & scatter_value_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, at::Tensor & out) { |
8260 | |
8261 | static auto op = create_scatter_value_out_typed_handle(); |
8262 | return op.redispatch(dispatchKeySet, self, dim, index, value, out); |
8263 | } |
8264 | |
8265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce, name, "aten::scatter" ) |
8266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce, overload_name, "reduce" ) |
8267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce, schema_str, "scatter.reduce(Tensor self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor" ) |
8268 | |
8269 | // aten::scatter.reduce(Tensor self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor |
8270 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_reduce::schema> create_scatter_reduce_typed_handle() { |
8271 | return c10::Dispatcher::singleton() |
8272 | .findSchemaOrThrow(scatter_reduce::name, scatter_reduce::overload_name) |
8273 | .typed<scatter_reduce::schema>(); |
8274 | } |
8275 | |
8276 | // aten::scatter.reduce(Tensor self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor |
8277 | at::Tensor scatter_reduce::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce) { |
8278 | |
8279 | static auto op = create_scatter_reduce_typed_handle(); |
8280 | return op.call(self, dim, index, src, reduce); |
8281 | } |
8282 | |
8283 | // aten::scatter.reduce(Tensor self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor |
8284 | at::Tensor scatter_reduce::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce) { |
8285 | |
8286 | static auto op = create_scatter_reduce_typed_handle(); |
8287 | return op.redispatch(dispatchKeySet, self, dim, index, src, reduce); |
8288 | } |
8289 | |
8290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__reduce, name, "aten::scatter_" ) |
8291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__reduce, overload_name, "reduce" ) |
8292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__reduce, schema_str, "scatter_.reduce(Tensor(a!) self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor(a!)" ) |
8293 | |
8294 | // aten::scatter_.reduce(Tensor(a!) self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor(a!) |
8295 | static C10_NOINLINE c10::TypedOperatorHandle<scatter__reduce::schema> create_scatter__reduce_typed_handle() { |
8296 | return c10::Dispatcher::singleton() |
8297 | .findSchemaOrThrow(scatter__reduce::name, scatter__reduce::overload_name) |
8298 | .typed<scatter__reduce::schema>(); |
8299 | } |
8300 | |
8301 | // aten::scatter_.reduce(Tensor(a!) self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor(a!) |
8302 | at::Tensor & scatter__reduce::call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce) { |
8303 | |
8304 | static auto op = create_scatter__reduce_typed_handle(); |
8305 | return op.call(self, dim, index, src, reduce); |
8306 | } |
8307 | |
8308 | // aten::scatter_.reduce(Tensor(a!) self, int dim, Tensor index, Tensor src, *, str reduce) -> Tensor(a!) |
8309 | at::Tensor & scatter__reduce::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce) { |
8310 | |
8311 | static auto op = create_scatter__reduce_typed_handle(); |
8312 | return op.redispatch(dispatchKeySet, self, dim, index, src, reduce); |
8313 | } |
8314 | |
8315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_out, name, "aten::scatter" ) |
8316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_out, overload_name, "reduce_out" ) |
8317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_out, schema_str, "scatter.reduce_out(Tensor self, int dim, Tensor index, Tensor src, *, str reduce, Tensor(a!) out) -> Tensor(a!)" ) |
8318 | |
8319 | // aten::scatter.reduce_out(Tensor self, int dim, Tensor index, Tensor src, *, str reduce, Tensor(a!) out) -> Tensor(a!) |
8320 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_reduce_out::schema> create_scatter_reduce_out_typed_handle() { |
8321 | return c10::Dispatcher::singleton() |
8322 | .findSchemaOrThrow(scatter_reduce_out::name, scatter_reduce_out::overload_name) |
8323 | .typed<scatter_reduce_out::schema>(); |
8324 | } |
8325 | |
8326 | // aten::scatter.reduce_out(Tensor self, int dim, Tensor index, Tensor src, *, str reduce, Tensor(a!) out) -> Tensor(a!) |
8327 | at::Tensor & scatter_reduce_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out) { |
8328 | |
8329 | static auto op = create_scatter_reduce_out_typed_handle(); |
8330 | return op.call(self, dim, index, src, reduce, out); |
8331 | } |
8332 | |
8333 | // aten::scatter.reduce_out(Tensor self, int dim, Tensor index, Tensor src, *, str reduce, Tensor(a!) out) -> Tensor(a!) |
8334 | at::Tensor & scatter_reduce_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out) { |
8335 | |
8336 | static auto op = create_scatter_reduce_out_typed_handle(); |
8337 | return op.redispatch(dispatchKeySet, self, dim, index, src, reduce, out); |
8338 | } |
8339 | |
8340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_reduce, name, "aten::scatter" ) |
8341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_reduce, overload_name, "value_reduce" ) |
8342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_reduce, schema_str, "scatter.value_reduce(Tensor self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor" ) |
8343 | |
8344 | // aten::scatter.value_reduce(Tensor self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor |
8345 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_value_reduce::schema> create_scatter_value_reduce_typed_handle() { |
8346 | return c10::Dispatcher::singleton() |
8347 | .findSchemaOrThrow(scatter_value_reduce::name, scatter_value_reduce::overload_name) |
8348 | .typed<scatter_value_reduce::schema>(); |
8349 | } |
8350 | |
8351 | // aten::scatter.value_reduce(Tensor self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor |
8352 | at::Tensor scatter_value_reduce::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce) { |
8353 | |
8354 | static auto op = create_scatter_value_reduce_typed_handle(); |
8355 | return op.call(self, dim, index, value, reduce); |
8356 | } |
8357 | |
8358 | // aten::scatter.value_reduce(Tensor self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor |
8359 | at::Tensor scatter_value_reduce::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce) { |
8360 | |
8361 | static auto op = create_scatter_value_reduce_typed_handle(); |
8362 | return op.redispatch(dispatchKeySet, self, dim, index, value, reduce); |
8363 | } |
8364 | |
8365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__value_reduce, name, "aten::scatter_" ) |
8366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__value_reduce, overload_name, "value_reduce" ) |
8367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter__value_reduce, schema_str, "scatter_.value_reduce(Tensor(a!) self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor(a!)" ) |
8368 | |
8369 | // aten::scatter_.value_reduce(Tensor(a!) self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor(a!) |
8370 | static C10_NOINLINE c10::TypedOperatorHandle<scatter__value_reduce::schema> create_scatter__value_reduce_typed_handle() { |
8371 | return c10::Dispatcher::singleton() |
8372 | .findSchemaOrThrow(scatter__value_reduce::name, scatter__value_reduce::overload_name) |
8373 | .typed<scatter__value_reduce::schema>(); |
8374 | } |
8375 | |
8376 | // aten::scatter_.value_reduce(Tensor(a!) self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor(a!) |
8377 | at::Tensor & scatter__value_reduce::call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce) { |
8378 | |
8379 | static auto op = create_scatter__value_reduce_typed_handle(); |
8380 | return op.call(self, dim, index, value, reduce); |
8381 | } |
8382 | |
8383 | // aten::scatter_.value_reduce(Tensor(a!) self, int dim, Tensor index, Scalar value, *, str reduce) -> Tensor(a!) |
8384 | at::Tensor & scatter__value_reduce::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce) { |
8385 | |
8386 | static auto op = create_scatter__value_reduce_typed_handle(); |
8387 | return op.redispatch(dispatchKeySet, self, dim, index, value, reduce); |
8388 | } |
8389 | |
8390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_reduce_out, name, "aten::scatter" ) |
8391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_reduce_out, overload_name, "value_reduce_out" ) |
8392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_value_reduce_out, schema_str, "scatter.value_reduce_out(Tensor self, int dim, Tensor index, Scalar value, *, str reduce, Tensor(a!) out) -> Tensor(a!)" ) |
8393 | |
8394 | // aten::scatter.value_reduce_out(Tensor self, int dim, Tensor index, Scalar value, *, str reduce, Tensor(a!) out) -> Tensor(a!) |
8395 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_value_reduce_out::schema> create_scatter_value_reduce_out_typed_handle() { |
8396 | return c10::Dispatcher::singleton() |
8397 | .findSchemaOrThrow(scatter_value_reduce_out::name, scatter_value_reduce_out::overload_name) |
8398 | .typed<scatter_value_reduce_out::schema>(); |
8399 | } |
8400 | |
8401 | // aten::scatter.value_reduce_out(Tensor self, int dim, Tensor index, Scalar value, *, str reduce, Tensor(a!) out) -> Tensor(a!) |
8402 | at::Tensor & scatter_value_reduce_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce, at::Tensor & out) { |
8403 | |
8404 | static auto op = create_scatter_value_reduce_out_typed_handle(); |
8405 | return op.call(self, dim, index, value, reduce, out); |
8406 | } |
8407 | |
8408 | // aten::scatter.value_reduce_out(Tensor self, int dim, Tensor index, Scalar value, *, str reduce, Tensor(a!) out) -> Tensor(a!) |
8409 | at::Tensor & scatter_value_reduce_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Scalar & value, c10::string_view reduce, at::Tensor & out) { |
8410 | |
8411 | static auto op = create_scatter_value_reduce_out_typed_handle(); |
8412 | return op.redispatch(dispatchKeySet, self, dim, index, value, reduce, out); |
8413 | } |
8414 | |
8415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_dimname_src, name, "aten::scatter" ) |
8416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_dimname_src, overload_name, "dimname_src" ) |
8417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_dimname_src, schema_str, "scatter.dimname_src(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor" ) |
8418 | |
8419 | // aten::scatter.dimname_src(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor |
8420 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_dimname_src::schema> create_scatter_dimname_src_typed_handle() { |
8421 | return c10::Dispatcher::singleton() |
8422 | .findSchemaOrThrow(scatter_dimname_src::name, scatter_dimname_src::overload_name) |
8423 | .typed<scatter_dimname_src::schema>(); |
8424 | } |
8425 | |
8426 | // aten::scatter.dimname_src(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor |
8427 | at::Tensor scatter_dimname_src::call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & src) { |
8428 | |
8429 | static auto op = create_scatter_dimname_src_typed_handle(); |
8430 | return op.call(self, dim, index, src); |
8431 | } |
8432 | |
8433 | // aten::scatter.dimname_src(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor |
8434 | at::Tensor scatter_dimname_src::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Tensor & src) { |
8435 | |
8436 | static auto op = create_scatter_dimname_src_typed_handle(); |
8437 | return op.redispatch(dispatchKeySet, self, dim, index, src); |
8438 | } |
8439 | |
8440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_dimname_value, name, "aten::scatter" ) |
8441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_dimname_value, overload_name, "dimname_value" ) |
8442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_dimname_value, schema_str, "scatter.dimname_value(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor" ) |
8443 | |
8444 | // aten::scatter.dimname_value(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor |
8445 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_dimname_value::schema> create_scatter_dimname_value_typed_handle() { |
8446 | return c10::Dispatcher::singleton() |
8447 | .findSchemaOrThrow(scatter_dimname_value::name, scatter_dimname_value::overload_name) |
8448 | .typed<scatter_dimname_value::schema>(); |
8449 | } |
8450 | |
8451 | // aten::scatter.dimname_value(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor |
8452 | at::Tensor scatter_dimname_value::call(const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Scalar & value) { |
8453 | |
8454 | static auto op = create_scatter_dimname_value_typed_handle(); |
8455 | return op.call(self, dim, index, value); |
8456 | } |
8457 | |
8458 | // aten::scatter.dimname_value(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor |
8459 | at::Tensor scatter_dimname_value::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, const at::Tensor & index, const at::Scalar & value) { |
8460 | |
8461 | static auto op = create_scatter_dimname_value_typed_handle(); |
8462 | return op.redispatch(dispatchKeySet, self, dim, index, value); |
8463 | } |
8464 | |
8465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_two, name, "aten::scatter_reduce" ) |
8466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_two, overload_name, "two" ) |
8467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_two, schema_str, "scatter_reduce.two(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor" ) |
8468 | |
8469 | // aten::scatter_reduce.two(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor |
8470 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_reduce_two::schema> create_scatter_reduce_two_typed_handle() { |
8471 | return c10::Dispatcher::singleton() |
8472 | .findSchemaOrThrow(scatter_reduce_two::name, scatter_reduce_two::overload_name) |
8473 | .typed<scatter_reduce_two::schema>(); |
8474 | } |
8475 | |
8476 | // aten::scatter_reduce.two(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor |
8477 | at::Tensor scatter_reduce_two::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self) { |
8478 | |
8479 | static auto op = create_scatter_reduce_two_typed_handle(); |
8480 | return op.call(self, dim, index, src, reduce, include_self); |
8481 | } |
8482 | |
8483 | // aten::scatter_reduce.two(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor |
8484 | at::Tensor scatter_reduce_two::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self) { |
8485 | |
8486 | static auto op = create_scatter_reduce_two_typed_handle(); |
8487 | return op.redispatch(dispatchKeySet, self, dim, index, src, reduce, include_self); |
8488 | } |
8489 | |
8490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce__two, name, "aten::scatter_reduce_" ) |
8491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce__two, overload_name, "two" ) |
8492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce__two, schema_str, "scatter_reduce_.two(Tensor(a!) self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor(a!)" ) |
8493 | |
8494 | // aten::scatter_reduce_.two(Tensor(a!) self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor(a!) |
8495 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_reduce__two::schema> create_scatter_reduce__two_typed_handle() { |
8496 | return c10::Dispatcher::singleton() |
8497 | .findSchemaOrThrow(scatter_reduce__two::name, scatter_reduce__two::overload_name) |
8498 | .typed<scatter_reduce__two::schema>(); |
8499 | } |
8500 | |
8501 | // aten::scatter_reduce_.two(Tensor(a!) self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor(a!) |
8502 | at::Tensor & scatter_reduce__two::call(at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self) { |
8503 | |
8504 | static auto op = create_scatter_reduce__two_typed_handle(); |
8505 | return op.call(self, dim, index, src, reduce, include_self); |
8506 | } |
8507 | |
8508 | // aten::scatter_reduce_.two(Tensor(a!) self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True) -> Tensor(a!) |
8509 | at::Tensor & scatter_reduce__two::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self) { |
8510 | |
8511 | static auto op = create_scatter_reduce__two_typed_handle(); |
8512 | return op.redispatch(dispatchKeySet, self, dim, index, src, reduce, include_self); |
8513 | } |
8514 | |
8515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_two_out, name, "aten::scatter_reduce" ) |
8516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_two_out, overload_name, "two_out" ) |
8517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scatter_reduce_two_out, schema_str, "scatter_reduce.two_out(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True, Tensor(a!) out) -> Tensor(a!)" ) |
8518 | |
8519 | // aten::scatter_reduce.two_out(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True, Tensor(a!) out) -> Tensor(a!) |
8520 | static C10_NOINLINE c10::TypedOperatorHandle<scatter_reduce_two_out::schema> create_scatter_reduce_two_out_typed_handle() { |
8521 | return c10::Dispatcher::singleton() |
8522 | .findSchemaOrThrow(scatter_reduce_two_out::name, scatter_reduce_two_out::overload_name) |
8523 | .typed<scatter_reduce_two_out::schema>(); |
8524 | } |
8525 | |
8526 | // aten::scatter_reduce.two_out(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True, Tensor(a!) out) -> Tensor(a!) |
8527 | at::Tensor & scatter_reduce_two_out::call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self, at::Tensor & out) { |
8528 | |
8529 | static auto op = create_scatter_reduce_two_out_typed_handle(); |
8530 | return op.call(self, dim, index, src, reduce, include_self, out); |
8531 | } |
8532 | |
8533 | // aten::scatter_reduce.two_out(Tensor self, int dim, Tensor index, Tensor src, str reduce, *, bool include_self=True, Tensor(a!) out) -> Tensor(a!) |
8534 | at::Tensor & scatter_reduce_two_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, bool include_self, at::Tensor & out) { |
8535 | |
8536 | static auto op = create_scatter_reduce_two_out_typed_handle(); |
8537 | return op.redispatch(dispatchKeySet, self, dim, index, src, reduce, include_self, out); |
8538 | } |
8539 | |
8540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__and___Scalar, name, "aten::__and__" ) |
8541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__and___Scalar, overload_name, "Scalar" ) |
8542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__and___Scalar, schema_str, "__and__.Scalar(Tensor self, Scalar other) -> Tensor" ) |
8543 | |
8544 | // aten::__and__.Scalar(Tensor self, Scalar other) -> Tensor |
8545 | static C10_NOINLINE c10::TypedOperatorHandle<__and___Scalar::schema> create___and___Scalar_typed_handle() { |
8546 | return c10::Dispatcher::singleton() |
8547 | .findSchemaOrThrow(__and___Scalar::name, __and___Scalar::overload_name) |
8548 | .typed<__and___Scalar::schema>(); |
8549 | } |
8550 | |
8551 | // aten::__and__.Scalar(Tensor self, Scalar other) -> Tensor |
8552 | at::Tensor __and___Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
8553 | |
8554 | static auto op = create___and___Scalar_typed_handle(); |
8555 | return op.call(self, other); |
8556 | } |
8557 | |
8558 | // aten::__and__.Scalar(Tensor self, Scalar other) -> Tensor |
8559 | at::Tensor __and___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
8560 | |
8561 | static auto op = create___and___Scalar_typed_handle(); |
8562 | return op.redispatch(dispatchKeySet, self, other); |
8563 | } |
8564 | |
8565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__and___Tensor, name, "aten::__and__" ) |
8566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__and___Tensor, overload_name, "Tensor" ) |
8567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__and___Tensor, schema_str, "__and__.Tensor(Tensor self, Tensor other) -> Tensor" ) |
8568 | |
8569 | // aten::__and__.Tensor(Tensor self, Tensor other) -> Tensor |
8570 | static C10_NOINLINE c10::TypedOperatorHandle<__and___Tensor::schema> create___and___Tensor_typed_handle() { |
8571 | return c10::Dispatcher::singleton() |
8572 | .findSchemaOrThrow(__and___Tensor::name, __and___Tensor::overload_name) |
8573 | .typed<__and___Tensor::schema>(); |
8574 | } |
8575 | |
8576 | // aten::__and__.Tensor(Tensor self, Tensor other) -> Tensor |
8577 | at::Tensor __and___Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
8578 | |
8579 | static auto op = create___and___Tensor_typed_handle(); |
8580 | return op.call(self, other); |
8581 | } |
8582 | |
8583 | // aten::__and__.Tensor(Tensor self, Tensor other) -> Tensor |
8584 | at::Tensor __and___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
8585 | |
8586 | static auto op = create___and___Tensor_typed_handle(); |
8587 | return op.redispatch(dispatchKeySet, self, other); |
8588 | } |
8589 | |
8590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__iand___Scalar, name, "aten::__iand__" ) |
8591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__iand___Scalar, overload_name, "Scalar" ) |
8592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__iand___Scalar, schema_str, "__iand__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)" ) |
8593 | |
8594 | // aten::__iand__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
8595 | static C10_NOINLINE c10::TypedOperatorHandle<__iand___Scalar::schema> create___iand___Scalar_typed_handle() { |
8596 | return c10::Dispatcher::singleton() |
8597 | .findSchemaOrThrow(__iand___Scalar::name, __iand___Scalar::overload_name) |
8598 | .typed<__iand___Scalar::schema>(); |
8599 | } |
8600 | |
8601 | // aten::__iand__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
8602 | at::Tensor & __iand___Scalar::call(at::Tensor & self, const at::Scalar & other) { |
8603 | |
8604 | static auto op = create___iand___Scalar_typed_handle(); |
8605 | return op.call(self, other); |
8606 | } |
8607 | |
8608 | // aten::__iand__.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
8609 | at::Tensor & __iand___Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
8610 | |
8611 | static auto op = create___iand___Scalar_typed_handle(); |
8612 | return op.redispatch(dispatchKeySet, self, other); |
8613 | } |
8614 | |
8615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__iand___Tensor, name, "aten::__iand__" ) |
8616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__iand___Tensor, overload_name, "Tensor" ) |
8617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(__iand___Tensor, schema_str, "__iand__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
8618 | |
8619 | // aten::__iand__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
8620 | static C10_NOINLINE c10::TypedOperatorHandle<__iand___Tensor::schema> create___iand___Tensor_typed_handle() { |
8621 | return c10::Dispatcher::singleton() |
8622 | .findSchemaOrThrow(__iand___Tensor::name, __iand___Tensor::overload_name) |
8623 | .typed<__iand___Tensor::schema>(); |
8624 | } |
8625 | |
8626 | // aten::__iand__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
8627 | at::Tensor & __iand___Tensor::call(at::Tensor & self, const at::Tensor & other) { |
8628 | |
8629 | static auto op = create___iand___Tensor_typed_handle(); |
8630 | return op.call(self, other); |
8631 | } |
8632 | |
8633 | // aten::__iand__.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
8634 | at::Tensor & __iand___Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
8635 | |
8636 | static auto op = create___iand___Tensor_typed_handle(); |
8637 | return op.redispatch(dispatchKeySet, self, other); |
8638 | } |
8639 | |
8640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_, name, "aten::tril_" ) |
8641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_, overload_name, "" ) |
8642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_, schema_str, "tril_(Tensor(a!) self, int diagonal=0) -> Tensor(a!)" ) |
8643 | |
8644 | // aten::tril_(Tensor(a!) self, int diagonal=0) -> Tensor(a!) |
8645 | static C10_NOINLINE c10::TypedOperatorHandle<tril_::schema> create_tril__typed_handle() { |
8646 | return c10::Dispatcher::singleton() |
8647 | .findSchemaOrThrow(tril_::name, tril_::overload_name) |
8648 | .typed<tril_::schema>(); |
8649 | } |
8650 | |
8651 | // aten::tril_(Tensor(a!) self, int diagonal=0) -> Tensor(a!) |
8652 | at::Tensor & tril_::call(at::Tensor & self, int64_t diagonal) { |
8653 | |
8654 | static auto op = create_tril__typed_handle(); |
8655 | return op.call(self, diagonal); |
8656 | } |
8657 | |
8658 | // aten::tril_(Tensor(a!) self, int diagonal=0) -> Tensor(a!) |
8659 | at::Tensor & tril_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, int64_t diagonal) { |
8660 | |
8661 | static auto op = create_tril__typed_handle(); |
8662 | return op.redispatch(dispatchKeySet, self, diagonal); |
8663 | } |
8664 | |
8665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform_, name, "aten::uniform_" ) |
8666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform_, overload_name, "" ) |
8667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform_, schema_str, "uniform_(Tensor(a!) self, float from=0, float to=1, *, Generator? generator=None) -> Tensor(a!)" ) |
8668 | |
8669 | // aten::uniform_(Tensor(a!) self, float from=0, float to=1, *, Generator? generator=None) -> Tensor(a!) |
8670 | static C10_NOINLINE c10::TypedOperatorHandle<uniform_::schema> create_uniform__typed_handle() { |
8671 | return c10::Dispatcher::singleton() |
8672 | .findSchemaOrThrow(uniform_::name, uniform_::overload_name) |
8673 | .typed<uniform_::schema>(); |
8674 | } |
8675 | |
8676 | // aten::uniform_(Tensor(a!) self, float from=0, float to=1, *, Generator? generator=None) -> Tensor(a!) |
8677 | at::Tensor & uniform_::call(at::Tensor & self, double from, double to, c10::optional<at::Generator> generator) { |
8678 | |
8679 | static auto op = create_uniform__typed_handle(); |
8680 | return op.call(self, from, to, generator); |
8681 | } |
8682 | |
8683 | // aten::uniform_(Tensor(a!) self, float from=0, float to=1, *, Generator? generator=None) -> Tensor(a!) |
8684 | at::Tensor & uniform_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, double from, double to, c10::optional<at::Generator> generator) { |
8685 | |
8686 | static auto op = create_uniform__typed_handle(); |
8687 | return op.redispatch(dispatchKeySet, self, from, to, generator); |
8688 | } |
8689 | |
8690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_out, name, "aten::tril" ) |
8691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_out, overload_name, "out" ) |
8692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_out, schema_str, "tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!)" ) |
8693 | |
8694 | // aten::tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) |
8695 | static C10_NOINLINE c10::TypedOperatorHandle<tril_out::schema> create_tril_out_typed_handle() { |
8696 | return c10::Dispatcher::singleton() |
8697 | .findSchemaOrThrow(tril_out::name, tril_out::overload_name) |
8698 | .typed<tril_out::schema>(); |
8699 | } |
8700 | |
8701 | // aten::tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) |
8702 | at::Tensor & tril_out::call(const at::Tensor & self, int64_t diagonal, at::Tensor & out) { |
8703 | |
8704 | static auto op = create_tril_out_typed_handle(); |
8705 | return op.call(self, diagonal, out); |
8706 | } |
8707 | |
8708 | // aten::tril.out(Tensor self, int diagonal=0, *, Tensor(a!) out) -> Tensor(a!) |
8709 | at::Tensor & tril_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal, at::Tensor & out) { |
8710 | |
8711 | static auto op = create_tril_out_typed_handle(); |
8712 | return op.redispatch(dispatchKeySet, self, diagonal, out); |
8713 | } |
8714 | |
8715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril, name, "aten::tril" ) |
8716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril, overload_name, "" ) |
8717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril, schema_str, "tril(Tensor self, int diagonal=0) -> Tensor" ) |
8718 | |
8719 | // aten::tril(Tensor self, int diagonal=0) -> Tensor |
8720 | static C10_NOINLINE c10::TypedOperatorHandle<tril::schema> create_tril_typed_handle() { |
8721 | return c10::Dispatcher::singleton() |
8722 | .findSchemaOrThrow(tril::name, tril::overload_name) |
8723 | .typed<tril::schema>(); |
8724 | } |
8725 | |
8726 | // aten::tril(Tensor self, int diagonal=0) -> Tensor |
8727 | at::Tensor tril::call(const at::Tensor & self, int64_t diagonal) { |
8728 | |
8729 | static auto op = create_tril_typed_handle(); |
8730 | return op.call(self, diagonal); |
8731 | } |
8732 | |
8733 | // aten::tril(Tensor self, int diagonal=0) -> Tensor |
8734 | at::Tensor tril::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t diagonal) { |
8735 | |
8736 | static auto op = create_tril_typed_handle(); |
8737 | return op.redispatch(dispatchKeySet, self, diagonal); |
8738 | } |
8739 | |
8740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_indices, name, "aten::tril_indices" ) |
8741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_indices, overload_name, "" ) |
8742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_indices, schema_str, "tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
8743 | |
8744 | // aten::tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
8745 | static C10_NOINLINE c10::TypedOperatorHandle<tril_indices::schema> create_tril_indices_typed_handle() { |
8746 | return c10::Dispatcher::singleton() |
8747 | .findSchemaOrThrow(tril_indices::name, tril_indices::overload_name) |
8748 | .typed<tril_indices::schema>(); |
8749 | } |
8750 | |
8751 | // aten::tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
8752 | at::Tensor tril_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) { |
8753 | |
8754 | static auto op = create_tril_indices_typed_handle(); |
8755 | return op.call(row, col, offset, dtype, layout, device, pin_memory); |
8756 | } |
8757 | |
8758 | // aten::tril_indices(int row, int col, int offset=0, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
8759 | at::Tensor tril_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) { |
8760 | |
8761 | static auto op = create_tril_indices_typed_handle(); |
8762 | return op.redispatch(dispatchKeySet, row, col, offset, dtype, layout, device, pin_memory); |
8763 | } |
8764 | |
8765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Scalar_out, name, "aten::less_equal" ) |
8766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Scalar_out, overload_name, "Scalar_out" ) |
8767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Scalar_out, schema_str, "less_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)" ) |
8768 | |
8769 | // aten::less_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
8770 | static C10_NOINLINE c10::TypedOperatorHandle<less_equal_Scalar_out::schema> create_less_equal_Scalar_out_typed_handle() { |
8771 | return c10::Dispatcher::singleton() |
8772 | .findSchemaOrThrow(less_equal_Scalar_out::name, less_equal_Scalar_out::overload_name) |
8773 | .typed<less_equal_Scalar_out::schema>(); |
8774 | } |
8775 | |
8776 | // aten::less_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
8777 | at::Tensor & less_equal_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
8778 | |
8779 | static auto op = create_less_equal_Scalar_out_typed_handle(); |
8780 | return op.call(self, other, out); |
8781 | } |
8782 | |
8783 | // aten::less_equal.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
8784 | at::Tensor & less_equal_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
8785 | |
8786 | static auto op = create_less_equal_Scalar_out_typed_handle(); |
8787 | return op.redispatch(dispatchKeySet, self, other, out); |
8788 | } |
8789 | |
8790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Scalar, name, "aten::less_equal" ) |
8791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Scalar, overload_name, "Scalar" ) |
8792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Scalar, schema_str, "less_equal.Scalar(Tensor self, Scalar other) -> Tensor" ) |
8793 | |
8794 | // aten::less_equal.Scalar(Tensor self, Scalar other) -> Tensor |
8795 | static C10_NOINLINE c10::TypedOperatorHandle<less_equal_Scalar::schema> create_less_equal_Scalar_typed_handle() { |
8796 | return c10::Dispatcher::singleton() |
8797 | .findSchemaOrThrow(less_equal_Scalar::name, less_equal_Scalar::overload_name) |
8798 | .typed<less_equal_Scalar::schema>(); |
8799 | } |
8800 | |
8801 | // aten::less_equal.Scalar(Tensor self, Scalar other) -> Tensor |
8802 | at::Tensor less_equal_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
8803 | |
8804 | static auto op = create_less_equal_Scalar_typed_handle(); |
8805 | return op.call(self, other); |
8806 | } |
8807 | |
8808 | // aten::less_equal.Scalar(Tensor self, Scalar other) -> Tensor |
8809 | at::Tensor less_equal_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
8810 | |
8811 | static auto op = create_less_equal_Scalar_typed_handle(); |
8812 | return op.redispatch(dispatchKeySet, self, other); |
8813 | } |
8814 | |
8815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Tensor_out, name, "aten::less_equal" ) |
8816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Tensor_out, overload_name, "Tensor_out" ) |
8817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Tensor_out, schema_str, "less_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
8818 | |
8819 | // aten::less_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
8820 | static C10_NOINLINE c10::TypedOperatorHandle<less_equal_Tensor_out::schema> create_less_equal_Tensor_out_typed_handle() { |
8821 | return c10::Dispatcher::singleton() |
8822 | .findSchemaOrThrow(less_equal_Tensor_out::name, less_equal_Tensor_out::overload_name) |
8823 | .typed<less_equal_Tensor_out::schema>(); |
8824 | } |
8825 | |
8826 | // aten::less_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
8827 | at::Tensor & less_equal_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
8828 | |
8829 | static auto op = create_less_equal_Tensor_out_typed_handle(); |
8830 | return op.call(self, other, out); |
8831 | } |
8832 | |
8833 | // aten::less_equal.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
8834 | at::Tensor & less_equal_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
8835 | |
8836 | static auto op = create_less_equal_Tensor_out_typed_handle(); |
8837 | return op.redispatch(dispatchKeySet, self, other, out); |
8838 | } |
8839 | |
8840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Tensor, name, "aten::less_equal" ) |
8841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Tensor, overload_name, "Tensor" ) |
8842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal_Tensor, schema_str, "less_equal.Tensor(Tensor self, Tensor other) -> Tensor" ) |
8843 | |
8844 | // aten::less_equal.Tensor(Tensor self, Tensor other) -> Tensor |
8845 | static C10_NOINLINE c10::TypedOperatorHandle<less_equal_Tensor::schema> create_less_equal_Tensor_typed_handle() { |
8846 | return c10::Dispatcher::singleton() |
8847 | .findSchemaOrThrow(less_equal_Tensor::name, less_equal_Tensor::overload_name) |
8848 | .typed<less_equal_Tensor::schema>(); |
8849 | } |
8850 | |
8851 | // aten::less_equal.Tensor(Tensor self, Tensor other) -> Tensor |
8852 | at::Tensor less_equal_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
8853 | |
8854 | static auto op = create_less_equal_Tensor_typed_handle(); |
8855 | return op.call(self, other); |
8856 | } |
8857 | |
8858 | // aten::less_equal.Tensor(Tensor self, Tensor other) -> Tensor |
8859 | at::Tensor less_equal_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
8860 | |
8861 | static auto op = create_less_equal_Tensor_typed_handle(); |
8862 | return op.redispatch(dispatchKeySet, self, other); |
8863 | } |
8864 | |
8865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal__Scalar, name, "aten::less_equal_" ) |
8866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal__Scalar, overload_name, "Scalar" ) |
8867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal__Scalar, schema_str, "less_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)" ) |
8868 | |
8869 | // aten::less_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
8870 | static C10_NOINLINE c10::TypedOperatorHandle<less_equal__Scalar::schema> create_less_equal__Scalar_typed_handle() { |
8871 | return c10::Dispatcher::singleton() |
8872 | .findSchemaOrThrow(less_equal__Scalar::name, less_equal__Scalar::overload_name) |
8873 | .typed<less_equal__Scalar::schema>(); |
8874 | } |
8875 | |
8876 | // aten::less_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
8877 | at::Tensor & less_equal__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
8878 | |
8879 | static auto op = create_less_equal__Scalar_typed_handle(); |
8880 | return op.call(self, other); |
8881 | } |
8882 | |
8883 | // aten::less_equal_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
8884 | at::Tensor & less_equal__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
8885 | |
8886 | static auto op = create_less_equal__Scalar_typed_handle(); |
8887 | return op.redispatch(dispatchKeySet, self, other); |
8888 | } |
8889 | |
8890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal__Tensor, name, "aten::less_equal_" ) |
8891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal__Tensor, overload_name, "Tensor" ) |
8892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_equal__Tensor, schema_str, "less_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
8893 | |
8894 | // aten::less_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
8895 | static C10_NOINLINE c10::TypedOperatorHandle<less_equal__Tensor::schema> create_less_equal__Tensor_typed_handle() { |
8896 | return c10::Dispatcher::singleton() |
8897 | .findSchemaOrThrow(less_equal__Tensor::name, less_equal__Tensor::overload_name) |
8898 | .typed<less_equal__Tensor::schema>(); |
8899 | } |
8900 | |
8901 | // aten::less_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
8902 | at::Tensor & less_equal__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
8903 | |
8904 | static auto op = create_less_equal__Tensor_typed_handle(); |
8905 | return op.call(self, other); |
8906 | } |
8907 | |
8908 | // aten::less_equal_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
8909 | at::Tensor & less_equal__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
8910 | |
8911 | static auto op = create_less_equal__Tensor_typed_handle(); |
8912 | return op.redispatch(dispatchKeySet, self, other); |
8913 | } |
8914 | |
8915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Scalar_out, name, "aten::gt" ) |
8916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Scalar_out, overload_name, "Scalar_out" ) |
8917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Scalar_out, schema_str, "gt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)" ) |
8918 | |
8919 | // aten::gt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
8920 | static C10_NOINLINE c10::TypedOperatorHandle<gt_Scalar_out::schema> create_gt_Scalar_out_typed_handle() { |
8921 | return c10::Dispatcher::singleton() |
8922 | .findSchemaOrThrow(gt_Scalar_out::name, gt_Scalar_out::overload_name) |
8923 | .typed<gt_Scalar_out::schema>(); |
8924 | } |
8925 | |
8926 | // aten::gt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
8927 | at::Tensor & gt_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
8928 | |
8929 | static auto op = create_gt_Scalar_out_typed_handle(); |
8930 | return op.call(self, other, out); |
8931 | } |
8932 | |
8933 | // aten::gt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
8934 | at::Tensor & gt_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
8935 | |
8936 | static auto op = create_gt_Scalar_out_typed_handle(); |
8937 | return op.redispatch(dispatchKeySet, self, other, out); |
8938 | } |
8939 | |
8940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Scalar, name, "aten::gt" ) |
8941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Scalar, overload_name, "Scalar" ) |
8942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Scalar, schema_str, "gt.Scalar(Tensor self, Scalar other) -> Tensor" ) |
8943 | |
8944 | // aten::gt.Scalar(Tensor self, Scalar other) -> Tensor |
8945 | static C10_NOINLINE c10::TypedOperatorHandle<gt_Scalar::schema> create_gt_Scalar_typed_handle() { |
8946 | return c10::Dispatcher::singleton() |
8947 | .findSchemaOrThrow(gt_Scalar::name, gt_Scalar::overload_name) |
8948 | .typed<gt_Scalar::schema>(); |
8949 | } |
8950 | |
8951 | // aten::gt.Scalar(Tensor self, Scalar other) -> Tensor |
8952 | at::Tensor gt_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
8953 | |
8954 | static auto op = create_gt_Scalar_typed_handle(); |
8955 | return op.call(self, other); |
8956 | } |
8957 | |
8958 | // aten::gt.Scalar(Tensor self, Scalar other) -> Tensor |
8959 | at::Tensor gt_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
8960 | |
8961 | static auto op = create_gt_Scalar_typed_handle(); |
8962 | return op.redispatch(dispatchKeySet, self, other); |
8963 | } |
8964 | |
8965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Tensor_out, name, "aten::gt" ) |
8966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Tensor_out, overload_name, "Tensor_out" ) |
8967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Tensor_out, schema_str, "gt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
8968 | |
8969 | // aten::gt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
8970 | static C10_NOINLINE c10::TypedOperatorHandle<gt_Tensor_out::schema> create_gt_Tensor_out_typed_handle() { |
8971 | return c10::Dispatcher::singleton() |
8972 | .findSchemaOrThrow(gt_Tensor_out::name, gt_Tensor_out::overload_name) |
8973 | .typed<gt_Tensor_out::schema>(); |
8974 | } |
8975 | |
8976 | // aten::gt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
8977 | at::Tensor & gt_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
8978 | |
8979 | static auto op = create_gt_Tensor_out_typed_handle(); |
8980 | return op.call(self, other, out); |
8981 | } |
8982 | |
8983 | // aten::gt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
8984 | at::Tensor & gt_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
8985 | |
8986 | static auto op = create_gt_Tensor_out_typed_handle(); |
8987 | return op.redispatch(dispatchKeySet, self, other, out); |
8988 | } |
8989 | |
8990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Tensor, name, "aten::gt" ) |
8991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Tensor, overload_name, "Tensor" ) |
8992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt_Tensor, schema_str, "gt.Tensor(Tensor self, Tensor other) -> Tensor" ) |
8993 | |
8994 | // aten::gt.Tensor(Tensor self, Tensor other) -> Tensor |
8995 | static C10_NOINLINE c10::TypedOperatorHandle<gt_Tensor::schema> create_gt_Tensor_typed_handle() { |
8996 | return c10::Dispatcher::singleton() |
8997 | .findSchemaOrThrow(gt_Tensor::name, gt_Tensor::overload_name) |
8998 | .typed<gt_Tensor::schema>(); |
8999 | } |
9000 | |
9001 | // aten::gt.Tensor(Tensor self, Tensor other) -> Tensor |
9002 | at::Tensor gt_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
9003 | |
9004 | static auto op = create_gt_Tensor_typed_handle(); |
9005 | return op.call(self, other); |
9006 | } |
9007 | |
9008 | // aten::gt.Tensor(Tensor self, Tensor other) -> Tensor |
9009 | at::Tensor gt_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
9010 | |
9011 | static auto op = create_gt_Tensor_typed_handle(); |
9012 | return op.redispatch(dispatchKeySet, self, other); |
9013 | } |
9014 | |
9015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt__Scalar, name, "aten::gt_" ) |
9016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt__Scalar, overload_name, "Scalar" ) |
9017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt__Scalar, schema_str, "gt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)" ) |
9018 | |
9019 | // aten::gt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9020 | static C10_NOINLINE c10::TypedOperatorHandle<gt__Scalar::schema> create_gt__Scalar_typed_handle() { |
9021 | return c10::Dispatcher::singleton() |
9022 | .findSchemaOrThrow(gt__Scalar::name, gt__Scalar::overload_name) |
9023 | .typed<gt__Scalar::schema>(); |
9024 | } |
9025 | |
9026 | // aten::gt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9027 | at::Tensor & gt__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
9028 | |
9029 | static auto op = create_gt__Scalar_typed_handle(); |
9030 | return op.call(self, other); |
9031 | } |
9032 | |
9033 | // aten::gt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9034 | at::Tensor & gt__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
9035 | |
9036 | static auto op = create_gt__Scalar_typed_handle(); |
9037 | return op.redispatch(dispatchKeySet, self, other); |
9038 | } |
9039 | |
9040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt__Tensor, name, "aten::gt_" ) |
9041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt__Tensor, overload_name, "Tensor" ) |
9042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(gt__Tensor, schema_str, "gt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
9043 | |
9044 | // aten::gt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9045 | static C10_NOINLINE c10::TypedOperatorHandle<gt__Tensor::schema> create_gt__Tensor_typed_handle() { |
9046 | return c10::Dispatcher::singleton() |
9047 | .findSchemaOrThrow(gt__Tensor::name, gt__Tensor::overload_name) |
9048 | .typed<gt__Tensor::schema>(); |
9049 | } |
9050 | |
9051 | // aten::gt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9052 | at::Tensor & gt__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
9053 | |
9054 | static auto op = create_gt__Tensor_typed_handle(); |
9055 | return op.call(self, other); |
9056 | } |
9057 | |
9058 | // aten::gt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9059 | at::Tensor & gt__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
9060 | |
9061 | static auto op = create_gt__Tensor_typed_handle(); |
9062 | return op.redispatch(dispatchKeySet, self, other); |
9063 | } |
9064 | |
9065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Scalar_out, name, "aten::lt" ) |
9066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Scalar_out, overload_name, "Scalar_out" ) |
9067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Scalar_out, schema_str, "lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9068 | |
9069 | // aten::lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
9070 | static C10_NOINLINE c10::TypedOperatorHandle<lt_Scalar_out::schema> create_lt_Scalar_out_typed_handle() { |
9071 | return c10::Dispatcher::singleton() |
9072 | .findSchemaOrThrow(lt_Scalar_out::name, lt_Scalar_out::overload_name) |
9073 | .typed<lt_Scalar_out::schema>(); |
9074 | } |
9075 | |
9076 | // aten::lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
9077 | at::Tensor & lt_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
9078 | |
9079 | static auto op = create_lt_Scalar_out_typed_handle(); |
9080 | return op.call(self, other, out); |
9081 | } |
9082 | |
9083 | // aten::lt.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
9084 | at::Tensor & lt_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
9085 | |
9086 | static auto op = create_lt_Scalar_out_typed_handle(); |
9087 | return op.redispatch(dispatchKeySet, self, other, out); |
9088 | } |
9089 | |
9090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Scalar, name, "aten::lt" ) |
9091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Scalar, overload_name, "Scalar" ) |
9092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Scalar, schema_str, "lt.Scalar(Tensor self, Scalar other) -> Tensor" ) |
9093 | |
9094 | // aten::lt.Scalar(Tensor self, Scalar other) -> Tensor |
9095 | static C10_NOINLINE c10::TypedOperatorHandle<lt_Scalar::schema> create_lt_Scalar_typed_handle() { |
9096 | return c10::Dispatcher::singleton() |
9097 | .findSchemaOrThrow(lt_Scalar::name, lt_Scalar::overload_name) |
9098 | .typed<lt_Scalar::schema>(); |
9099 | } |
9100 | |
9101 | // aten::lt.Scalar(Tensor self, Scalar other) -> Tensor |
9102 | at::Tensor lt_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
9103 | |
9104 | static auto op = create_lt_Scalar_typed_handle(); |
9105 | return op.call(self, other); |
9106 | } |
9107 | |
9108 | // aten::lt.Scalar(Tensor self, Scalar other) -> Tensor |
9109 | at::Tensor lt_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
9110 | |
9111 | static auto op = create_lt_Scalar_typed_handle(); |
9112 | return op.redispatch(dispatchKeySet, self, other); |
9113 | } |
9114 | |
9115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Tensor_out, name, "aten::lt" ) |
9116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Tensor_out, overload_name, "Tensor_out" ) |
9117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Tensor_out, schema_str, "lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9118 | |
9119 | // aten::lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9120 | static C10_NOINLINE c10::TypedOperatorHandle<lt_Tensor_out::schema> create_lt_Tensor_out_typed_handle() { |
9121 | return c10::Dispatcher::singleton() |
9122 | .findSchemaOrThrow(lt_Tensor_out::name, lt_Tensor_out::overload_name) |
9123 | .typed<lt_Tensor_out::schema>(); |
9124 | } |
9125 | |
9126 | // aten::lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9127 | at::Tensor & lt_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9128 | |
9129 | static auto op = create_lt_Tensor_out_typed_handle(); |
9130 | return op.call(self, other, out); |
9131 | } |
9132 | |
9133 | // aten::lt.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9134 | at::Tensor & lt_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9135 | |
9136 | static auto op = create_lt_Tensor_out_typed_handle(); |
9137 | return op.redispatch(dispatchKeySet, self, other, out); |
9138 | } |
9139 | |
9140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Tensor, name, "aten::lt" ) |
9141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Tensor, overload_name, "Tensor" ) |
9142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt_Tensor, schema_str, "lt.Tensor(Tensor self, Tensor other) -> Tensor" ) |
9143 | |
9144 | // aten::lt.Tensor(Tensor self, Tensor other) -> Tensor |
9145 | static C10_NOINLINE c10::TypedOperatorHandle<lt_Tensor::schema> create_lt_Tensor_typed_handle() { |
9146 | return c10::Dispatcher::singleton() |
9147 | .findSchemaOrThrow(lt_Tensor::name, lt_Tensor::overload_name) |
9148 | .typed<lt_Tensor::schema>(); |
9149 | } |
9150 | |
9151 | // aten::lt.Tensor(Tensor self, Tensor other) -> Tensor |
9152 | at::Tensor lt_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
9153 | |
9154 | static auto op = create_lt_Tensor_typed_handle(); |
9155 | return op.call(self, other); |
9156 | } |
9157 | |
9158 | // aten::lt.Tensor(Tensor self, Tensor other) -> Tensor |
9159 | at::Tensor lt_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
9160 | |
9161 | static auto op = create_lt_Tensor_typed_handle(); |
9162 | return op.redispatch(dispatchKeySet, self, other); |
9163 | } |
9164 | |
9165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt__Scalar, name, "aten::lt_" ) |
9166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt__Scalar, overload_name, "Scalar" ) |
9167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt__Scalar, schema_str, "lt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)" ) |
9168 | |
9169 | // aten::lt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9170 | static C10_NOINLINE c10::TypedOperatorHandle<lt__Scalar::schema> create_lt__Scalar_typed_handle() { |
9171 | return c10::Dispatcher::singleton() |
9172 | .findSchemaOrThrow(lt__Scalar::name, lt__Scalar::overload_name) |
9173 | .typed<lt__Scalar::schema>(); |
9174 | } |
9175 | |
9176 | // aten::lt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9177 | at::Tensor & lt__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
9178 | |
9179 | static auto op = create_lt__Scalar_typed_handle(); |
9180 | return op.call(self, other); |
9181 | } |
9182 | |
9183 | // aten::lt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9184 | at::Tensor & lt__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
9185 | |
9186 | static auto op = create_lt__Scalar_typed_handle(); |
9187 | return op.redispatch(dispatchKeySet, self, other); |
9188 | } |
9189 | |
9190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt__Tensor, name, "aten::lt_" ) |
9191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt__Tensor, overload_name, "Tensor" ) |
9192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(lt__Tensor, schema_str, "lt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
9193 | |
9194 | // aten::lt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9195 | static C10_NOINLINE c10::TypedOperatorHandle<lt__Tensor::schema> create_lt__Tensor_typed_handle() { |
9196 | return c10::Dispatcher::singleton() |
9197 | .findSchemaOrThrow(lt__Tensor::name, lt__Tensor::overload_name) |
9198 | .typed<lt__Tensor::schema>(); |
9199 | } |
9200 | |
9201 | // aten::lt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9202 | at::Tensor & lt__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
9203 | |
9204 | static auto op = create_lt__Tensor_typed_handle(); |
9205 | return op.call(self, other); |
9206 | } |
9207 | |
9208 | // aten::lt_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9209 | at::Tensor & lt__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
9210 | |
9211 | static auto op = create_lt__Tensor_typed_handle(); |
9212 | return op.redispatch(dispatchKeySet, self, other); |
9213 | } |
9214 | |
9215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Scalar_out, name, "aten::less" ) |
9216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Scalar_out, overload_name, "Scalar_out" ) |
9217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Scalar_out, schema_str, "less.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9218 | |
9219 | // aten::less.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
9220 | static C10_NOINLINE c10::TypedOperatorHandle<less_Scalar_out::schema> create_less_Scalar_out_typed_handle() { |
9221 | return c10::Dispatcher::singleton() |
9222 | .findSchemaOrThrow(less_Scalar_out::name, less_Scalar_out::overload_name) |
9223 | .typed<less_Scalar_out::schema>(); |
9224 | } |
9225 | |
9226 | // aten::less.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
9227 | at::Tensor & less_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
9228 | |
9229 | static auto op = create_less_Scalar_out_typed_handle(); |
9230 | return op.call(self, other, out); |
9231 | } |
9232 | |
9233 | // aten::less.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
9234 | at::Tensor & less_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
9235 | |
9236 | static auto op = create_less_Scalar_out_typed_handle(); |
9237 | return op.redispatch(dispatchKeySet, self, other, out); |
9238 | } |
9239 | |
9240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Scalar, name, "aten::less" ) |
9241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Scalar, overload_name, "Scalar" ) |
9242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Scalar, schema_str, "less.Scalar(Tensor self, Scalar other) -> Tensor" ) |
9243 | |
9244 | // aten::less.Scalar(Tensor self, Scalar other) -> Tensor |
9245 | static C10_NOINLINE c10::TypedOperatorHandle<less_Scalar::schema> create_less_Scalar_typed_handle() { |
9246 | return c10::Dispatcher::singleton() |
9247 | .findSchemaOrThrow(less_Scalar::name, less_Scalar::overload_name) |
9248 | .typed<less_Scalar::schema>(); |
9249 | } |
9250 | |
9251 | // aten::less.Scalar(Tensor self, Scalar other) -> Tensor |
9252 | at::Tensor less_Scalar::call(const at::Tensor & self, const at::Scalar & other) { |
9253 | |
9254 | static auto op = create_less_Scalar_typed_handle(); |
9255 | return op.call(self, other); |
9256 | } |
9257 | |
9258 | // aten::less.Scalar(Tensor self, Scalar other) -> Tensor |
9259 | at::Tensor less_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
9260 | |
9261 | static auto op = create_less_Scalar_typed_handle(); |
9262 | return op.redispatch(dispatchKeySet, self, other); |
9263 | } |
9264 | |
9265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Tensor_out, name, "aten::less" ) |
9266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Tensor_out, overload_name, "Tensor_out" ) |
9267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Tensor_out, schema_str, "less.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9268 | |
9269 | // aten::less.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9270 | static C10_NOINLINE c10::TypedOperatorHandle<less_Tensor_out::schema> create_less_Tensor_out_typed_handle() { |
9271 | return c10::Dispatcher::singleton() |
9272 | .findSchemaOrThrow(less_Tensor_out::name, less_Tensor_out::overload_name) |
9273 | .typed<less_Tensor_out::schema>(); |
9274 | } |
9275 | |
9276 | // aten::less.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9277 | at::Tensor & less_Tensor_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9278 | |
9279 | static auto op = create_less_Tensor_out_typed_handle(); |
9280 | return op.call(self, other, out); |
9281 | } |
9282 | |
9283 | // aten::less.Tensor_out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9284 | at::Tensor & less_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9285 | |
9286 | static auto op = create_less_Tensor_out_typed_handle(); |
9287 | return op.redispatch(dispatchKeySet, self, other, out); |
9288 | } |
9289 | |
9290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Tensor, name, "aten::less" ) |
9291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Tensor, overload_name, "Tensor" ) |
9292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less_Tensor, schema_str, "less.Tensor(Tensor self, Tensor other) -> Tensor" ) |
9293 | |
9294 | // aten::less.Tensor(Tensor self, Tensor other) -> Tensor |
9295 | static C10_NOINLINE c10::TypedOperatorHandle<less_Tensor::schema> create_less_Tensor_typed_handle() { |
9296 | return c10::Dispatcher::singleton() |
9297 | .findSchemaOrThrow(less_Tensor::name, less_Tensor::overload_name) |
9298 | .typed<less_Tensor::schema>(); |
9299 | } |
9300 | |
9301 | // aten::less.Tensor(Tensor self, Tensor other) -> Tensor |
9302 | at::Tensor less_Tensor::call(const at::Tensor & self, const at::Tensor & other) { |
9303 | |
9304 | static auto op = create_less_Tensor_typed_handle(); |
9305 | return op.call(self, other); |
9306 | } |
9307 | |
9308 | // aten::less.Tensor(Tensor self, Tensor other) -> Tensor |
9309 | at::Tensor less_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
9310 | |
9311 | static auto op = create_less_Tensor_typed_handle(); |
9312 | return op.redispatch(dispatchKeySet, self, other); |
9313 | } |
9314 | |
9315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less__Scalar, name, "aten::less_" ) |
9316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less__Scalar, overload_name, "Scalar" ) |
9317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less__Scalar, schema_str, "less_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)" ) |
9318 | |
9319 | // aten::less_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9320 | static C10_NOINLINE c10::TypedOperatorHandle<less__Scalar::schema> create_less__Scalar_typed_handle() { |
9321 | return c10::Dispatcher::singleton() |
9322 | .findSchemaOrThrow(less__Scalar::name, less__Scalar::overload_name) |
9323 | .typed<less__Scalar::schema>(); |
9324 | } |
9325 | |
9326 | // aten::less_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9327 | at::Tensor & less__Scalar::call(at::Tensor & self, const at::Scalar & other) { |
9328 | |
9329 | static auto op = create_less__Scalar_typed_handle(); |
9330 | return op.call(self, other); |
9331 | } |
9332 | |
9333 | // aten::less_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!) |
9334 | at::Tensor & less__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Scalar & other) { |
9335 | |
9336 | static auto op = create_less__Scalar_typed_handle(); |
9337 | return op.redispatch(dispatchKeySet, self, other); |
9338 | } |
9339 | |
9340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less__Tensor, name, "aten::less_" ) |
9341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less__Tensor, overload_name, "Tensor" ) |
9342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(less__Tensor, schema_str, "less_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
9343 | |
9344 | // aten::less_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9345 | static C10_NOINLINE c10::TypedOperatorHandle<less__Tensor::schema> create_less__Tensor_typed_handle() { |
9346 | return c10::Dispatcher::singleton() |
9347 | .findSchemaOrThrow(less__Tensor::name, less__Tensor::overload_name) |
9348 | .typed<less__Tensor::schema>(); |
9349 | } |
9350 | |
9351 | // aten::less_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9352 | at::Tensor & less__Tensor::call(at::Tensor & self, const at::Tensor & other) { |
9353 | |
9354 | static auto op = create_less__Tensor_typed_handle(); |
9355 | return op.call(self, other); |
9356 | } |
9357 | |
9358 | // aten::less_.Tensor(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9359 | at::Tensor & less__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
9360 | |
9361 | static auto op = create_less__Tensor_typed_handle(); |
9362 | return op.redispatch(dispatchKeySet, self, other); |
9363 | } |
9364 | |
9365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select_out, name, "aten::masked_select" ) |
9366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select_out, overload_name, "out" ) |
9367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select_out, schema_str, "masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!)" ) |
9368 | |
9369 | // aten::masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) |
9370 | static C10_NOINLINE c10::TypedOperatorHandle<masked_select_out::schema> create_masked_select_out_typed_handle() { |
9371 | return c10::Dispatcher::singleton() |
9372 | .findSchemaOrThrow(masked_select_out::name, masked_select_out::overload_name) |
9373 | .typed<masked_select_out::schema>(); |
9374 | } |
9375 | |
9376 | // aten::masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) |
9377 | at::Tensor & masked_select_out::call(const at::Tensor & self, const at::Tensor & mask, at::Tensor & out) { |
9378 | |
9379 | static auto op = create_masked_select_out_typed_handle(); |
9380 | return op.call(self, mask, out); |
9381 | } |
9382 | |
9383 | // aten::masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!) |
9384 | at::Tensor & masked_select_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask, at::Tensor & out) { |
9385 | |
9386 | static auto op = create_masked_select_out_typed_handle(); |
9387 | return op.redispatch(dispatchKeySet, self, mask, out); |
9388 | } |
9389 | |
9390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select, name, "aten::masked_select" ) |
9391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select, overload_name, "" ) |
9392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(masked_select, schema_str, "masked_select(Tensor self, Tensor mask) -> Tensor" ) |
9393 | |
9394 | // aten::masked_select(Tensor self, Tensor mask) -> Tensor |
9395 | static C10_NOINLINE c10::TypedOperatorHandle<masked_select::schema> create_masked_select_typed_handle() { |
9396 | return c10::Dispatcher::singleton() |
9397 | .findSchemaOrThrow(masked_select::name, masked_select::overload_name) |
9398 | .typed<masked_select::schema>(); |
9399 | } |
9400 | |
9401 | // aten::masked_select(Tensor self, Tensor mask) -> Tensor |
9402 | at::Tensor masked_select::call(const at::Tensor & self, const at::Tensor & mask) { |
9403 | |
9404 | static auto op = create_masked_select_typed_handle(); |
9405 | return op.call(self, mask); |
9406 | } |
9407 | |
9408 | // aten::masked_select(Tensor self, Tensor mask) -> Tensor |
9409 | at::Tensor masked_select::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & mask) { |
9410 | |
9411 | static auto op = create_masked_select_typed_handle(); |
9412 | return op.redispatch(dispatchKeySet, self, mask); |
9413 | } |
9414 | |
9415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv_out, name, "aten::addcdiv" ) |
9416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv_out, overload_name, "out" ) |
9417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv_out, schema_str, "addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!)" ) |
9418 | |
9419 | // aten::addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) |
9420 | static C10_NOINLINE c10::TypedOperatorHandle<addcdiv_out::schema> create_addcdiv_out_typed_handle() { |
9421 | return c10::Dispatcher::singleton() |
9422 | .findSchemaOrThrow(addcdiv_out::name, addcdiv_out::overload_name) |
9423 | .typed<addcdiv_out::schema>(); |
9424 | } |
9425 | |
9426 | // aten::addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) |
9427 | at::Tensor & addcdiv_out::call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out) { |
9428 | |
9429 | static auto op = create_addcdiv_out_typed_handle(); |
9430 | return op.call(self, tensor1, tensor2, value, out); |
9431 | } |
9432 | |
9433 | // aten::addcdiv.out(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1, Tensor(a!) out) -> Tensor(a!) |
9434 | at::Tensor & addcdiv_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value, at::Tensor & out) { |
9435 | |
9436 | static auto op = create_addcdiv_out_typed_handle(); |
9437 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value, out); |
9438 | } |
9439 | |
9440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv, name, "aten::addcdiv" ) |
9441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv, overload_name, "" ) |
9442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv, schema_str, "addcdiv(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor" ) |
9443 | |
9444 | // aten::addcdiv(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor |
9445 | static C10_NOINLINE c10::TypedOperatorHandle<addcdiv::schema> create_addcdiv_typed_handle() { |
9446 | return c10::Dispatcher::singleton() |
9447 | .findSchemaOrThrow(addcdiv::name, addcdiv::overload_name) |
9448 | .typed<addcdiv::schema>(); |
9449 | } |
9450 | |
9451 | // aten::addcdiv(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor |
9452 | at::Tensor addcdiv::call(const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
9453 | |
9454 | static auto op = create_addcdiv_typed_handle(); |
9455 | return op.call(self, tensor1, tensor2, value); |
9456 | } |
9457 | |
9458 | // aten::addcdiv(Tensor self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor |
9459 | at::Tensor addcdiv::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
9460 | |
9461 | static auto op = create_addcdiv_typed_handle(); |
9462 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value); |
9463 | } |
9464 | |
9465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv_, name, "aten::addcdiv_" ) |
9466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv_, overload_name, "" ) |
9467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(addcdiv_, schema_str, "addcdiv_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!)" ) |
9468 | |
9469 | // aten::addcdiv_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!) |
9470 | static C10_NOINLINE c10::TypedOperatorHandle<addcdiv_::schema> create_addcdiv__typed_handle() { |
9471 | return c10::Dispatcher::singleton() |
9472 | .findSchemaOrThrow(addcdiv_::name, addcdiv_::overload_name) |
9473 | .typed<addcdiv_::schema>(); |
9474 | } |
9475 | |
9476 | // aten::addcdiv_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!) |
9477 | at::Tensor & addcdiv_::call(at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
9478 | |
9479 | static auto op = create_addcdiv__typed_handle(); |
9480 | return op.call(self, tensor1, tensor2, value); |
9481 | } |
9482 | |
9483 | // aten::addcdiv_(Tensor(a!) self, Tensor tensor1, Tensor tensor2, *, Scalar value=1) -> Tensor(a!) |
9484 | at::Tensor & addcdiv_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & tensor1, const at::Tensor & tensor2, const at::Scalar & value) { |
9485 | |
9486 | static auto op = create_addcdiv__typed_handle(); |
9487 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value); |
9488 | } |
9489 | |
9490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cholesky_solve_helper, name, "aten::_cholesky_solve_helper" ) |
9491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cholesky_solve_helper, overload_name, "" ) |
9492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cholesky_solve_helper, schema_str, "_cholesky_solve_helper(Tensor self, Tensor A, bool upper) -> Tensor" ) |
9493 | |
9494 | // aten::_cholesky_solve_helper(Tensor self, Tensor A, bool upper) -> Tensor |
9495 | static C10_NOINLINE c10::TypedOperatorHandle<_cholesky_solve_helper::schema> create__cholesky_solve_helper_typed_handle() { |
9496 | return c10::Dispatcher::singleton() |
9497 | .findSchemaOrThrow(_cholesky_solve_helper::name, _cholesky_solve_helper::overload_name) |
9498 | .typed<_cholesky_solve_helper::schema>(); |
9499 | } |
9500 | |
9501 | // aten::_cholesky_solve_helper(Tensor self, Tensor A, bool upper) -> Tensor |
9502 | at::Tensor _cholesky_solve_helper::call(const at::Tensor & self, const at::Tensor & A, bool upper) { |
9503 | |
9504 | static auto op = create__cholesky_solve_helper_typed_handle(); |
9505 | return op.call(self, A, upper); |
9506 | } |
9507 | |
9508 | // aten::_cholesky_solve_helper(Tensor self, Tensor A, bool upper) -> Tensor |
9509 | at::Tensor _cholesky_solve_helper::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper) { |
9510 | |
9511 | static auto op = create__cholesky_solve_helper_typed_handle(); |
9512 | return op.redispatch(dispatchKeySet, self, A, upper); |
9513 | } |
9514 | |
9515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_inverse, name, "aten::cholesky_inverse" ) |
9516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_inverse, overload_name, "" ) |
9517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_inverse, schema_str, "cholesky_inverse(Tensor self, bool upper=False) -> Tensor" ) |
9518 | |
9519 | // aten::cholesky_inverse(Tensor self, bool upper=False) -> Tensor |
9520 | static C10_NOINLINE c10::TypedOperatorHandle<cholesky_inverse::schema> create_cholesky_inverse_typed_handle() { |
9521 | return c10::Dispatcher::singleton() |
9522 | .findSchemaOrThrow(cholesky_inverse::name, cholesky_inverse::overload_name) |
9523 | .typed<cholesky_inverse::schema>(); |
9524 | } |
9525 | |
9526 | // aten::cholesky_inverse(Tensor self, bool upper=False) -> Tensor |
9527 | at::Tensor cholesky_inverse::call(const at::Tensor & self, bool upper) { |
9528 | |
9529 | static auto op = create_cholesky_inverse_typed_handle(); |
9530 | return op.call(self, upper); |
9531 | } |
9532 | |
9533 | // aten::cholesky_inverse(Tensor self, bool upper=False) -> Tensor |
9534 | at::Tensor cholesky_inverse::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper) { |
9535 | |
9536 | static auto op = create_cholesky_inverse_typed_handle(); |
9537 | return op.redispatch(dispatchKeySet, self, upper); |
9538 | } |
9539 | |
9540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_inverse_out, name, "aten::cholesky_inverse" ) |
9541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_inverse_out, overload_name, "out" ) |
9542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cholesky_inverse_out, schema_str, "cholesky_inverse.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
9543 | |
9544 | // aten::cholesky_inverse.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) |
9545 | static C10_NOINLINE c10::TypedOperatorHandle<cholesky_inverse_out::schema> create_cholesky_inverse_out_typed_handle() { |
9546 | return c10::Dispatcher::singleton() |
9547 | .findSchemaOrThrow(cholesky_inverse_out::name, cholesky_inverse_out::overload_name) |
9548 | .typed<cholesky_inverse_out::schema>(); |
9549 | } |
9550 | |
9551 | // aten::cholesky_inverse.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) |
9552 | at::Tensor & cholesky_inverse_out::call(const at::Tensor & self, bool upper, at::Tensor & out) { |
9553 | |
9554 | static auto op = create_cholesky_inverse_out_typed_handle(); |
9555 | return op.call(self, upper, out); |
9556 | } |
9557 | |
9558 | // aten::cholesky_inverse.out(Tensor self, bool upper=False, *, Tensor(a!) out) -> Tensor(a!) |
9559 | at::Tensor & cholesky_inverse_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool upper, at::Tensor & out) { |
9560 | |
9561 | static auto op = create_cholesky_inverse_out_typed_handle(); |
9562 | return op.redispatch(dispatchKeySet, self, upper, out); |
9563 | } |
9564 | |
9565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_lu_with_info, name, "aten::_lu_with_info" ) |
9566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_lu_with_info, overload_name, "" ) |
9567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_lu_with_info, schema_str, "_lu_with_info(Tensor self, bool pivot=True, bool check_errors=True) -> (Tensor LU, Tensor pivots, Tensor info)" ) |
9568 | |
9569 | // aten::_lu_with_info(Tensor self, bool pivot=True, bool check_errors=True) -> (Tensor LU, Tensor pivots, Tensor info) |
9570 | static C10_NOINLINE c10::TypedOperatorHandle<_lu_with_info::schema> create__lu_with_info_typed_handle() { |
9571 | return c10::Dispatcher::singleton() |
9572 | .findSchemaOrThrow(_lu_with_info::name, _lu_with_info::overload_name) |
9573 | .typed<_lu_with_info::schema>(); |
9574 | } |
9575 | |
9576 | // aten::_lu_with_info(Tensor self, bool pivot=True, bool check_errors=True) -> (Tensor LU, Tensor pivots, Tensor info) |
9577 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _lu_with_info::call(const at::Tensor & self, bool pivot, bool check_errors) { |
9578 | |
9579 | static auto op = create__lu_with_info_typed_handle(); |
9580 | return op.call(self, pivot, check_errors); |
9581 | } |
9582 | |
9583 | // aten::_lu_with_info(Tensor self, bool pivot=True, bool check_errors=True) -> (Tensor LU, Tensor pivots, Tensor info) |
9584 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> _lu_with_info::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool pivot, bool check_errors) { |
9585 | |
9586 | static auto op = create__lu_with_info_typed_handle(); |
9587 | return op.redispatch(dispatchKeySet, self, pivot, check_errors); |
9588 | } |
9589 | |
9590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2_out, name, "aten::atan2" ) |
9591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2_out, overload_name, "out" ) |
9592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2_out, schema_str, "atan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9593 | |
9594 | // aten::atan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9595 | static C10_NOINLINE c10::TypedOperatorHandle<atan2_out::schema> create_atan2_out_typed_handle() { |
9596 | return c10::Dispatcher::singleton() |
9597 | .findSchemaOrThrow(atan2_out::name, atan2_out::overload_name) |
9598 | .typed<atan2_out::schema>(); |
9599 | } |
9600 | |
9601 | // aten::atan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9602 | at::Tensor & atan2_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9603 | |
9604 | static auto op = create_atan2_out_typed_handle(); |
9605 | return op.call(self, other, out); |
9606 | } |
9607 | |
9608 | // aten::atan2.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9609 | at::Tensor & atan2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9610 | |
9611 | static auto op = create_atan2_out_typed_handle(); |
9612 | return op.redispatch(dispatchKeySet, self, other, out); |
9613 | } |
9614 | |
9615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2_, name, "aten::atan2_" ) |
9616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2_, overload_name, "" ) |
9617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2_, schema_str, "atan2_(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
9618 | |
9619 | // aten::atan2_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9620 | static C10_NOINLINE c10::TypedOperatorHandle<atan2_::schema> create_atan2__typed_handle() { |
9621 | return c10::Dispatcher::singleton() |
9622 | .findSchemaOrThrow(atan2_::name, atan2_::overload_name) |
9623 | .typed<atan2_::schema>(); |
9624 | } |
9625 | |
9626 | // aten::atan2_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9627 | at::Tensor & atan2_::call(at::Tensor & self, const at::Tensor & other) { |
9628 | |
9629 | static auto op = create_atan2__typed_handle(); |
9630 | return op.call(self, other); |
9631 | } |
9632 | |
9633 | // aten::atan2_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9634 | at::Tensor & atan2_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
9635 | |
9636 | static auto op = create_atan2__typed_handle(); |
9637 | return op.redispatch(dispatchKeySet, self, other); |
9638 | } |
9639 | |
9640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2, name, "aten::atan2" ) |
9641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2, overload_name, "" ) |
9642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(atan2, schema_str, "atan2(Tensor self, Tensor other) -> Tensor" ) |
9643 | |
9644 | // aten::atan2(Tensor self, Tensor other) -> Tensor |
9645 | static C10_NOINLINE c10::TypedOperatorHandle<atan2::schema> create_atan2_typed_handle() { |
9646 | return c10::Dispatcher::singleton() |
9647 | .findSchemaOrThrow(atan2::name, atan2::overload_name) |
9648 | .typed<atan2::schema>(); |
9649 | } |
9650 | |
9651 | // aten::atan2(Tensor self, Tensor other) -> Tensor |
9652 | at::Tensor atan2::call(const at::Tensor & self, const at::Tensor & other) { |
9653 | |
9654 | static auto op = create_atan2_typed_handle(); |
9655 | return op.call(self, other); |
9656 | } |
9657 | |
9658 | // aten::atan2(Tensor self, Tensor other) -> Tensor |
9659 | at::Tensor atan2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
9660 | |
9661 | static auto op = create_atan2_typed_handle(); |
9662 | return op.redispatch(dispatchKeySet, self, other); |
9663 | } |
9664 | |
9665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd, name, "aten::histogramdd" ) |
9666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd, overload_name, "" ) |
9667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd, schema_str, "histogramdd(Tensor self, int[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges)" ) |
9668 | |
9669 | // aten::histogramdd(Tensor self, int[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9670 | static C10_NOINLINE c10::TypedOperatorHandle<histogramdd::schema> create_histogramdd_typed_handle() { |
9671 | return c10::Dispatcher::singleton() |
9672 | .findSchemaOrThrow(histogramdd::name, histogramdd::overload_name) |
9673 | .typed<histogramdd::schema>(); |
9674 | } |
9675 | |
9676 | // aten::histogramdd(Tensor self, int[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9677 | ::std::tuple<at::Tensor,::std::vector<at::Tensor>> histogramdd::call(const at::Tensor & self, at::IntArrayRef bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
9678 | |
9679 | static auto op = create_histogramdd_typed_handle(); |
9680 | return op.call(self, bins, range, weight, density); |
9681 | } |
9682 | |
9683 | // aten::histogramdd(Tensor self, int[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9684 | ::std::tuple<at::Tensor,::std::vector<at::Tensor>> histogramdd::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) { |
9685 | |
9686 | static auto op = create_histogramdd_typed_handle(); |
9687 | return op.redispatch(dispatchKeySet, self, bins, range, weight, density); |
9688 | } |
9689 | |
9690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd_int_bins, name, "aten::histogramdd" ) |
9691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd_int_bins, overload_name, "int_bins" ) |
9692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd_int_bins, schema_str, "histogramdd.int_bins(Tensor self, int bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges)" ) |
9693 | |
9694 | // aten::histogramdd.int_bins(Tensor self, int bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9695 | static C10_NOINLINE c10::TypedOperatorHandle<histogramdd_int_bins::schema> create_histogramdd_int_bins_typed_handle() { |
9696 | return c10::Dispatcher::singleton() |
9697 | .findSchemaOrThrow(histogramdd_int_bins::name, histogramdd_int_bins::overload_name) |
9698 | .typed<histogramdd_int_bins::schema>(); |
9699 | } |
9700 | |
9701 | // aten::histogramdd.int_bins(Tensor self, int bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9702 | ::std::tuple<at::Tensor,::std::vector<at::Tensor>> histogramdd_int_bins::call(const at::Tensor & self, int64_t bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
9703 | |
9704 | static auto op = create_histogramdd_int_bins_typed_handle(); |
9705 | return op.call(self, bins, range, weight, density); |
9706 | } |
9707 | |
9708 | // aten::histogramdd.int_bins(Tensor self, int bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9709 | ::std::tuple<at::Tensor,::std::vector<at::Tensor>> histogramdd_int_bins::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
9710 | |
9711 | static auto op = create_histogramdd_int_bins_typed_handle(); |
9712 | return op.redispatch(dispatchKeySet, self, bins, range, weight, density); |
9713 | } |
9714 | |
9715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd_TensorList_bins, name, "aten::histogramdd" ) |
9716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd_TensorList_bins, overload_name, "TensorList_bins" ) |
9717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(histogramdd_TensorList_bins, schema_str, "histogramdd.TensorList_bins(Tensor self, Tensor[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges)" ) |
9718 | |
9719 | // aten::histogramdd.TensorList_bins(Tensor self, Tensor[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9720 | static C10_NOINLINE c10::TypedOperatorHandle<histogramdd_TensorList_bins::schema> create_histogramdd_TensorList_bins_typed_handle() { |
9721 | return c10::Dispatcher::singleton() |
9722 | .findSchemaOrThrow(histogramdd_TensorList_bins::name, histogramdd_TensorList_bins::overload_name) |
9723 | .typed<histogramdd_TensorList_bins::schema>(); |
9724 | } |
9725 | |
9726 | // aten::histogramdd.TensorList_bins(Tensor self, Tensor[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9727 | ::std::tuple<at::Tensor,::std::vector<at::Tensor>> histogramdd_TensorList_bins::call(const at::Tensor & self, at::TensorList bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
9728 | |
9729 | static auto op = create_histogramdd_TensorList_bins_typed_handle(); |
9730 | return op.call(self, bins, range, weight, density); |
9731 | } |
9732 | |
9733 | // aten::histogramdd.TensorList_bins(Tensor self, Tensor[] bins, float[]? range=None, Tensor? weight=None, bool density=False) -> (Tensor hist, Tensor[] bin_edges) |
9734 | ::std::tuple<at::Tensor,::std::vector<at::Tensor>> histogramdd_TensorList_bins::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::TensorList bins, c10::optional<at::ArrayRef<double>> range, const c10::optional<at::Tensor> & weight, bool density) { |
9735 | |
9736 | static auto op = create_histogramdd_TensorList_bins_typed_handle(); |
9737 | return op.redispatch(dispatchKeySet, self, bins, range, weight, density); |
9738 | } |
9739 | |
9740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot_out, name, "aten::hypot" ) |
9741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot_out, overload_name, "out" ) |
9742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot_out, schema_str, "hypot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9743 | |
9744 | // aten::hypot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9745 | static C10_NOINLINE c10::TypedOperatorHandle<hypot_out::schema> create_hypot_out_typed_handle() { |
9746 | return c10::Dispatcher::singleton() |
9747 | .findSchemaOrThrow(hypot_out::name, hypot_out::overload_name) |
9748 | .typed<hypot_out::schema>(); |
9749 | } |
9750 | |
9751 | // aten::hypot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9752 | at::Tensor & hypot_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9753 | |
9754 | static auto op = create_hypot_out_typed_handle(); |
9755 | return op.call(self, other, out); |
9756 | } |
9757 | |
9758 | // aten::hypot.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9759 | at::Tensor & hypot_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9760 | |
9761 | static auto op = create_hypot_out_typed_handle(); |
9762 | return op.redispatch(dispatchKeySet, self, other, out); |
9763 | } |
9764 | |
9765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot, name, "aten::hypot" ) |
9766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot, overload_name, "" ) |
9767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot, schema_str, "hypot(Tensor self, Tensor other) -> Tensor" ) |
9768 | |
9769 | // aten::hypot(Tensor self, Tensor other) -> Tensor |
9770 | static C10_NOINLINE c10::TypedOperatorHandle<hypot::schema> create_hypot_typed_handle() { |
9771 | return c10::Dispatcher::singleton() |
9772 | .findSchemaOrThrow(hypot::name, hypot::overload_name) |
9773 | .typed<hypot::schema>(); |
9774 | } |
9775 | |
9776 | // aten::hypot(Tensor self, Tensor other) -> Tensor |
9777 | at::Tensor hypot::call(const at::Tensor & self, const at::Tensor & other) { |
9778 | |
9779 | static auto op = create_hypot_typed_handle(); |
9780 | return op.call(self, other); |
9781 | } |
9782 | |
9783 | // aten::hypot(Tensor self, Tensor other) -> Tensor |
9784 | at::Tensor hypot::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
9785 | |
9786 | static auto op = create_hypot_typed_handle(); |
9787 | return op.redispatch(dispatchKeySet, self, other); |
9788 | } |
9789 | |
9790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot_, name, "aten::hypot_" ) |
9791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot_, overload_name, "" ) |
9792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hypot_, schema_str, "hypot_(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
9793 | |
9794 | // aten::hypot_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9795 | static C10_NOINLINE c10::TypedOperatorHandle<hypot_::schema> create_hypot__typed_handle() { |
9796 | return c10::Dispatcher::singleton() |
9797 | .findSchemaOrThrow(hypot_::name, hypot_::overload_name) |
9798 | .typed<hypot_::schema>(); |
9799 | } |
9800 | |
9801 | // aten::hypot_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9802 | at::Tensor & hypot_::call(at::Tensor & self, const at::Tensor & other) { |
9803 | |
9804 | static auto op = create_hypot__typed_handle(); |
9805 | return op.call(self, other); |
9806 | } |
9807 | |
9808 | // aten::hypot_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9809 | at::Tensor & hypot_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
9810 | |
9811 | static auto op = create_hypot__typed_handle(); |
9812 | return op.redispatch(dispatchKeySet, self, other); |
9813 | } |
9814 | |
9815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac_out, name, "aten::igammac" ) |
9816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac_out, overload_name, "out" ) |
9817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac_out, schema_str, "igammac.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9818 | |
9819 | // aten::igammac.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9820 | static C10_NOINLINE c10::TypedOperatorHandle<igammac_out::schema> create_igammac_out_typed_handle() { |
9821 | return c10::Dispatcher::singleton() |
9822 | .findSchemaOrThrow(igammac_out::name, igammac_out::overload_name) |
9823 | .typed<igammac_out::schema>(); |
9824 | } |
9825 | |
9826 | // aten::igammac.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9827 | at::Tensor & igammac_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9828 | |
9829 | static auto op = create_igammac_out_typed_handle(); |
9830 | return op.call(self, other, out); |
9831 | } |
9832 | |
9833 | // aten::igammac.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9834 | at::Tensor & igammac_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9835 | |
9836 | static auto op = create_igammac_out_typed_handle(); |
9837 | return op.redispatch(dispatchKeySet, self, other, out); |
9838 | } |
9839 | |
9840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac, name, "aten::igammac" ) |
9841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac, overload_name, "" ) |
9842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac, schema_str, "igammac(Tensor self, Tensor other) -> Tensor" ) |
9843 | |
9844 | // aten::igammac(Tensor self, Tensor other) -> Tensor |
9845 | static C10_NOINLINE c10::TypedOperatorHandle<igammac::schema> create_igammac_typed_handle() { |
9846 | return c10::Dispatcher::singleton() |
9847 | .findSchemaOrThrow(igammac::name, igammac::overload_name) |
9848 | .typed<igammac::schema>(); |
9849 | } |
9850 | |
9851 | // aten::igammac(Tensor self, Tensor other) -> Tensor |
9852 | at::Tensor igammac::call(const at::Tensor & self, const at::Tensor & other) { |
9853 | |
9854 | static auto op = create_igammac_typed_handle(); |
9855 | return op.call(self, other); |
9856 | } |
9857 | |
9858 | // aten::igammac(Tensor self, Tensor other) -> Tensor |
9859 | at::Tensor igammac::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
9860 | |
9861 | static auto op = create_igammac_typed_handle(); |
9862 | return op.redispatch(dispatchKeySet, self, other); |
9863 | } |
9864 | |
9865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac_, name, "aten::igammac_" ) |
9866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac_, overload_name, "" ) |
9867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(igammac_, schema_str, "igammac_(Tensor(a!) self, Tensor other) -> Tensor(a!)" ) |
9868 | |
9869 | // aten::igammac_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9870 | static C10_NOINLINE c10::TypedOperatorHandle<igammac_::schema> create_igammac__typed_handle() { |
9871 | return c10::Dispatcher::singleton() |
9872 | .findSchemaOrThrow(igammac_::name, igammac_::overload_name) |
9873 | .typed<igammac_::schema>(); |
9874 | } |
9875 | |
9876 | // aten::igammac_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9877 | at::Tensor & igammac_::call(at::Tensor & self, const at::Tensor & other) { |
9878 | |
9879 | static auto op = create_igammac__typed_handle(); |
9880 | return op.call(self, other); |
9881 | } |
9882 | |
9883 | // aten::igammac_(Tensor(a!) self, Tensor other) -> Tensor(a!) |
9884 | at::Tensor & igammac_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & other) { |
9885 | |
9886 | static auto op = create_igammac__typed_handle(); |
9887 | return op.redispatch(dispatchKeySet, self, other); |
9888 | } |
9889 | |
9890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmax, name, "aten::fmax" ) |
9891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmax, overload_name, "" ) |
9892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmax, schema_str, "fmax(Tensor self, Tensor other) -> Tensor" ) |
9893 | |
9894 | // aten::fmax(Tensor self, Tensor other) -> Tensor |
9895 | static C10_NOINLINE c10::TypedOperatorHandle<fmax::schema> create_fmax_typed_handle() { |
9896 | return c10::Dispatcher::singleton() |
9897 | .findSchemaOrThrow(fmax::name, fmax::overload_name) |
9898 | .typed<fmax::schema>(); |
9899 | } |
9900 | |
9901 | // aten::fmax(Tensor self, Tensor other) -> Tensor |
9902 | at::Tensor fmax::call(const at::Tensor & self, const at::Tensor & other) { |
9903 | |
9904 | static auto op = create_fmax_typed_handle(); |
9905 | return op.call(self, other); |
9906 | } |
9907 | |
9908 | // aten::fmax(Tensor self, Tensor other) -> Tensor |
9909 | at::Tensor fmax::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
9910 | |
9911 | static auto op = create_fmax_typed_handle(); |
9912 | return op.redispatch(dispatchKeySet, self, other); |
9913 | } |
9914 | |
9915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmax_out, name, "aten::fmax" ) |
9916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmax_out, overload_name, "out" ) |
9917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fmax_out, schema_str, "fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
9918 | |
9919 | // aten::fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9920 | static C10_NOINLINE c10::TypedOperatorHandle<fmax_out::schema> create_fmax_out_typed_handle() { |
9921 | return c10::Dispatcher::singleton() |
9922 | .findSchemaOrThrow(fmax_out::name, fmax_out::overload_name) |
9923 | .typed<fmax_out::schema>(); |
9924 | } |
9925 | |
9926 | // aten::fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9927 | at::Tensor & fmax_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9928 | |
9929 | static auto op = create_fmax_out_typed_handle(); |
9930 | return op.call(self, other, out); |
9931 | } |
9932 | |
9933 | // aten::fmax.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
9934 | at::Tensor & fmax_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
9935 | |
9936 | static auto op = create_fmax_out_typed_handle(); |
9937 | return op.redispatch(dispatchKeySet, self, other, out); |
9938 | } |
9939 | |
9940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_values, name, "aten::sort" ) |
9941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_values, overload_name, "values" ) |
9942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_values, schema_str, "sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)" ) |
9943 | |
9944 | // aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
9945 | static C10_NOINLINE c10::TypedOperatorHandle<sort_values::schema> create_sort_values_typed_handle() { |
9946 | return c10::Dispatcher::singleton() |
9947 | .findSchemaOrThrow(sort_values::name, sort_values::overload_name) |
9948 | .typed<sort_values::schema>(); |
9949 | } |
9950 | |
9951 | // aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
9952 | ::std::tuple<at::Tensor &,at::Tensor &> sort_values::call(const at::Tensor & self, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
9953 | |
9954 | static auto op = create_sort_values_typed_handle(); |
9955 | return op.call(self, dim, descending, values, indices); |
9956 | } |
9957 | |
9958 | // aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
9959 | ::std::tuple<at::Tensor &,at::Tensor &> sort_values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
9960 | |
9961 | static auto op = create_sort_values_typed_handle(); |
9962 | return op.redispatch(dispatchKeySet, self, dim, descending, values, indices); |
9963 | } |
9964 | |
9965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_values_stable, name, "aten::sort" ) |
9966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_values_stable, overload_name, "values_stable" ) |
9967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_values_stable, schema_str, "sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)" ) |
9968 | |
9969 | // aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
9970 | static C10_NOINLINE c10::TypedOperatorHandle<sort_values_stable::schema> create_sort_values_stable_typed_handle() { |
9971 | return c10::Dispatcher::singleton() |
9972 | .findSchemaOrThrow(sort_values_stable::name, sort_values_stable::overload_name) |
9973 | .typed<sort_values_stable::schema>(); |
9974 | } |
9975 | |
9976 | // aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
9977 | ::std::tuple<at::Tensor &,at::Tensor &> sort_values_stable::call(const at::Tensor & self, c10::optional<bool> stable, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
9978 | |
9979 | static auto op = create_sort_values_stable_typed_handle(); |
9980 | return op.call(self, stable, dim, descending, values, indices); |
9981 | } |
9982 | |
9983 | // aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
9984 | ::std::tuple<at::Tensor &,at::Tensor &> sort_values_stable::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<bool> stable, int64_t dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
9985 | |
9986 | static auto op = create_sort_values_stable_typed_handle(); |
9987 | return op.redispatch(dispatchKeySet, self, stable, dim, descending, values, indices); |
9988 | } |
9989 | |
9990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort, name, "aten::sort" ) |
9991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort, overload_name, "" ) |
9992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort, schema_str, "sort(Tensor self, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices)" ) |
9993 | |
9994 | // aten::sort(Tensor self, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) |
9995 | static C10_NOINLINE c10::TypedOperatorHandle<sort::schema> create_sort_typed_handle() { |
9996 | return c10::Dispatcher::singleton() |
9997 | .findSchemaOrThrow(sort::name, sort::overload_name) |
9998 | .typed<sort::schema>(); |
9999 | } |
10000 | |
10001 | // aten::sort(Tensor self, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) |
10002 | ::std::tuple<at::Tensor,at::Tensor> sort::call(const at::Tensor & self, int64_t dim, bool descending) { |
10003 | |
10004 | static auto op = create_sort_typed_handle(); |
10005 | return op.call(self, dim, descending); |
10006 | } |
10007 | |
10008 | // aten::sort(Tensor self, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) |
10009 | ::std::tuple<at::Tensor,at::Tensor> sort::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool descending) { |
10010 | |
10011 | static auto op = create_sort_typed_handle(); |
10012 | return op.redispatch(dispatchKeySet, self, dim, descending); |
10013 | } |
10014 | |
10015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_stable, name, "aten::sort" ) |
10016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_stable, overload_name, "stable" ) |
10017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_stable, schema_str, "sort.stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices)" ) |
10018 | |
10019 | // aten::sort.stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) |
10020 | static C10_NOINLINE c10::TypedOperatorHandle<sort_stable::schema> create_sort_stable_typed_handle() { |
10021 | return c10::Dispatcher::singleton() |
10022 | .findSchemaOrThrow(sort_stable::name, sort_stable::overload_name) |
10023 | .typed<sort_stable::schema>(); |
10024 | } |
10025 | |
10026 | // aten::sort.stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) |
10027 | ::std::tuple<at::Tensor,at::Tensor> sort_stable::call(const at::Tensor & self, c10::optional<bool> stable, int64_t dim, bool descending) { |
10028 | |
10029 | static auto op = create_sort_stable_typed_handle(); |
10030 | return op.call(self, stable, dim, descending); |
10031 | } |
10032 | |
10033 | // aten::sort.stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False) -> (Tensor values, Tensor indices) |
10034 | ::std::tuple<at::Tensor,at::Tensor> sort_stable::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<bool> stable, int64_t dim, bool descending) { |
10035 | |
10036 | static auto op = create_sort_stable_typed_handle(); |
10037 | return op.redispatch(dispatchKeySet, self, stable, dim, descending); |
10038 | } |
10039 | |
10040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_values, name, "aten::sort" ) |
10041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_values, overload_name, "dimname_values" ) |
10042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_values, schema_str, "sort.dimname_values(Tensor self, Dimname dim, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)" ) |
10043 | |
10044 | // aten::sort.dimname_values(Tensor self, Dimname dim, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
10045 | static C10_NOINLINE c10::TypedOperatorHandle<sort_dimname_values::schema> create_sort_dimname_values_typed_handle() { |
10046 | return c10::Dispatcher::singleton() |
10047 | .findSchemaOrThrow(sort_dimname_values::name, sort_dimname_values::overload_name) |
10048 | .typed<sort_dimname_values::schema>(); |
10049 | } |
10050 | |
10051 | // aten::sort.dimname_values(Tensor self, Dimname dim, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
10052 | ::std::tuple<at::Tensor &,at::Tensor &> sort_dimname_values::call(const at::Tensor & self, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
10053 | |
10054 | static auto op = create_sort_dimname_values_typed_handle(); |
10055 | return op.call(self, dim, descending, values, indices); |
10056 | } |
10057 | |
10058 | // aten::sort.dimname_values(Tensor self, Dimname dim, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
10059 | ::std::tuple<at::Tensor &,at::Tensor &> sort_dimname_values::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
10060 | |
10061 | static auto op = create_sort_dimname_values_typed_handle(); |
10062 | return op.redispatch(dispatchKeySet, self, dim, descending, values, indices); |
10063 | } |
10064 | |
10065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_values_stable, name, "aten::sort" ) |
10066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_values_stable, overload_name, "dimname_values_stable" ) |
10067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_values_stable, schema_str, "sort.dimname_values_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)" ) |
10068 | |
10069 | // aten::sort.dimname_values_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
10070 | static C10_NOINLINE c10::TypedOperatorHandle<sort_dimname_values_stable::schema> create_sort_dimname_values_stable_typed_handle() { |
10071 | return c10::Dispatcher::singleton() |
10072 | .findSchemaOrThrow(sort_dimname_values_stable::name, sort_dimname_values_stable::overload_name) |
10073 | .typed<sort_dimname_values_stable::schema>(); |
10074 | } |
10075 | |
10076 | // aten::sort.dimname_values_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
10077 | ::std::tuple<at::Tensor &,at::Tensor &> sort_dimname_values_stable::call(const at::Tensor & self, c10::optional<bool> stable, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
10078 | |
10079 | static auto op = create_sort_dimname_values_stable_typed_handle(); |
10080 | return op.call(self, stable, dim, descending, values, indices); |
10081 | } |
10082 | |
10083 | // aten::sort.dimname_values_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) |
10084 | ::std::tuple<at::Tensor &,at::Tensor &> sort_dimname_values_stable::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<bool> stable, at::Dimname dim, bool descending, at::Tensor & values, at::Tensor & indices) { |
10085 | |
10086 | static auto op = create_sort_dimname_values_stable_typed_handle(); |
10087 | return op.redispatch(dispatchKeySet, self, stable, dim, descending, values, indices); |
10088 | } |
10089 | |
10090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname, name, "aten::sort" ) |
10091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname, overload_name, "dimname" ) |
10092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname, schema_str, "sort.dimname(Tensor self, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices)" ) |
10093 | |
10094 | // aten::sort.dimname(Tensor self, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) |
10095 | static C10_NOINLINE c10::TypedOperatorHandle<sort_dimname::schema> create_sort_dimname_typed_handle() { |
10096 | return c10::Dispatcher::singleton() |
10097 | .findSchemaOrThrow(sort_dimname::name, sort_dimname::overload_name) |
10098 | .typed<sort_dimname::schema>(); |
10099 | } |
10100 | |
10101 | // aten::sort.dimname(Tensor self, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) |
10102 | ::std::tuple<at::Tensor,at::Tensor> sort_dimname::call(const at::Tensor & self, at::Dimname dim, bool descending) { |
10103 | |
10104 | static auto op = create_sort_dimname_typed_handle(); |
10105 | return op.call(self, dim, descending); |
10106 | } |
10107 | |
10108 | // aten::sort.dimname(Tensor self, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) |
10109 | ::std::tuple<at::Tensor,at::Tensor> sort_dimname::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Dimname dim, bool descending) { |
10110 | |
10111 | static auto op = create_sort_dimname_typed_handle(); |
10112 | return op.redispatch(dispatchKeySet, self, dim, descending); |
10113 | } |
10114 | |
10115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_stable, name, "aten::sort" ) |
10116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_stable, overload_name, "dimname_stable" ) |
10117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sort_dimname_stable, schema_str, "sort.dimname_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices)" ) |
10118 | |
10119 | // aten::sort.dimname_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) |
10120 | static C10_NOINLINE c10::TypedOperatorHandle<sort_dimname_stable::schema> create_sort_dimname_stable_typed_handle() { |
10121 | return c10::Dispatcher::singleton() |
10122 | .findSchemaOrThrow(sort_dimname_stable::name, sort_dimname_stable::overload_name) |
10123 | .typed<sort_dimname_stable::schema>(); |
10124 | } |
10125 | |
10126 | // aten::sort.dimname_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) |
10127 | ::std::tuple<at::Tensor,at::Tensor> sort_dimname_stable::call(const at::Tensor & self, c10::optional<bool> stable, at::Dimname dim, bool descending) { |
10128 | |
10129 | static auto op = create_sort_dimname_stable_typed_handle(); |
10130 | return op.call(self, stable, dim, descending); |
10131 | } |
10132 | |
10133 | // aten::sort.dimname_stable(Tensor self, *, bool? stable, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices) |
10134 | ::std::tuple<at::Tensor,at::Tensor> sort_dimname_stable::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<bool> stable, at::Dimname dim, bool descending) { |
10135 | |
10136 | static auto op = create_sort_dimname_stable_typed_handle(); |
10137 | return op.redispatch(dispatchKeySet, self, stable, dim, descending); |
10138 | } |
10139 | |
10140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all, name, "aten::all" ) |
10141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all, overload_name, "" ) |
10142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all, schema_str, "all(Tensor self) -> Tensor" ) |
10143 | |
10144 | // aten::all(Tensor self) -> Tensor |
10145 | static C10_NOINLINE c10::TypedOperatorHandle<all::schema> create_all_typed_handle() { |
10146 | return c10::Dispatcher::singleton() |
10147 | .findSchemaOrThrow(all::name, all::overload_name) |
10148 | .typed<all::schema>(); |
10149 | } |
10150 | |
10151 | // aten::all(Tensor self) -> Tensor |
10152 | at::Tensor all::call(const at::Tensor & self) { |
10153 | |
10154 | static auto op = create_all_typed_handle(); |
10155 | return op.call(self); |
10156 | } |
10157 | |
10158 | // aten::all(Tensor self) -> Tensor |
10159 | at::Tensor all::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
10160 | |
10161 | static auto op = create_all_typed_handle(); |
10162 | return op.redispatch(dispatchKeySet, self); |
10163 | } |
10164 | |
10165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_all_out, name, "aten::all" ) |
10166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_all_out, overload_name, "all_out" ) |
10167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(all_all_out, schema_str, "all.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
10168 | |
10169 | // aten::all.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
10170 | static C10_NOINLINE c10::TypedOperatorHandle<all_all_out::schema> create_all_all_out_typed_handle() { |
10171 | return c10::Dispatcher::singleton() |
10172 | .findSchemaOrThrow(all_all_out::name, all_all_out::overload_name) |
10173 | .typed<all_all_out::schema>(); |
10174 | } |
10175 | |
10176 | // aten::all.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
10177 | at::Tensor & all_all_out::call(const at::Tensor & self, at::Tensor & out) { |
10178 | |
10179 | static auto op = create_all_all_out_typed_handle(); |
10180 | return op.call(self, out); |
10181 | } |
10182 | |
10183 | // aten::all.all_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
10184 | at::Tensor & all_all_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
10185 | |
10186 | static auto op = create_all_all_out_typed_handle(); |
10187 | return op.redispatch(dispatchKeySet, self, out); |
10188 | } |
10189 | |
10190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale_, name, "aten::_amp_update_scale_" ) |
10191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale_, overload_name, "" ) |
10192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale_, schema_str, "_amp_update_scale_(Tensor(a!) self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> Tensor(a!)" ) |
10193 | |
10194 | // aten::_amp_update_scale_(Tensor(a!) self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> Tensor(a!) |
10195 | static C10_NOINLINE c10::TypedOperatorHandle<_amp_update_scale_::schema> create__amp_update_scale__typed_handle() { |
10196 | return c10::Dispatcher::singleton() |
10197 | .findSchemaOrThrow(_amp_update_scale_::name, _amp_update_scale_::overload_name) |
10198 | .typed<_amp_update_scale_::schema>(); |
10199 | } |
10200 | |
10201 | // aten::_amp_update_scale_(Tensor(a!) self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> Tensor(a!) |
10202 | at::Tensor & _amp_update_scale_::call(at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval) { |
10203 | |
10204 | static auto op = create__amp_update_scale__typed_handle(); |
10205 | return op.call(self, growth_tracker, found_inf, scale_growth_factor, scale_backoff_factor, growth_interval); |
10206 | } |
10207 | |
10208 | // aten::_amp_update_scale_(Tensor(a!) self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> Tensor(a!) |
10209 | at::Tensor & _amp_update_scale_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval) { |
10210 | |
10211 | static auto op = create__amp_update_scale__typed_handle(); |
10212 | return op.redispatch(dispatchKeySet, self, growth_tracker, found_inf, scale_growth_factor, scale_backoff_factor, growth_interval); |
10213 | } |
10214 | |
10215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp, name, "aten::_foreach_exp" ) |
10216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp, overload_name, "" ) |
10217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp, schema_str, "_foreach_exp(Tensor[] self) -> Tensor[]" ) |
10218 | |
10219 | // aten::_foreach_exp(Tensor[] self) -> Tensor[] |
10220 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_exp::schema> create__foreach_exp_typed_handle() { |
10221 | return c10::Dispatcher::singleton() |
10222 | .findSchemaOrThrow(_foreach_exp::name, _foreach_exp::overload_name) |
10223 | .typed<_foreach_exp::schema>(); |
10224 | } |
10225 | |
10226 | // aten::_foreach_exp(Tensor[] self) -> Tensor[] |
10227 | ::std::vector<at::Tensor> _foreach_exp::call(at::TensorList self) { |
10228 | |
10229 | static auto op = create__foreach_exp_typed_handle(); |
10230 | return op.call(self); |
10231 | } |
10232 | |
10233 | // aten::_foreach_exp(Tensor[] self) -> Tensor[] |
10234 | ::std::vector<at::Tensor> _foreach_exp::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10235 | |
10236 | static auto op = create__foreach_exp_typed_handle(); |
10237 | return op.redispatch(dispatchKeySet, self); |
10238 | } |
10239 | |
10240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp_, name, "aten::_foreach_exp_" ) |
10241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp_, overload_name, "" ) |
10242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp_, schema_str, "_foreach_exp_(Tensor(a!)[] self) -> ()" ) |
10243 | |
10244 | // aten::_foreach_exp_(Tensor(a!)[] self) -> () |
10245 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_exp_::schema> create__foreach_exp__typed_handle() { |
10246 | return c10::Dispatcher::singleton() |
10247 | .findSchemaOrThrow(_foreach_exp_::name, _foreach_exp_::overload_name) |
10248 | .typed<_foreach_exp_::schema>(); |
10249 | } |
10250 | |
10251 | // aten::_foreach_exp_(Tensor(a!)[] self) -> () |
10252 | void _foreach_exp_::call(at::TensorList self) { |
10253 | |
10254 | static auto op = create__foreach_exp__typed_handle(); |
10255 | return op.call(self); |
10256 | } |
10257 | |
10258 | // aten::_foreach_exp_(Tensor(a!)[] self) -> () |
10259 | void _foreach_exp_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10260 | |
10261 | static auto op = create__foreach_exp__typed_handle(); |
10262 | return op.redispatch(dispatchKeySet, self); |
10263 | } |
10264 | |
10265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt, name, "aten::_foreach_sqrt" ) |
10266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt, overload_name, "" ) |
10267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt, schema_str, "_foreach_sqrt(Tensor[] self) -> Tensor[]" ) |
10268 | |
10269 | // aten::_foreach_sqrt(Tensor[] self) -> Tensor[] |
10270 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sqrt::schema> create__foreach_sqrt_typed_handle() { |
10271 | return c10::Dispatcher::singleton() |
10272 | .findSchemaOrThrow(_foreach_sqrt::name, _foreach_sqrt::overload_name) |
10273 | .typed<_foreach_sqrt::schema>(); |
10274 | } |
10275 | |
10276 | // aten::_foreach_sqrt(Tensor[] self) -> Tensor[] |
10277 | ::std::vector<at::Tensor> _foreach_sqrt::call(at::TensorList self) { |
10278 | |
10279 | static auto op = create__foreach_sqrt_typed_handle(); |
10280 | return op.call(self); |
10281 | } |
10282 | |
10283 | // aten::_foreach_sqrt(Tensor[] self) -> Tensor[] |
10284 | ::std::vector<at::Tensor> _foreach_sqrt::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10285 | |
10286 | static auto op = create__foreach_sqrt_typed_handle(); |
10287 | return op.redispatch(dispatchKeySet, self); |
10288 | } |
10289 | |
10290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt_, name, "aten::_foreach_sqrt_" ) |
10291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt_, overload_name, "" ) |
10292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt_, schema_str, "_foreach_sqrt_(Tensor(a!)[] self) -> ()" ) |
10293 | |
10294 | // aten::_foreach_sqrt_(Tensor(a!)[] self) -> () |
10295 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sqrt_::schema> create__foreach_sqrt__typed_handle() { |
10296 | return c10::Dispatcher::singleton() |
10297 | .findSchemaOrThrow(_foreach_sqrt_::name, _foreach_sqrt_::overload_name) |
10298 | .typed<_foreach_sqrt_::schema>(); |
10299 | } |
10300 | |
10301 | // aten::_foreach_sqrt_(Tensor(a!)[] self) -> () |
10302 | void _foreach_sqrt_::call(at::TensorList self) { |
10303 | |
10304 | static auto op = create__foreach_sqrt__typed_handle(); |
10305 | return op.call(self); |
10306 | } |
10307 | |
10308 | // aten::_foreach_sqrt_(Tensor(a!)[] self) -> () |
10309 | void _foreach_sqrt_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10310 | |
10311 | static auto op = create__foreach_sqrt__typed_handle(); |
10312 | return op.redispatch(dispatchKeySet, self); |
10313 | } |
10314 | |
10315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log, name, "aten::_foreach_log" ) |
10316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log, overload_name, "" ) |
10317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log, schema_str, "_foreach_log(Tensor[] self) -> Tensor[]" ) |
10318 | |
10319 | // aten::_foreach_log(Tensor[] self) -> Tensor[] |
10320 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log::schema> create__foreach_log_typed_handle() { |
10321 | return c10::Dispatcher::singleton() |
10322 | .findSchemaOrThrow(_foreach_log::name, _foreach_log::overload_name) |
10323 | .typed<_foreach_log::schema>(); |
10324 | } |
10325 | |
10326 | // aten::_foreach_log(Tensor[] self) -> Tensor[] |
10327 | ::std::vector<at::Tensor> _foreach_log::call(at::TensorList self) { |
10328 | |
10329 | static auto op = create__foreach_log_typed_handle(); |
10330 | return op.call(self); |
10331 | } |
10332 | |
10333 | // aten::_foreach_log(Tensor[] self) -> Tensor[] |
10334 | ::std::vector<at::Tensor> _foreach_log::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10335 | |
10336 | static auto op = create__foreach_log_typed_handle(); |
10337 | return op.redispatch(dispatchKeySet, self); |
10338 | } |
10339 | |
10340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log_, name, "aten::_foreach_log_" ) |
10341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log_, overload_name, "" ) |
10342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log_, schema_str, "_foreach_log_(Tensor(a!)[] self) -> ()" ) |
10343 | |
10344 | // aten::_foreach_log_(Tensor(a!)[] self) -> () |
10345 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log_::schema> create__foreach_log__typed_handle() { |
10346 | return c10::Dispatcher::singleton() |
10347 | .findSchemaOrThrow(_foreach_log_::name, _foreach_log_::overload_name) |
10348 | .typed<_foreach_log_::schema>(); |
10349 | } |
10350 | |
10351 | // aten::_foreach_log_(Tensor(a!)[] self) -> () |
10352 | void _foreach_log_::call(at::TensorList self) { |
10353 | |
10354 | static auto op = create__foreach_log__typed_handle(); |
10355 | return op.call(self); |
10356 | } |
10357 | |
10358 | // aten::_foreach_log_(Tensor(a!)[] self) -> () |
10359 | void _foreach_log_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10360 | |
10361 | static auto op = create__foreach_log__typed_handle(); |
10362 | return op.redispatch(dispatchKeySet, self); |
10363 | } |
10364 | |
10365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p, name, "aten::_foreach_log1p" ) |
10366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p, overload_name, "" ) |
10367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p, schema_str, "_foreach_log1p(Tensor[] self) -> Tensor[]" ) |
10368 | |
10369 | // aten::_foreach_log1p(Tensor[] self) -> Tensor[] |
10370 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log1p::schema> create__foreach_log1p_typed_handle() { |
10371 | return c10::Dispatcher::singleton() |
10372 | .findSchemaOrThrow(_foreach_log1p::name, _foreach_log1p::overload_name) |
10373 | .typed<_foreach_log1p::schema>(); |
10374 | } |
10375 | |
10376 | // aten::_foreach_log1p(Tensor[] self) -> Tensor[] |
10377 | ::std::vector<at::Tensor> _foreach_log1p::call(at::TensorList self) { |
10378 | |
10379 | static auto op = create__foreach_log1p_typed_handle(); |
10380 | return op.call(self); |
10381 | } |
10382 | |
10383 | // aten::_foreach_log1p(Tensor[] self) -> Tensor[] |
10384 | ::std::vector<at::Tensor> _foreach_log1p::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10385 | |
10386 | static auto op = create__foreach_log1p_typed_handle(); |
10387 | return op.redispatch(dispatchKeySet, self); |
10388 | } |
10389 | |
10390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p_, name, "aten::_foreach_log1p_" ) |
10391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p_, overload_name, "" ) |
10392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p_, schema_str, "_foreach_log1p_(Tensor(a!)[] self) -> ()" ) |
10393 | |
10394 | // aten::_foreach_log1p_(Tensor(a!)[] self) -> () |
10395 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log1p_::schema> create__foreach_log1p__typed_handle() { |
10396 | return c10::Dispatcher::singleton() |
10397 | .findSchemaOrThrow(_foreach_log1p_::name, _foreach_log1p_::overload_name) |
10398 | .typed<_foreach_log1p_::schema>(); |
10399 | } |
10400 | |
10401 | // aten::_foreach_log1p_(Tensor(a!)[] self) -> () |
10402 | void _foreach_log1p_::call(at::TensorList self) { |
10403 | |
10404 | static auto op = create__foreach_log1p__typed_handle(); |
10405 | return op.call(self); |
10406 | } |
10407 | |
10408 | // aten::_foreach_log1p_(Tensor(a!)[] self) -> () |
10409 | void _foreach_log1p_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10410 | |
10411 | static auto op = create__foreach_log1p__typed_handle(); |
10412 | return op.redispatch(dispatchKeySet, self); |
10413 | } |
10414 | |
10415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg, name, "aten::_foreach_neg" ) |
10416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg, overload_name, "" ) |
10417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg, schema_str, "_foreach_neg(Tensor[] self) -> Tensor[]" ) |
10418 | |
10419 | // aten::_foreach_neg(Tensor[] self) -> Tensor[] |
10420 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_neg::schema> create__foreach_neg_typed_handle() { |
10421 | return c10::Dispatcher::singleton() |
10422 | .findSchemaOrThrow(_foreach_neg::name, _foreach_neg::overload_name) |
10423 | .typed<_foreach_neg::schema>(); |
10424 | } |
10425 | |
10426 | // aten::_foreach_neg(Tensor[] self) -> Tensor[] |
10427 | ::std::vector<at::Tensor> _foreach_neg::call(at::TensorList self) { |
10428 | |
10429 | static auto op = create__foreach_neg_typed_handle(); |
10430 | return op.call(self); |
10431 | } |
10432 | |
10433 | // aten::_foreach_neg(Tensor[] self) -> Tensor[] |
10434 | ::std::vector<at::Tensor> _foreach_neg::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10435 | |
10436 | static auto op = create__foreach_neg_typed_handle(); |
10437 | return op.redispatch(dispatchKeySet, self); |
10438 | } |
10439 | |
10440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg_, name, "aten::_foreach_neg_" ) |
10441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg_, overload_name, "" ) |
10442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg_, schema_str, "_foreach_neg_(Tensor(a!)[] self) -> ()" ) |
10443 | |
10444 | // aten::_foreach_neg_(Tensor(a!)[] self) -> () |
10445 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_neg_::schema> create__foreach_neg__typed_handle() { |
10446 | return c10::Dispatcher::singleton() |
10447 | .findSchemaOrThrow(_foreach_neg_::name, _foreach_neg_::overload_name) |
10448 | .typed<_foreach_neg_::schema>(); |
10449 | } |
10450 | |
10451 | // aten::_foreach_neg_(Tensor(a!)[] self) -> () |
10452 | void _foreach_neg_::call(at::TensorList self) { |
10453 | |
10454 | static auto op = create__foreach_neg__typed_handle(); |
10455 | return op.call(self); |
10456 | } |
10457 | |
10458 | // aten::_foreach_neg_(Tensor(a!)[] self) -> () |
10459 | void _foreach_neg_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10460 | |
10461 | static auto op = create__foreach_neg__typed_handle(); |
10462 | return op.redispatch(dispatchKeySet, self); |
10463 | } |
10464 | |
10465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin, name, "aten::_foreach_sin" ) |
10466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin, overload_name, "" ) |
10467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin, schema_str, "_foreach_sin(Tensor[] self) -> Tensor[]" ) |
10468 | |
10469 | // aten::_foreach_sin(Tensor[] self) -> Tensor[] |
10470 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sin::schema> create__foreach_sin_typed_handle() { |
10471 | return c10::Dispatcher::singleton() |
10472 | .findSchemaOrThrow(_foreach_sin::name, _foreach_sin::overload_name) |
10473 | .typed<_foreach_sin::schema>(); |
10474 | } |
10475 | |
10476 | // aten::_foreach_sin(Tensor[] self) -> Tensor[] |
10477 | ::std::vector<at::Tensor> _foreach_sin::call(at::TensorList self) { |
10478 | |
10479 | static auto op = create__foreach_sin_typed_handle(); |
10480 | return op.call(self); |
10481 | } |
10482 | |
10483 | // aten::_foreach_sin(Tensor[] self) -> Tensor[] |
10484 | ::std::vector<at::Tensor> _foreach_sin::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10485 | |
10486 | static auto op = create__foreach_sin_typed_handle(); |
10487 | return op.redispatch(dispatchKeySet, self); |
10488 | } |
10489 | |
10490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin_, name, "aten::_foreach_sin_" ) |
10491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin_, overload_name, "" ) |
10492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin_, schema_str, "_foreach_sin_(Tensor(a!)[] self) -> ()" ) |
10493 | |
10494 | // aten::_foreach_sin_(Tensor(a!)[] self) -> () |
10495 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sin_::schema> create__foreach_sin__typed_handle() { |
10496 | return c10::Dispatcher::singleton() |
10497 | .findSchemaOrThrow(_foreach_sin_::name, _foreach_sin_::overload_name) |
10498 | .typed<_foreach_sin_::schema>(); |
10499 | } |
10500 | |
10501 | // aten::_foreach_sin_(Tensor(a!)[] self) -> () |
10502 | void _foreach_sin_::call(at::TensorList self) { |
10503 | |
10504 | static auto op = create__foreach_sin__typed_handle(); |
10505 | return op.call(self); |
10506 | } |
10507 | |
10508 | // aten::_foreach_sin_(Tensor(a!)[] self) -> () |
10509 | void _foreach_sin_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10510 | |
10511 | static auto op = create__foreach_sin__typed_handle(); |
10512 | return op.redispatch(dispatchKeySet, self); |
10513 | } |
10514 | |
10515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal, name, "aten::_foreach_reciprocal" ) |
10516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal, overload_name, "" ) |
10517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal, schema_str, "_foreach_reciprocal(Tensor[] self) -> Tensor[]" ) |
10518 | |
10519 | // aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] |
10520 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_reciprocal::schema> create__foreach_reciprocal_typed_handle() { |
10521 | return c10::Dispatcher::singleton() |
10522 | .findSchemaOrThrow(_foreach_reciprocal::name, _foreach_reciprocal::overload_name) |
10523 | .typed<_foreach_reciprocal::schema>(); |
10524 | } |
10525 | |
10526 | // aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] |
10527 | ::std::vector<at::Tensor> _foreach_reciprocal::call(at::TensorList self) { |
10528 | |
10529 | static auto op = create__foreach_reciprocal_typed_handle(); |
10530 | return op.call(self); |
10531 | } |
10532 | |
10533 | // aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] |
10534 | ::std::vector<at::Tensor> _foreach_reciprocal::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10535 | |
10536 | static auto op = create__foreach_reciprocal_typed_handle(); |
10537 | return op.redispatch(dispatchKeySet, self); |
10538 | } |
10539 | |
10540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal_, name, "aten::_foreach_reciprocal_" ) |
10541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal_, overload_name, "" ) |
10542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal_, schema_str, "_foreach_reciprocal_(Tensor(a!)[] self) -> ()" ) |
10543 | |
10544 | // aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () |
10545 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_reciprocal_::schema> create__foreach_reciprocal__typed_handle() { |
10546 | return c10::Dispatcher::singleton() |
10547 | .findSchemaOrThrow(_foreach_reciprocal_::name, _foreach_reciprocal_::overload_name) |
10548 | .typed<_foreach_reciprocal_::schema>(); |
10549 | } |
10550 | |
10551 | // aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () |
10552 | void _foreach_reciprocal_::call(at::TensorList self) { |
10553 | |
10554 | static auto op = create__foreach_reciprocal__typed_handle(); |
10555 | return op.call(self); |
10556 | } |
10557 | |
10558 | // aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () |
10559 | void _foreach_reciprocal_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10560 | |
10561 | static auto op = create__foreach_reciprocal__typed_handle(); |
10562 | return op.redispatch(dispatchKeySet, self); |
10563 | } |
10564 | |
10565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid, name, "aten::_foreach_sigmoid" ) |
10566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid, overload_name, "" ) |
10567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid, schema_str, "_foreach_sigmoid(Tensor[] self) -> Tensor[]" ) |
10568 | |
10569 | // aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] |
10570 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sigmoid::schema> create__foreach_sigmoid_typed_handle() { |
10571 | return c10::Dispatcher::singleton() |
10572 | .findSchemaOrThrow(_foreach_sigmoid::name, _foreach_sigmoid::overload_name) |
10573 | .typed<_foreach_sigmoid::schema>(); |
10574 | } |
10575 | |
10576 | // aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] |
10577 | ::std::vector<at::Tensor> _foreach_sigmoid::call(at::TensorList self) { |
10578 | |
10579 | static auto op = create__foreach_sigmoid_typed_handle(); |
10580 | return op.call(self); |
10581 | } |
10582 | |
10583 | // aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] |
10584 | ::std::vector<at::Tensor> _foreach_sigmoid::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10585 | |
10586 | static auto op = create__foreach_sigmoid_typed_handle(); |
10587 | return op.redispatch(dispatchKeySet, self); |
10588 | } |
10589 | |
10590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid_, name, "aten::_foreach_sigmoid_" ) |
10591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid_, overload_name, "" ) |
10592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid_, schema_str, "_foreach_sigmoid_(Tensor(a!)[] self) -> ()" ) |
10593 | |
10594 | // aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () |
10595 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sigmoid_::schema> create__foreach_sigmoid__typed_handle() { |
10596 | return c10::Dispatcher::singleton() |
10597 | .findSchemaOrThrow(_foreach_sigmoid_::name, _foreach_sigmoid_::overload_name) |
10598 | .typed<_foreach_sigmoid_::schema>(); |
10599 | } |
10600 | |
10601 | // aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () |
10602 | void _foreach_sigmoid_::call(at::TensorList self) { |
10603 | |
10604 | static auto op = create__foreach_sigmoid__typed_handle(); |
10605 | return op.call(self); |
10606 | } |
10607 | |
10608 | // aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () |
10609 | void _foreach_sigmoid_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self) { |
10610 | |
10611 | static auto op = create__foreach_sigmoid__typed_handle(); |
10612 | return op.redispatch(dispatchKeySet, self); |
10613 | } |
10614 | |
10615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__Scalar, name, "aten::_foreach_addcdiv_" ) |
10616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__Scalar, overload_name, "Scalar" ) |
10617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__Scalar, schema_str, "_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> ()" ) |
10618 | |
10619 | // aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () |
10620 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv__Scalar::schema> create__foreach_addcdiv__Scalar_typed_handle() { |
10621 | return c10::Dispatcher::singleton() |
10622 | .findSchemaOrThrow(_foreach_addcdiv__Scalar::name, _foreach_addcdiv__Scalar::overload_name) |
10623 | .typed<_foreach_addcdiv__Scalar::schema>(); |
10624 | } |
10625 | |
10626 | // aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () |
10627 | void _foreach_addcdiv__Scalar::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value) { |
10628 | |
10629 | static auto op = create__foreach_addcdiv__Scalar_typed_handle(); |
10630 | return op.call(self, tensor1, tensor2, value); |
10631 | } |
10632 | |
10633 | // aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () |
10634 | void _foreach_addcdiv__Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value) { |
10635 | |
10636 | static auto op = create__foreach_addcdiv__Scalar_typed_handle(); |
10637 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value); |
10638 | } |
10639 | |
10640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__ScalarList, name, "aten::_foreach_addcdiv_" ) |
10641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__ScalarList, overload_name, "ScalarList" ) |
10642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__ScalarList, schema_str, "_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> ()" ) |
10643 | |
10644 | // aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () |
10645 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv__ScalarList::schema> create__foreach_addcdiv__ScalarList_typed_handle() { |
10646 | return c10::Dispatcher::singleton() |
10647 | .findSchemaOrThrow(_foreach_addcdiv__ScalarList::name, _foreach_addcdiv__ScalarList::overload_name) |
10648 | .typed<_foreach_addcdiv__ScalarList::schema>(); |
10649 | } |
10650 | |
10651 | // aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () |
10652 | void _foreach_addcdiv__ScalarList::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef<at::Scalar> scalars) { |
10653 | |
10654 | static auto op = create__foreach_addcdiv__ScalarList_typed_handle(); |
10655 | return op.call(self, tensor1, tensor2, scalars); |
10656 | } |
10657 | |
10658 | // aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () |
10659 | void _foreach_addcdiv__ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef<at::Scalar> scalars) { |
10660 | |
10661 | static auto op = create__foreach_addcdiv__ScalarList_typed_handle(); |
10662 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, scalars); |
10663 | } |
10664 | |
10665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__Tensor, name, "aten::_foreach_addcdiv_" ) |
10666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__Tensor, overload_name, "Tensor" ) |
10667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv__Tensor, schema_str, "_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> ()" ) |
10668 | |
10669 | // aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () |
10670 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv__Tensor::schema> create__foreach_addcdiv__Tensor_typed_handle() { |
10671 | return c10::Dispatcher::singleton() |
10672 | .findSchemaOrThrow(_foreach_addcdiv__Tensor::name, _foreach_addcdiv__Tensor::overload_name) |
10673 | .typed<_foreach_addcdiv__Tensor::schema>(); |
10674 | } |
10675 | |
10676 | // aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () |
10677 | void _foreach_addcdiv__Tensor::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { |
10678 | |
10679 | static auto op = create__foreach_addcdiv__Tensor_typed_handle(); |
10680 | return op.call(self, tensor1, tensor2, scalars); |
10681 | } |
10682 | |
10683 | // aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () |
10684 | void _foreach_addcdiv__Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { |
10685 | |
10686 | static auto op = create__foreach_addcdiv__Tensor_typed_handle(); |
10687 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, scalars); |
10688 | } |
10689 | |
10690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Scalar, name, "aten::_foreach_addcdiv" ) |
10691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Scalar, overload_name, "Scalar" ) |
10692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Scalar, schema_str, "_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[]" ) |
10693 | |
10694 | // aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] |
10695 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv_Scalar::schema> create__foreach_addcdiv_Scalar_typed_handle() { |
10696 | return c10::Dispatcher::singleton() |
10697 | .findSchemaOrThrow(_foreach_addcdiv_Scalar::name, _foreach_addcdiv_Scalar::overload_name) |
10698 | .typed<_foreach_addcdiv_Scalar::schema>(); |
10699 | } |
10700 | |
10701 | // aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] |
10702 | ::std::vector<at::Tensor> _foreach_addcdiv_Scalar::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value) { |
10703 | |
10704 | static auto op = create__foreach_addcdiv_Scalar_typed_handle(); |
10705 | return op.call(self, tensor1, tensor2, value); |
10706 | } |
10707 | |
10708 | // aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] |
10709 | ::std::vector<at::Tensor> _foreach_addcdiv_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value) { |
10710 | |
10711 | static auto op = create__foreach_addcdiv_Scalar_typed_handle(); |
10712 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value); |
10713 | } |
10714 | |
10715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_ScalarList, name, "aten::_foreach_addcdiv" ) |
10716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_ScalarList, overload_name, "ScalarList" ) |
10717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_ScalarList, schema_str, "_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[]" ) |
10718 | |
10719 | // aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] |
10720 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv_ScalarList::schema> create__foreach_addcdiv_ScalarList_typed_handle() { |
10721 | return c10::Dispatcher::singleton() |
10722 | .findSchemaOrThrow(_foreach_addcdiv_ScalarList::name, _foreach_addcdiv_ScalarList::overload_name) |
10723 | .typed<_foreach_addcdiv_ScalarList::schema>(); |
10724 | } |
10725 | |
10726 | // aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] |
10727 | ::std::vector<at::Tensor> _foreach_addcdiv_ScalarList::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef<at::Scalar> scalars) { |
10728 | |
10729 | static auto op = create__foreach_addcdiv_ScalarList_typed_handle(); |
10730 | return op.call(self, tensor1, tensor2, scalars); |
10731 | } |
10732 | |
10733 | // aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] |
10734 | ::std::vector<at::Tensor> _foreach_addcdiv_ScalarList::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef<at::Scalar> scalars) { |
10735 | |
10736 | static auto op = create__foreach_addcdiv_ScalarList_typed_handle(); |
10737 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, scalars); |
10738 | } |
10739 | |
10740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Tensor, name, "aten::_foreach_addcdiv" ) |
10741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Tensor, overload_name, "Tensor" ) |
10742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Tensor, schema_str, "_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[]" ) |
10743 | |
10744 | // aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] |
10745 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv_Tensor::schema> create__foreach_addcdiv_Tensor_typed_handle() { |
10746 | return c10::Dispatcher::singleton() |
10747 | .findSchemaOrThrow(_foreach_addcdiv_Tensor::name, _foreach_addcdiv_Tensor::overload_name) |
10748 | .typed<_foreach_addcdiv_Tensor::schema>(); |
10749 | } |
10750 | |
10751 | // aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] |
10752 | ::std::vector<at::Tensor> _foreach_addcdiv_Tensor::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { |
10753 | |
10754 | static auto op = create__foreach_addcdiv_Tensor_typed_handle(); |
10755 | return op.call(self, tensor1, tensor2, scalars); |
10756 | } |
10757 | |
10758 | // aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] |
10759 | ::std::vector<at::Tensor> _foreach_addcdiv_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars) { |
10760 | |
10761 | static auto op = create__foreach_addcdiv_Tensor_typed_handle(); |
10762 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, scalars); |
10763 | } |
10764 | |
10765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_norm_Scalar, name, "aten::_foreach_norm" ) |
10766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_norm_Scalar, overload_name, "Scalar" ) |
10767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_norm_Scalar, schema_str, "_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[]" ) |
10768 | |
10769 | // aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] |
10770 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_norm_Scalar::schema> create__foreach_norm_Scalar_typed_handle() { |
10771 | return c10::Dispatcher::singleton() |
10772 | .findSchemaOrThrow(_foreach_norm_Scalar::name, _foreach_norm_Scalar::overload_name) |
10773 | .typed<_foreach_norm_Scalar::schema>(); |
10774 | } |
10775 | |
10776 | // aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] |
10777 | ::std::vector<at::Tensor> _foreach_norm_Scalar::call(at::TensorList self, const at::Scalar & ord) { |
10778 | |
10779 | static auto op = create__foreach_norm_Scalar_typed_handle(); |
10780 | return op.call(self, ord); |
10781 | } |
10782 | |
10783 | // aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] |
10784 | ::std::vector<at::Tensor> _foreach_norm_Scalar::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord) { |
10785 | |
10786 | static auto op = create__foreach_norm_Scalar_typed_handle(); |
10787 | return op.redispatch(dispatchKeySet, self, ord); |
10788 | } |
10789 | |
10790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convert_indices_from_coo_to_csr, name, "aten::_convert_indices_from_coo_to_csr" ) |
10791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convert_indices_from_coo_to_csr, overload_name, "" ) |
10792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convert_indices_from_coo_to_csr, schema_str, "_convert_indices_from_coo_to_csr(Tensor self, int size, *, bool out_int32=False) -> Tensor" ) |
10793 | |
10794 | // aten::_convert_indices_from_coo_to_csr(Tensor self, int size, *, bool out_int32=False) -> Tensor |
10795 | static C10_NOINLINE c10::TypedOperatorHandle<_convert_indices_from_coo_to_csr::schema> create__convert_indices_from_coo_to_csr_typed_handle() { |
10796 | return c10::Dispatcher::singleton() |
10797 | .findSchemaOrThrow(_convert_indices_from_coo_to_csr::name, _convert_indices_from_coo_to_csr::overload_name) |
10798 | .typed<_convert_indices_from_coo_to_csr::schema>(); |
10799 | } |
10800 | |
10801 | // aten::_convert_indices_from_coo_to_csr(Tensor self, int size, *, bool out_int32=False) -> Tensor |
10802 | at::Tensor _convert_indices_from_coo_to_csr::call(const at::Tensor & self, int64_t size, bool out_int32) { |
10803 | |
10804 | static auto op = create__convert_indices_from_coo_to_csr_typed_handle(); |
10805 | return op.call(self, size, out_int32); |
10806 | } |
10807 | |
10808 | // aten::_convert_indices_from_coo_to_csr(Tensor self, int size, *, bool out_int32=False) -> Tensor |
10809 | at::Tensor _convert_indices_from_coo_to_csr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t size, bool out_int32) { |
10810 | |
10811 | static auto op = create__convert_indices_from_coo_to_csr_typed_handle(); |
10812 | return op.redispatch(dispatchKeySet, self, size, out_int32); |
10813 | } |
10814 | |
10815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convert_indices_from_coo_to_csr_out, name, "aten::_convert_indices_from_coo_to_csr" ) |
10816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convert_indices_from_coo_to_csr_out, overload_name, "out" ) |
10817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_convert_indices_from_coo_to_csr_out, schema_str, "_convert_indices_from_coo_to_csr.out(Tensor self, int size, *, bool out_int32=False, Tensor(a!) out) -> Tensor(a!)" ) |
10818 | |
10819 | // aten::_convert_indices_from_coo_to_csr.out(Tensor self, int size, *, bool out_int32=False, Tensor(a!) out) -> Tensor(a!) |
10820 | static C10_NOINLINE c10::TypedOperatorHandle<_convert_indices_from_coo_to_csr_out::schema> create__convert_indices_from_coo_to_csr_out_typed_handle() { |
10821 | return c10::Dispatcher::singleton() |
10822 | .findSchemaOrThrow(_convert_indices_from_coo_to_csr_out::name, _convert_indices_from_coo_to_csr_out::overload_name) |
10823 | .typed<_convert_indices_from_coo_to_csr_out::schema>(); |
10824 | } |
10825 | |
10826 | // aten::_convert_indices_from_coo_to_csr.out(Tensor self, int size, *, bool out_int32=False, Tensor(a!) out) -> Tensor(a!) |
10827 | at::Tensor & _convert_indices_from_coo_to_csr_out::call(const at::Tensor & self, int64_t size, bool out_int32, at::Tensor & out) { |
10828 | |
10829 | static auto op = create__convert_indices_from_coo_to_csr_out_typed_handle(); |
10830 | return op.call(self, size, out_int32, out); |
10831 | } |
10832 | |
10833 | // aten::_convert_indices_from_coo_to_csr.out(Tensor self, int size, *, bool out_int32=False, Tensor(a!) out) -> Tensor(a!) |
10834 | at::Tensor & _convert_indices_from_coo_to_csr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t size, bool out_int32, at::Tensor & out) { |
10835 | |
10836 | static auto op = create__convert_indices_from_coo_to_csr_out_typed_handle(); |
10837 | return op.redispatch(dispatchKeySet, self, size, out_int32, out); |
10838 | } |
10839 | |
10840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_out, name, "aten::multi_margin_loss" ) |
10841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_out, overload_name, "out" ) |
10842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss_out, schema_str, "multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)" ) |
10843 | |
10844 | // aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
10845 | static C10_NOINLINE c10::TypedOperatorHandle<multi_margin_loss_out::schema> create_multi_margin_loss_out_typed_handle() { |
10846 | return c10::Dispatcher::singleton() |
10847 | .findSchemaOrThrow(multi_margin_loss_out::name, multi_margin_loss_out::overload_name) |
10848 | .typed<multi_margin_loss_out::schema>(); |
10849 | } |
10850 | |
10851 | // aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
10852 | at::Tensor & multi_margin_loss_out::call(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & out) { |
10853 | |
10854 | static auto op = create_multi_margin_loss_out_typed_handle(); |
10855 | return op.call(self, target, p, margin, weight, reduction, out); |
10856 | } |
10857 | |
10858 | // aten::multi_margin_loss.out(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
10859 | at::Tensor & multi_margin_loss_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & out) { |
10860 | |
10861 | static auto op = create_multi_margin_loss_out_typed_handle(); |
10862 | return op.redispatch(dispatchKeySet, self, target, p, margin, weight, reduction, out); |
10863 | } |
10864 | |
10865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss, name, "aten::multi_margin_loss" ) |
10866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss, overload_name, "" ) |
10867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multi_margin_loss, schema_str, "multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor" ) |
10868 | |
10869 | // aten::multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor |
10870 | static C10_NOINLINE c10::TypedOperatorHandle<multi_margin_loss::schema> create_multi_margin_loss_typed_handle() { |
10871 | return c10::Dispatcher::singleton() |
10872 | .findSchemaOrThrow(multi_margin_loss::name, multi_margin_loss::overload_name) |
10873 | .typed<multi_margin_loss::schema>(); |
10874 | } |
10875 | |
10876 | // aten::multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor |
10877 | at::Tensor multi_margin_loss::call(const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction) { |
10878 | |
10879 | static auto op = create_multi_margin_loss_typed_handle(); |
10880 | return op.call(self, target, p, margin, weight, reduction); |
10881 | } |
10882 | |
10883 | // aten::multi_margin_loss(Tensor self, Tensor target, Scalar p=1, Scalar margin=1, Tensor? weight=None, int reduction=Mean) -> Tensor |
10884 | at::Tensor multi_margin_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const at::Scalar & p, const at::Scalar & margin, const c10::optional<at::Tensor> & weight, int64_t reduction) { |
10885 | |
10886 | static auto op = create_multi_margin_loss_typed_handle(); |
10887 | return op.redispatch(dispatchKeySet, self, target, p, margin, weight, reduction); |
10888 | } |
10889 | |
10890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_out, name, "aten::multilabel_margin_loss" ) |
10891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_out, overload_name, "out" ) |
10892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_out, schema_str, "multilabel_margin_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)" ) |
10893 | |
10894 | // aten::multilabel_margin_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
10895 | static C10_NOINLINE c10::TypedOperatorHandle<multilabel_margin_loss_out::schema> create_multilabel_margin_loss_out_typed_handle() { |
10896 | return c10::Dispatcher::singleton() |
10897 | .findSchemaOrThrow(multilabel_margin_loss_out::name, multilabel_margin_loss_out::overload_name) |
10898 | .typed<multilabel_margin_loss_out::schema>(); |
10899 | } |
10900 | |
10901 | // aten::multilabel_margin_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
10902 | at::Tensor & multilabel_margin_loss_out::call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out) { |
10903 | |
10904 | static auto op = create_multilabel_margin_loss_out_typed_handle(); |
10905 | return op.call(self, target, reduction, out); |
10906 | } |
10907 | |
10908 | // aten::multilabel_margin_loss.out(Tensor self, Tensor target, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
10909 | at::Tensor & multilabel_margin_loss_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & out) { |
10910 | |
10911 | static auto op = create_multilabel_margin_loss_out_typed_handle(); |
10912 | return op.redispatch(dispatchKeySet, self, target, reduction, out); |
10913 | } |
10914 | |
10915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss, name, "aten::multilabel_margin_loss" ) |
10916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss, overload_name, "" ) |
10917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss, schema_str, "multilabel_margin_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor" ) |
10918 | |
10919 | // aten::multilabel_margin_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor |
10920 | static C10_NOINLINE c10::TypedOperatorHandle<multilabel_margin_loss::schema> create_multilabel_margin_loss_typed_handle() { |
10921 | return c10::Dispatcher::singleton() |
10922 | .findSchemaOrThrow(multilabel_margin_loss::name, multilabel_margin_loss::overload_name) |
10923 | .typed<multilabel_margin_loss::schema>(); |
10924 | } |
10925 | |
10926 | // aten::multilabel_margin_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor |
10927 | at::Tensor multilabel_margin_loss::call(const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
10928 | |
10929 | static auto op = create_multilabel_margin_loss_typed_handle(); |
10930 | return op.call(self, target, reduction); |
10931 | } |
10932 | |
10933 | // aten::multilabel_margin_loss(Tensor self, Tensor target, int reduction=Mean) -> Tensor |
10934 | at::Tensor multilabel_margin_loss::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
10935 | |
10936 | static auto op = create_multilabel_margin_loss_typed_handle(); |
10937 | return op.redispatch(dispatchKeySet, self, target, reduction); |
10938 | } |
10939 | |
10940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_forward_output, name, "aten::multilabel_margin_loss_forward" ) |
10941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_forward_output, overload_name, "output" ) |
10942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_forward_output, schema_str, "multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!))" ) |
10943 | |
10944 | // aten::multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!)) |
10945 | static C10_NOINLINE c10::TypedOperatorHandle<multilabel_margin_loss_forward_output::schema> create_multilabel_margin_loss_forward_output_typed_handle() { |
10946 | return c10::Dispatcher::singleton() |
10947 | .findSchemaOrThrow(multilabel_margin_loss_forward_output::name, multilabel_margin_loss_forward_output::overload_name) |
10948 | .typed<multilabel_margin_loss_forward_output::schema>(); |
10949 | } |
10950 | |
10951 | // aten::multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!)) |
10952 | ::std::tuple<at::Tensor &,at::Tensor &> multilabel_margin_loss_forward_output::call(const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target) { |
10953 | |
10954 | static auto op = create_multilabel_margin_loss_forward_output_typed_handle(); |
10955 | return op.call(self, target, reduction, output, is_target); |
10956 | } |
10957 | |
10958 | // aten::multilabel_margin_loss_forward.output(Tensor self, Tensor target, int reduction, *, Tensor(a!) output, Tensor(b!) is_target) -> (Tensor(a!), Tensor(b!)) |
10959 | ::std::tuple<at::Tensor &,at::Tensor &> multilabel_margin_loss_forward_output::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & output, at::Tensor & is_target) { |
10960 | |
10961 | static auto op = create_multilabel_margin_loss_forward_output_typed_handle(); |
10962 | return op.redispatch(dispatchKeySet, self, target, reduction, output, is_target); |
10963 | } |
10964 | |
10965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_forward, name, "aten::multilabel_margin_loss_forward" ) |
10966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_forward, overload_name, "" ) |
10967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(multilabel_margin_loss_forward, schema_str, "multilabel_margin_loss_forward(Tensor self, Tensor target, int reduction) -> (Tensor output, Tensor is_target)" ) |
10968 | |
10969 | // aten::multilabel_margin_loss_forward(Tensor self, Tensor target, int reduction) -> (Tensor output, Tensor is_target) |
10970 | static C10_NOINLINE c10::TypedOperatorHandle<multilabel_margin_loss_forward::schema> create_multilabel_margin_loss_forward_typed_handle() { |
10971 | return c10::Dispatcher::singleton() |
10972 | .findSchemaOrThrow(multilabel_margin_loss_forward::name, multilabel_margin_loss_forward::overload_name) |
10973 | .typed<multilabel_margin_loss_forward::schema>(); |
10974 | } |
10975 | |
10976 | // aten::multilabel_margin_loss_forward(Tensor self, Tensor target, int reduction) -> (Tensor output, Tensor is_target) |
10977 | ::std::tuple<at::Tensor,at::Tensor> multilabel_margin_loss_forward::call(const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
10978 | |
10979 | static auto op = create_multilabel_margin_loss_forward_typed_handle(); |
10980 | return op.call(self, target, reduction); |
10981 | } |
10982 | |
10983 | // aten::multilabel_margin_loss_forward(Tensor self, Tensor target, int reduction) -> (Tensor output, Tensor is_target) |
10984 | ::std::tuple<at::Tensor,at::Tensor> multilabel_margin_loss_forward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
10985 | |
10986 | static auto op = create_multilabel_margin_loss_forward_typed_handle(); |
10987 | return op.redispatch(dispatchKeySet, self, target, reduction); |
10988 | } |
10989 | |
10990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nll_loss_forward_output, name, "aten::nll_loss_forward" ) |
10991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nll_loss_forward_output, overload_name, "output" ) |
10992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nll_loss_forward_output, schema_str, "nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!))" ) |
10993 | |
10994 | // aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) |
10995 | static C10_NOINLINE c10::TypedOperatorHandle<nll_loss_forward_output::schema> create_nll_loss_forward_output_typed_handle() { |
10996 | return c10::Dispatcher::singleton() |
10997 | .findSchemaOrThrow(nll_loss_forward_output::name, nll_loss_forward_output::overload_name) |
10998 | .typed<nll_loss_forward_output::schema>(); |
10999 | } |
11000 | |
11001 | // aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) |
11002 | ::std::tuple<at::Tensor &,at::Tensor &> nll_loss_forward_output::call(const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & output, at::Tensor & total_weight) { |
11003 | |
11004 | static auto op = create_nll_loss_forward_output_typed_handle(); |
11005 | return op.call(self, target, weight, reduction, ignore_index, output, total_weight); |
11006 | } |
11007 | |
11008 | // aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) |
11009 | ::std::tuple<at::Tensor &,at::Tensor &> nll_loss_forward_output::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, int64_t reduction, c10::SymInt ignore_index, at::Tensor & output, at::Tensor & total_weight) { |
11010 | |
11011 | static auto op = create_nll_loss_forward_output_typed_handle(); |
11012 | return op.redispatch(dispatchKeySet, self, target, weight, reduction, ignore_index, output, total_weight); |
11013 | } |
11014 | |
11015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nll_loss_forward, name, "aten::nll_loss_forward" ) |
11016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nll_loss_forward, overload_name, "" ) |
11017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(nll_loss_forward, schema_str, "nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight)" ) |
11018 | |
11019 | // aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) |
11020 | static C10_NOINLINE c10::TypedOperatorHandle<nll_loss_forward::schema> create_nll_loss_forward_typed_handle() { |
11021 | return c10::Dispatcher::singleton() |
11022 | .findSchemaOrThrow(nll_loss_forward::name, nll_loss_forward::overload_name) |
11023 | .typed<nll_loss_forward::schema>(); |
11024 | } |
11025 | |
11026 | // aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) |
11027 | ::std::tuple<at::Tensor,at::Tensor> nll_loss_forward::call(const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, int64_t reduction, c10::SymInt ignore_index) { |
11028 | |
11029 | static auto op = create_nll_loss_forward_typed_handle(); |
11030 | return op.call(self, target, weight, reduction, ignore_index); |
11031 | } |
11032 | |
11033 | // aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) |
11034 | ::std::tuple<at::Tensor,at::Tensor> nll_loss_forward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, int64_t reduction, c10::SymInt ignore_index) { |
11035 | |
11036 | static auto op = create_nll_loss_forward_typed_handle(); |
11037 | return op.redispatch(dispatchKeySet, self, target, weight, reduction, ignore_index); |
11038 | } |
11039 | |
11040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(soft_margin_loss_backward_grad_input, name, "aten::soft_margin_loss_backward" ) |
11041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(soft_margin_loss_backward_grad_input, overload_name, "grad_input" ) |
11042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(soft_margin_loss_backward_grad_input, schema_str, "soft_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11043 | |
11044 | // aten::soft_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) |
11045 | static C10_NOINLINE c10::TypedOperatorHandle<soft_margin_loss_backward_grad_input::schema> create_soft_margin_loss_backward_grad_input_typed_handle() { |
11046 | return c10::Dispatcher::singleton() |
11047 | .findSchemaOrThrow(soft_margin_loss_backward_grad_input::name, soft_margin_loss_backward_grad_input::overload_name) |
11048 | .typed<soft_margin_loss_backward_grad_input::schema>(); |
11049 | } |
11050 | |
11051 | // aten::soft_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) |
11052 | at::Tensor & soft_margin_loss_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input) { |
11053 | |
11054 | static auto op = create_soft_margin_loss_backward_grad_input_typed_handle(); |
11055 | return op.call(grad_output, self, target, reduction, grad_input); |
11056 | } |
11057 | |
11058 | // aten::soft_margin_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, int reduction, *, Tensor(a!) grad_input) -> Tensor(a!) |
11059 | at::Tensor & soft_margin_loss_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction, at::Tensor & grad_input) { |
11060 | |
11061 | static auto op = create_soft_margin_loss_backward_grad_input_typed_handle(); |
11062 | return op.redispatch(dispatchKeySet, grad_output, self, target, reduction, grad_input); |
11063 | } |
11064 | |
11065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(soft_margin_loss_backward, name, "aten::soft_margin_loss_backward" ) |
11066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(soft_margin_loss_backward, overload_name, "" ) |
11067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(soft_margin_loss_backward, schema_str, "soft_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor" ) |
11068 | |
11069 | // aten::soft_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor |
11070 | static C10_NOINLINE c10::TypedOperatorHandle<soft_margin_loss_backward::schema> create_soft_margin_loss_backward_typed_handle() { |
11071 | return c10::Dispatcher::singleton() |
11072 | .findSchemaOrThrow(soft_margin_loss_backward::name, soft_margin_loss_backward::overload_name) |
11073 | .typed<soft_margin_loss_backward::schema>(); |
11074 | } |
11075 | |
11076 | // aten::soft_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor |
11077 | at::Tensor soft_margin_loss_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
11078 | |
11079 | static auto op = create_soft_margin_loss_backward_typed_handle(); |
11080 | return op.call(grad_output, self, target, reduction); |
11081 | } |
11082 | |
11083 | // aten::soft_margin_loss_backward(Tensor grad_output, Tensor self, Tensor target, int reduction) -> Tensor |
11084 | at::Tensor soft_margin_loss_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, int64_t reduction) { |
11085 | |
11086 | static auto op = create_soft_margin_loss_backward_typed_handle(); |
11087 | return op.redispatch(dispatchKeySet, grad_output, self, target, reduction); |
11088 | } |
11089 | |
11090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_jvp, name, "aten::glu_jvp" ) |
11091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_jvp, overload_name, "" ) |
11092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_jvp, schema_str, "glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor" ) |
11093 | |
11094 | // aten::glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor |
11095 | static C10_NOINLINE c10::TypedOperatorHandle<glu_jvp::schema> create_glu_jvp_typed_handle() { |
11096 | return c10::Dispatcher::singleton() |
11097 | .findSchemaOrThrow(glu_jvp::name, glu_jvp::overload_name) |
11098 | .typed<glu_jvp::schema>(); |
11099 | } |
11100 | |
11101 | // aten::glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor |
11102 | at::Tensor glu_jvp::call(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim) { |
11103 | |
11104 | static auto op = create_glu_jvp_typed_handle(); |
11105 | return op.call(glu, x, dx, dim); |
11106 | } |
11107 | |
11108 | // aten::glu_jvp(Tensor glu, Tensor x, Tensor dx, int dim) -> Tensor |
11109 | at::Tensor glu_jvp::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim) { |
11110 | |
11111 | static auto op = create_glu_jvp_typed_handle(); |
11112 | return op.redispatch(dispatchKeySet, glu, x, dx, dim); |
11113 | } |
11114 | |
11115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish_out, name, "aten::hardswish" ) |
11116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish_out, overload_name, "out" ) |
11117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish_out, schema_str, "hardswish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
11118 | |
11119 | // aten::hardswish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
11120 | static C10_NOINLINE c10::TypedOperatorHandle<hardswish_out::schema> create_hardswish_out_typed_handle() { |
11121 | return c10::Dispatcher::singleton() |
11122 | .findSchemaOrThrow(hardswish_out::name, hardswish_out::overload_name) |
11123 | .typed<hardswish_out::schema>(); |
11124 | } |
11125 | |
11126 | // aten::hardswish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
11127 | at::Tensor & hardswish_out::call(const at::Tensor & self, at::Tensor & out) { |
11128 | |
11129 | static auto op = create_hardswish_out_typed_handle(); |
11130 | return op.call(self, out); |
11131 | } |
11132 | |
11133 | // aten::hardswish.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
11134 | at::Tensor & hardswish_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
11135 | |
11136 | static auto op = create_hardswish_out_typed_handle(); |
11137 | return op.redispatch(dispatchKeySet, self, out); |
11138 | } |
11139 | |
11140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish, name, "aten::hardswish" ) |
11141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish, overload_name, "" ) |
11142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish, schema_str, "hardswish(Tensor self) -> Tensor" ) |
11143 | |
11144 | // aten::hardswish(Tensor self) -> Tensor |
11145 | static C10_NOINLINE c10::TypedOperatorHandle<hardswish::schema> create_hardswish_typed_handle() { |
11146 | return c10::Dispatcher::singleton() |
11147 | .findSchemaOrThrow(hardswish::name, hardswish::overload_name) |
11148 | .typed<hardswish::schema>(); |
11149 | } |
11150 | |
11151 | // aten::hardswish(Tensor self) -> Tensor |
11152 | at::Tensor hardswish::call(const at::Tensor & self) { |
11153 | |
11154 | static auto op = create_hardswish_typed_handle(); |
11155 | return op.call(self); |
11156 | } |
11157 | |
11158 | // aten::hardswish(Tensor self) -> Tensor |
11159 | at::Tensor hardswish::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
11160 | |
11161 | static auto op = create_hardswish_typed_handle(); |
11162 | return op.redispatch(dispatchKeySet, self); |
11163 | } |
11164 | |
11165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish_, name, "aten::hardswish_" ) |
11166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish_, overload_name, "" ) |
11167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(hardswish_, schema_str, "hardswish_(Tensor(a!) self) -> Tensor(a!)" ) |
11168 | |
11169 | // aten::hardswish_(Tensor(a!) self) -> Tensor(a!) |
11170 | static C10_NOINLINE c10::TypedOperatorHandle<hardswish_::schema> create_hardswish__typed_handle() { |
11171 | return c10::Dispatcher::singleton() |
11172 | .findSchemaOrThrow(hardswish_::name, hardswish_::overload_name) |
11173 | .typed<hardswish_::schema>(); |
11174 | } |
11175 | |
11176 | // aten::hardswish_(Tensor(a!) self) -> Tensor(a!) |
11177 | at::Tensor & hardswish_::call(at::Tensor & self) { |
11178 | |
11179 | static auto op = create_hardswish__typed_handle(); |
11180 | return op.call(self); |
11181 | } |
11182 | |
11183 | // aten::hardswish_(Tensor(a!) self) -> Tensor(a!) |
11184 | at::Tensor & hardswish_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self) { |
11185 | |
11186 | static auto op = create_hardswish__typed_handle(); |
11187 | return op.redispatch(dispatchKeySet, self); |
11188 | } |
11189 | |
11190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_out, name, "aten::rrelu_with_noise" ) |
11191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_out, overload_name, "out" ) |
11192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_out, schema_str, "rrelu_with_noise.out(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
11193 | |
11194 | // aten::rrelu_with_noise.out(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
11195 | static C10_NOINLINE c10::TypedOperatorHandle<rrelu_with_noise_out::schema> create_rrelu_with_noise_out_typed_handle() { |
11196 | return c10::Dispatcher::singleton() |
11197 | .findSchemaOrThrow(rrelu_with_noise_out::name, rrelu_with_noise_out::overload_name) |
11198 | .typed<rrelu_with_noise_out::schema>(); |
11199 | } |
11200 | |
11201 | // aten::rrelu_with_noise.out(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
11202 | at::Tensor & rrelu_with_noise_out::call(const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator, at::Tensor & out) { |
11203 | |
11204 | static auto op = create_rrelu_with_noise_out_typed_handle(); |
11205 | return op.call(self, noise, lower, upper, training, generator, out); |
11206 | } |
11207 | |
11208 | // aten::rrelu_with_noise.out(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None, *, Tensor(a!) out) -> Tensor(a!) |
11209 | at::Tensor & rrelu_with_noise_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator, at::Tensor & out) { |
11210 | |
11211 | static auto op = create_rrelu_with_noise_out_typed_handle(); |
11212 | return op.redispatch(dispatchKeySet, self, noise, lower, upper, training, generator, out); |
11213 | } |
11214 | |
11215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise, name, "aten::rrelu_with_noise" ) |
11216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise, overload_name, "" ) |
11217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise, schema_str, "rrelu_with_noise(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor" ) |
11218 | |
11219 | // aten::rrelu_with_noise(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor |
11220 | static C10_NOINLINE c10::TypedOperatorHandle<rrelu_with_noise::schema> create_rrelu_with_noise_typed_handle() { |
11221 | return c10::Dispatcher::singleton() |
11222 | .findSchemaOrThrow(rrelu_with_noise::name, rrelu_with_noise::overload_name) |
11223 | .typed<rrelu_with_noise::schema>(); |
11224 | } |
11225 | |
11226 | // aten::rrelu_with_noise(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor |
11227 | at::Tensor rrelu_with_noise::call(const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
11228 | |
11229 | static auto op = create_rrelu_with_noise_typed_handle(); |
11230 | return op.call(self, noise, lower, upper, training, generator); |
11231 | } |
11232 | |
11233 | // aten::rrelu_with_noise(Tensor self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor |
11234 | at::Tensor rrelu_with_noise::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
11235 | |
11236 | static auto op = create_rrelu_with_noise_typed_handle(); |
11237 | return op.redispatch(dispatchKeySet, self, noise, lower, upper, training, generator); |
11238 | } |
11239 | |
11240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_, name, "aten::rrelu_with_noise_" ) |
11241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_, overload_name, "" ) |
11242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rrelu_with_noise_, schema_str, "rrelu_with_noise_(Tensor(a!) self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!)" ) |
11243 | |
11244 | // aten::rrelu_with_noise_(Tensor(a!) self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) |
11245 | static C10_NOINLINE c10::TypedOperatorHandle<rrelu_with_noise_::schema> create_rrelu_with_noise__typed_handle() { |
11246 | return c10::Dispatcher::singleton() |
11247 | .findSchemaOrThrow(rrelu_with_noise_::name, rrelu_with_noise_::overload_name) |
11248 | .typed<rrelu_with_noise_::schema>(); |
11249 | } |
11250 | |
11251 | // aten::rrelu_with_noise_(Tensor(a!) self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) |
11252 | at::Tensor & rrelu_with_noise_::call(at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
11253 | |
11254 | static auto op = create_rrelu_with_noise__typed_handle(); |
11255 | return op.call(self, noise, lower, upper, training, generator); |
11256 | } |
11257 | |
11258 | // aten::rrelu_with_noise_(Tensor(a!) self, Tensor noise, Scalar lower=0.125, Scalar upper=0.3333333333333333, bool training=False, Generator? generator=None) -> Tensor(a!) |
11259 | at::Tensor & rrelu_with_noise_::redispatch(c10::DispatchKeySet dispatchKeySet, at::Tensor & self, const at::Tensor & noise, const at::Scalar & lower, const at::Scalar & upper, bool training, c10::optional<at::Generator> generator) { |
11260 | |
11261 | static auto op = create_rrelu_with_noise__typed_handle(); |
11262 | return op.redispatch(dispatchKeySet, self, noise, lower, upper, training, generator); |
11263 | } |
11264 | |
11265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softshrink_backward_grad_input, name, "aten::softshrink_backward" ) |
11266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softshrink_backward_grad_input, overload_name, "grad_input" ) |
11267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softshrink_backward_grad_input, schema_str, "softshrink_backward.grad_input(Tensor grad_output, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11268 | |
11269 | // aten::softshrink_backward.grad_input(Tensor grad_output, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) |
11270 | static C10_NOINLINE c10::TypedOperatorHandle<softshrink_backward_grad_input::schema> create_softshrink_backward_grad_input_typed_handle() { |
11271 | return c10::Dispatcher::singleton() |
11272 | .findSchemaOrThrow(softshrink_backward_grad_input::name, softshrink_backward_grad_input::overload_name) |
11273 | .typed<softshrink_backward_grad_input::schema>(); |
11274 | } |
11275 | |
11276 | // aten::softshrink_backward.grad_input(Tensor grad_output, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) |
11277 | at::Tensor & softshrink_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input) { |
11278 | |
11279 | static auto op = create_softshrink_backward_grad_input_typed_handle(); |
11280 | return op.call(grad_output, self, lambd, grad_input); |
11281 | } |
11282 | |
11283 | // aten::softshrink_backward.grad_input(Tensor grad_output, Tensor self, Scalar lambd, *, Tensor(a!) grad_input) -> Tensor(a!) |
11284 | at::Tensor & softshrink_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd, at::Tensor & grad_input) { |
11285 | |
11286 | static auto op = create_softshrink_backward_grad_input_typed_handle(); |
11287 | return op.redispatch(dispatchKeySet, grad_output, self, lambd, grad_input); |
11288 | } |
11289 | |
11290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softshrink_backward, name, "aten::softshrink_backward" ) |
11291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softshrink_backward, overload_name, "" ) |
11292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(softshrink_backward, schema_str, "softshrink_backward(Tensor grad_output, Tensor self, Scalar lambd) -> Tensor" ) |
11293 | |
11294 | // aten::softshrink_backward(Tensor grad_output, Tensor self, Scalar lambd) -> Tensor |
11295 | static C10_NOINLINE c10::TypedOperatorHandle<softshrink_backward::schema> create_softshrink_backward_typed_handle() { |
11296 | return c10::Dispatcher::singleton() |
11297 | .findSchemaOrThrow(softshrink_backward::name, softshrink_backward::overload_name) |
11298 | .typed<softshrink_backward::schema>(); |
11299 | } |
11300 | |
11301 | // aten::softshrink_backward(Tensor grad_output, Tensor self, Scalar lambd) -> Tensor |
11302 | at::Tensor softshrink_backward::call(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd) { |
11303 | |
11304 | static auto op = create_softshrink_backward_typed_handle(); |
11305 | return op.call(grad_output, self, lambd); |
11306 | } |
11307 | |
11308 | // aten::softshrink_backward(Tensor grad_output, Tensor self, Scalar lambd) -> Tensor |
11309 | at::Tensor softshrink_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & lambd) { |
11310 | |
11311 | static auto op = create_softshrink_backward_typed_handle(); |
11312 | return op.redispatch(dispatchKeySet, grad_output, self, lambd); |
11313 | } |
11314 | |
11315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_backward, name, "aten::_adaptive_avg_pool2d_backward" ) |
11316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_backward, overload_name, "" ) |
11317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_backward, schema_str, "_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor" ) |
11318 | |
11319 | // aten::_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor |
11320 | static C10_NOINLINE c10::TypedOperatorHandle<_adaptive_avg_pool2d_backward::schema> create__adaptive_avg_pool2d_backward_typed_handle() { |
11321 | return c10::Dispatcher::singleton() |
11322 | .findSchemaOrThrow(_adaptive_avg_pool2d_backward::name, _adaptive_avg_pool2d_backward::overload_name) |
11323 | .typed<_adaptive_avg_pool2d_backward::schema>(); |
11324 | } |
11325 | |
11326 | // aten::_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor |
11327 | at::Tensor _adaptive_avg_pool2d_backward::call(const at::Tensor & grad_output, const at::Tensor & self) { |
11328 | |
11329 | static auto op = create__adaptive_avg_pool2d_backward_typed_handle(); |
11330 | return op.call(grad_output, self); |
11331 | } |
11332 | |
11333 | // aten::_adaptive_avg_pool2d_backward(Tensor grad_output, Tensor self) -> Tensor |
11334 | at::Tensor _adaptive_avg_pool2d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self) { |
11335 | |
11336 | static auto op = create__adaptive_avg_pool2d_backward_typed_handle(); |
11337 | return op.redispatch(dispatchKeySet, grad_output, self); |
11338 | } |
11339 | |
11340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool2d_out, name, "aten::avg_pool2d" ) |
11341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool2d_out, overload_name, "out" ) |
11342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool2d_out, schema_str, "avg_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
11343 | |
11344 | // aten::avg_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) |
11345 | static C10_NOINLINE c10::TypedOperatorHandle<avg_pool2d_out::schema> create_avg_pool2d_out_typed_handle() { |
11346 | return c10::Dispatcher::singleton() |
11347 | .findSchemaOrThrow(avg_pool2d_out::name, avg_pool2d_out::overload_name) |
11348 | .typed<avg_pool2d_out::schema>(); |
11349 | } |
11350 | |
11351 | // aten::avg_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) |
11352 | at::Tensor & avg_pool2d_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) { |
11353 | |
11354 | static auto op = create_avg_pool2d_out_typed_handle(); |
11355 | return op.call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); |
11356 | } |
11357 | |
11358 | // aten::avg_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None, *, Tensor(a!) out) -> Tensor(a!) |
11359 | at::Tensor & avg_pool2d_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) { |
11360 | |
11361 | static auto op = create_avg_pool2d_out_typed_handle(); |
11362 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override, out); |
11363 | } |
11364 | |
11365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool2d, name, "aten::avg_pool2d" ) |
11366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool2d, overload_name, "" ) |
11367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(avg_pool2d, schema_str, "avg_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor" ) |
11368 | |
11369 | // aten::avg_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor |
11370 | static C10_NOINLINE c10::TypedOperatorHandle<avg_pool2d::schema> create_avg_pool2d_typed_handle() { |
11371 | return c10::Dispatcher::singleton() |
11372 | .findSchemaOrThrow(avg_pool2d::name, avg_pool2d::overload_name) |
11373 | .typed<avg_pool2d::schema>(); |
11374 | } |
11375 | |
11376 | // aten::avg_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor |
11377 | at::Tensor avg_pool2d::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) { |
11378 | |
11379 | static auto op = create_avg_pool2d_typed_handle(); |
11380 | return op.call(self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); |
11381 | } |
11382 | |
11383 | // aten::avg_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, bool ceil_mode=False, bool count_include_pad=True, int? divisor_override=None) -> Tensor |
11384 | at::Tensor avg_pool2d::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) { |
11385 | |
11386 | static auto op = create_avg_pool2d_typed_handle(); |
11387 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, ceil_mode, count_include_pad, divisor_override); |
11388 | } |
11389 | |
11390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool2d_backward_grad_input, name, "aten::fractional_max_pool2d_backward" ) |
11391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool2d_backward_grad_input, overload_name, "grad_input" ) |
11392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool2d_backward_grad_input, schema_str, "fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11393 | |
11394 | // aten::fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
11395 | static C10_NOINLINE c10::TypedOperatorHandle<fractional_max_pool2d_backward_grad_input::schema> create_fractional_max_pool2d_backward_grad_input_typed_handle() { |
11396 | return c10::Dispatcher::singleton() |
11397 | .findSchemaOrThrow(fractional_max_pool2d_backward_grad_input::name, fractional_max_pool2d_backward_grad_input::overload_name) |
11398 | .typed<fractional_max_pool2d_backward_grad_input::schema>(); |
11399 | } |
11400 | |
11401 | // aten::fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
11402 | at::Tensor & fractional_max_pool2d_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input) { |
11403 | |
11404 | static auto op = create_fractional_max_pool2d_backward_grad_input_typed_handle(); |
11405 | return op.call(grad_output, self, kernel_size, output_size, indices, grad_input); |
11406 | } |
11407 | |
11408 | // aten::fractional_max_pool2d_backward.grad_input(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
11409 | at::Tensor & fractional_max_pool2d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices, at::Tensor & grad_input) { |
11410 | |
11411 | static auto op = create_fractional_max_pool2d_backward_grad_input_typed_handle(); |
11412 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, output_size, indices, grad_input); |
11413 | } |
11414 | |
11415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool2d_backward, name, "aten::fractional_max_pool2d_backward" ) |
11416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool2d_backward, overload_name, "" ) |
11417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fractional_max_pool2d_backward, schema_str, "fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor" ) |
11418 | |
11419 | // aten::fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor |
11420 | static C10_NOINLINE c10::TypedOperatorHandle<fractional_max_pool2d_backward::schema> create_fractional_max_pool2d_backward_typed_handle() { |
11421 | return c10::Dispatcher::singleton() |
11422 | .findSchemaOrThrow(fractional_max_pool2d_backward::name, fractional_max_pool2d_backward::overload_name) |
11423 | .typed<fractional_max_pool2d_backward::schema>(); |
11424 | } |
11425 | |
11426 | // aten::fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor |
11427 | at::Tensor fractional_max_pool2d_backward::call(const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) { |
11428 | |
11429 | static auto op = create_fractional_max_pool2d_backward_typed_handle(); |
11430 | return op.call(grad_output, self, kernel_size, output_size, indices); |
11431 | } |
11432 | |
11433 | // aten::fractional_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] output_size, Tensor indices) -> Tensor |
11434 | at::Tensor fractional_max_pool2d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::IntArrayRef kernel_size, at::IntArrayRef output_size, const at::Tensor & indices) { |
11435 | |
11436 | static auto op = create_fractional_max_pool2d_backward_typed_handle(); |
11437 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, output_size, indices); |
11438 | } |
11439 | |
11440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_backward_grad_input, name, "aten::max_pool3d_with_indices_backward" ) |
11441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_backward_grad_input, overload_name, "grad_input" ) |
11442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_backward_grad_input, schema_str, "max_pool3d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11443 | |
11444 | // aten::max_pool3d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
11445 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool3d_with_indices_backward_grad_input::schema> create_max_pool3d_with_indices_backward_grad_input_typed_handle() { |
11446 | return c10::Dispatcher::singleton() |
11447 | .findSchemaOrThrow(max_pool3d_with_indices_backward_grad_input::name, max_pool3d_with_indices_backward_grad_input::overload_name) |
11448 | .typed<max_pool3d_with_indices_backward_grad_input::schema>(); |
11449 | } |
11450 | |
11451 | // aten::max_pool3d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
11452 | at::Tensor & max_pool3d_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) { |
11453 | |
11454 | static auto op = create_max_pool3d_with_indices_backward_grad_input_typed_handle(); |
11455 | return op.call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices, grad_input); |
11456 | } |
11457 | |
11458 | // aten::max_pool3d_with_indices_backward.grad_input(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices, *, Tensor(a!) grad_input) -> Tensor(a!) |
11459 | at::Tensor & max_pool3d_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) { |
11460 | |
11461 | static auto op = create_max_pool3d_with_indices_backward_grad_input_typed_handle(); |
11462 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices, grad_input); |
11463 | } |
11464 | |
11465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_backward, name, "aten::max_pool3d_with_indices_backward" ) |
11466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_backward, overload_name, "" ) |
11467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(max_pool3d_with_indices_backward, schema_str, "max_pool3d_with_indices_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices) -> Tensor" ) |
11468 | |
11469 | // aten::max_pool3d_with_indices_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices) -> Tensor |
11470 | static C10_NOINLINE c10::TypedOperatorHandle<max_pool3d_with_indices_backward::schema> create_max_pool3d_with_indices_backward_typed_handle() { |
11471 | return c10::Dispatcher::singleton() |
11472 | .findSchemaOrThrow(max_pool3d_with_indices_backward::name, max_pool3d_with_indices_backward::overload_name) |
11473 | .typed<max_pool3d_with_indices_backward::schema>(); |
11474 | } |
11475 | |
11476 | // aten::max_pool3d_with_indices_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices) -> Tensor |
11477 | at::Tensor max_pool3d_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) { |
11478 | |
11479 | static auto op = create_max_pool3d_with_indices_backward_typed_handle(); |
11480 | return op.call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices); |
11481 | } |
11482 | |
11483 | // aten::max_pool3d_with_indices_backward(Tensor grad_output, Tensor self, int[3] kernel_size, int[3] stride, int[3] padding, int[3] dilation, bool ceil_mode, Tensor indices) -> Tensor |
11484 | at::Tensor max_pool3d_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) { |
11485 | |
11486 | static auto op = create_max_pool3d_with_indices_backward_typed_handle(); |
11487 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, indices); |
11488 | } |
11489 | |
11490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_backward_grad_input, name, "aten::reflection_pad1d_backward" ) |
11491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_backward_grad_input, overload_name, "grad_input" ) |
11492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_backward_grad_input, schema_str, "reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11493 | |
11494 | // aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11495 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad1d_backward_grad_input::schema> create_reflection_pad1d_backward_grad_input_typed_handle() { |
11496 | return c10::Dispatcher::singleton() |
11497 | .findSchemaOrThrow(reflection_pad1d_backward_grad_input::name, reflection_pad1d_backward_grad_input::overload_name) |
11498 | .typed<reflection_pad1d_backward_grad_input::schema>(); |
11499 | } |
11500 | |
11501 | // aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11502 | at::Tensor & reflection_pad1d_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11503 | |
11504 | static auto op = create_reflection_pad1d_backward_grad_input_typed_handle(); |
11505 | return op.call(grad_output, self, padding, grad_input); |
11506 | } |
11507 | |
11508 | // aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11509 | at::Tensor & reflection_pad1d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11510 | |
11511 | static auto op = create_reflection_pad1d_backward_grad_input_typed_handle(); |
11512 | return op.redispatch(dispatchKeySet, grad_output, self, padding, grad_input); |
11513 | } |
11514 | |
11515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_backward, name, "aten::reflection_pad1d_backward" ) |
11516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_backward, overload_name, "" ) |
11517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad1d_backward, schema_str, "reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor" ) |
11518 | |
11519 | // aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor |
11520 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad1d_backward::schema> create_reflection_pad1d_backward_typed_handle() { |
11521 | return c10::Dispatcher::singleton() |
11522 | .findSchemaOrThrow(reflection_pad1d_backward::name, reflection_pad1d_backward::overload_name) |
11523 | .typed<reflection_pad1d_backward::schema>(); |
11524 | } |
11525 | |
11526 | // aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor |
11527 | at::Tensor reflection_pad1d_backward::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11528 | |
11529 | static auto op = create_reflection_pad1d_backward_typed_handle(); |
11530 | return op.call(grad_output, self, padding); |
11531 | } |
11532 | |
11533 | // aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor |
11534 | at::Tensor reflection_pad1d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11535 | |
11536 | static auto op = create_reflection_pad1d_backward_typed_handle(); |
11537 | return op.redispatch(dispatchKeySet, grad_output, self, padding); |
11538 | } |
11539 | |
11540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_backward_grad_input, name, "aten::reflection_pad2d_backward" ) |
11541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_backward_grad_input, overload_name, "grad_input" ) |
11542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_backward_grad_input, schema_str, "reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11543 | |
11544 | // aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11545 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad2d_backward_grad_input::schema> create_reflection_pad2d_backward_grad_input_typed_handle() { |
11546 | return c10::Dispatcher::singleton() |
11547 | .findSchemaOrThrow(reflection_pad2d_backward_grad_input::name, reflection_pad2d_backward_grad_input::overload_name) |
11548 | .typed<reflection_pad2d_backward_grad_input::schema>(); |
11549 | } |
11550 | |
11551 | // aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11552 | at::Tensor & reflection_pad2d_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11553 | |
11554 | static auto op = create_reflection_pad2d_backward_grad_input_typed_handle(); |
11555 | return op.call(grad_output, self, padding, grad_input); |
11556 | } |
11557 | |
11558 | // aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11559 | at::Tensor & reflection_pad2d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11560 | |
11561 | static auto op = create_reflection_pad2d_backward_grad_input_typed_handle(); |
11562 | return op.redispatch(dispatchKeySet, grad_output, self, padding, grad_input); |
11563 | } |
11564 | |
11565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_backward, name, "aten::reflection_pad2d_backward" ) |
11566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_backward, overload_name, "" ) |
11567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(reflection_pad2d_backward, schema_str, "reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor" ) |
11568 | |
11569 | // aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor |
11570 | static C10_NOINLINE c10::TypedOperatorHandle<reflection_pad2d_backward::schema> create_reflection_pad2d_backward_typed_handle() { |
11571 | return c10::Dispatcher::singleton() |
11572 | .findSchemaOrThrow(reflection_pad2d_backward::name, reflection_pad2d_backward::overload_name) |
11573 | .typed<reflection_pad2d_backward::schema>(); |
11574 | } |
11575 | |
11576 | // aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor |
11577 | at::Tensor reflection_pad2d_backward::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11578 | |
11579 | static auto op = create_reflection_pad2d_backward_typed_handle(); |
11580 | return op.call(grad_output, self, padding); |
11581 | } |
11582 | |
11583 | // aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor |
11584 | at::Tensor reflection_pad2d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11585 | |
11586 | static auto op = create_reflection_pad2d_backward_typed_handle(); |
11587 | return op.redispatch(dispatchKeySet, grad_output, self, padding); |
11588 | } |
11589 | |
11590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad1d_backward_grad_input, name, "aten::replication_pad1d_backward" ) |
11591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad1d_backward_grad_input, overload_name, "grad_input" ) |
11592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad1d_backward_grad_input, schema_str, "replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11593 | |
11594 | // aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11595 | static C10_NOINLINE c10::TypedOperatorHandle<replication_pad1d_backward_grad_input::schema> create_replication_pad1d_backward_grad_input_typed_handle() { |
11596 | return c10::Dispatcher::singleton() |
11597 | .findSchemaOrThrow(replication_pad1d_backward_grad_input::name, replication_pad1d_backward_grad_input::overload_name) |
11598 | .typed<replication_pad1d_backward_grad_input::schema>(); |
11599 | } |
11600 | |
11601 | // aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11602 | at::Tensor & replication_pad1d_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11603 | |
11604 | static auto op = create_replication_pad1d_backward_grad_input_typed_handle(); |
11605 | return op.call(grad_output, self, padding, grad_input); |
11606 | } |
11607 | |
11608 | // aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11609 | at::Tensor & replication_pad1d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11610 | |
11611 | static auto op = create_replication_pad1d_backward_grad_input_typed_handle(); |
11612 | return op.redispatch(dispatchKeySet, grad_output, self, padding, grad_input); |
11613 | } |
11614 | |
11615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad1d_backward, name, "aten::replication_pad1d_backward" ) |
11616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad1d_backward, overload_name, "" ) |
11617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad1d_backward, schema_str, "replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor" ) |
11618 | |
11619 | // aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor |
11620 | static C10_NOINLINE c10::TypedOperatorHandle<replication_pad1d_backward::schema> create_replication_pad1d_backward_typed_handle() { |
11621 | return c10::Dispatcher::singleton() |
11622 | .findSchemaOrThrow(replication_pad1d_backward::name, replication_pad1d_backward::overload_name) |
11623 | .typed<replication_pad1d_backward::schema>(); |
11624 | } |
11625 | |
11626 | // aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor |
11627 | at::Tensor replication_pad1d_backward::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11628 | |
11629 | static auto op = create_replication_pad1d_backward_typed_handle(); |
11630 | return op.call(grad_output, self, padding); |
11631 | } |
11632 | |
11633 | // aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor |
11634 | at::Tensor replication_pad1d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11635 | |
11636 | static auto op = create_replication_pad1d_backward_typed_handle(); |
11637 | return op.redispatch(dispatchKeySet, grad_output, self, padding); |
11638 | } |
11639 | |
11640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad3d_backward_grad_input, name, "aten::replication_pad3d_backward" ) |
11641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad3d_backward_grad_input, overload_name, "grad_input" ) |
11642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad3d_backward_grad_input, schema_str, "replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11643 | |
11644 | // aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11645 | static C10_NOINLINE c10::TypedOperatorHandle<replication_pad3d_backward_grad_input::schema> create_replication_pad3d_backward_grad_input_typed_handle() { |
11646 | return c10::Dispatcher::singleton() |
11647 | .findSchemaOrThrow(replication_pad3d_backward_grad_input::name, replication_pad3d_backward_grad_input::overload_name) |
11648 | .typed<replication_pad3d_backward_grad_input::schema>(); |
11649 | } |
11650 | |
11651 | // aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11652 | at::Tensor & replication_pad3d_backward_grad_input::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11653 | |
11654 | static auto op = create_replication_pad3d_backward_grad_input_typed_handle(); |
11655 | return op.call(grad_output, self, padding, grad_input); |
11656 | } |
11657 | |
11658 | // aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) |
11659 | at::Tensor & replication_pad3d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding, at::Tensor & grad_input) { |
11660 | |
11661 | static auto op = create_replication_pad3d_backward_grad_input_typed_handle(); |
11662 | return op.redispatch(dispatchKeySet, grad_output, self, padding, grad_input); |
11663 | } |
11664 | |
11665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad3d_backward, name, "aten::replication_pad3d_backward" ) |
11666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad3d_backward, overload_name, "" ) |
11667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(replication_pad3d_backward, schema_str, "replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor" ) |
11668 | |
11669 | // aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor |
11670 | static C10_NOINLINE c10::TypedOperatorHandle<replication_pad3d_backward::schema> create_replication_pad3d_backward_typed_handle() { |
11671 | return c10::Dispatcher::singleton() |
11672 | .findSchemaOrThrow(replication_pad3d_backward::name, replication_pad3d_backward::overload_name) |
11673 | .typed<replication_pad3d_backward::schema>(); |
11674 | } |
11675 | |
11676 | // aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor |
11677 | at::Tensor replication_pad3d_backward::call(const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11678 | |
11679 | static auto op = create_replication_pad3d_backward_typed_handle(); |
11680 | return op.call(grad_output, self, padding); |
11681 | } |
11682 | |
11683 | // aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor |
11684 | at::Tensor replication_pad3d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, c10::SymIntArrayRef padding) { |
11685 | |
11686 | static auto op = create_replication_pad3d_backward_typed_handle(); |
11687 | return op.redispatch(dispatchKeySet, grad_output, self, padding); |
11688 | } |
11689 | |
11690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_vec, name, "aten::_upsample_nearest_exact2d" ) |
11691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_vec, overload_name, "vec" ) |
11692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_vec, schema_str, "_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor" ) |
11693 | |
11694 | // aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
11695 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact2d_vec::schema> create__upsample_nearest_exact2d_vec_typed_handle() { |
11696 | return c10::Dispatcher::singleton() |
11697 | .findSchemaOrThrow(_upsample_nearest_exact2d_vec::name, _upsample_nearest_exact2d_vec::overload_name) |
11698 | .typed<_upsample_nearest_exact2d_vec::schema>(); |
11699 | } |
11700 | |
11701 | // aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
11702 | at::Tensor _upsample_nearest_exact2d_vec::call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional<at::ArrayRef<double>> scale_factors) { |
11703 | |
11704 | static auto op = create__upsample_nearest_exact2d_vec_typed_handle(); |
11705 | return op.call(input, output_size, scale_factors); |
11706 | } |
11707 | |
11708 | // aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
11709 | at::Tensor _upsample_nearest_exact2d_vec::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional<at::ArrayRef<double>> scale_factors) { |
11710 | |
11711 | static auto op = create__upsample_nearest_exact2d_vec_typed_handle(); |
11712 | return op.redispatch(dispatchKeySet, input, output_size, scale_factors); |
11713 | } |
11714 | |
11715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d_vec, name, "aten::_upsample_nearest_exact3d" ) |
11716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d_vec, overload_name, "vec" ) |
11717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d_vec, schema_str, "_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor" ) |
11718 | |
11719 | // aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
11720 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact3d_vec::schema> create__upsample_nearest_exact3d_vec_typed_handle() { |
11721 | return c10::Dispatcher::singleton() |
11722 | .findSchemaOrThrow(_upsample_nearest_exact3d_vec::name, _upsample_nearest_exact3d_vec::overload_name) |
11723 | .typed<_upsample_nearest_exact3d_vec::schema>(); |
11724 | } |
11725 | |
11726 | // aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
11727 | at::Tensor _upsample_nearest_exact3d_vec::call(const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional<at::ArrayRef<double>> scale_factors) { |
11728 | |
11729 | static auto op = create__upsample_nearest_exact3d_vec_typed_handle(); |
11730 | return op.call(input, output_size, scale_factors); |
11731 | } |
11732 | |
11733 | // aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor |
11734 | at::Tensor _upsample_nearest_exact3d_vec::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::OptionalSymIntArrayRef output_size, c10::optional<at::ArrayRef<double>> scale_factors) { |
11735 | |
11736 | static auto op = create__upsample_nearest_exact3d_vec_typed_handle(); |
11737 | return op.redispatch(dispatchKeySet, input, output_size, scale_factors); |
11738 | } |
11739 | |
11740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_bilinear2d_backward_grad_input, name, "aten::upsample_bilinear2d_backward" ) |
11741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_bilinear2d_backward_grad_input, overload_name, "grad_input" ) |
11742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_bilinear2d_backward_grad_input, schema_str, "upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11743 | |
11744 | // aten::upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11745 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_bilinear2d_backward_grad_input::schema> create_upsample_bilinear2d_backward_grad_input_typed_handle() { |
11746 | return c10::Dispatcher::singleton() |
11747 | .findSchemaOrThrow(upsample_bilinear2d_backward_grad_input::name, upsample_bilinear2d_backward_grad_input::overload_name) |
11748 | .typed<upsample_bilinear2d_backward_grad_input::schema>(); |
11749 | } |
11750 | |
11751 | // aten::upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11752 | at::Tensor & upsample_bilinear2d_backward_grad_input::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
11753 | |
11754 | static auto op = create_upsample_bilinear2d_backward_grad_input_typed_handle(); |
11755 | return op.call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); |
11756 | } |
11757 | |
11758 | // aten::upsample_bilinear2d_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11759 | at::Tensor & upsample_bilinear2d_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
11760 | |
11761 | static auto op = create_upsample_bilinear2d_backward_grad_input_typed_handle(); |
11762 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); |
11763 | } |
11764 | |
11765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_bilinear2d_backward, name, "aten::upsample_bilinear2d_backward" ) |
11766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_bilinear2d_backward, overload_name, "" ) |
11767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(upsample_bilinear2d_backward, schema_str, "upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor" ) |
11768 | |
11769 | // aten::upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
11770 | static C10_NOINLINE c10::TypedOperatorHandle<upsample_bilinear2d_backward::schema> create_upsample_bilinear2d_backward_typed_handle() { |
11771 | return c10::Dispatcher::singleton() |
11772 | .findSchemaOrThrow(upsample_bilinear2d_backward::name, upsample_bilinear2d_backward::overload_name) |
11773 | .typed<upsample_bilinear2d_backward::schema>(); |
11774 | } |
11775 | |
11776 | // aten::upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
11777 | at::Tensor upsample_bilinear2d_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
11778 | |
11779 | static auto op = create_upsample_bilinear2d_backward_typed_handle(); |
11780 | return op.call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); |
11781 | } |
11782 | |
11783 | // aten::upsample_bilinear2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
11784 | at::Tensor upsample_bilinear2d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
11785 | |
11786 | static auto op = create_upsample_bilinear2d_backward_typed_handle(); |
11787 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales_h, scales_w); |
11788 | } |
11789 | |
11790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_backward_grad_input, name, "aten::_upsample_bicubic2d_aa_backward" ) |
11791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_backward_grad_input, overload_name, "grad_input" ) |
11792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_backward_grad_input, schema_str, "_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11793 | |
11794 | // aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11795 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bicubic2d_aa_backward_grad_input::schema> create__upsample_bicubic2d_aa_backward_grad_input_typed_handle() { |
11796 | return c10::Dispatcher::singleton() |
11797 | .findSchemaOrThrow(_upsample_bicubic2d_aa_backward_grad_input::name, _upsample_bicubic2d_aa_backward_grad_input::overload_name) |
11798 | .typed<_upsample_bicubic2d_aa_backward_grad_input::schema>(); |
11799 | } |
11800 | |
11801 | // aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11802 | at::Tensor & _upsample_bicubic2d_aa_backward_grad_input::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
11803 | |
11804 | static auto op = create__upsample_bicubic2d_aa_backward_grad_input_typed_handle(); |
11805 | return op.call(grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); |
11806 | } |
11807 | |
11808 | // aten::_upsample_bicubic2d_aa_backward.grad_input(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11809 | at::Tensor & _upsample_bicubic2d_aa_backward_grad_input::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & grad_input) { |
11810 | |
11811 | static auto op = create__upsample_bicubic2d_aa_backward_grad_input_typed_handle(); |
11812 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales_h, scales_w, grad_input); |
11813 | } |
11814 | |
11815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_backward, name, "aten::_upsample_bicubic2d_aa_backward" ) |
11816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_backward, overload_name, "" ) |
11817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_bicubic2d_aa_backward, schema_str, "_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor" ) |
11818 | |
11819 | // aten::_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
11820 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_bicubic2d_aa_backward::schema> create__upsample_bicubic2d_aa_backward_typed_handle() { |
11821 | return c10::Dispatcher::singleton() |
11822 | .findSchemaOrThrow(_upsample_bicubic2d_aa_backward::name, _upsample_bicubic2d_aa_backward::overload_name) |
11823 | .typed<_upsample_bicubic2d_aa_backward::schema>(); |
11824 | } |
11825 | |
11826 | // aten::_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
11827 | at::Tensor _upsample_bicubic2d_aa_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
11828 | |
11829 | static auto op = create__upsample_bicubic2d_aa_backward_typed_handle(); |
11830 | return op.call(grad_output, output_size, input_size, align_corners, scales_h, scales_w); |
11831 | } |
11832 | |
11833 | // aten::_upsample_bicubic2d_aa_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> Tensor |
11834 | at::Tensor _upsample_bicubic2d_aa_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, bool align_corners, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
11835 | |
11836 | static auto op = create__upsample_bicubic2d_aa_backward_typed_handle(); |
11837 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, align_corners, scales_h, scales_w); |
11838 | } |
11839 | |
11840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact1d_backward_grad_input, name, "aten::_upsample_nearest_exact1d_backward" ) |
11841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact1d_backward_grad_input, overload_name, "grad_input" ) |
11842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact1d_backward_grad_input, schema_str, "_upsample_nearest_exact1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!)" ) |
11843 | |
11844 | // aten::_upsample_nearest_exact1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11845 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact1d_backward_grad_input::schema> create__upsample_nearest_exact1d_backward_grad_input_typed_handle() { |
11846 | return c10::Dispatcher::singleton() |
11847 | .findSchemaOrThrow(_upsample_nearest_exact1d_backward_grad_input::name, _upsample_nearest_exact1d_backward_grad_input::overload_name) |
11848 | .typed<_upsample_nearest_exact1d_backward_grad_input::schema>(); |
11849 | } |
11850 | |
11851 | // aten::_upsample_nearest_exact1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11852 | at::Tensor & _upsample_nearest_exact1d_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) { |
11853 | |
11854 | static auto op = create__upsample_nearest_exact1d_backward_grad_input_typed_handle(); |
11855 | return op.call(grad_output, output_size, input_size, scales, grad_input); |
11856 | } |
11857 | |
11858 | // aten::_upsample_nearest_exact1d_backward.grad_input(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None, *, Tensor(a!) grad_input) -> Tensor(a!) |
11859 | at::Tensor & _upsample_nearest_exact1d_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) { |
11860 | |
11861 | static auto op = create__upsample_nearest_exact1d_backward_grad_input_typed_handle(); |
11862 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales, grad_input); |
11863 | } |
11864 | |
11865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact1d_backward, name, "aten::_upsample_nearest_exact1d_backward" ) |
11866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact1d_backward, overload_name, "" ) |
11867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact1d_backward, schema_str, "_upsample_nearest_exact1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor" ) |
11868 | |
11869 | // aten::_upsample_nearest_exact1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor |
11870 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact1d_backward::schema> create__upsample_nearest_exact1d_backward_typed_handle() { |
11871 | return c10::Dispatcher::singleton() |
11872 | .findSchemaOrThrow(_upsample_nearest_exact1d_backward::name, _upsample_nearest_exact1d_backward::overload_name) |
11873 | .typed<_upsample_nearest_exact1d_backward::schema>(); |
11874 | } |
11875 | |
11876 | // aten::_upsample_nearest_exact1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor |
11877 | at::Tensor _upsample_nearest_exact1d_backward::call(const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales) { |
11878 | |
11879 | static auto op = create__upsample_nearest_exact1d_backward_typed_handle(); |
11880 | return op.call(grad_output, output_size, input_size, scales); |
11881 | } |
11882 | |
11883 | // aten::_upsample_nearest_exact1d_backward(Tensor grad_output, SymInt[1] output_size, SymInt[3] input_size, float? scales=None) -> Tensor |
11884 | at::Tensor _upsample_nearest_exact1d_backward::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef output_size, c10::SymIntArrayRef input_size, c10::optional<double> scales) { |
11885 | |
11886 | static auto op = create__upsample_nearest_exact1d_backward_typed_handle(); |
11887 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales); |
11888 | } |
11889 | |
11890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_out, name, "aten::_upsample_nearest_exact2d" ) |
11891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_out, overload_name, "out" ) |
11892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_out, schema_str, "_upsample_nearest_exact2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
11893 | |
11894 | // aten::_upsample_nearest_exact2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
11895 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact2d_out::schema> create__upsample_nearest_exact2d_out_typed_handle() { |
11896 | return c10::Dispatcher::singleton() |
11897 | .findSchemaOrThrow(_upsample_nearest_exact2d_out::name, _upsample_nearest_exact2d_out::overload_name) |
11898 | .typed<_upsample_nearest_exact2d_out::schema>(); |
11899 | } |
11900 | |
11901 | // aten::_upsample_nearest_exact2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
11902 | at::Tensor & _upsample_nearest_exact2d_out::call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
11903 | |
11904 | static auto op = create__upsample_nearest_exact2d_out_typed_handle(); |
11905 | return op.call(self, output_size, scales_h, scales_w, out); |
11906 | } |
11907 | |
11908 | // aten::_upsample_nearest_exact2d.out(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
11909 | at::Tensor & _upsample_nearest_exact2d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
11910 | |
11911 | static auto op = create__upsample_nearest_exact2d_out_typed_handle(); |
11912 | return op.redispatch(dispatchKeySet, self, output_size, scales_h, scales_w, out); |
11913 | } |
11914 | |
11915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d, name, "aten::_upsample_nearest_exact2d" ) |
11916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d, overload_name, "" ) |
11917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d, schema_str, "_upsample_nearest_exact2d(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None) -> Tensor" ) |
11918 | |
11919 | // aten::_upsample_nearest_exact2d(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None) -> Tensor |
11920 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact2d::schema> create__upsample_nearest_exact2d_typed_handle() { |
11921 | return c10::Dispatcher::singleton() |
11922 | .findSchemaOrThrow(_upsample_nearest_exact2d::name, _upsample_nearest_exact2d::overload_name) |
11923 | .typed<_upsample_nearest_exact2d::schema>(); |
11924 | } |
11925 | |
11926 | // aten::_upsample_nearest_exact2d(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None) -> Tensor |
11927 | at::Tensor _upsample_nearest_exact2d::call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
11928 | |
11929 | static auto op = create__upsample_nearest_exact2d_typed_handle(); |
11930 | return op.call(self, output_size, scales_h, scales_w); |
11931 | } |
11932 | |
11933 | // aten::_upsample_nearest_exact2d(Tensor self, SymInt[2] output_size, float? scales_h=None, float? scales_w=None) -> Tensor |
11934 | at::Tensor _upsample_nearest_exact2d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
11935 | |
11936 | static auto op = create__upsample_nearest_exact2d_typed_handle(); |
11937 | return op.redispatch(dispatchKeySet, self, output_size, scales_h, scales_w); |
11938 | } |
11939 | |
11940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_backward_grad_input, name, "aten::_upsample_nearest_exact2d_backward" ) |
11941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_backward_grad_input, overload_name, "grad_input" ) |
11942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_backward_grad_input, schema_str, "_upsample_nearest_exact2d_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!)" ) |
11943 | |
11944 | // aten::_upsample_nearest_exact2d_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!) |
11945 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact2d_backward_grad_input::schema> create__upsample_nearest_exact2d_backward_grad_input_typed_handle() { |
11946 | return c10::Dispatcher::singleton() |
11947 | .findSchemaOrThrow(_upsample_nearest_exact2d_backward_grad_input::name, _upsample_nearest_exact2d_backward_grad_input::overload_name) |
11948 | .typed<_upsample_nearest_exact2d_backward_grad_input::schema>(); |
11949 | } |
11950 | |
11951 | // aten::_upsample_nearest_exact2d_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!) |
11952 | at::Tensor & _upsample_nearest_exact2d_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) { |
11953 | |
11954 | static auto op = create__upsample_nearest_exact2d_backward_grad_input_typed_handle(); |
11955 | return op.call(grad_output, output_size, input_size, scales_h, scales_w, grad_input); |
11956 | } |
11957 | |
11958 | // aten::_upsample_nearest_exact2d_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!) |
11959 | at::Tensor & _upsample_nearest_exact2d_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) { |
11960 | |
11961 | static auto op = create__upsample_nearest_exact2d_backward_grad_input_typed_handle(); |
11962 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales_h, scales_w, grad_input); |
11963 | } |
11964 | |
11965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_backward, name, "aten::_upsample_nearest_exact2d_backward" ) |
11966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_backward, overload_name, "" ) |
11967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact2d_backward, schema_str, "_upsample_nearest_exact2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor" ) |
11968 | |
11969 | // aten::_upsample_nearest_exact2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor |
11970 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact2d_backward::schema> create__upsample_nearest_exact2d_backward_typed_handle() { |
11971 | return c10::Dispatcher::singleton() |
11972 | .findSchemaOrThrow(_upsample_nearest_exact2d_backward::name, _upsample_nearest_exact2d_backward::overload_name) |
11973 | .typed<_upsample_nearest_exact2d_backward::schema>(); |
11974 | } |
11975 | |
11976 | // aten::_upsample_nearest_exact2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor |
11977 | at::Tensor _upsample_nearest_exact2d_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) { |
11978 | |
11979 | static auto op = create__upsample_nearest_exact2d_backward_typed_handle(); |
11980 | return op.call(grad_output, output_size, input_size, scales_h, scales_w); |
11981 | } |
11982 | |
11983 | // aten::_upsample_nearest_exact2d_backward(Tensor grad_output, SymInt[2] output_size, SymInt[4] input_size, float? scales_h=None, float? scales_w=None) -> Tensor |
11984 | at::Tensor _upsample_nearest_exact2d_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) { |
11985 | |
11986 | static auto op = create__upsample_nearest_exact2d_backward_typed_handle(); |
11987 | return op.redispatch(dispatchKeySet, grad_output, output_size, input_size, scales_h, scales_w); |
11988 | } |
11989 | |
11990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d_out, name, "aten::_upsample_nearest_exact3d" ) |
11991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d_out, overload_name, "out" ) |
11992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d_out, schema_str, "_upsample_nearest_exact3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
11993 | |
11994 | // aten::_upsample_nearest_exact3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
11995 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact3d_out::schema> create__upsample_nearest_exact3d_out_typed_handle() { |
11996 | return c10::Dispatcher::singleton() |
11997 | .findSchemaOrThrow(_upsample_nearest_exact3d_out::name, _upsample_nearest_exact3d_out::overload_name) |
11998 | .typed<_upsample_nearest_exact3d_out::schema>(); |
11999 | } |
12000 | |
12001 | // aten::_upsample_nearest_exact3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
12002 | at::Tensor & _upsample_nearest_exact3d_out::call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
12003 | |
12004 | static auto op = create__upsample_nearest_exact3d_out_typed_handle(); |
12005 | return op.call(self, output_size, scales_d, scales_h, scales_w, out); |
12006 | } |
12007 | |
12008 | // aten::_upsample_nearest_exact3d.out(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None, *, Tensor(a!) out) -> Tensor(a!) |
12009 | at::Tensor & _upsample_nearest_exact3d_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w, at::Tensor & out) { |
12010 | |
12011 | static auto op = create__upsample_nearest_exact3d_out_typed_handle(); |
12012 | return op.redispatch(dispatchKeySet, self, output_size, scales_d, scales_h, scales_w, out); |
12013 | } |
12014 | |
12015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d, name, "aten::_upsample_nearest_exact3d" ) |
12016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d, overload_name, "" ) |
12017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_upsample_nearest_exact3d, schema_str, "_upsample_nearest_exact3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor" ) |
12018 | |
12019 | // aten::_upsample_nearest_exact3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
12020 | static C10_NOINLINE c10::TypedOperatorHandle<_upsample_nearest_exact3d::schema> create__upsample_nearest_exact3d_typed_handle() { |
12021 | return c10::Dispatcher::singleton() |
12022 | .findSchemaOrThrow(_upsample_nearest_exact3d::name, _upsample_nearest_exact3d::overload_name) |
12023 | .typed<_upsample_nearest_exact3d::schema>(); |
12024 | } |
12025 | |
12026 | // aten::_upsample_nearest_exact3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
12027 | at::Tensor _upsample_nearest_exact3d::call(const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
12028 | |
12029 | static auto op = create__upsample_nearest_exact3d_typed_handle(); |
12030 | return op.call(self, output_size, scales_d, scales_h, scales_w); |
12031 | } |
12032 | |
12033 | // aten::_upsample_nearest_exact3d(Tensor self, SymInt[3] output_size, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> Tensor |
12034 | at::Tensor _upsample_nearest_exact3d::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef output_size, c10::optional<double> scales_d, c10::optional<double> scales_h, c10::optional<double> scales_w) { |
12035 | |
12036 | static auto op = create__upsample_nearest_exact3d_typed_handle(); |
12037 | return op.redispatch(dispatchKeySet, self, output_size, scales_d, scales_h, scales_w); |
12038 | } |
12039 | |
12040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_dilated3d, name, "aten::slow_conv_dilated3d" ) |
12041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_dilated3d, overload_name, "" ) |
12042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_dilated3d, schema_str, "slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor" ) |
12043 | |
12044 | // aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor |
12045 | static C10_NOINLINE c10::TypedOperatorHandle<slow_conv_dilated3d::schema> create_slow_conv_dilated3d_typed_handle() { |
12046 | return c10::Dispatcher::singleton() |
12047 | .findSchemaOrThrow(slow_conv_dilated3d::name, slow_conv_dilated3d::overload_name) |
12048 | .typed<slow_conv_dilated3d::schema>(); |
12049 | } |
12050 | |
12051 | // aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor |
12052 | at::Tensor slow_conv_dilated3d::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::IntArrayRef dilation) { |
12053 | |
12054 | static auto op = create_slow_conv_dilated3d_typed_handle(); |
12055 | return op.call(self, weight, kernel_size, bias, stride, padding, dilation); |
12056 | } |
12057 | |
12058 | // aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor |
12059 | at::Tensor slow_conv_dilated3d::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::IntArrayRef dilation) { |
12060 | |
12061 | static auto op = create_slow_conv_dilated3d_typed_handle(); |
12062 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding, dilation); |
12063 | } |
12064 | |
12065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isinf, name, "aten::isinf" ) |
12066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isinf, overload_name, "" ) |
12067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isinf, schema_str, "isinf(Tensor self) -> Tensor" ) |
12068 | |
12069 | // aten::isinf(Tensor self) -> Tensor |
12070 | static C10_NOINLINE c10::TypedOperatorHandle<isinf::schema> create_isinf_typed_handle() { |
12071 | return c10::Dispatcher::singleton() |
12072 | .findSchemaOrThrow(isinf::name, isinf::overload_name) |
12073 | .typed<isinf::schema>(); |
12074 | } |
12075 | |
12076 | // aten::isinf(Tensor self) -> Tensor |
12077 | at::Tensor isinf::call(const at::Tensor & self) { |
12078 | |
12079 | static auto op = create_isinf_typed_handle(); |
12080 | return op.call(self); |
12081 | } |
12082 | |
12083 | // aten::isinf(Tensor self) -> Tensor |
12084 | at::Tensor isinf::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
12085 | |
12086 | static auto op = create_isinf_typed_handle(); |
12087 | return op.redispatch(dispatchKeySet, self); |
12088 | } |
12089 | |
12090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_digamma, name, "aten::special_digamma" ) |
12091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_digamma, overload_name, "" ) |
12092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_digamma, schema_str, "special_digamma(Tensor self) -> Tensor" ) |
12093 | |
12094 | // aten::special_digamma(Tensor self) -> Tensor |
12095 | static C10_NOINLINE c10::TypedOperatorHandle<special_digamma::schema> create_special_digamma_typed_handle() { |
12096 | return c10::Dispatcher::singleton() |
12097 | .findSchemaOrThrow(special_digamma::name, special_digamma::overload_name) |
12098 | .typed<special_digamma::schema>(); |
12099 | } |
12100 | |
12101 | // aten::special_digamma(Tensor self) -> Tensor |
12102 | at::Tensor special_digamma::call(const at::Tensor & self) { |
12103 | |
12104 | static auto op = create_special_digamma_typed_handle(); |
12105 | return op.call(self); |
12106 | } |
12107 | |
12108 | // aten::special_digamma(Tensor self) -> Tensor |
12109 | at::Tensor special_digamma::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
12110 | |
12111 | static auto op = create_special_digamma_typed_handle(); |
12112 | return op.redispatch(dispatchKeySet, self); |
12113 | } |
12114 | |
12115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_digamma_out, name, "aten::special_digamma" ) |
12116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_digamma_out, overload_name, "out" ) |
12117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_digamma_out, schema_str, "special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
12118 | |
12119 | // aten::special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
12120 | static C10_NOINLINE c10::TypedOperatorHandle<special_digamma_out::schema> create_special_digamma_out_typed_handle() { |
12121 | return c10::Dispatcher::singleton() |
12122 | .findSchemaOrThrow(special_digamma_out::name, special_digamma_out::overload_name) |
12123 | .typed<special_digamma_out::schema>(); |
12124 | } |
12125 | |
12126 | // aten::special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
12127 | at::Tensor & special_digamma_out::call(const at::Tensor & self, at::Tensor & out) { |
12128 | |
12129 | static auto op = create_special_digamma_out_typed_handle(); |
12130 | return op.call(self, out); |
12131 | } |
12132 | |
12133 | // aten::special_digamma.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
12134 | at::Tensor & special_digamma_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
12135 | |
12136 | static auto op = create_special_digamma_out_typed_handle(); |
12137 | return op.redispatch(dispatchKeySet, self, out); |
12138 | } |
12139 | |
12140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtr, name, "aten::special_ndtr" ) |
12141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtr, overload_name, "" ) |
12142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtr, schema_str, "special_ndtr(Tensor self) -> Tensor" ) |
12143 | |
12144 | // aten::special_ndtr(Tensor self) -> Tensor |
12145 | static C10_NOINLINE c10::TypedOperatorHandle<special_ndtr::schema> create_special_ndtr_typed_handle() { |
12146 | return c10::Dispatcher::singleton() |
12147 | .findSchemaOrThrow(special_ndtr::name, special_ndtr::overload_name) |
12148 | .typed<special_ndtr::schema>(); |
12149 | } |
12150 | |
12151 | // aten::special_ndtr(Tensor self) -> Tensor |
12152 | at::Tensor special_ndtr::call(const at::Tensor & self) { |
12153 | |
12154 | static auto op = create_special_ndtr_typed_handle(); |
12155 | return op.call(self); |
12156 | } |
12157 | |
12158 | // aten::special_ndtr(Tensor self) -> Tensor |
12159 | at::Tensor special_ndtr::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
12160 | |
12161 | static auto op = create_special_ndtr_typed_handle(); |
12162 | return op.redispatch(dispatchKeySet, self); |
12163 | } |
12164 | |
12165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtr_out, name, "aten::special_ndtr" ) |
12166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtr_out, overload_name, "out" ) |
12167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_ndtr_out, schema_str, "special_ndtr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
12168 | |
12169 | // aten::special_ndtr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
12170 | static C10_NOINLINE c10::TypedOperatorHandle<special_ndtr_out::schema> create_special_ndtr_out_typed_handle() { |
12171 | return c10::Dispatcher::singleton() |
12172 | .findSchemaOrThrow(special_ndtr_out::name, special_ndtr_out::overload_name) |
12173 | .typed<special_ndtr_out::schema>(); |
12174 | } |
12175 | |
12176 | // aten::special_ndtr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
12177 | at::Tensor & special_ndtr_out::call(const at::Tensor & self, at::Tensor & out) { |
12178 | |
12179 | static auto op = create_special_ndtr_out_typed_handle(); |
12180 | return op.call(self, out); |
12181 | } |
12182 | |
12183 | // aten::special_ndtr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
12184 | at::Tensor & special_ndtr_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
12185 | |
12186 | static auto op = create_special_ndtr_out_typed_handle(); |
12187 | return op.redispatch(dispatchKeySet, self, out); |
12188 | } |
12189 | |
12190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta, name, "aten::special_zeta" ) |
12191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta, overload_name, "" ) |
12192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta, schema_str, "special_zeta(Tensor self, Tensor other) -> Tensor" ) |
12193 | |
12194 | // aten::special_zeta(Tensor self, Tensor other) -> Tensor |
12195 | static C10_NOINLINE c10::TypedOperatorHandle<special_zeta::schema> create_special_zeta_typed_handle() { |
12196 | return c10::Dispatcher::singleton() |
12197 | .findSchemaOrThrow(special_zeta::name, special_zeta::overload_name) |
12198 | .typed<special_zeta::schema>(); |
12199 | } |
12200 | |
12201 | // aten::special_zeta(Tensor self, Tensor other) -> Tensor |
12202 | at::Tensor special_zeta::call(const at::Tensor & self, const at::Tensor & other) { |
12203 | |
12204 | static auto op = create_special_zeta_typed_handle(); |
12205 | return op.call(self, other); |
12206 | } |
12207 | |
12208 | // aten::special_zeta(Tensor self, Tensor other) -> Tensor |
12209 | at::Tensor special_zeta::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other) { |
12210 | |
12211 | static auto op = create_special_zeta_typed_handle(); |
12212 | return op.redispatch(dispatchKeySet, self, other); |
12213 | } |
12214 | |
12215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_self_scalar, name, "aten::special_zeta" ) |
12216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_self_scalar, overload_name, "self_scalar" ) |
12217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_self_scalar, schema_str, "special_zeta.self_scalar(Scalar self, Tensor other) -> Tensor" ) |
12218 | |
12219 | // aten::special_zeta.self_scalar(Scalar self, Tensor other) -> Tensor |
12220 | static C10_NOINLINE c10::TypedOperatorHandle<special_zeta_self_scalar::schema> create_special_zeta_self_scalar_typed_handle() { |
12221 | return c10::Dispatcher::singleton() |
12222 | .findSchemaOrThrow(special_zeta_self_scalar::name, special_zeta_self_scalar::overload_name) |
12223 | .typed<special_zeta_self_scalar::schema>(); |
12224 | } |
12225 | |
12226 | // aten::special_zeta.self_scalar(Scalar self, Tensor other) -> Tensor |
12227 | at::Tensor special_zeta_self_scalar::call(const at::Scalar & self, const at::Tensor & other) { |
12228 | |
12229 | static auto op = create_special_zeta_self_scalar_typed_handle(); |
12230 | return op.call(self, other); |
12231 | } |
12232 | |
12233 | // aten::special_zeta.self_scalar(Scalar self, Tensor other) -> Tensor |
12234 | at::Tensor special_zeta_self_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other) { |
12235 | |
12236 | static auto op = create_special_zeta_self_scalar_typed_handle(); |
12237 | return op.redispatch(dispatchKeySet, self, other); |
12238 | } |
12239 | |
12240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_other_scalar, name, "aten::special_zeta" ) |
12241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_other_scalar, overload_name, "other_scalar" ) |
12242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_other_scalar, schema_str, "special_zeta.other_scalar(Tensor self, Scalar other) -> Tensor" ) |
12243 | |
12244 | // aten::special_zeta.other_scalar(Tensor self, Scalar other) -> Tensor |
12245 | static C10_NOINLINE c10::TypedOperatorHandle<special_zeta_other_scalar::schema> create_special_zeta_other_scalar_typed_handle() { |
12246 | return c10::Dispatcher::singleton() |
12247 | .findSchemaOrThrow(special_zeta_other_scalar::name, special_zeta_other_scalar::overload_name) |
12248 | .typed<special_zeta_other_scalar::schema>(); |
12249 | } |
12250 | |
12251 | // aten::special_zeta.other_scalar(Tensor self, Scalar other) -> Tensor |
12252 | at::Tensor special_zeta_other_scalar::call(const at::Tensor & self, const at::Scalar & other) { |
12253 | |
12254 | static auto op = create_special_zeta_other_scalar_typed_handle(); |
12255 | return op.call(self, other); |
12256 | } |
12257 | |
12258 | // aten::special_zeta.other_scalar(Tensor self, Scalar other) -> Tensor |
12259 | at::Tensor special_zeta_other_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other) { |
12260 | |
12261 | static auto op = create_special_zeta_other_scalar_typed_handle(); |
12262 | return op.redispatch(dispatchKeySet, self, other); |
12263 | } |
12264 | |
12265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_out, name, "aten::special_zeta" ) |
12266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_out, overload_name, "out" ) |
12267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_out, schema_str, "special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
12268 | |
12269 | // aten::special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
12270 | static C10_NOINLINE c10::TypedOperatorHandle<special_zeta_out::schema> create_special_zeta_out_typed_handle() { |
12271 | return c10::Dispatcher::singleton() |
12272 | .findSchemaOrThrow(special_zeta_out::name, special_zeta_out::overload_name) |
12273 | .typed<special_zeta_out::schema>(); |
12274 | } |
12275 | |
12276 | // aten::special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
12277 | at::Tensor & special_zeta_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
12278 | |
12279 | static auto op = create_special_zeta_out_typed_handle(); |
12280 | return op.call(self, other, out); |
12281 | } |
12282 | |
12283 | // aten::special_zeta.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
12284 | at::Tensor & special_zeta_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
12285 | |
12286 | static auto op = create_special_zeta_out_typed_handle(); |
12287 | return op.redispatch(dispatchKeySet, self, other, out); |
12288 | } |
12289 | |
12290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_self_scalar_out, name, "aten::special_zeta" ) |
12291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_self_scalar_out, overload_name, "self_scalar_out" ) |
12292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_self_scalar_out, schema_str, "special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
12293 | |
12294 | // aten::special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
12295 | static C10_NOINLINE c10::TypedOperatorHandle<special_zeta_self_scalar_out::schema> create_special_zeta_self_scalar_out_typed_handle() { |
12296 | return c10::Dispatcher::singleton() |
12297 | .findSchemaOrThrow(special_zeta_self_scalar_out::name, special_zeta_self_scalar_out::overload_name) |
12298 | .typed<special_zeta_self_scalar_out::schema>(); |
12299 | } |
12300 | |
12301 | // aten::special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
12302 | at::Tensor & special_zeta_self_scalar_out::call(const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
12303 | |
12304 | static auto op = create_special_zeta_self_scalar_out_typed_handle(); |
12305 | return op.call(self, other, out); |
12306 | } |
12307 | |
12308 | // aten::special_zeta.self_scalar_out(Scalar self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
12309 | at::Tensor & special_zeta_self_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & self, const at::Tensor & other, at::Tensor & out) { |
12310 | |
12311 | static auto op = create_special_zeta_self_scalar_out_typed_handle(); |
12312 | return op.redispatch(dispatchKeySet, self, other, out); |
12313 | } |
12314 | |
12315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_other_scalar_out, name, "aten::special_zeta" ) |
12316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_other_scalar_out, overload_name, "other_scalar_out" ) |
12317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_zeta_other_scalar_out, schema_str, "special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!)" ) |
12318 | |
12319 | // aten::special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
12320 | static C10_NOINLINE c10::TypedOperatorHandle<special_zeta_other_scalar_out::schema> create_special_zeta_other_scalar_out_typed_handle() { |
12321 | return c10::Dispatcher::singleton() |
12322 | .findSchemaOrThrow(special_zeta_other_scalar_out::name, special_zeta_other_scalar_out::overload_name) |
12323 | .typed<special_zeta_other_scalar_out::schema>(); |
12324 | } |
12325 | |
12326 | // aten::special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
12327 | at::Tensor & special_zeta_other_scalar_out::call(const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
12328 | |
12329 | static auto op = create_special_zeta_other_scalar_out_typed_handle(); |
12330 | return op.call(self, other, out); |
12331 | } |
12332 | |
12333 | // aten::special_zeta.other_scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) |
12334 | at::Tensor & special_zeta_other_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, at::Tensor & out) { |
12335 | |
12336 | static auto op = create_special_zeta_other_scalar_out_typed_handle(); |
12337 | return op.redispatch(dispatchKeySet, self, other, out); |
12338 | } |
12339 | |
12340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_round, name, "aten::special_round" ) |
12341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_round, overload_name, "" ) |
12342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_round, schema_str, "special_round(Tensor self, *, int decimals=0) -> Tensor" ) |
12343 | |
12344 | // aten::special_round(Tensor self, *, int decimals=0) -> Tensor |
12345 | static C10_NOINLINE c10::TypedOperatorHandle<special_round::schema> create_special_round_typed_handle() { |
12346 | return c10::Dispatcher::singleton() |
12347 | .findSchemaOrThrow(special_round::name, special_round::overload_name) |
12348 | .typed<special_round::schema>(); |
12349 | } |
12350 | |
12351 | // aten::special_round(Tensor self, *, int decimals=0) -> Tensor |
12352 | at::Tensor special_round::call(const at::Tensor & self, int64_t decimals) { |
12353 | |
12354 | static auto op = create_special_round_typed_handle(); |
12355 | return op.call(self, decimals); |
12356 | } |
12357 | |
12358 | // aten::special_round(Tensor self, *, int decimals=0) -> Tensor |
12359 | at::Tensor special_round::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t decimals) { |
12360 | |
12361 | static auto op = create_special_round_typed_handle(); |
12362 | return op.redispatch(dispatchKeySet, self, decimals); |
12363 | } |
12364 | |
12365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_round_out, name, "aten::special_round" ) |
12366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_round_out, overload_name, "out" ) |
12367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_round_out, schema_str, "special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!)" ) |
12368 | |
12369 | // aten::special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!) |
12370 | static C10_NOINLINE c10::TypedOperatorHandle<special_round_out::schema> create_special_round_out_typed_handle() { |
12371 | return c10::Dispatcher::singleton() |
12372 | .findSchemaOrThrow(special_round_out::name, special_round_out::overload_name) |
12373 | .typed<special_round_out::schema>(); |
12374 | } |
12375 | |
12376 | // aten::special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!) |
12377 | at::Tensor & special_round_out::call(const at::Tensor & self, int64_t decimals, at::Tensor & out) { |
12378 | |
12379 | static auto op = create_special_round_out_typed_handle(); |
12380 | return op.call(self, decimals, out); |
12381 | } |
12382 | |
12383 | // aten::special_round.out(Tensor self, *, int decimals=0, Tensor(a!) out) -> Tensor(a!) |
12384 | at::Tensor & special_round_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t decimals, at::Tensor & out) { |
12385 | |
12386 | static auto op = create_special_round_out_typed_handle(); |
12387 | return op.redispatch(dispatchKeySet, self, decimals, out); |
12388 | } |
12389 | |
12390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifft, name, "aten::fft_ifft" ) |
12391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifft, overload_name, "" ) |
12392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifft, schema_str, "fft_ifft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor" ) |
12393 | |
12394 | // aten::fft_ifft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12395 | static C10_NOINLINE c10::TypedOperatorHandle<fft_ifft::schema> create_fft_ifft_typed_handle() { |
12396 | return c10::Dispatcher::singleton() |
12397 | .findSchemaOrThrow(fft_ifft::name, fft_ifft::overload_name) |
12398 | .typed<fft_ifft::schema>(); |
12399 | } |
12400 | |
12401 | // aten::fft_ifft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12402 | at::Tensor fft_ifft::call(const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm) { |
12403 | |
12404 | static auto op = create_fft_ifft_typed_handle(); |
12405 | return op.call(self, n, dim, norm); |
12406 | } |
12407 | |
12408 | // aten::fft_ifft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12409 | at::Tensor fft_ifft::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm) { |
12410 | |
12411 | static auto op = create_fft_ifft_typed_handle(); |
12412 | return op.redispatch(dispatchKeySet, self, n, dim, norm); |
12413 | } |
12414 | |
12415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifft_out, name, "aten::fft_ifft" ) |
12416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifft_out, overload_name, "out" ) |
12417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifft_out, schema_str, "fft_ifft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
12418 | |
12419 | // aten::fft_ifft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12420 | static C10_NOINLINE c10::TypedOperatorHandle<fft_ifft_out::schema> create_fft_ifft_out_typed_handle() { |
12421 | return c10::Dispatcher::singleton() |
12422 | .findSchemaOrThrow(fft_ifft_out::name, fft_ifft_out::overload_name) |
12423 | .typed<fft_ifft_out::schema>(); |
12424 | } |
12425 | |
12426 | // aten::fft_ifft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12427 | at::Tensor & fft_ifft_out::call(const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12428 | |
12429 | static auto op = create_fft_ifft_out_typed_handle(); |
12430 | return op.call(self, n, dim, norm, out); |
12431 | } |
12432 | |
12433 | // aten::fft_ifft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12434 | at::Tensor & fft_ifft_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12435 | |
12436 | static auto op = create_fft_ifft_out_typed_handle(); |
12437 | return op.redispatch(dispatchKeySet, self, n, dim, norm, out); |
12438 | } |
12439 | |
12440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfft, name, "aten::fft_hfft" ) |
12441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfft, overload_name, "" ) |
12442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfft, schema_str, "fft_hfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor" ) |
12443 | |
12444 | // aten::fft_hfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12445 | static C10_NOINLINE c10::TypedOperatorHandle<fft_hfft::schema> create_fft_hfft_typed_handle() { |
12446 | return c10::Dispatcher::singleton() |
12447 | .findSchemaOrThrow(fft_hfft::name, fft_hfft::overload_name) |
12448 | .typed<fft_hfft::schema>(); |
12449 | } |
12450 | |
12451 | // aten::fft_hfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12452 | at::Tensor fft_hfft::call(const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm) { |
12453 | |
12454 | static auto op = create_fft_hfft_typed_handle(); |
12455 | return op.call(self, n, dim, norm); |
12456 | } |
12457 | |
12458 | // aten::fft_hfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12459 | at::Tensor fft_hfft::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm) { |
12460 | |
12461 | static auto op = create_fft_hfft_typed_handle(); |
12462 | return op.redispatch(dispatchKeySet, self, n, dim, norm); |
12463 | } |
12464 | |
12465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfft_out, name, "aten::fft_hfft" ) |
12466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfft_out, overload_name, "out" ) |
12467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_hfft_out, schema_str, "fft_hfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
12468 | |
12469 | // aten::fft_hfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12470 | static C10_NOINLINE c10::TypedOperatorHandle<fft_hfft_out::schema> create_fft_hfft_out_typed_handle() { |
12471 | return c10::Dispatcher::singleton() |
12472 | .findSchemaOrThrow(fft_hfft_out::name, fft_hfft_out::overload_name) |
12473 | .typed<fft_hfft_out::schema>(); |
12474 | } |
12475 | |
12476 | // aten::fft_hfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12477 | at::Tensor & fft_hfft_out::call(const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12478 | |
12479 | static auto op = create_fft_hfft_out_typed_handle(); |
12480 | return op.call(self, n, dim, norm, out); |
12481 | } |
12482 | |
12483 | // aten::fft_hfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12484 | at::Tensor & fft_hfft_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12485 | |
12486 | static auto op = create_fft_hfft_out_typed_handle(); |
12487 | return op.redispatch(dispatchKeySet, self, n, dim, norm, out); |
12488 | } |
12489 | |
12490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft, name, "aten::fft_ihfft" ) |
12491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft, overload_name, "" ) |
12492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft, schema_str, "fft_ihfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor" ) |
12493 | |
12494 | // aten::fft_ihfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12495 | static C10_NOINLINE c10::TypedOperatorHandle<fft_ihfft::schema> create_fft_ihfft_typed_handle() { |
12496 | return c10::Dispatcher::singleton() |
12497 | .findSchemaOrThrow(fft_ihfft::name, fft_ihfft::overload_name) |
12498 | .typed<fft_ihfft::schema>(); |
12499 | } |
12500 | |
12501 | // aten::fft_ihfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12502 | at::Tensor fft_ihfft::call(const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm) { |
12503 | |
12504 | static auto op = create_fft_ihfft_typed_handle(); |
12505 | return op.call(self, n, dim, norm); |
12506 | } |
12507 | |
12508 | // aten::fft_ihfft(Tensor self, int? n=None, int dim=-1, str? norm=None) -> Tensor |
12509 | at::Tensor fft_ihfft::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm) { |
12510 | |
12511 | static auto op = create_fft_ihfft_typed_handle(); |
12512 | return op.redispatch(dispatchKeySet, self, n, dim, norm); |
12513 | } |
12514 | |
12515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft_out, name, "aten::fft_ihfft" ) |
12516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft_out, overload_name, "out" ) |
12517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft_out, schema_str, "fft_ihfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
12518 | |
12519 | // aten::fft_ihfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12520 | static C10_NOINLINE c10::TypedOperatorHandle<fft_ihfft_out::schema> create_fft_ihfft_out_typed_handle() { |
12521 | return c10::Dispatcher::singleton() |
12522 | .findSchemaOrThrow(fft_ihfft_out::name, fft_ihfft_out::overload_name) |
12523 | .typed<fft_ihfft_out::schema>(); |
12524 | } |
12525 | |
12526 | // aten::fft_ihfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12527 | at::Tensor & fft_ihfft_out::call(const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12528 | |
12529 | static auto op = create_fft_ihfft_out_typed_handle(); |
12530 | return op.call(self, n, dim, norm, out); |
12531 | } |
12532 | |
12533 | // aten::fft_ihfft.out(Tensor self, int? n=None, int dim=-1, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12534 | at::Tensor & fft_ihfft_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> n, int64_t dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12535 | |
12536 | static auto op = create_fft_ihfft_out_typed_handle(); |
12537 | return op.redispatch(dispatchKeySet, self, n, dim, norm, out); |
12538 | } |
12539 | |
12540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft2, name, "aten::fft_ihfft2" ) |
12541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft2, overload_name, "" ) |
12542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft2, schema_str, "fft_ihfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor" ) |
12543 | |
12544 | // aten::fft_ihfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
12545 | static C10_NOINLINE c10::TypedOperatorHandle<fft_ihfft2::schema> create_fft_ihfft2_typed_handle() { |
12546 | return c10::Dispatcher::singleton() |
12547 | .findSchemaOrThrow(fft_ihfft2::name, fft_ihfft2::overload_name) |
12548 | .typed<fft_ihfft2::schema>(); |
12549 | } |
12550 | |
12551 | // aten::fft_ihfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
12552 | at::Tensor fft_ihfft2::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm) { |
12553 | |
12554 | static auto op = create_fft_ihfft2_typed_handle(); |
12555 | return op.call(self, s, dim, norm); |
12556 | } |
12557 | |
12558 | // aten::fft_ihfft2(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None) -> Tensor |
12559 | at::Tensor fft_ihfft2::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm) { |
12560 | |
12561 | static auto op = create_fft_ihfft2_typed_handle(); |
12562 | return op.redispatch(dispatchKeySet, self, s, dim, norm); |
12563 | } |
12564 | |
12565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft2_out, name, "aten::fft_ihfft2" ) |
12566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft2_out, overload_name, "out" ) |
12567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ihfft2_out, schema_str, "fft_ihfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
12568 | |
12569 | // aten::fft_ihfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12570 | static C10_NOINLINE c10::TypedOperatorHandle<fft_ihfft2_out::schema> create_fft_ihfft2_out_typed_handle() { |
12571 | return c10::Dispatcher::singleton() |
12572 | .findSchemaOrThrow(fft_ihfft2_out::name, fft_ihfft2_out::overload_name) |
12573 | .typed<fft_ihfft2_out::schema>(); |
12574 | } |
12575 | |
12576 | // aten::fft_ihfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12577 | const at::Tensor & fft_ihfft2_out::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm, const at::Tensor & out) { |
12578 | |
12579 | static auto op = create_fft_ihfft2_out_typed_handle(); |
12580 | return op.call(self, s, dim, norm, out); |
12581 | } |
12582 | |
12583 | // aten::fft_ihfft2.out(Tensor self, int[1]? s=None, int[1] dim=[-2,-1], str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12584 | const at::Tensor & fft_ihfft2_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::IntArrayRef dim, c10::optional<c10::string_view> norm, const at::Tensor & out) { |
12585 | |
12586 | static auto op = create_fft_ihfft2_out_typed_handle(); |
12587 | return op.redispatch(dispatchKeySet, self, s, dim, norm, out); |
12588 | } |
12589 | |
12590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_irfftn, name, "aten::fft_irfftn" ) |
12591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_irfftn, overload_name, "" ) |
12592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_irfftn, schema_str, "fft_irfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor" ) |
12593 | |
12594 | // aten::fft_irfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
12595 | static C10_NOINLINE c10::TypedOperatorHandle<fft_irfftn::schema> create_fft_irfftn_typed_handle() { |
12596 | return c10::Dispatcher::singleton() |
12597 | .findSchemaOrThrow(fft_irfftn::name, fft_irfftn::overload_name) |
12598 | .typed<fft_irfftn::schema>(); |
12599 | } |
12600 | |
12601 | // aten::fft_irfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
12602 | at::Tensor fft_irfftn::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm) { |
12603 | |
12604 | static auto op = create_fft_irfftn_typed_handle(); |
12605 | return op.call(self, s, dim, norm); |
12606 | } |
12607 | |
12608 | // aten::fft_irfftn(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None) -> Tensor |
12609 | at::Tensor fft_irfftn::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm) { |
12610 | |
12611 | static auto op = create_fft_irfftn_typed_handle(); |
12612 | return op.redispatch(dispatchKeySet, self, s, dim, norm); |
12613 | } |
12614 | |
12615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_irfftn_out, name, "aten::fft_irfftn" ) |
12616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_irfftn_out, overload_name, "out" ) |
12617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_irfftn_out, schema_str, "fft_irfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
12618 | |
12619 | // aten::fft_irfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12620 | static C10_NOINLINE c10::TypedOperatorHandle<fft_irfftn_out::schema> create_fft_irfftn_out_typed_handle() { |
12621 | return c10::Dispatcher::singleton() |
12622 | .findSchemaOrThrow(fft_irfftn_out::name, fft_irfftn_out::overload_name) |
12623 | .typed<fft_irfftn_out::schema>(); |
12624 | } |
12625 | |
12626 | // aten::fft_irfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12627 | at::Tensor & fft_irfftn_out::call(const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12628 | |
12629 | static auto op = create_fft_irfftn_out_typed_handle(); |
12630 | return op.call(self, s, dim, norm, out); |
12631 | } |
12632 | |
12633 | // aten::fft_irfftn.out(Tensor self, int[1]? s=None, int[1]? dim=None, str? norm=None, *, Tensor(a!) out) -> Tensor(a!) |
12634 | at::Tensor & fft_irfftn_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef s, at::OptionalIntArrayRef dim, c10::optional<c10::string_view> norm, at::Tensor & out) { |
12635 | |
12636 | static auto op = create_fft_irfftn_out_typed_handle(); |
12637 | return op.redispatch(dispatchKeySet, self, s, dim, norm, out); |
12638 | } |
12639 | |
12640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifftshift, name, "aten::fft_ifftshift" ) |
12641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifftshift, overload_name, "" ) |
12642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fft_ifftshift, schema_str, "fft_ifftshift(Tensor self, int[1]? dim=None) -> Tensor" ) |
12643 | |
12644 | // aten::fft_ifftshift(Tensor self, int[1]? dim=None) -> Tensor |
12645 | static C10_NOINLINE c10::TypedOperatorHandle<fft_ifftshift::schema> create_fft_ifftshift_typed_handle() { |
12646 | return c10::Dispatcher::singleton() |
12647 | .findSchemaOrThrow(fft_ifftshift::name, fft_ifftshift::overload_name) |
12648 | .typed<fft_ifftshift::schema>(); |
12649 | } |
12650 | |
12651 | // aten::fft_ifftshift(Tensor self, int[1]? dim=None) -> Tensor |
12652 | at::Tensor fft_ifftshift::call(const at::Tensor & self, at::OptionalIntArrayRef dim) { |
12653 | |
12654 | static auto op = create_fft_ifftshift_typed_handle(); |
12655 | return op.call(self, dim); |
12656 | } |
12657 | |
12658 | // aten::fft_ifftshift(Tensor self, int[1]? dim=None) -> Tensor |
12659 | at::Tensor fft_ifftshift::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim) { |
12660 | |
12661 | static auto op = create_fft_ifftshift_typed_handle(); |
12662 | return op.redispatch(dispatchKeySet, self, dim); |
12663 | } |
12664 | |
12665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slogdet, name, "aten::slogdet" ) |
12666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slogdet, overload_name, "" ) |
12667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slogdet, schema_str, "slogdet(Tensor self) -> (Tensor sign, Tensor logabsdet)" ) |
12668 | |
12669 | // aten::slogdet(Tensor self) -> (Tensor sign, Tensor logabsdet) |
12670 | static C10_NOINLINE c10::TypedOperatorHandle<slogdet::schema> create_slogdet_typed_handle() { |
12671 | return c10::Dispatcher::singleton() |
12672 | .findSchemaOrThrow(slogdet::name, slogdet::overload_name) |
12673 | .typed<slogdet::schema>(); |
12674 | } |
12675 | |
12676 | // aten::slogdet(Tensor self) -> (Tensor sign, Tensor logabsdet) |
12677 | ::std::tuple<at::Tensor,at::Tensor> slogdet::call(const at::Tensor & self) { |
12678 | |
12679 | static auto op = create_slogdet_typed_handle(); |
12680 | return op.call(self); |
12681 | } |
12682 | |
12683 | // aten::slogdet(Tensor self) -> (Tensor sign, Tensor logabsdet) |
12684 | ::std::tuple<at::Tensor,at::Tensor> slogdet::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
12685 | |
12686 | static auto op = create_slogdet_typed_handle(); |
12687 | return op.redispatch(dispatchKeySet, self); |
12688 | } |
12689 | |
12690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slogdet_out, name, "aten::slogdet" ) |
12691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slogdet_out, overload_name, "out" ) |
12692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slogdet_out, schema_str, "slogdet.out(Tensor self, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet)" ) |
12693 | |
12694 | // aten::slogdet.out(Tensor self, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet) |
12695 | static C10_NOINLINE c10::TypedOperatorHandle<slogdet_out::schema> create_slogdet_out_typed_handle() { |
12696 | return c10::Dispatcher::singleton() |
12697 | .findSchemaOrThrow(slogdet_out::name, slogdet_out::overload_name) |
12698 | .typed<slogdet_out::schema>(); |
12699 | } |
12700 | |
12701 | // aten::slogdet.out(Tensor self, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet) |
12702 | ::std::tuple<at::Tensor &,at::Tensor &> slogdet_out::call(const at::Tensor & self, at::Tensor & sign, at::Tensor & logabsdet) { |
12703 | |
12704 | static auto op = create_slogdet_out_typed_handle(); |
12705 | return op.call(self, sign, logabsdet); |
12706 | } |
12707 | |
12708 | // aten::slogdet.out(Tensor self, *, Tensor(a!) sign, Tensor(b!) logabsdet) -> (Tensor(a!) sign, Tensor(b!) logabsdet) |
12709 | ::std::tuple<at::Tensor &,at::Tensor &> slogdet_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & sign, at::Tensor & logabsdet) { |
12710 | |
12711 | static auto op = create_slogdet_out_typed_handle(); |
12712 | return op.redispatch(dispatchKeySet, self, sign, logabsdet); |
12713 | } |
12714 | |
12715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eig, name, "aten::linalg_eig" ) |
12716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eig, overload_name, "" ) |
12717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eig, schema_str, "linalg_eig(Tensor self) -> (Tensor eigenvalues, Tensor eigenvectors)" ) |
12718 | |
12719 | // aten::linalg_eig(Tensor self) -> (Tensor eigenvalues, Tensor eigenvectors) |
12720 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_eig::schema> create_linalg_eig_typed_handle() { |
12721 | return c10::Dispatcher::singleton() |
12722 | .findSchemaOrThrow(linalg_eig::name, linalg_eig::overload_name) |
12723 | .typed<linalg_eig::schema>(); |
12724 | } |
12725 | |
12726 | // aten::linalg_eig(Tensor self) -> (Tensor eigenvalues, Tensor eigenvectors) |
12727 | ::std::tuple<at::Tensor,at::Tensor> linalg_eig::call(const at::Tensor & self) { |
12728 | |
12729 | static auto op = create_linalg_eig_typed_handle(); |
12730 | return op.call(self); |
12731 | } |
12732 | |
12733 | // aten::linalg_eig(Tensor self) -> (Tensor eigenvalues, Tensor eigenvectors) |
12734 | ::std::tuple<at::Tensor,at::Tensor> linalg_eig::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
12735 | |
12736 | static auto op = create_linalg_eig_typed_handle(); |
12737 | return op.redispatch(dispatchKeySet, self); |
12738 | } |
12739 | |
12740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eig_out, name, "aten::linalg_eig" ) |
12741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eig_out, overload_name, "out" ) |
12742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eig_out, schema_str, "linalg_eig.out(Tensor self, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors)" ) |
12743 | |
12744 | // aten::linalg_eig.out(Tensor self, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
12745 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_eig_out::schema> create_linalg_eig_out_typed_handle() { |
12746 | return c10::Dispatcher::singleton() |
12747 | .findSchemaOrThrow(linalg_eig_out::name, linalg_eig_out::overload_name) |
12748 | .typed<linalg_eig_out::schema>(); |
12749 | } |
12750 | |
12751 | // aten::linalg_eig.out(Tensor self, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
12752 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_eig_out::call(const at::Tensor & self, at::Tensor & eigenvalues, at::Tensor & eigenvectors) { |
12753 | |
12754 | static auto op = create_linalg_eig_out_typed_handle(); |
12755 | return op.call(self, eigenvalues, eigenvectors); |
12756 | } |
12757 | |
12758 | // aten::linalg_eig.out(Tensor self, *, Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
12759 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_eig_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & eigenvalues, at::Tensor & eigenvectors) { |
12760 | |
12761 | static auto op = create_linalg_eig_out_typed_handle(); |
12762 | return op.redispatch(dispatchKeySet, self, eigenvalues, eigenvectors); |
12763 | } |
12764 | |
12765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigh, name, "aten::linalg_eigh" ) |
12766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigh, overload_name, "" ) |
12767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigh, schema_str, "linalg_eigh(Tensor self, str UPLO=\"L\") -> (Tensor eigenvalues, Tensor eigenvectors)" ) |
12768 | |
12769 | // aten::linalg_eigh(Tensor self, str UPLO="L") -> (Tensor eigenvalues, Tensor eigenvectors) |
12770 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_eigh::schema> create_linalg_eigh_typed_handle() { |
12771 | return c10::Dispatcher::singleton() |
12772 | .findSchemaOrThrow(linalg_eigh::name, linalg_eigh::overload_name) |
12773 | .typed<linalg_eigh::schema>(); |
12774 | } |
12775 | |
12776 | // aten::linalg_eigh(Tensor self, str UPLO="L") -> (Tensor eigenvalues, Tensor eigenvectors) |
12777 | ::std::tuple<at::Tensor,at::Tensor> linalg_eigh::call(const at::Tensor & self, c10::string_view UPLO) { |
12778 | |
12779 | static auto op = create_linalg_eigh_typed_handle(); |
12780 | return op.call(self, UPLO); |
12781 | } |
12782 | |
12783 | // aten::linalg_eigh(Tensor self, str UPLO="L") -> (Tensor eigenvalues, Tensor eigenvectors) |
12784 | ::std::tuple<at::Tensor,at::Tensor> linalg_eigh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO) { |
12785 | |
12786 | static auto op = create_linalg_eigh_typed_handle(); |
12787 | return op.redispatch(dispatchKeySet, self, UPLO); |
12788 | } |
12789 | |
12790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigh_eigvals, name, "aten::linalg_eigh" ) |
12791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigh_eigvals, overload_name, "eigvals" ) |
12792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigh_eigvals, schema_str, "linalg_eigh.eigvals(Tensor self, str UPLO=\"L\", *, Tensor(a!) eigvals, Tensor(b!) eigvecs) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors)" ) |
12793 | |
12794 | // aten::linalg_eigh.eigvals(Tensor self, str UPLO="L", *, Tensor(a!) eigvals, Tensor(b!) eigvecs) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
12795 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_eigh_eigvals::schema> create_linalg_eigh_eigvals_typed_handle() { |
12796 | return c10::Dispatcher::singleton() |
12797 | .findSchemaOrThrow(linalg_eigh_eigvals::name, linalg_eigh_eigvals::overload_name) |
12798 | .typed<linalg_eigh_eigvals::schema>(); |
12799 | } |
12800 | |
12801 | // aten::linalg_eigh.eigvals(Tensor self, str UPLO="L", *, Tensor(a!) eigvals, Tensor(b!) eigvecs) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
12802 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_eigh_eigvals::call(const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs) { |
12803 | |
12804 | static auto op = create_linalg_eigh_eigvals_typed_handle(); |
12805 | return op.call(self, UPLO, eigvals, eigvecs); |
12806 | } |
12807 | |
12808 | // aten::linalg_eigh.eigvals(Tensor self, str UPLO="L", *, Tensor(a!) eigvals, Tensor(b!) eigvecs) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) |
12809 | ::std::tuple<at::Tensor &,at::Tensor &> linalg_eigh_eigvals::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO, at::Tensor & eigvals, at::Tensor & eigvecs) { |
12810 | |
12811 | static auto op = create_linalg_eigh_eigvals_typed_handle(); |
12812 | return op.redispatch(dispatchKeySet, self, UPLO, eigvals, eigvecs); |
12813 | } |
12814 | |
12815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigvalsh, name, "aten::linalg_eigvalsh" ) |
12816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigvalsh, overload_name, "" ) |
12817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigvalsh, schema_str, "linalg_eigvalsh(Tensor self, str UPLO=\"L\") -> Tensor" ) |
12818 | |
12819 | // aten::linalg_eigvalsh(Tensor self, str UPLO="L") -> Tensor |
12820 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_eigvalsh::schema> create_linalg_eigvalsh_typed_handle() { |
12821 | return c10::Dispatcher::singleton() |
12822 | .findSchemaOrThrow(linalg_eigvalsh::name, linalg_eigvalsh::overload_name) |
12823 | .typed<linalg_eigvalsh::schema>(); |
12824 | } |
12825 | |
12826 | // aten::linalg_eigvalsh(Tensor self, str UPLO="L") -> Tensor |
12827 | at::Tensor linalg_eigvalsh::call(const at::Tensor & self, c10::string_view UPLO) { |
12828 | |
12829 | static auto op = create_linalg_eigvalsh_typed_handle(); |
12830 | return op.call(self, UPLO); |
12831 | } |
12832 | |
12833 | // aten::linalg_eigvalsh(Tensor self, str UPLO="L") -> Tensor |
12834 | at::Tensor linalg_eigvalsh::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO) { |
12835 | |
12836 | static auto op = create_linalg_eigvalsh_typed_handle(); |
12837 | return op.redispatch(dispatchKeySet, self, UPLO); |
12838 | } |
12839 | |
12840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigvalsh_out, name, "aten::linalg_eigvalsh" ) |
12841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigvalsh_out, overload_name, "out" ) |
12842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_eigvalsh_out, schema_str, "linalg_eigvalsh.out(Tensor self, str UPLO=\"L\", *, Tensor(a!) out) -> Tensor(a!)" ) |
12843 | |
12844 | // aten::linalg_eigvalsh.out(Tensor self, str UPLO="L", *, Tensor(a!) out) -> Tensor(a!) |
12845 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_eigvalsh_out::schema> create_linalg_eigvalsh_out_typed_handle() { |
12846 | return c10::Dispatcher::singleton() |
12847 | .findSchemaOrThrow(linalg_eigvalsh_out::name, linalg_eigvalsh_out::overload_name) |
12848 | .typed<linalg_eigvalsh_out::schema>(); |
12849 | } |
12850 | |
12851 | // aten::linalg_eigvalsh.out(Tensor self, str UPLO="L", *, Tensor(a!) out) -> Tensor(a!) |
12852 | at::Tensor & linalg_eigvalsh_out::call(const at::Tensor & self, c10::string_view UPLO, at::Tensor & out) { |
12853 | |
12854 | static auto op = create_linalg_eigvalsh_out_typed_handle(); |
12855 | return op.call(self, UPLO, out); |
12856 | } |
12857 | |
12858 | // aten::linalg_eigvalsh.out(Tensor self, str UPLO="L", *, Tensor(a!) out) -> Tensor(a!) |
12859 | at::Tensor & linalg_eigvalsh_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view UPLO, at::Tensor & out) { |
12860 | |
12861 | static auto op = create_linalg_eigvalsh_out_typed_handle(); |
12862 | return op.redispatch(dispatchKeySet, self, UPLO, out); |
12863 | } |
12864 | |
12865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_householder_product, name, "aten::linalg_householder_product" ) |
12866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_householder_product, overload_name, "" ) |
12867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_householder_product, schema_str, "linalg_householder_product(Tensor input, Tensor tau) -> Tensor" ) |
12868 | |
12869 | // aten::linalg_householder_product(Tensor input, Tensor tau) -> Tensor |
12870 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_householder_product::schema> create_linalg_householder_product_typed_handle() { |
12871 | return c10::Dispatcher::singleton() |
12872 | .findSchemaOrThrow(linalg_householder_product::name, linalg_householder_product::overload_name) |
12873 | .typed<linalg_householder_product::schema>(); |
12874 | } |
12875 | |
12876 | // aten::linalg_householder_product(Tensor input, Tensor tau) -> Tensor |
12877 | at::Tensor linalg_householder_product::call(const at::Tensor & input, const at::Tensor & tau) { |
12878 | |
12879 | static auto op = create_linalg_householder_product_typed_handle(); |
12880 | return op.call(input, tau); |
12881 | } |
12882 | |
12883 | // aten::linalg_householder_product(Tensor input, Tensor tau) -> Tensor |
12884 | at::Tensor linalg_householder_product::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & tau) { |
12885 | |
12886 | static auto op = create_linalg_householder_product_typed_handle(); |
12887 | return op.redispatch(dispatchKeySet, input, tau); |
12888 | } |
12889 | |
12890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_householder_product_out, name, "aten::linalg_householder_product" ) |
12891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_householder_product_out, overload_name, "out" ) |
12892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_householder_product_out, schema_str, "linalg_householder_product.out(Tensor input, Tensor tau, *, Tensor(a!) out) -> Tensor(a!)" ) |
12893 | |
12894 | // aten::linalg_householder_product.out(Tensor input, Tensor tau, *, Tensor(a!) out) -> Tensor(a!) |
12895 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_householder_product_out::schema> create_linalg_householder_product_out_typed_handle() { |
12896 | return c10::Dispatcher::singleton() |
12897 | .findSchemaOrThrow(linalg_householder_product_out::name, linalg_householder_product_out::overload_name) |
12898 | .typed<linalg_householder_product_out::schema>(); |
12899 | } |
12900 | |
12901 | // aten::linalg_householder_product.out(Tensor input, Tensor tau, *, Tensor(a!) out) -> Tensor(a!) |
12902 | at::Tensor & linalg_householder_product_out::call(const at::Tensor & input, const at::Tensor & tau, at::Tensor & out) { |
12903 | |
12904 | static auto op = create_linalg_householder_product_out_typed_handle(); |
12905 | return op.call(input, tau, out); |
12906 | } |
12907 | |
12908 | // aten::linalg_householder_product.out(Tensor input, Tensor tau, *, Tensor(a!) out) -> Tensor(a!) |
12909 | at::Tensor & linalg_householder_product_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & tau, at::Tensor & out) { |
12910 | |
12911 | static auto op = create_linalg_householder_product_out_typed_handle(); |
12912 | return op.redispatch(dispatchKeySet, input, tau, out); |
12913 | } |
12914 | |
12915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm, name, "aten::linalg_matrix_norm" ) |
12916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm, overload_name, "" ) |
12917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm, schema_str, "linalg_matrix_norm(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor" ) |
12918 | |
12919 | // aten::linalg_matrix_norm(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
12920 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_norm::schema> create_linalg_matrix_norm_typed_handle() { |
12921 | return c10::Dispatcher::singleton() |
12922 | .findSchemaOrThrow(linalg_matrix_norm::name, linalg_matrix_norm::overload_name) |
12923 | .typed<linalg_matrix_norm::schema>(); |
12924 | } |
12925 | |
12926 | // aten::linalg_matrix_norm(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
12927 | at::Tensor linalg_matrix_norm::call(const at::Tensor & self, const at::Scalar & ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
12928 | |
12929 | static auto op = create_linalg_matrix_norm_typed_handle(); |
12930 | return op.call(self, ord, dim, keepdim, dtype); |
12931 | } |
12932 | |
12933 | // aten::linalg_matrix_norm(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
12934 | at::Tensor linalg_matrix_norm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
12935 | |
12936 | static auto op = create_linalg_matrix_norm_typed_handle(); |
12937 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype); |
12938 | } |
12939 | |
12940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_out, name, "aten::linalg_matrix_norm" ) |
12941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_out, overload_name, "out" ) |
12942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_out, schema_str, "linalg_matrix_norm.out(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)" ) |
12943 | |
12944 | // aten::linalg_matrix_norm.out(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
12945 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_norm_out::schema> create_linalg_matrix_norm_out_typed_handle() { |
12946 | return c10::Dispatcher::singleton() |
12947 | .findSchemaOrThrow(linalg_matrix_norm_out::name, linalg_matrix_norm_out::overload_name) |
12948 | .typed<linalg_matrix_norm_out::schema>(); |
12949 | } |
12950 | |
12951 | // aten::linalg_matrix_norm.out(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
12952 | at::Tensor & linalg_matrix_norm_out::call(const at::Tensor & self, const at::Scalar & ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
12953 | |
12954 | static auto op = create_linalg_matrix_norm_out_typed_handle(); |
12955 | return op.call(self, ord, dim, keepdim, dtype, out); |
12956 | } |
12957 | |
12958 | // aten::linalg_matrix_norm.out(Tensor self, Scalar ord, int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
12959 | at::Tensor & linalg_matrix_norm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
12960 | |
12961 | static auto op = create_linalg_matrix_norm_out_typed_handle(); |
12962 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype, out); |
12963 | } |
12964 | |
12965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_str_ord, name, "aten::linalg_matrix_norm" ) |
12966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_str_ord, overload_name, "str_ord" ) |
12967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_str_ord, schema_str, "linalg_matrix_norm.str_ord(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor" ) |
12968 | |
12969 | // aten::linalg_matrix_norm.str_ord(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
12970 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_norm_str_ord::schema> create_linalg_matrix_norm_str_ord_typed_handle() { |
12971 | return c10::Dispatcher::singleton() |
12972 | .findSchemaOrThrow(linalg_matrix_norm_str_ord::name, linalg_matrix_norm_str_ord::overload_name) |
12973 | .typed<linalg_matrix_norm_str_ord::schema>(); |
12974 | } |
12975 | |
12976 | // aten::linalg_matrix_norm.str_ord(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
12977 | at::Tensor linalg_matrix_norm_str_ord::call(const at::Tensor & self, c10::string_view ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
12978 | |
12979 | static auto op = create_linalg_matrix_norm_str_ord_typed_handle(); |
12980 | return op.call(self, ord, dim, keepdim, dtype); |
12981 | } |
12982 | |
12983 | // aten::linalg_matrix_norm.str_ord(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None) -> Tensor |
12984 | at::Tensor linalg_matrix_norm_str_ord::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype) { |
12985 | |
12986 | static auto op = create_linalg_matrix_norm_str_ord_typed_handle(); |
12987 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype); |
12988 | } |
12989 | |
12990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_str_ord_out, name, "aten::linalg_matrix_norm" ) |
12991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_str_ord_out, overload_name, "str_ord_out" ) |
12992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_matrix_norm_str_ord_out, schema_str, "linalg_matrix_norm.str_ord_out(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)" ) |
12993 | |
12994 | // aten::linalg_matrix_norm.str_ord_out(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
12995 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_matrix_norm_str_ord_out::schema> create_linalg_matrix_norm_str_ord_out_typed_handle() { |
12996 | return c10::Dispatcher::singleton() |
12997 | .findSchemaOrThrow(linalg_matrix_norm_str_ord_out::name, linalg_matrix_norm_str_ord_out::overload_name) |
12998 | .typed<linalg_matrix_norm_str_ord_out::schema>(); |
12999 | } |
13000 | |
13001 | // aten::linalg_matrix_norm.str_ord_out(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
13002 | at::Tensor & linalg_matrix_norm_str_ord_out::call(const at::Tensor & self, c10::string_view ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
13003 | |
13004 | static auto op = create_linalg_matrix_norm_str_ord_out_typed_handle(); |
13005 | return op.call(self, ord, dim, keepdim, dtype, out); |
13006 | } |
13007 | |
13008 | // aten::linalg_matrix_norm.str_ord_out(Tensor self, str ord='fro', int[] dim=[-2,-1], bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
13009 | at::Tensor & linalg_matrix_norm_str_ord_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::string_view ord, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
13010 | |
13011 | static auto op = create_linalg_matrix_norm_str_ord_out_typed_handle(); |
13012 | return op.redispatch(dispatchKeySet, self, ord, dim, keepdim, dtype, out); |
13013 | } |
13014 | |
13015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svd, name, "aten::linalg_svd" ) |
13016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svd, overload_name, "" ) |
13017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svd, schema_str, "linalg_svd(Tensor A, bool full_matrices=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh)" ) |
13018 | |
13019 | // aten::linalg_svd(Tensor A, bool full_matrices=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh) |
13020 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_svd::schema> create_linalg_svd_typed_handle() { |
13021 | return c10::Dispatcher::singleton() |
13022 | .findSchemaOrThrow(linalg_svd::name, linalg_svd::overload_name) |
13023 | .typed<linalg_svd::schema>(); |
13024 | } |
13025 | |
13026 | // aten::linalg_svd(Tensor A, bool full_matrices=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh) |
13027 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> linalg_svd::call(const at::Tensor & A, bool full_matrices, c10::optional<c10::string_view> driver) { |
13028 | |
13029 | static auto op = create_linalg_svd_typed_handle(); |
13030 | return op.call(A, full_matrices, driver); |
13031 | } |
13032 | |
13033 | // aten::linalg_svd(Tensor A, bool full_matrices=True, *, str? driver=None) -> (Tensor U, Tensor S, Tensor Vh) |
13034 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor> linalg_svd::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool full_matrices, c10::optional<c10::string_view> driver) { |
13035 | |
13036 | static auto op = create_linalg_svd_typed_handle(); |
13037 | return op.redispatch(dispatchKeySet, A, full_matrices, driver); |
13038 | } |
13039 | |
13040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svd_U, name, "aten::linalg_svd" ) |
13041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svd_U, overload_name, "U" ) |
13042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(linalg_svd_U, schema_str, "linalg_svd.U(Tensor A, bool full_matrices=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh)" ) |
13043 | |
13044 | // aten::linalg_svd.U(Tensor A, bool full_matrices=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) |
13045 | static C10_NOINLINE c10::TypedOperatorHandle<linalg_svd_U::schema> create_linalg_svd_U_typed_handle() { |
13046 | return c10::Dispatcher::singleton() |
13047 | .findSchemaOrThrow(linalg_svd_U::name, linalg_svd_U::overload_name) |
13048 | .typed<linalg_svd_U::schema>(); |
13049 | } |
13050 | |
13051 | // aten::linalg_svd.U(Tensor A, bool full_matrices=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) |
13052 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> linalg_svd_U::call(const at::Tensor & A, bool full_matrices, c10::optional<c10::string_view> driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh) { |
13053 | |
13054 | static auto op = create_linalg_svd_U_typed_handle(); |
13055 | return op.call(A, full_matrices, driver, U, S, Vh); |
13056 | } |
13057 | |
13058 | // aten::linalg_svd.U(Tensor A, bool full_matrices=True, *, str? driver=None, Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) Vh) |
13059 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> linalg_svd_U::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & A, bool full_matrices, c10::optional<c10::string_view> driver, at::Tensor & U, at::Tensor & S, at::Tensor & Vh) { |
13060 | |
13061 | static auto op = create_linalg_svd_U_typed_handle(); |
13062 | return op.redispatch(dispatchKeySet, A, full_matrices, driver, U, S, Vh); |
13063 | } |
13064 | |
13065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_floatlist, name, "aten::_test_optional_floatlist" ) |
13066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_floatlist, overload_name, "" ) |
13067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_floatlist, schema_str, "_test_optional_floatlist(Tensor values, float[]? addends) -> Tensor" ) |
13068 | |
13069 | // aten::_test_optional_floatlist(Tensor values, float[]? addends) -> Tensor |
13070 | static C10_NOINLINE c10::TypedOperatorHandle<_test_optional_floatlist::schema> create__test_optional_floatlist_typed_handle() { |
13071 | return c10::Dispatcher::singleton() |
13072 | .findSchemaOrThrow(_test_optional_floatlist::name, _test_optional_floatlist::overload_name) |
13073 | .typed<_test_optional_floatlist::schema>(); |
13074 | } |
13075 | |
13076 | // aten::_test_optional_floatlist(Tensor values, float[]? addends) -> Tensor |
13077 | at::Tensor _test_optional_floatlist::call(const at::Tensor & values, c10::optional<at::ArrayRef<double>> addends) { |
13078 | |
13079 | static auto op = create__test_optional_floatlist_typed_handle(); |
13080 | return op.call(values, addends); |
13081 | } |
13082 | |
13083 | // aten::_test_optional_floatlist(Tensor values, float[]? addends) -> Tensor |
13084 | at::Tensor _test_optional_floatlist::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & values, c10::optional<at::ArrayRef<double>> addends) { |
13085 | |
13086 | static auto op = create__test_optional_floatlist_typed_handle(); |
13087 | return op.redispatch(dispatchKeySet, values, addends); |
13088 | } |
13089 | |
13090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_dense_tensors, name, "aten::unflatten_dense_tensors" ) |
13091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_dense_tensors, overload_name, "" ) |
13092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unflatten_dense_tensors, schema_str, "unflatten_dense_tensors(Tensor flat, Tensor[] tensors) -> Tensor[]" ) |
13093 | |
13094 | // aten::unflatten_dense_tensors(Tensor flat, Tensor[] tensors) -> Tensor[] |
13095 | static C10_NOINLINE c10::TypedOperatorHandle<unflatten_dense_tensors::schema> create_unflatten_dense_tensors_typed_handle() { |
13096 | return c10::Dispatcher::singleton() |
13097 | .findSchemaOrThrow(unflatten_dense_tensors::name, unflatten_dense_tensors::overload_name) |
13098 | .typed<unflatten_dense_tensors::schema>(); |
13099 | } |
13100 | |
13101 | // aten::unflatten_dense_tensors(Tensor flat, Tensor[] tensors) -> Tensor[] |
13102 | ::std::vector<at::Tensor> unflatten_dense_tensors::call(const at::Tensor & flat, at::TensorList tensors) { |
13103 | |
13104 | static auto op = create_unflatten_dense_tensors_typed_handle(); |
13105 | return op.call(flat, tensors); |
13106 | } |
13107 | |
13108 | // aten::unflatten_dense_tensors(Tensor flat, Tensor[] tensors) -> Tensor[] |
13109 | ::std::vector<at::Tensor> unflatten_dense_tensors::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & flat, at::TensorList tensors) { |
13110 | |
13111 | static auto op = create_unflatten_dense_tensors_typed_handle(); |
13112 | return op.redispatch(dispatchKeySet, flat, tensors); |
13113 | } |
13114 | |
13115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_tensor_list, name, "aten::_nested_tensor_from_tensor_list" ) |
13116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_tensor_list, overload_name, "" ) |
13117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_tensor_list, schema_str, "_nested_tensor_from_tensor_list(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor" ) |
13118 | |
13119 | // aten::_nested_tensor_from_tensor_list(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
13120 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_from_tensor_list::schema> create__nested_tensor_from_tensor_list_typed_handle() { |
13121 | return c10::Dispatcher::singleton() |
13122 | .findSchemaOrThrow(_nested_tensor_from_tensor_list::name, _nested_tensor_from_tensor_list::overload_name) |
13123 | .typed<_nested_tensor_from_tensor_list::schema>(); |
13124 | } |
13125 | |
13126 | // aten::_nested_tensor_from_tensor_list(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
13127 | at::Tensor _nested_tensor_from_tensor_list::call(at::TensorList list, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
13128 | |
13129 | static auto op = create__nested_tensor_from_tensor_list_typed_handle(); |
13130 | return op.call(list, dtype, layout, device, pin_memory); |
13131 | } |
13132 | |
13133 | // aten::_nested_tensor_from_tensor_list(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor |
13134 | at::Tensor _nested_tensor_from_tensor_list::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList list, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory) { |
13135 | |
13136 | static auto op = create__nested_tensor_from_tensor_list_typed_handle(); |
13137 | return op.redispatch(dispatchKeySet, list, dtype, layout, device, pin_memory); |
13138 | } |
13139 | |
13140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_broadcast_to_copy, name, "aten::_sparse_broadcast_to_copy" ) |
13141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_broadcast_to_copy, overload_name, "" ) |
13142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_broadcast_to_copy, schema_str, "_sparse_broadcast_to_copy(Tensor self, int[] size) -> Tensor" ) |
13143 | |
13144 | // aten::_sparse_broadcast_to_copy(Tensor self, int[] size) -> Tensor |
13145 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_broadcast_to_copy::schema> create__sparse_broadcast_to_copy_typed_handle() { |
13146 | return c10::Dispatcher::singleton() |
13147 | .findSchemaOrThrow(_sparse_broadcast_to_copy::name, _sparse_broadcast_to_copy::overload_name) |
13148 | .typed<_sparse_broadcast_to_copy::schema>(); |
13149 | } |
13150 | |
13151 | // aten::_sparse_broadcast_to_copy(Tensor self, int[] size) -> Tensor |
13152 | at::Tensor _sparse_broadcast_to_copy::call(const at::Tensor & self, at::IntArrayRef size) { |
13153 | |
13154 | static auto op = create__sparse_broadcast_to_copy_typed_handle(); |
13155 | return op.call(self, size); |
13156 | } |
13157 | |
13158 | // aten::_sparse_broadcast_to_copy(Tensor self, int[] size) -> Tensor |
13159 | at::Tensor _sparse_broadcast_to_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size) { |
13160 | |
13161 | static auto op = create__sparse_broadcast_to_copy_typed_handle(); |
13162 | return op.redispatch(dispatchKeySet, self, size); |
13163 | } |
13164 | |
13165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(transpose_copy_int, name, "aten::transpose_copy" ) |
13166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(transpose_copy_int, overload_name, "int" ) |
13167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(transpose_copy_int, schema_str, "transpose_copy.int(Tensor self, int dim0, int dim1) -> Tensor" ) |
13168 | |
13169 | // aten::transpose_copy.int(Tensor self, int dim0, int dim1) -> Tensor |
13170 | static C10_NOINLINE c10::TypedOperatorHandle<transpose_copy_int::schema> create_transpose_copy_int_typed_handle() { |
13171 | return c10::Dispatcher::singleton() |
13172 | .findSchemaOrThrow(transpose_copy_int::name, transpose_copy_int::overload_name) |
13173 | .typed<transpose_copy_int::schema>(); |
13174 | } |
13175 | |
13176 | // aten::transpose_copy.int(Tensor self, int dim0, int dim1) -> Tensor |
13177 | at::Tensor transpose_copy_int::call(const at::Tensor & self, int64_t dim0, int64_t dim1) { |
13178 | |
13179 | static auto op = create_transpose_copy_int_typed_handle(); |
13180 | return op.call(self, dim0, dim1); |
13181 | } |
13182 | |
13183 | // aten::transpose_copy.int(Tensor self, int dim0, int dim1) -> Tensor |
13184 | at::Tensor transpose_copy_int::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1) { |
13185 | |
13186 | static auto op = create_transpose_copy_int_typed_handle(); |
13187 | return op.redispatch(dispatchKeySet, self, dim0, dim1); |
13188 | } |
13189 | |
13190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_indices_copy, name, "aten::_indices_copy" ) |
13191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_indices_copy, overload_name, "" ) |
13192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_indices_copy, schema_str, "_indices_copy(Tensor self) -> Tensor" ) |
13193 | |
13194 | // aten::_indices_copy(Tensor self) -> Tensor |
13195 | static C10_NOINLINE c10::TypedOperatorHandle<_indices_copy::schema> create__indices_copy_typed_handle() { |
13196 | return c10::Dispatcher::singleton() |
13197 | .findSchemaOrThrow(_indices_copy::name, _indices_copy::overload_name) |
13198 | .typed<_indices_copy::schema>(); |
13199 | } |
13200 | |
13201 | // aten::_indices_copy(Tensor self) -> Tensor |
13202 | at::Tensor _indices_copy::call(const at::Tensor & self) { |
13203 | |
13204 | static auto op = create__indices_copy_typed_handle(); |
13205 | return op.call(self); |
13206 | } |
13207 | |
13208 | // aten::_indices_copy(Tensor self) -> Tensor |
13209 | at::Tensor _indices_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
13210 | |
13211 | static auto op = create__indices_copy_typed_handle(); |
13212 | return op.redispatch(dispatchKeySet, self); |
13213 | } |
13214 | |
13215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_values_copy, name, "aten::_values_copy" ) |
13216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_values_copy, overload_name, "" ) |
13217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_values_copy, schema_str, "_values_copy(Tensor self) -> Tensor" ) |
13218 | |
13219 | // aten::_values_copy(Tensor self) -> Tensor |
13220 | static C10_NOINLINE c10::TypedOperatorHandle<_values_copy::schema> create__values_copy_typed_handle() { |
13221 | return c10::Dispatcher::singleton() |
13222 | .findSchemaOrThrow(_values_copy::name, _values_copy::overload_name) |
13223 | .typed<_values_copy::schema>(); |
13224 | } |
13225 | |
13226 | // aten::_values_copy(Tensor self) -> Tensor |
13227 | at::Tensor _values_copy::call(const at::Tensor & self) { |
13228 | |
13229 | static auto op = create__values_copy_typed_handle(); |
13230 | return op.call(self); |
13231 | } |
13232 | |
13233 | // aten::_values_copy(Tensor self) -> Tensor |
13234 | at::Tensor _values_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
13235 | |
13236 | static auto op = create__values_copy_typed_handle(); |
13237 | return op.redispatch(dispatchKeySet, self); |
13238 | } |
13239 | |
13240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values_copy, name, "aten::values_copy" ) |
13241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values_copy, overload_name, "" ) |
13242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values_copy, schema_str, "values_copy(Tensor self) -> Tensor" ) |
13243 | |
13244 | // aten::values_copy(Tensor self) -> Tensor |
13245 | static C10_NOINLINE c10::TypedOperatorHandle<values_copy::schema> create_values_copy_typed_handle() { |
13246 | return c10::Dispatcher::singleton() |
13247 | .findSchemaOrThrow(values_copy::name, values_copy::overload_name) |
13248 | .typed<values_copy::schema>(); |
13249 | } |
13250 | |
13251 | // aten::values_copy(Tensor self) -> Tensor |
13252 | at::Tensor values_copy::call(const at::Tensor & self) { |
13253 | |
13254 | static auto op = create_values_copy_typed_handle(); |
13255 | return op.call(self); |
13256 | } |
13257 | |
13258 | // aten::values_copy(Tensor self) -> Tensor |
13259 | at::Tensor values_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
13260 | |
13261 | static auto op = create_values_copy_typed_handle(); |
13262 | return op.redispatch(dispatchKeySet, self); |
13263 | } |
13264 | |
13265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy, name, "aten::view_copy" ) |
13266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy, overload_name, "" ) |
13267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy, schema_str, "view_copy(Tensor self, SymInt[] size) -> Tensor" ) |
13268 | |
13269 | // aten::view_copy(Tensor self, SymInt[] size) -> Tensor |
13270 | static C10_NOINLINE c10::TypedOperatorHandle<view_copy::schema> create_view_copy_typed_handle() { |
13271 | return c10::Dispatcher::singleton() |
13272 | .findSchemaOrThrow(view_copy::name, view_copy::overload_name) |
13273 | .typed<view_copy::schema>(); |
13274 | } |
13275 | |
13276 | // aten::view_copy(Tensor self, SymInt[] size) -> Tensor |
13277 | at::Tensor view_copy::call(const at::Tensor & self, c10::SymIntArrayRef size) { |
13278 | |
13279 | static auto op = create_view_copy_typed_handle(); |
13280 | return op.call(self, size); |
13281 | } |
13282 | |
13283 | // aten::view_copy(Tensor self, SymInt[] size) -> Tensor |
13284 | at::Tensor view_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size) { |
13285 | |
13286 | static auto op = create_view_copy_typed_handle(); |
13287 | return op.redispatch(dispatchKeySet, self, size); |
13288 | } |
13289 | |
13290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_dtype, name, "aten::view_copy" ) |
13291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_dtype, overload_name, "dtype" ) |
13292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_dtype, schema_str, "view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor" ) |
13293 | |
13294 | // aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor |
13295 | static C10_NOINLINE c10::TypedOperatorHandle<view_copy_dtype::schema> create_view_copy_dtype_typed_handle() { |
13296 | return c10::Dispatcher::singleton() |
13297 | .findSchemaOrThrow(view_copy_dtype::name, view_copy_dtype::overload_name) |
13298 | .typed<view_copy_dtype::schema>(); |
13299 | } |
13300 | |
13301 | // aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor |
13302 | at::Tensor view_copy_dtype::call(const at::Tensor & self, at::ScalarType dtype) { |
13303 | |
13304 | static auto op = create_view_copy_dtype_typed_handle(); |
13305 | return op.call(self, dtype); |
13306 | } |
13307 | |
13308 | // aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor |
13309 | at::Tensor view_copy_dtype::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype) { |
13310 | |
13311 | static auto op = create_view_copy_dtype_typed_handle(); |
13312 | return op.redispatch(dispatchKeySet, self, dtype); |
13313 | } |
13314 | |
13315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold_copy, name, "aten::unfold_copy" ) |
13316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold_copy, overload_name, "" ) |
13317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold_copy, schema_str, "unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor" ) |
13318 | |
13319 | // aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor |
13320 | static C10_NOINLINE c10::TypedOperatorHandle<unfold_copy::schema> create_unfold_copy_typed_handle() { |
13321 | return c10::Dispatcher::singleton() |
13322 | .findSchemaOrThrow(unfold_copy::name, unfold_copy::overload_name) |
13323 | .typed<unfold_copy::schema>(); |
13324 | } |
13325 | |
13326 | // aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor |
13327 | at::Tensor unfold_copy::call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) { |
13328 | |
13329 | static auto op = create_unfold_copy_typed_handle(); |
13330 | return op.call(self, dimension, size, step); |
13331 | } |
13332 | |
13333 | // aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor |
13334 | at::Tensor unfold_copy::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step) { |
13335 | |
13336 | static auto op = create_unfold_copy_typed_handle(); |
13337 | return op.redispatch(dispatchKeySet, self, dimension, size, step); |
13338 | } |
13339 | |
13340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scaled_dot_product_attention, name, "aten::scaled_dot_product_attention" ) |
13341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scaled_dot_product_attention, overload_name, "" ) |
13342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scaled_dot_product_attention, schema_str, "scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor" ) |
13343 | |
13344 | // aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor |
13345 | static C10_NOINLINE c10::TypedOperatorHandle<scaled_dot_product_attention::schema> create_scaled_dot_product_attention_typed_handle() { |
13346 | return c10::Dispatcher::singleton() |
13347 | .findSchemaOrThrow(scaled_dot_product_attention::name, scaled_dot_product_attention::overload_name) |
13348 | .typed<scaled_dot_product_attention::schema>(); |
13349 | } |
13350 | |
13351 | // aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor |
13352 | at::Tensor scaled_dot_product_attention::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) { |
13353 | |
13354 | static auto op = create_scaled_dot_product_attention_typed_handle(); |
13355 | return op.call(query, key, value, attn_mask, dropout_p, is_causal); |
13356 | } |
13357 | |
13358 | // aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor |
13359 | at::Tensor scaled_dot_product_attention::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) { |
13360 | |
13361 | static auto op = create_scaled_dot_product_attention_typed_handle(); |
13362 | return op.redispatch(dispatchKeySet, query, key, value, attn_mask, dropout_p, is_causal); |
13363 | } |
13364 | |
13365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_decoder_only_multi_head_attention, name, "aten::_native_decoder_only_multi_head_attention" ) |
13366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_decoder_only_multi_head_attention, overload_name, "" ) |
13367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_decoder_only_multi_head_attention, schema_str, "_native_decoder_only_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True) -> (Tensor, Tensor, Tensor, Tensor)" ) |
13368 | |
13369 | // aten::_native_decoder_only_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True) -> (Tensor, Tensor, Tensor, Tensor) |
13370 | static C10_NOINLINE c10::TypedOperatorHandle<_native_decoder_only_multi_head_attention::schema> create__native_decoder_only_multi_head_attention_typed_handle() { |
13371 | return c10::Dispatcher::singleton() |
13372 | .findSchemaOrThrow(_native_decoder_only_multi_head_attention::name, _native_decoder_only_multi_head_attention::overload_name) |
13373 | .typed<_native_decoder_only_multi_head_attention::schema>(); |
13374 | } |
13375 | |
13376 | // aten::_native_decoder_only_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True) -> (Tensor, Tensor, Tensor, Tensor) |
13377 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _native_decoder_only_multi_head_attention::call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, const c10::optional<at::Tensor> & incr_key, const c10::optional<at::Tensor> & incr_value, bool need_weights, bool average_attn_weights) { |
13378 | |
13379 | static auto op = create__native_decoder_only_multi_head_attention_typed_handle(); |
13380 | return op.call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, incr_key, incr_value, need_weights, average_attn_weights); |
13381 | } |
13382 | |
13383 | // aten::_native_decoder_only_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True) -> (Tensor, Tensor, Tensor, Tensor) |
13384 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor> _native_decoder_only_multi_head_attention::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, const c10::optional<at::Tensor> & incr_key, const c10::optional<at::Tensor> & incr_value, bool need_weights, bool average_attn_weights) { |
13385 | |
13386 | static auto op = create__native_decoder_only_multi_head_attention_typed_handle(); |
13387 | return op.redispatch(dispatchKeySet, query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, incr_key, incr_value, need_weights, average_attn_weights); |
13388 | } |
13389 | |
13390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y1, name, "aten::special_bessel_y1" ) |
13391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y1, overload_name, "" ) |
13392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y1, schema_str, "special_bessel_y1(Tensor self) -> Tensor" ) |
13393 | |
13394 | // aten::special_bessel_y1(Tensor self) -> Tensor |
13395 | static C10_NOINLINE c10::TypedOperatorHandle<special_bessel_y1::schema> create_special_bessel_y1_typed_handle() { |
13396 | return c10::Dispatcher::singleton() |
13397 | .findSchemaOrThrow(special_bessel_y1::name, special_bessel_y1::overload_name) |
13398 | .typed<special_bessel_y1::schema>(); |
13399 | } |
13400 | |
13401 | // aten::special_bessel_y1(Tensor self) -> Tensor |
13402 | at::Tensor special_bessel_y1::call(const at::Tensor & self) { |
13403 | |
13404 | static auto op = create_special_bessel_y1_typed_handle(); |
13405 | return op.call(self); |
13406 | } |
13407 | |
13408 | // aten::special_bessel_y1(Tensor self) -> Tensor |
13409 | at::Tensor special_bessel_y1::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
13410 | |
13411 | static auto op = create_special_bessel_y1_typed_handle(); |
13412 | return op.redispatch(dispatchKeySet, self); |
13413 | } |
13414 | |
13415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y1_out, name, "aten::special_bessel_y1" ) |
13416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y1_out, overload_name, "out" ) |
13417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_bessel_y1_out, schema_str, "special_bessel_y1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
13418 | |
13419 | // aten::special_bessel_y1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
13420 | static C10_NOINLINE c10::TypedOperatorHandle<special_bessel_y1_out::schema> create_special_bessel_y1_out_typed_handle() { |
13421 | return c10::Dispatcher::singleton() |
13422 | .findSchemaOrThrow(special_bessel_y1_out::name, special_bessel_y1_out::overload_name) |
13423 | .typed<special_bessel_y1_out::schema>(); |
13424 | } |
13425 | |
13426 | // aten::special_bessel_y1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
13427 | at::Tensor & special_bessel_y1_out::call(const at::Tensor & self, at::Tensor & out) { |
13428 | |
13429 | static auto op = create_special_bessel_y1_out_typed_handle(); |
13430 | return op.call(self, out); |
13431 | } |
13432 | |
13433 | // aten::special_bessel_y1.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
13434 | at::Tensor & special_bessel_y1_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
13435 | |
13436 | static auto op = create_special_bessel_y1_out_typed_handle(); |
13437 | return op.redispatch(dispatchKeySet, self, out); |
13438 | } |
13439 | |
13440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l, name, "aten::special_laguerre_polynomial_l" ) |
13441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l, overload_name, "" ) |
13442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l, schema_str, "special_laguerre_polynomial_l(Tensor x, Tensor n) -> Tensor" ) |
13443 | |
13444 | // aten::special_laguerre_polynomial_l(Tensor x, Tensor n) -> Tensor |
13445 | static C10_NOINLINE c10::TypedOperatorHandle<special_laguerre_polynomial_l::schema> create_special_laguerre_polynomial_l_typed_handle() { |
13446 | return c10::Dispatcher::singleton() |
13447 | .findSchemaOrThrow(special_laguerre_polynomial_l::name, special_laguerre_polynomial_l::overload_name) |
13448 | .typed<special_laguerre_polynomial_l::schema>(); |
13449 | } |
13450 | |
13451 | // aten::special_laguerre_polynomial_l(Tensor x, Tensor n) -> Tensor |
13452 | at::Tensor special_laguerre_polynomial_l::call(const at::Tensor & x, const at::Tensor & n) { |
13453 | |
13454 | static auto op = create_special_laguerre_polynomial_l_typed_handle(); |
13455 | return op.call(x, n); |
13456 | } |
13457 | |
13458 | // aten::special_laguerre_polynomial_l(Tensor x, Tensor n) -> Tensor |
13459 | at::Tensor special_laguerre_polynomial_l::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
13460 | |
13461 | static auto op = create_special_laguerre_polynomial_l_typed_handle(); |
13462 | return op.redispatch(dispatchKeySet, x, n); |
13463 | } |
13464 | |
13465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_x_scalar, name, "aten::special_laguerre_polynomial_l" ) |
13466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_x_scalar, overload_name, "x_scalar" ) |
13467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_x_scalar, schema_str, "special_laguerre_polynomial_l.x_scalar(Scalar x, Tensor n) -> Tensor" ) |
13468 | |
13469 | // aten::special_laguerre_polynomial_l.x_scalar(Scalar x, Tensor n) -> Tensor |
13470 | static C10_NOINLINE c10::TypedOperatorHandle<special_laguerre_polynomial_l_x_scalar::schema> create_special_laguerre_polynomial_l_x_scalar_typed_handle() { |
13471 | return c10::Dispatcher::singleton() |
13472 | .findSchemaOrThrow(special_laguerre_polynomial_l_x_scalar::name, special_laguerre_polynomial_l_x_scalar::overload_name) |
13473 | .typed<special_laguerre_polynomial_l_x_scalar::schema>(); |
13474 | } |
13475 | |
13476 | // aten::special_laguerre_polynomial_l.x_scalar(Scalar x, Tensor n) -> Tensor |
13477 | at::Tensor special_laguerre_polynomial_l_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
13478 | |
13479 | static auto op = create_special_laguerre_polynomial_l_x_scalar_typed_handle(); |
13480 | return op.call(x, n); |
13481 | } |
13482 | |
13483 | // aten::special_laguerre_polynomial_l.x_scalar(Scalar x, Tensor n) -> Tensor |
13484 | at::Tensor special_laguerre_polynomial_l_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
13485 | |
13486 | static auto op = create_special_laguerre_polynomial_l_x_scalar_typed_handle(); |
13487 | return op.redispatch(dispatchKeySet, x, n); |
13488 | } |
13489 | |
13490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_n_scalar, name, "aten::special_laguerre_polynomial_l" ) |
13491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_n_scalar, overload_name, "n_scalar" ) |
13492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_n_scalar, schema_str, "special_laguerre_polynomial_l.n_scalar(Tensor x, Scalar n) -> Tensor" ) |
13493 | |
13494 | // aten::special_laguerre_polynomial_l.n_scalar(Tensor x, Scalar n) -> Tensor |
13495 | static C10_NOINLINE c10::TypedOperatorHandle<special_laguerre_polynomial_l_n_scalar::schema> create_special_laguerre_polynomial_l_n_scalar_typed_handle() { |
13496 | return c10::Dispatcher::singleton() |
13497 | .findSchemaOrThrow(special_laguerre_polynomial_l_n_scalar::name, special_laguerre_polynomial_l_n_scalar::overload_name) |
13498 | .typed<special_laguerre_polynomial_l_n_scalar::schema>(); |
13499 | } |
13500 | |
13501 | // aten::special_laguerre_polynomial_l.n_scalar(Tensor x, Scalar n) -> Tensor |
13502 | at::Tensor special_laguerre_polynomial_l_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
13503 | |
13504 | static auto op = create_special_laguerre_polynomial_l_n_scalar_typed_handle(); |
13505 | return op.call(x, n); |
13506 | } |
13507 | |
13508 | // aten::special_laguerre_polynomial_l.n_scalar(Tensor x, Scalar n) -> Tensor |
13509 | at::Tensor special_laguerre_polynomial_l_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
13510 | |
13511 | static auto op = create_special_laguerre_polynomial_l_n_scalar_typed_handle(); |
13512 | return op.redispatch(dispatchKeySet, x, n); |
13513 | } |
13514 | |
13515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_out, name, "aten::special_laguerre_polynomial_l" ) |
13516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_out, overload_name, "out" ) |
13517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_out, schema_str, "special_laguerre_polynomial_l.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13518 | |
13519 | // aten::special_laguerre_polynomial_l.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13520 | static C10_NOINLINE c10::TypedOperatorHandle<special_laguerre_polynomial_l_out::schema> create_special_laguerre_polynomial_l_out_typed_handle() { |
13521 | return c10::Dispatcher::singleton() |
13522 | .findSchemaOrThrow(special_laguerre_polynomial_l_out::name, special_laguerre_polynomial_l_out::overload_name) |
13523 | .typed<special_laguerre_polynomial_l_out::schema>(); |
13524 | } |
13525 | |
13526 | // aten::special_laguerre_polynomial_l.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13527 | at::Tensor & special_laguerre_polynomial_l_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
13528 | |
13529 | static auto op = create_special_laguerre_polynomial_l_out_typed_handle(); |
13530 | return op.call(x, n, out); |
13531 | } |
13532 | |
13533 | // aten::special_laguerre_polynomial_l.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13534 | at::Tensor & special_laguerre_polynomial_l_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
13535 | |
13536 | static auto op = create_special_laguerre_polynomial_l_out_typed_handle(); |
13537 | return op.redispatch(dispatchKeySet, x, n, out); |
13538 | } |
13539 | |
13540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_x_scalar_out, name, "aten::special_laguerre_polynomial_l" ) |
13541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_x_scalar_out, overload_name, "x_scalar_out" ) |
13542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_x_scalar_out, schema_str, "special_laguerre_polynomial_l.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13543 | |
13544 | // aten::special_laguerre_polynomial_l.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13545 | static C10_NOINLINE c10::TypedOperatorHandle<special_laguerre_polynomial_l_x_scalar_out::schema> create_special_laguerre_polynomial_l_x_scalar_out_typed_handle() { |
13546 | return c10::Dispatcher::singleton() |
13547 | .findSchemaOrThrow(special_laguerre_polynomial_l_x_scalar_out::name, special_laguerre_polynomial_l_x_scalar_out::overload_name) |
13548 | .typed<special_laguerre_polynomial_l_x_scalar_out::schema>(); |
13549 | } |
13550 | |
13551 | // aten::special_laguerre_polynomial_l.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13552 | at::Tensor & special_laguerre_polynomial_l_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
13553 | |
13554 | static auto op = create_special_laguerre_polynomial_l_x_scalar_out_typed_handle(); |
13555 | return op.call(x, n, out); |
13556 | } |
13557 | |
13558 | // aten::special_laguerre_polynomial_l.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13559 | at::Tensor & special_laguerre_polynomial_l_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
13560 | |
13561 | static auto op = create_special_laguerre_polynomial_l_x_scalar_out_typed_handle(); |
13562 | return op.redispatch(dispatchKeySet, x, n, out); |
13563 | } |
13564 | |
13565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_n_scalar_out, name, "aten::special_laguerre_polynomial_l" ) |
13566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_n_scalar_out, overload_name, "n_scalar_out" ) |
13567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_laguerre_polynomial_l_n_scalar_out, schema_str, "special_laguerre_polynomial_l.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13568 | |
13569 | // aten::special_laguerre_polynomial_l.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13570 | static C10_NOINLINE c10::TypedOperatorHandle<special_laguerre_polynomial_l_n_scalar_out::schema> create_special_laguerre_polynomial_l_n_scalar_out_typed_handle() { |
13571 | return c10::Dispatcher::singleton() |
13572 | .findSchemaOrThrow(special_laguerre_polynomial_l_n_scalar_out::name, special_laguerre_polynomial_l_n_scalar_out::overload_name) |
13573 | .typed<special_laguerre_polynomial_l_n_scalar_out::schema>(); |
13574 | } |
13575 | |
13576 | // aten::special_laguerre_polynomial_l.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13577 | at::Tensor & special_laguerre_polynomial_l_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
13578 | |
13579 | static auto op = create_special_laguerre_polynomial_l_n_scalar_out_typed_handle(); |
13580 | return op.call(x, n, out); |
13581 | } |
13582 | |
13583 | // aten::special_laguerre_polynomial_l.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13584 | at::Tensor & special_laguerre_polynomial_l_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
13585 | |
13586 | static auto op = create_special_laguerre_polynomial_l_n_scalar_out_typed_handle(); |
13587 | return op.redispatch(dispatchKeySet, x, n, out); |
13588 | } |
13589 | |
13590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p, name, "aten::special_legendre_polynomial_p" ) |
13591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p, overload_name, "" ) |
13592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p, schema_str, "special_legendre_polynomial_p(Tensor x, Tensor n) -> Tensor" ) |
13593 | |
13594 | // aten::special_legendre_polynomial_p(Tensor x, Tensor n) -> Tensor |
13595 | static C10_NOINLINE c10::TypedOperatorHandle<special_legendre_polynomial_p::schema> create_special_legendre_polynomial_p_typed_handle() { |
13596 | return c10::Dispatcher::singleton() |
13597 | .findSchemaOrThrow(special_legendre_polynomial_p::name, special_legendre_polynomial_p::overload_name) |
13598 | .typed<special_legendre_polynomial_p::schema>(); |
13599 | } |
13600 | |
13601 | // aten::special_legendre_polynomial_p(Tensor x, Tensor n) -> Tensor |
13602 | at::Tensor special_legendre_polynomial_p::call(const at::Tensor & x, const at::Tensor & n) { |
13603 | |
13604 | static auto op = create_special_legendre_polynomial_p_typed_handle(); |
13605 | return op.call(x, n); |
13606 | } |
13607 | |
13608 | // aten::special_legendre_polynomial_p(Tensor x, Tensor n) -> Tensor |
13609 | at::Tensor special_legendre_polynomial_p::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
13610 | |
13611 | static auto op = create_special_legendre_polynomial_p_typed_handle(); |
13612 | return op.redispatch(dispatchKeySet, x, n); |
13613 | } |
13614 | |
13615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_x_scalar, name, "aten::special_legendre_polynomial_p" ) |
13616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_x_scalar, overload_name, "x_scalar" ) |
13617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_x_scalar, schema_str, "special_legendre_polynomial_p.x_scalar(Scalar x, Tensor n) -> Tensor" ) |
13618 | |
13619 | // aten::special_legendre_polynomial_p.x_scalar(Scalar x, Tensor n) -> Tensor |
13620 | static C10_NOINLINE c10::TypedOperatorHandle<special_legendre_polynomial_p_x_scalar::schema> create_special_legendre_polynomial_p_x_scalar_typed_handle() { |
13621 | return c10::Dispatcher::singleton() |
13622 | .findSchemaOrThrow(special_legendre_polynomial_p_x_scalar::name, special_legendre_polynomial_p_x_scalar::overload_name) |
13623 | .typed<special_legendre_polynomial_p_x_scalar::schema>(); |
13624 | } |
13625 | |
13626 | // aten::special_legendre_polynomial_p.x_scalar(Scalar x, Tensor n) -> Tensor |
13627 | at::Tensor special_legendre_polynomial_p_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
13628 | |
13629 | static auto op = create_special_legendre_polynomial_p_x_scalar_typed_handle(); |
13630 | return op.call(x, n); |
13631 | } |
13632 | |
13633 | // aten::special_legendre_polynomial_p.x_scalar(Scalar x, Tensor n) -> Tensor |
13634 | at::Tensor special_legendre_polynomial_p_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
13635 | |
13636 | static auto op = create_special_legendre_polynomial_p_x_scalar_typed_handle(); |
13637 | return op.redispatch(dispatchKeySet, x, n); |
13638 | } |
13639 | |
13640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_n_scalar, name, "aten::special_legendre_polynomial_p" ) |
13641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_n_scalar, overload_name, "n_scalar" ) |
13642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_n_scalar, schema_str, "special_legendre_polynomial_p.n_scalar(Tensor x, Scalar n) -> Tensor" ) |
13643 | |
13644 | // aten::special_legendre_polynomial_p.n_scalar(Tensor x, Scalar n) -> Tensor |
13645 | static C10_NOINLINE c10::TypedOperatorHandle<special_legendre_polynomial_p_n_scalar::schema> create_special_legendre_polynomial_p_n_scalar_typed_handle() { |
13646 | return c10::Dispatcher::singleton() |
13647 | .findSchemaOrThrow(special_legendre_polynomial_p_n_scalar::name, special_legendre_polynomial_p_n_scalar::overload_name) |
13648 | .typed<special_legendre_polynomial_p_n_scalar::schema>(); |
13649 | } |
13650 | |
13651 | // aten::special_legendre_polynomial_p.n_scalar(Tensor x, Scalar n) -> Tensor |
13652 | at::Tensor special_legendre_polynomial_p_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
13653 | |
13654 | static auto op = create_special_legendre_polynomial_p_n_scalar_typed_handle(); |
13655 | return op.call(x, n); |
13656 | } |
13657 | |
13658 | // aten::special_legendre_polynomial_p.n_scalar(Tensor x, Scalar n) -> Tensor |
13659 | at::Tensor special_legendre_polynomial_p_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
13660 | |
13661 | static auto op = create_special_legendre_polynomial_p_n_scalar_typed_handle(); |
13662 | return op.redispatch(dispatchKeySet, x, n); |
13663 | } |
13664 | |
13665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_out, name, "aten::special_legendre_polynomial_p" ) |
13666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_out, overload_name, "out" ) |
13667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_out, schema_str, "special_legendre_polynomial_p.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13668 | |
13669 | // aten::special_legendre_polynomial_p.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13670 | static C10_NOINLINE c10::TypedOperatorHandle<special_legendre_polynomial_p_out::schema> create_special_legendre_polynomial_p_out_typed_handle() { |
13671 | return c10::Dispatcher::singleton() |
13672 | .findSchemaOrThrow(special_legendre_polynomial_p_out::name, special_legendre_polynomial_p_out::overload_name) |
13673 | .typed<special_legendre_polynomial_p_out::schema>(); |
13674 | } |
13675 | |
13676 | // aten::special_legendre_polynomial_p.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13677 | at::Tensor & special_legendre_polynomial_p_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
13678 | |
13679 | static auto op = create_special_legendre_polynomial_p_out_typed_handle(); |
13680 | return op.call(x, n, out); |
13681 | } |
13682 | |
13683 | // aten::special_legendre_polynomial_p.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13684 | at::Tensor & special_legendre_polynomial_p_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
13685 | |
13686 | static auto op = create_special_legendre_polynomial_p_out_typed_handle(); |
13687 | return op.redispatch(dispatchKeySet, x, n, out); |
13688 | } |
13689 | |
13690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_x_scalar_out, name, "aten::special_legendre_polynomial_p" ) |
13691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_x_scalar_out, overload_name, "x_scalar_out" ) |
13692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_x_scalar_out, schema_str, "special_legendre_polynomial_p.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13693 | |
13694 | // aten::special_legendre_polynomial_p.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13695 | static C10_NOINLINE c10::TypedOperatorHandle<special_legendre_polynomial_p_x_scalar_out::schema> create_special_legendre_polynomial_p_x_scalar_out_typed_handle() { |
13696 | return c10::Dispatcher::singleton() |
13697 | .findSchemaOrThrow(special_legendre_polynomial_p_x_scalar_out::name, special_legendre_polynomial_p_x_scalar_out::overload_name) |
13698 | .typed<special_legendre_polynomial_p_x_scalar_out::schema>(); |
13699 | } |
13700 | |
13701 | // aten::special_legendre_polynomial_p.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13702 | at::Tensor & special_legendre_polynomial_p_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
13703 | |
13704 | static auto op = create_special_legendre_polynomial_p_x_scalar_out_typed_handle(); |
13705 | return op.call(x, n, out); |
13706 | } |
13707 | |
13708 | // aten::special_legendre_polynomial_p.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13709 | at::Tensor & special_legendre_polynomial_p_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
13710 | |
13711 | static auto op = create_special_legendre_polynomial_p_x_scalar_out_typed_handle(); |
13712 | return op.redispatch(dispatchKeySet, x, n, out); |
13713 | } |
13714 | |
13715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_n_scalar_out, name, "aten::special_legendre_polynomial_p" ) |
13716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_n_scalar_out, overload_name, "n_scalar_out" ) |
13717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_legendre_polynomial_p_n_scalar_out, schema_str, "special_legendre_polynomial_p.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13718 | |
13719 | // aten::special_legendre_polynomial_p.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13720 | static C10_NOINLINE c10::TypedOperatorHandle<special_legendre_polynomial_p_n_scalar_out::schema> create_special_legendre_polynomial_p_n_scalar_out_typed_handle() { |
13721 | return c10::Dispatcher::singleton() |
13722 | .findSchemaOrThrow(special_legendre_polynomial_p_n_scalar_out::name, special_legendre_polynomial_p_n_scalar_out::overload_name) |
13723 | .typed<special_legendre_polynomial_p_n_scalar_out::schema>(); |
13724 | } |
13725 | |
13726 | // aten::special_legendre_polynomial_p.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13727 | at::Tensor & special_legendre_polynomial_p_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
13728 | |
13729 | static auto op = create_special_legendre_polynomial_p_n_scalar_out_typed_handle(); |
13730 | return op.call(x, n, out); |
13731 | } |
13732 | |
13733 | // aten::special_legendre_polynomial_p.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13734 | at::Tensor & special_legendre_polynomial_p_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
13735 | |
13736 | static auto op = create_special_legendre_polynomial_p_n_scalar_out_typed_handle(); |
13737 | return op.redispatch(dispatchKeySet, x, n, out); |
13738 | } |
13739 | |
13740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k0, name, "aten::special_scaled_modified_bessel_k0" ) |
13741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k0, overload_name, "" ) |
13742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k0, schema_str, "special_scaled_modified_bessel_k0(Tensor x) -> Tensor" ) |
13743 | |
13744 | // aten::special_scaled_modified_bessel_k0(Tensor x) -> Tensor |
13745 | static C10_NOINLINE c10::TypedOperatorHandle<special_scaled_modified_bessel_k0::schema> create_special_scaled_modified_bessel_k0_typed_handle() { |
13746 | return c10::Dispatcher::singleton() |
13747 | .findSchemaOrThrow(special_scaled_modified_bessel_k0::name, special_scaled_modified_bessel_k0::overload_name) |
13748 | .typed<special_scaled_modified_bessel_k0::schema>(); |
13749 | } |
13750 | |
13751 | // aten::special_scaled_modified_bessel_k0(Tensor x) -> Tensor |
13752 | at::Tensor special_scaled_modified_bessel_k0::call(const at::Tensor & x) { |
13753 | |
13754 | static auto op = create_special_scaled_modified_bessel_k0_typed_handle(); |
13755 | return op.call(x); |
13756 | } |
13757 | |
13758 | // aten::special_scaled_modified_bessel_k0(Tensor x) -> Tensor |
13759 | at::Tensor special_scaled_modified_bessel_k0::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x) { |
13760 | |
13761 | static auto op = create_special_scaled_modified_bessel_k0_typed_handle(); |
13762 | return op.redispatch(dispatchKeySet, x); |
13763 | } |
13764 | |
13765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k0_out, name, "aten::special_scaled_modified_bessel_k0" ) |
13766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k0_out, overload_name, "out" ) |
13767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_scaled_modified_bessel_k0_out, schema_str, "special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!)" ) |
13768 | |
13769 | // aten::special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
13770 | static C10_NOINLINE c10::TypedOperatorHandle<special_scaled_modified_bessel_k0_out::schema> create_special_scaled_modified_bessel_k0_out_typed_handle() { |
13771 | return c10::Dispatcher::singleton() |
13772 | .findSchemaOrThrow(special_scaled_modified_bessel_k0_out::name, special_scaled_modified_bessel_k0_out::overload_name) |
13773 | .typed<special_scaled_modified_bessel_k0_out::schema>(); |
13774 | } |
13775 | |
13776 | // aten::special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
13777 | at::Tensor & special_scaled_modified_bessel_k0_out::call(const at::Tensor & x, at::Tensor & out) { |
13778 | |
13779 | static auto op = create_special_scaled_modified_bessel_k0_out_typed_handle(); |
13780 | return op.call(x, out); |
13781 | } |
13782 | |
13783 | // aten::special_scaled_modified_bessel_k0.out(Tensor x, *, Tensor(a!) out) -> Tensor(a!) |
13784 | at::Tensor & special_scaled_modified_bessel_k0_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, at::Tensor & out) { |
13785 | |
13786 | static auto op = create_special_scaled_modified_bessel_k0_out_typed_handle(); |
13787 | return op.redispatch(dispatchKeySet, x, out); |
13788 | } |
13789 | |
13790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u, name, "aten::special_shifted_chebyshev_polynomial_u" ) |
13791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u, overload_name, "" ) |
13792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u, schema_str, "special_shifted_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor" ) |
13793 | |
13794 | // aten::special_shifted_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor |
13795 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_u::schema> create_special_shifted_chebyshev_polynomial_u_typed_handle() { |
13796 | return c10::Dispatcher::singleton() |
13797 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_u::name, special_shifted_chebyshev_polynomial_u::overload_name) |
13798 | .typed<special_shifted_chebyshev_polynomial_u::schema>(); |
13799 | } |
13800 | |
13801 | // aten::special_shifted_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor |
13802 | at::Tensor special_shifted_chebyshev_polynomial_u::call(const at::Tensor & x, const at::Tensor & n) { |
13803 | |
13804 | static auto op = create_special_shifted_chebyshev_polynomial_u_typed_handle(); |
13805 | return op.call(x, n); |
13806 | } |
13807 | |
13808 | // aten::special_shifted_chebyshev_polynomial_u(Tensor x, Tensor n) -> Tensor |
13809 | at::Tensor special_shifted_chebyshev_polynomial_u::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n) { |
13810 | |
13811 | static auto op = create_special_shifted_chebyshev_polynomial_u_typed_handle(); |
13812 | return op.redispatch(dispatchKeySet, x, n); |
13813 | } |
13814 | |
13815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_x_scalar, name, "aten::special_shifted_chebyshev_polynomial_u" ) |
13816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_x_scalar, overload_name, "x_scalar" ) |
13817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_x_scalar, schema_str, "special_shifted_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor" ) |
13818 | |
13819 | // aten::special_shifted_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor |
13820 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_u_x_scalar::schema> create_special_shifted_chebyshev_polynomial_u_x_scalar_typed_handle() { |
13821 | return c10::Dispatcher::singleton() |
13822 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_u_x_scalar::name, special_shifted_chebyshev_polynomial_u_x_scalar::overload_name) |
13823 | .typed<special_shifted_chebyshev_polynomial_u_x_scalar::schema>(); |
13824 | } |
13825 | |
13826 | // aten::special_shifted_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor |
13827 | at::Tensor special_shifted_chebyshev_polynomial_u_x_scalar::call(const at::Scalar & x, const at::Tensor & n) { |
13828 | |
13829 | static auto op = create_special_shifted_chebyshev_polynomial_u_x_scalar_typed_handle(); |
13830 | return op.call(x, n); |
13831 | } |
13832 | |
13833 | // aten::special_shifted_chebyshev_polynomial_u.x_scalar(Scalar x, Tensor n) -> Tensor |
13834 | at::Tensor special_shifted_chebyshev_polynomial_u_x_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n) { |
13835 | |
13836 | static auto op = create_special_shifted_chebyshev_polynomial_u_x_scalar_typed_handle(); |
13837 | return op.redispatch(dispatchKeySet, x, n); |
13838 | } |
13839 | |
13840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_n_scalar, name, "aten::special_shifted_chebyshev_polynomial_u" ) |
13841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_n_scalar, overload_name, "n_scalar" ) |
13842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_n_scalar, schema_str, "special_shifted_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor" ) |
13843 | |
13844 | // aten::special_shifted_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor |
13845 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_u_n_scalar::schema> create_special_shifted_chebyshev_polynomial_u_n_scalar_typed_handle() { |
13846 | return c10::Dispatcher::singleton() |
13847 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_u_n_scalar::name, special_shifted_chebyshev_polynomial_u_n_scalar::overload_name) |
13848 | .typed<special_shifted_chebyshev_polynomial_u_n_scalar::schema>(); |
13849 | } |
13850 | |
13851 | // aten::special_shifted_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor |
13852 | at::Tensor special_shifted_chebyshev_polynomial_u_n_scalar::call(const at::Tensor & x, const at::Scalar & n) { |
13853 | |
13854 | static auto op = create_special_shifted_chebyshev_polynomial_u_n_scalar_typed_handle(); |
13855 | return op.call(x, n); |
13856 | } |
13857 | |
13858 | // aten::special_shifted_chebyshev_polynomial_u.n_scalar(Tensor x, Scalar n) -> Tensor |
13859 | at::Tensor special_shifted_chebyshev_polynomial_u_n_scalar::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n) { |
13860 | |
13861 | static auto op = create_special_shifted_chebyshev_polynomial_u_n_scalar_typed_handle(); |
13862 | return op.redispatch(dispatchKeySet, x, n); |
13863 | } |
13864 | |
13865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_out, name, "aten::special_shifted_chebyshev_polynomial_u" ) |
13866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_out, overload_name, "out" ) |
13867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_out, schema_str, "special_shifted_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13868 | |
13869 | // aten::special_shifted_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13870 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_u_out::schema> create_special_shifted_chebyshev_polynomial_u_out_typed_handle() { |
13871 | return c10::Dispatcher::singleton() |
13872 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_u_out::name, special_shifted_chebyshev_polynomial_u_out::overload_name) |
13873 | .typed<special_shifted_chebyshev_polynomial_u_out::schema>(); |
13874 | } |
13875 | |
13876 | // aten::special_shifted_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13877 | at::Tensor & special_shifted_chebyshev_polynomial_u_out::call(const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
13878 | |
13879 | static auto op = create_special_shifted_chebyshev_polynomial_u_out_typed_handle(); |
13880 | return op.call(x, n, out); |
13881 | } |
13882 | |
13883 | // aten::special_shifted_chebyshev_polynomial_u.out(Tensor x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13884 | at::Tensor & special_shifted_chebyshev_polynomial_u_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Tensor & n, at::Tensor & out) { |
13885 | |
13886 | static auto op = create_special_shifted_chebyshev_polynomial_u_out_typed_handle(); |
13887 | return op.redispatch(dispatchKeySet, x, n, out); |
13888 | } |
13889 | |
13890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_x_scalar_out, name, "aten::special_shifted_chebyshev_polynomial_u" ) |
13891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_x_scalar_out, overload_name, "x_scalar_out" ) |
13892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_x_scalar_out, schema_str, "special_shifted_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13893 | |
13894 | // aten::special_shifted_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13895 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_u_x_scalar_out::schema> create_special_shifted_chebyshev_polynomial_u_x_scalar_out_typed_handle() { |
13896 | return c10::Dispatcher::singleton() |
13897 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_u_x_scalar_out::name, special_shifted_chebyshev_polynomial_u_x_scalar_out::overload_name) |
13898 | .typed<special_shifted_chebyshev_polynomial_u_x_scalar_out::schema>(); |
13899 | } |
13900 | |
13901 | // aten::special_shifted_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13902 | at::Tensor & special_shifted_chebyshev_polynomial_u_x_scalar_out::call(const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
13903 | |
13904 | static auto op = create_special_shifted_chebyshev_polynomial_u_x_scalar_out_typed_handle(); |
13905 | return op.call(x, n, out); |
13906 | } |
13907 | |
13908 | // aten::special_shifted_chebyshev_polynomial_u.x_scalar_out(Scalar x, Tensor n, *, Tensor(a!) out) -> Tensor(a!) |
13909 | at::Tensor & special_shifted_chebyshev_polynomial_u_x_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & x, const at::Tensor & n, at::Tensor & out) { |
13910 | |
13911 | static auto op = create_special_shifted_chebyshev_polynomial_u_x_scalar_out_typed_handle(); |
13912 | return op.redispatch(dispatchKeySet, x, n, out); |
13913 | } |
13914 | |
13915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_n_scalar_out, name, "aten::special_shifted_chebyshev_polynomial_u" ) |
13916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_n_scalar_out, overload_name, "n_scalar_out" ) |
13917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(special_shifted_chebyshev_polynomial_u_n_scalar_out, schema_str, "special_shifted_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!)" ) |
13918 | |
13919 | // aten::special_shifted_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13920 | static C10_NOINLINE c10::TypedOperatorHandle<special_shifted_chebyshev_polynomial_u_n_scalar_out::schema> create_special_shifted_chebyshev_polynomial_u_n_scalar_out_typed_handle() { |
13921 | return c10::Dispatcher::singleton() |
13922 | .findSchemaOrThrow(special_shifted_chebyshev_polynomial_u_n_scalar_out::name, special_shifted_chebyshev_polynomial_u_n_scalar_out::overload_name) |
13923 | .typed<special_shifted_chebyshev_polynomial_u_n_scalar_out::schema>(); |
13924 | } |
13925 | |
13926 | // aten::special_shifted_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13927 | at::Tensor & special_shifted_chebyshev_polynomial_u_n_scalar_out::call(const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
13928 | |
13929 | static auto op = create_special_shifted_chebyshev_polynomial_u_n_scalar_out_typed_handle(); |
13930 | return op.call(x, n, out); |
13931 | } |
13932 | |
13933 | // aten::special_shifted_chebyshev_polynomial_u.n_scalar_out(Tensor x, Scalar n, *, Tensor(a!) out) -> Tensor(a!) |
13934 | at::Tensor & special_shifted_chebyshev_polynomial_u_n_scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x, const at::Scalar & n, at::Tensor & out) { |
13935 | |
13936 | static auto op = create_special_shifted_chebyshev_polynomial_u_n_scalar_out_typed_handle(); |
13937 | return op.redispatch(dispatchKeySet, x, n, out); |
13938 | } |
13939 | |
13940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam_, name, "aten::_fused_adam_" ) |
13941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam_, overload_name, "" ) |
13942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam_, schema_str, "_fused_adam_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> ()" ) |
13943 | |
13944 | // aten::_fused_adam_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () |
13945 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_adam_::schema> create__fused_adam__typed_handle() { |
13946 | return c10::Dispatcher::singleton() |
13947 | .findSchemaOrThrow(_fused_adam_::name, _fused_adam_::overload_name) |
13948 | .typed<_fused_adam_::schema>(); |
13949 | } |
13950 | |
13951 | // aten::_fused_adam_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () |
13952 | void _fused_adam_::call(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional<at::Tensor> & grad_scale, const c10::optional<at::Tensor> & found_inf) { |
13953 | |
13954 | static auto op = create__fused_adam__typed_handle(); |
13955 | return op.call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); |
13956 | } |
13957 | |
13958 | // aten::_fused_adam_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () |
13959 | void _fused_adam_::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional<at::Tensor> & grad_scale, const c10::optional<at::Tensor> & found_inf) { |
13960 | |
13961 | static auto op = create__fused_adam__typed_handle(); |
13962 | return op.redispatch(dispatchKeySet, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); |
13963 | } |
13964 | |
13965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_new_zeros_with_same_feature_meta_out, name, "aten::_new_zeros_with_same_feature_meta" ) |
13966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_new_zeros_with_same_feature_meta_out, overload_name, "out" ) |
13967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_new_zeros_with_same_feature_meta_out, schema_str, "_new_zeros_with_same_feature_meta.out(Tensor self, Tensor other, *, int self_num_batch_dims=0, Tensor(a!) out) -> Tensor(a!)" ) |
13968 | |
13969 | // aten::_new_zeros_with_same_feature_meta.out(Tensor self, Tensor other, *, int self_num_batch_dims=0, Tensor(a!) out) -> Tensor(a!) |
13970 | static C10_NOINLINE c10::TypedOperatorHandle<_new_zeros_with_same_feature_meta_out::schema> create__new_zeros_with_same_feature_meta_out_typed_handle() { |
13971 | return c10::Dispatcher::singleton() |
13972 | .findSchemaOrThrow(_new_zeros_with_same_feature_meta_out::name, _new_zeros_with_same_feature_meta_out::overload_name) |
13973 | .typed<_new_zeros_with_same_feature_meta_out::schema>(); |
13974 | } |
13975 | |
13976 | // aten::_new_zeros_with_same_feature_meta.out(Tensor self, Tensor other, *, int self_num_batch_dims=0, Tensor(a!) out) -> Tensor(a!) |
13977 | at::Tensor & _new_zeros_with_same_feature_meta_out::call(const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims, at::Tensor & out) { |
13978 | |
13979 | static auto op = create__new_zeros_with_same_feature_meta_out_typed_handle(); |
13980 | return op.call(self, other, self_num_batch_dims, out); |
13981 | } |
13982 | |
13983 | // aten::_new_zeros_with_same_feature_meta.out(Tensor self, Tensor other, *, int self_num_batch_dims=0, Tensor(a!) out) -> Tensor(a!) |
13984 | at::Tensor & _new_zeros_with_same_feature_meta_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, int64_t self_num_batch_dims, at::Tensor & out) { |
13985 | |
13986 | static auto op = create__new_zeros_with_same_feature_meta_out_typed_handle(); |
13987 | return op.redispatch(dispatchKeySet, self, other, self_num_batch_dims, out); |
13988 | } |
13989 | |
13990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_init_dropout_state_out, name, "aten::_cudnn_init_dropout_state" ) |
13991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_init_dropout_state_out, overload_name, "out" ) |
13992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cudnn_init_dropout_state_out, schema_str, "_cudnn_init_dropout_state.out(float dropout, bool train, int dropout_seed, *, Tensor(a!) out) -> Tensor(a!)" ) |
13993 | |
13994 | // aten::_cudnn_init_dropout_state.out(float dropout, bool train, int dropout_seed, *, Tensor(a!) out) -> Tensor(a!) |
13995 | static C10_NOINLINE c10::TypedOperatorHandle<_cudnn_init_dropout_state_out::schema> create__cudnn_init_dropout_state_out_typed_handle() { |
13996 | return c10::Dispatcher::singleton() |
13997 | .findSchemaOrThrow(_cudnn_init_dropout_state_out::name, _cudnn_init_dropout_state_out::overload_name) |
13998 | .typed<_cudnn_init_dropout_state_out::schema>(); |
13999 | } |
14000 | |
14001 | // aten::_cudnn_init_dropout_state.out(float dropout, bool train, int dropout_seed, *, Tensor(a!) out) -> Tensor(a!) |
14002 | at::Tensor & _cudnn_init_dropout_state_out::call(double dropout, bool train, int64_t dropout_seed, at::Tensor & out) { |
14003 | |
14004 | static auto op = create__cudnn_init_dropout_state_out_typed_handle(); |
14005 | return op.call(dropout, train, dropout_seed, out); |
14006 | } |
14007 | |
14008 | // aten::_cudnn_init_dropout_state.out(float dropout, bool train, int dropout_seed, *, Tensor(a!) out) -> Tensor(a!) |
14009 | at::Tensor & _cudnn_init_dropout_state_out::redispatch(c10::DispatchKeySet dispatchKeySet, double dropout, bool train, int64_t dropout_seed, at::Tensor & out) { |
14010 | |
14011 | static auto op = create__cudnn_init_dropout_state_out_typed_handle(); |
14012 | return op.redispatch(dispatchKeySet, dropout, train, dropout_seed, out); |
14013 | } |
14014 | |
14015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_dropout_out, name, "aten::native_dropout" ) |
14016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_dropout_out, overload_name, "out" ) |
14017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_dropout_out, schema_str, "native_dropout.out(Tensor input, float p, bool? train, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))" ) |
14018 | |
14019 | // aten::native_dropout.out(Tensor input, float p, bool? train, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
14020 | static C10_NOINLINE c10::TypedOperatorHandle<native_dropout_out::schema> create_native_dropout_out_typed_handle() { |
14021 | return c10::Dispatcher::singleton() |
14022 | .findSchemaOrThrow(native_dropout_out::name, native_dropout_out::overload_name) |
14023 | .typed<native_dropout_out::schema>(); |
14024 | } |
14025 | |
14026 | // aten::native_dropout.out(Tensor input, float p, bool? train, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
14027 | ::std::tuple<at::Tensor &,at::Tensor &> native_dropout_out::call(const at::Tensor & input, double p, c10::optional<bool> train, at::Tensor & out0, at::Tensor & out1) { |
14028 | |
14029 | static auto op = create_native_dropout_out_typed_handle(); |
14030 | return op.call(input, p, train, out0, out1); |
14031 | } |
14032 | |
14033 | // aten::native_dropout.out(Tensor input, float p, bool? train, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
14034 | ::std::tuple<at::Tensor &,at::Tensor &> native_dropout_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, double p, c10::optional<bool> train, at::Tensor & out0, at::Tensor & out1) { |
14035 | |
14036 | static auto op = create_native_dropout_out_typed_handle(); |
14037 | return op.redispatch(dispatchKeySet, input, p, train, out0, out1); |
14038 | } |
14039 | |
14040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Scalar_out, name, "aten::add" ) |
14041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Scalar_out, overload_name, "Scalar_out" ) |
14042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(add_Scalar_out, schema_str, "add.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!)" ) |
14043 | |
14044 | // aten::add.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) |
14045 | static C10_NOINLINE c10::TypedOperatorHandle<add_Scalar_out::schema> create_add_Scalar_out_typed_handle() { |
14046 | return c10::Dispatcher::singleton() |
14047 | .findSchemaOrThrow(add_Scalar_out::name, add_Scalar_out::overload_name) |
14048 | .typed<add_Scalar_out::schema>(); |
14049 | } |
14050 | |
14051 | // aten::add.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) |
14052 | at::Tensor & add_Scalar_out::call(const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out) { |
14053 | |
14054 | static auto op = create_add_Scalar_out_typed_handle(); |
14055 | return op.call(self, other, alpha, out); |
14056 | } |
14057 | |
14058 | // aten::add.Scalar_out(Tensor self, Scalar other, Scalar alpha=1, *, Tensor(a!) out) -> Tensor(a!) |
14059 | at::Tensor & add_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & other, const at::Scalar & alpha, at::Tensor & out) { |
14060 | |
14061 | static auto op = create_add_Scalar_out_typed_handle(); |
14062 | return op.redispatch(dispatchKeySet, self, other, alpha, out); |
14063 | } |
14064 | |
14065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_Tensor_out, name, "aten::bernoulli" ) |
14066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_Tensor_out, overload_name, "Tensor_out" ) |
14067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_Tensor_out, schema_str, "bernoulli.Tensor_out(Tensor self, Tensor p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)" ) |
14068 | |
14069 | // aten::bernoulli.Tensor_out(Tensor self, Tensor p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
14070 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli_Tensor_out::schema> create_bernoulli_Tensor_out_typed_handle() { |
14071 | return c10::Dispatcher::singleton() |
14072 | .findSchemaOrThrow(bernoulli_Tensor_out::name, bernoulli_Tensor_out::overload_name) |
14073 | .typed<bernoulli_Tensor_out::schema>(); |
14074 | } |
14075 | |
14076 | // aten::bernoulli.Tensor_out(Tensor self, Tensor p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
14077 | at::Tensor & bernoulli_Tensor_out::call(const at::Tensor & self, const at::Tensor & p, c10::optional<at::Generator> generator, at::Tensor & out) { |
14078 | |
14079 | static auto op = create_bernoulli_Tensor_out_typed_handle(); |
14080 | return op.call(self, p, generator, out); |
14081 | } |
14082 | |
14083 | // aten::bernoulli.Tensor_out(Tensor self, Tensor p, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
14084 | at::Tensor & bernoulli_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & p, c10::optional<at::Generator> generator, at::Tensor & out) { |
14085 | |
14086 | static auto op = create_bernoulli_Tensor_out_typed_handle(); |
14087 | return op.redispatch(dispatchKeySet, self, p, generator, out); |
14088 | } |
14089 | |
14090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_Tensor, name, "aten::bernoulli" ) |
14091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_Tensor, overload_name, "Tensor" ) |
14092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_Tensor, schema_str, "bernoulli.Tensor(Tensor self, Tensor p, *, Generator? generator=None) -> Tensor" ) |
14093 | |
14094 | // aten::bernoulli.Tensor(Tensor self, Tensor p, *, Generator? generator=None) -> Tensor |
14095 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli_Tensor::schema> create_bernoulli_Tensor_typed_handle() { |
14096 | return c10::Dispatcher::singleton() |
14097 | .findSchemaOrThrow(bernoulli_Tensor::name, bernoulli_Tensor::overload_name) |
14098 | .typed<bernoulli_Tensor::schema>(); |
14099 | } |
14100 | |
14101 | // aten::bernoulli.Tensor(Tensor self, Tensor p, *, Generator? generator=None) -> Tensor |
14102 | at::Tensor bernoulli_Tensor::call(const at::Tensor & self, const at::Tensor & p, c10::optional<at::Generator> generator) { |
14103 | |
14104 | static auto op = create_bernoulli_Tensor_typed_handle(); |
14105 | return op.call(self, p, generator); |
14106 | } |
14107 | |
14108 | // aten::bernoulli.Tensor(Tensor self, Tensor p, *, Generator? generator=None) -> Tensor |
14109 | at::Tensor bernoulli_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & p, c10::optional<at::Generator> generator) { |
14110 | |
14111 | static auto op = create_bernoulli_Tensor_typed_handle(); |
14112 | return op.redispatch(dispatchKeySet, self, p, generator); |
14113 | } |
14114 | |
14115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_float_out, name, "aten::bernoulli" ) |
14116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_float_out, overload_name, "float_out" ) |
14117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bernoulli_float_out, schema_str, "bernoulli.float_out(Tensor self, float p=0.5, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)" ) |
14118 | |
14119 | // aten::bernoulli.float_out(Tensor self, float p=0.5, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
14120 | static C10_NOINLINE c10::TypedOperatorHandle<bernoulli_float_out::schema> create_bernoulli_float_out_typed_handle() { |
14121 | return c10::Dispatcher::singleton() |
14122 | .findSchemaOrThrow(bernoulli_float_out::name, bernoulli_float_out::overload_name) |
14123 | .typed<bernoulli_float_out::schema>(); |
14124 | } |
14125 | |
14126 | // aten::bernoulli.float_out(Tensor self, float p=0.5, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
14127 | at::Tensor & bernoulli_float_out::call(const at::Tensor & self, double p, c10::optional<at::Generator> generator, at::Tensor & out) { |
14128 | |
14129 | static auto op = create_bernoulli_float_out_typed_handle(); |
14130 | return op.call(self, p, generator, out); |
14131 | } |
14132 | |
14133 | // aten::bernoulli.float_out(Tensor self, float p=0.5, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
14134 | at::Tensor & bernoulli_float_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, c10::optional<at::Generator> generator, at::Tensor & out) { |
14135 | |
14136 | static auto op = create_bernoulli_float_out_typed_handle(); |
14137 | return op.redispatch(dispatchKeySet, self, p, generator, out); |
14138 | } |
14139 | |
14140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binary_cross_entropy_with_logits_out, name, "aten::binary_cross_entropy_with_logits" ) |
14141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binary_cross_entropy_with_logits_out, overload_name, "out" ) |
14142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(binary_cross_entropy_with_logits_out, schema_str, "binary_cross_entropy_with_logits.out(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!)" ) |
14143 | |
14144 | // aten::binary_cross_entropy_with_logits.out(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
14145 | static C10_NOINLINE c10::TypedOperatorHandle<binary_cross_entropy_with_logits_out::schema> create_binary_cross_entropy_with_logits_out_typed_handle() { |
14146 | return c10::Dispatcher::singleton() |
14147 | .findSchemaOrThrow(binary_cross_entropy_with_logits_out::name, binary_cross_entropy_with_logits_out::overload_name) |
14148 | .typed<binary_cross_entropy_with_logits_out::schema>(); |
14149 | } |
14150 | |
14151 | // aten::binary_cross_entropy_with_logits.out(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
14152 | at::Tensor & binary_cross_entropy_with_logits_out::call(const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & pos_weight, int64_t reduction, at::Tensor & out) { |
14153 | |
14154 | static auto op = create_binary_cross_entropy_with_logits_out_typed_handle(); |
14155 | return op.call(self, target, weight, pos_weight, reduction, out); |
14156 | } |
14157 | |
14158 | // aten::binary_cross_entropy_with_logits.out(Tensor self, Tensor target, Tensor? weight=None, Tensor? pos_weight=None, int reduction=Mean, *, Tensor(a!) out) -> Tensor(a!) |
14159 | at::Tensor & binary_cross_entropy_with_logits_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & pos_weight, int64_t reduction, at::Tensor & out) { |
14160 | |
14161 | static auto op = create_binary_cross_entropy_with_logits_out_typed_handle(); |
14162 | return op.redispatch(dispatchKeySet, self, target, weight, pos_weight, reduction, out); |
14163 | } |
14164 | |
14165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bincount_out, name, "aten::bincount" ) |
14166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bincount_out, overload_name, "out" ) |
14167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(bincount_out, schema_str, "bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!)" ) |
14168 | |
14169 | // aten::bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!) |
14170 | static C10_NOINLINE c10::TypedOperatorHandle<bincount_out::schema> create_bincount_out_typed_handle() { |
14171 | return c10::Dispatcher::singleton() |
14172 | .findSchemaOrThrow(bincount_out::name, bincount_out::overload_name) |
14173 | .typed<bincount_out::schema>(); |
14174 | } |
14175 | |
14176 | // aten::bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!) |
14177 | at::Tensor & bincount_out::call(const at::Tensor & self, const c10::optional<at::Tensor> & weights, int64_t minlength, at::Tensor & out) { |
14178 | |
14179 | static auto op = create_bincount_out_typed_handle(); |
14180 | return op.call(self, weights, minlength, out); |
14181 | } |
14182 | |
14183 | // aten::bincount.out(Tensor self, Tensor? weights=None, int minlength=0, *, Tensor(a!) out) -> Tensor(a!) |
14184 | at::Tensor & bincount_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Tensor> & weights, int64_t minlength, at::Tensor & out) { |
14185 | |
14186 | static auto op = create_bincount_out_typed_handle(); |
14187 | return op.redispatch(dispatchKeySet, self, weights, minlength, out); |
14188 | } |
14189 | |
14190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(block_diag_out, name, "aten::block_diag" ) |
14191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(block_diag_out, overload_name, "out" ) |
14192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(block_diag_out, schema_str, "block_diag.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!)" ) |
14193 | |
14194 | // aten::block_diag.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
14195 | static C10_NOINLINE c10::TypedOperatorHandle<block_diag_out::schema> create_block_diag_out_typed_handle() { |
14196 | return c10::Dispatcher::singleton() |
14197 | .findSchemaOrThrow(block_diag_out::name, block_diag_out::overload_name) |
14198 | .typed<block_diag_out::schema>(); |
14199 | } |
14200 | |
14201 | // aten::block_diag.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
14202 | at::Tensor & block_diag_out::call(at::TensorList tensors, at::Tensor & out) { |
14203 | |
14204 | static auto op = create_block_diag_out_typed_handle(); |
14205 | return op.call(tensors, out); |
14206 | } |
14207 | |
14208 | // aten::block_diag.out(Tensor[] tensors, *, Tensor(a!) out) -> Tensor(a!) |
14209 | at::Tensor & block_diag_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, at::Tensor & out) { |
14210 | |
14211 | static auto op = create_block_diag_out_typed_handle(); |
14212 | return op.redispatch(dispatchKeySet, tensors, out); |
14213 | } |
14214 | |
14215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_dim_IntList_out, name, "aten::count_nonzero" ) |
14216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_dim_IntList_out, overload_name, "dim_IntList_out" ) |
14217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_dim_IntList_out, schema_str, "count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!)" ) |
14218 | |
14219 | // aten::count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) |
14220 | static C10_NOINLINE c10::TypedOperatorHandle<count_nonzero_dim_IntList_out::schema> create_count_nonzero_dim_IntList_out_typed_handle() { |
14221 | return c10::Dispatcher::singleton() |
14222 | .findSchemaOrThrow(count_nonzero_dim_IntList_out::name, count_nonzero_dim_IntList_out::overload_name) |
14223 | .typed<count_nonzero_dim_IntList_out::schema>(); |
14224 | } |
14225 | |
14226 | // aten::count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) |
14227 | at::Tensor & count_nonzero_dim_IntList_out::call(const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { |
14228 | |
14229 | static auto op = create_count_nonzero_dim_IntList_out_typed_handle(); |
14230 | return op.call(self, dim, out); |
14231 | } |
14232 | |
14233 | // aten::count_nonzero.dim_IntList_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) |
14234 | at::Tensor & count_nonzero_dim_IntList_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { |
14235 | |
14236 | static auto op = create_count_nonzero_dim_IntList_out_typed_handle(); |
14237 | return op.redispatch(dispatchKeySet, self, dim, out); |
14238 | } |
14239 | |
14240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_out, name, "aten::count_nonzero" ) |
14241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_out, overload_name, "out" ) |
14242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(count_nonzero_out, schema_str, "count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
14243 | |
14244 | // aten::count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
14245 | static C10_NOINLINE c10::TypedOperatorHandle<count_nonzero_out::schema> create_count_nonzero_out_typed_handle() { |
14246 | return c10::Dispatcher::singleton() |
14247 | .findSchemaOrThrow(count_nonzero_out::name, count_nonzero_out::overload_name) |
14248 | .typed<count_nonzero_out::schema>(); |
14249 | } |
14250 | |
14251 | // aten::count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
14252 | at::Tensor & count_nonzero_out::call(const at::Tensor & self, c10::optional<int64_t> dim, at::Tensor & out) { |
14253 | |
14254 | static auto op = create_count_nonzero_out_typed_handle(); |
14255 | return op.call(self, dim, out); |
14256 | } |
14257 | |
14258 | // aten::count_nonzero.out(Tensor self, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) |
14259 | at::Tensor & count_nonzero_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<int64_t> dim, at::Tensor & out) { |
14260 | |
14261 | static auto op = create_count_nonzero_out_typed_handle(); |
14262 | return op.redispatch(dispatchKeySet, self, dim, out); |
14263 | } |
14264 | |
14265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_add_relu_out, name, "aten::cudnn_convolution_add_relu" ) |
14266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_add_relu_out, overload_name, "out" ) |
14267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(cudnn_convolution_add_relu_out, schema_str, "cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!)" ) |
14268 | |
14269 | // aten::cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
14270 | static C10_NOINLINE c10::TypedOperatorHandle<cudnn_convolution_add_relu_out::schema> create_cudnn_convolution_add_relu_out_typed_handle() { |
14271 | return c10::Dispatcher::singleton() |
14272 | .findSchemaOrThrow(cudnn_convolution_add_relu_out::name, cudnn_convolution_add_relu_out::overload_name) |
14273 | .typed<cudnn_convolution_add_relu_out::schema>(); |
14274 | } |
14275 | |
14276 | // aten::cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
14277 | at::Tensor & cudnn_convolution_add_relu_out::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, at::Tensor & out) { |
14278 | |
14279 | static auto op = create_cudnn_convolution_add_relu_out_typed_handle(); |
14280 | return op.call(self, weight, z, alpha, bias, stride, padding, dilation, groups, out); |
14281 | } |
14282 | |
14283 | // aten::cudnn_convolution_add_relu.out(Tensor self, Tensor weight, Tensor z, Scalar? alpha, Tensor? bias, int[] stride, int[] padding, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) |
14284 | at::Tensor & cudnn_convolution_add_relu_out::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, at::Tensor & out) { |
14285 | |
14286 | static auto op = create_cudnn_convolution_add_relu_out_typed_handle(); |
14287 | return op.redispatch(dispatchKeySet, self, weight, z, alpha, bias, stride, padding, dilation, groups, out); |
14288 | } |
14289 | |
14290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward_out, name, "aten::_ctc_loss_backward" ) |
14291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward_out, overload_name, "out" ) |
14292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_ctc_loss_backward_out, schema_str, "_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
14293 | |
14294 | // aten::_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!) |
14295 | static C10_NOINLINE c10::TypedOperatorHandle<_ctc_loss_backward_out::schema> create__ctc_loss_backward_out_typed_handle() { |
14296 | return c10::Dispatcher::singleton() |
14297 | .findSchemaOrThrow(_ctc_loss_backward_out::name, _ctc_loss_backward_out::overload_name) |
14298 | .typed<_ctc_loss_backward_out::schema>(); |
14299 | } |
14300 | |
14301 | // aten::_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!) |
14302 | at::Tensor & _ctc_loss_backward_out::call(const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out) { |
14303 | |
14304 | static auto op = create__ctc_loss_backward_out_typed_handle(); |
14305 | return op.call(grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity, out); |
14306 | } |
14307 | |
14308 | // aten::_ctc_loss_backward.out(Tensor grad, Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, Tensor neg_log_likelihood, Tensor log_alpha, int blank, bool zero_infinity=False, *, Tensor(a!) out) -> Tensor(a!) |
14309 | at::Tensor & _ctc_loss_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & log_probs, const at::Tensor & targets, at::IntArrayRef input_lengths, at::IntArrayRef target_lengths, const at::Tensor & neg_log_likelihood, const at::Tensor & log_alpha, int64_t blank, bool zero_infinity, at::Tensor & out) { |
14310 | |
14311 | static auto op = create__ctc_loss_backward_out_typed_handle(); |
14312 | return op.redispatch(dispatchKeySet, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity, out); |
14313 | } |
14314 | |
14315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_backward_out, name, "aten::diagonal_backward" ) |
14316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_backward_out, overload_name, "out" ) |
14317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(diagonal_backward_out, schema_str, "diagonal_backward.out(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2, *, Tensor(a!) out) -> Tensor(a!)" ) |
14318 | |
14319 | // aten::diagonal_backward.out(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2, *, Tensor(a!) out) -> Tensor(a!) |
14320 | static C10_NOINLINE c10::TypedOperatorHandle<diagonal_backward_out::schema> create_diagonal_backward_out_typed_handle() { |
14321 | return c10::Dispatcher::singleton() |
14322 | .findSchemaOrThrow(diagonal_backward_out::name, diagonal_backward_out::overload_name) |
14323 | .typed<diagonal_backward_out::schema>(); |
14324 | } |
14325 | |
14326 | // aten::diagonal_backward.out(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2, *, Tensor(a!) out) -> Tensor(a!) |
14327 | at::Tensor & diagonal_backward_out::call(const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out) { |
14328 | |
14329 | static auto op = create_diagonal_backward_out_typed_handle(); |
14330 | return op.call(grad_output, input_sizes, offset, dim1, dim2, out); |
14331 | } |
14332 | |
14333 | // aten::diagonal_backward.out(Tensor grad_output, SymInt[] input_sizes, int offset, int dim1, int dim2, *, Tensor(a!) out) -> Tensor(a!) |
14334 | at::Tensor & diagonal_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, c10::SymIntArrayRef input_sizes, int64_t offset, int64_t dim1, int64_t dim2, at::Tensor & out) { |
14335 | |
14336 | static auto op = create_diagonal_backward_out_typed_handle(); |
14337 | return op.redispatch(dispatchKeySet, grad_output, input_sizes, offset, dim1, dim2, out); |
14338 | } |
14339 | |
14340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm_out, name, "aten::embedding_renorm" ) |
14341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm_out, overload_name, "out" ) |
14342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm_out, schema_str, "embedding_renorm.out(Tensor self, Tensor indices, float max_norm, float norm_type, *, Tensor(a!) out) -> Tensor(a!)" ) |
14343 | |
14344 | // aten::embedding_renorm.out(Tensor self, Tensor indices, float max_norm, float norm_type, *, Tensor(a!) out) -> Tensor(a!) |
14345 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_renorm_out::schema> create_embedding_renorm_out_typed_handle() { |
14346 | return c10::Dispatcher::singleton() |
14347 | .findSchemaOrThrow(embedding_renorm_out::name, embedding_renorm_out::overload_name) |
14348 | .typed<embedding_renorm_out::schema>(); |
14349 | } |
14350 | |
14351 | // aten::embedding_renorm.out(Tensor self, Tensor indices, float max_norm, float norm_type, *, Tensor(a!) out) -> Tensor(a!) |
14352 | at::Tensor & embedding_renorm_out::call(const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type, at::Tensor & out) { |
14353 | |
14354 | static auto op = create_embedding_renorm_out_typed_handle(); |
14355 | return op.call(self, indices, max_norm, norm_type, out); |
14356 | } |
14357 | |
14358 | // aten::embedding_renorm.out(Tensor self, Tensor indices, float max_norm, float norm_type, *, Tensor(a!) out) -> Tensor(a!) |
14359 | at::Tensor & embedding_renorm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type, at::Tensor & out) { |
14360 | |
14361 | static auto op = create_embedding_renorm_out_typed_handle(); |
14362 | return op.redispatch(dispatchKeySet, self, indices, max_norm, norm_type, out); |
14363 | } |
14364 | |
14365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm, name, "aten::embedding_renorm" ) |
14366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm, overload_name, "" ) |
14367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(embedding_renorm, schema_str, "embedding_renorm(Tensor self, Tensor indices, float max_norm, float norm_type) -> Tensor" ) |
14368 | |
14369 | // aten::embedding_renorm(Tensor self, Tensor indices, float max_norm, float norm_type) -> Tensor |
14370 | static C10_NOINLINE c10::TypedOperatorHandle<embedding_renorm::schema> create_embedding_renorm_typed_handle() { |
14371 | return c10::Dispatcher::singleton() |
14372 | .findSchemaOrThrow(embedding_renorm::name, embedding_renorm::overload_name) |
14373 | .typed<embedding_renorm::schema>(); |
14374 | } |
14375 | |
14376 | // aten::embedding_renorm(Tensor self, Tensor indices, float max_norm, float norm_type) -> Tensor |
14377 | at::Tensor embedding_renorm::call(const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type) { |
14378 | |
14379 | static auto op = create_embedding_renorm_typed_handle(); |
14380 | return op.call(self, indices, max_norm, norm_type); |
14381 | } |
14382 | |
14383 | // aten::embedding_renorm(Tensor self, Tensor indices, float max_norm, float norm_type) -> Tensor |
14384 | at::Tensor embedding_renorm::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & indices, double max_norm, double norm_type) { |
14385 | |
14386 | static auto op = create_embedding_renorm_typed_handle(); |
14387 | return op.redispatch(dispatchKeySet, self, indices, max_norm, norm_type); |
14388 | } |
14389 | |
14390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_per_sample_weights_backward_out, name, "aten::_embedding_bag_per_sample_weights_backward" ) |
14391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_per_sample_weights_backward_out, overload_name, "out" ) |
14392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_embedding_bag_per_sample_weights_backward_out, schema_str, "_embedding_bag_per_sample_weights_backward.out(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!)" ) |
14393 | |
14394 | // aten::_embedding_bag_per_sample_weights_backward.out(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) |
14395 | static C10_NOINLINE c10::TypedOperatorHandle<_embedding_bag_per_sample_weights_backward_out::schema> create__embedding_bag_per_sample_weights_backward_out_typed_handle() { |
14396 | return c10::Dispatcher::singleton() |
14397 | .findSchemaOrThrow(_embedding_bag_per_sample_weights_backward_out::name, _embedding_bag_per_sample_weights_backward_out::overload_name) |
14398 | .typed<_embedding_bag_per_sample_weights_backward_out::schema>(); |
14399 | } |
14400 | |
14401 | // aten::_embedding_bag_per_sample_weights_backward.out(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) |
14402 | at::Tensor & _embedding_bag_per_sample_weights_backward_out::call(const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out) { |
14403 | |
14404 | static auto op = create__embedding_bag_per_sample_weights_backward_out_typed_handle(); |
14405 | return op.call(grad, weight, indices, offsets, offset2bag, mode, padding_idx, out); |
14406 | } |
14407 | |
14408 | // aten::_embedding_bag_per_sample_weights_backward.out(Tensor grad, Tensor weight, Tensor indices, Tensor offsets, Tensor offset2bag, int mode, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) |
14409 | at::Tensor & _embedding_bag_per_sample_weights_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & weight, const at::Tensor & indices, const at::Tensor & offsets, const at::Tensor & offset2bag, int64_t mode, int64_t padding_idx, at::Tensor & out) { |
14410 | |
14411 | static auto op = create__embedding_bag_per_sample_weights_backward_out_typed_handle(); |
14412 | return op.redispatch(dispatchKeySet, grad, weight, indices, offsets, offset2bag, mode, padding_idx, out); |
14413 | } |
14414 | |
14415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_names_out, name, "aten::empty" ) |
14416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_names_out, overload_name, "names_out" ) |
14417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_names_out, schema_str, "empty.names_out(int[] size, *, Dimname[]? names, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)" ) |
14418 | |
14419 | // aten::empty.names_out(int[] size, *, Dimname[]? names, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14420 | static C10_NOINLINE c10::TypedOperatorHandle<empty_names_out::schema> create_empty_names_out_typed_handle() { |
14421 | return c10::Dispatcher::singleton() |
14422 | .findSchemaOrThrow(empty_names_out::name, empty_names_out::overload_name) |
14423 | .typed<empty_names_out::schema>(); |
14424 | } |
14425 | |
14426 | // aten::empty.names_out(int[] size, *, Dimname[]? names, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14427 | at::Tensor & empty_names_out::call(at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14428 | |
14429 | static auto op = create_empty_names_out_typed_handle(); |
14430 | return op.call(size, names, memory_format, out); |
14431 | } |
14432 | |
14433 | // aten::empty.names_out(int[] size, *, Dimname[]? names, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14434 | at::Tensor & empty_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, c10::optional<at::DimnameList> names, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14435 | |
14436 | static auto op = create_empty_names_out_typed_handle(); |
14437 | return op.redispatch(dispatchKeySet, size, names, memory_format, out); |
14438 | } |
14439 | |
14440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_strided_out, name, "aten::new_empty_strided" ) |
14441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_strided_out, overload_name, "out" ) |
14442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_empty_strided_out, schema_str, "new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!)" ) |
14443 | |
14444 | // aten::new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) |
14445 | static C10_NOINLINE c10::TypedOperatorHandle<new_empty_strided_out::schema> create_new_empty_strided_out_typed_handle() { |
14446 | return c10::Dispatcher::singleton() |
14447 | .findSchemaOrThrow(new_empty_strided_out::name, new_empty_strided_out::overload_name) |
14448 | .typed<new_empty_strided_out::schema>(); |
14449 | } |
14450 | |
14451 | // aten::new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) |
14452 | at::Tensor & new_empty_strided_out::call(const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { |
14453 | |
14454 | static auto op = create_new_empty_strided_out_typed_handle(); |
14455 | return op.call(self, size, stride, out); |
14456 | } |
14457 | |
14458 | // aten::new_empty_strided.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) |
14459 | at::Tensor & new_empty_strided_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { |
14460 | |
14461 | static auto op = create_new_empty_strided_out_typed_handle(); |
14462 | return op.redispatch(dispatchKeySet, self, size, stride, out); |
14463 | } |
14464 | |
14465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_full_out, name, "aten::new_full" ) |
14466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_full_out, overload_name, "out" ) |
14467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_full_out, schema_str, "new_full.out(Tensor self, SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)" ) |
14468 | |
14469 | // aten::new_full.out(Tensor self, SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) |
14470 | static C10_NOINLINE c10::TypedOperatorHandle<new_full_out::schema> create_new_full_out_typed_handle() { |
14471 | return c10::Dispatcher::singleton() |
14472 | .findSchemaOrThrow(new_full_out::name, new_full_out::overload_name) |
14473 | .typed<new_full_out::schema>(); |
14474 | } |
14475 | |
14476 | // aten::new_full.out(Tensor self, SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) |
14477 | at::Tensor & new_full_out::call(const at::Tensor & self, c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { |
14478 | |
14479 | static auto op = create_new_full_out_typed_handle(); |
14480 | return op.call(self, size, fill_value, out); |
14481 | } |
14482 | |
14483 | // aten::new_full.out(Tensor self, SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!) |
14484 | at::Tensor & new_full_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, const at::Scalar & fill_value, at::Tensor & out) { |
14485 | |
14486 | static auto op = create_new_full_out_typed_handle(); |
14487 | return op.redispatch(dispatchKeySet, self, size, fill_value, out); |
14488 | } |
14489 | |
14490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_ones_out, name, "aten::new_ones" ) |
14491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_ones_out, overload_name, "out" ) |
14492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(new_ones_out, schema_str, "new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)" ) |
14493 | |
14494 | // aten::new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
14495 | static C10_NOINLINE c10::TypedOperatorHandle<new_ones_out::schema> create_new_ones_out_typed_handle() { |
14496 | return c10::Dispatcher::singleton() |
14497 | .findSchemaOrThrow(new_ones_out::name, new_ones_out::overload_name) |
14498 | .typed<new_ones_out::schema>(); |
14499 | } |
14500 | |
14501 | // aten::new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
14502 | at::Tensor & new_ones_out::call(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
14503 | |
14504 | static auto op = create_new_ones_out_typed_handle(); |
14505 | return op.call(self, size, out); |
14506 | } |
14507 | |
14508 | // aten::new_ones.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
14509 | at::Tensor & new_ones_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
14510 | |
14511 | static auto op = create_new_ones_out_typed_handle(); |
14512 | return op.redispatch(dispatchKeySet, self, size, out); |
14513 | } |
14514 | |
14515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_empty_per_channel_affine_quantized_out, name, "aten::_empty_per_channel_affine_quantized" ) |
14516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_empty_per_channel_affine_quantized_out, overload_name, "out" ) |
14517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_empty_per_channel_affine_quantized_out, schema_str, "_empty_per_channel_affine_quantized.out(int[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!)" ) |
14518 | |
14519 | // aten::_empty_per_channel_affine_quantized.out(int[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) |
14520 | static C10_NOINLINE c10::TypedOperatorHandle<_empty_per_channel_affine_quantized_out::schema> create__empty_per_channel_affine_quantized_out_typed_handle() { |
14521 | return c10::Dispatcher::singleton() |
14522 | .findSchemaOrThrow(_empty_per_channel_affine_quantized_out::name, _empty_per_channel_affine_quantized_out::overload_name) |
14523 | .typed<_empty_per_channel_affine_quantized_out::schema>(); |
14524 | } |
14525 | |
14526 | // aten::_empty_per_channel_affine_quantized.out(int[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) |
14527 | at::Tensor & _empty_per_channel_affine_quantized_out::call(at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14528 | |
14529 | static auto op = create__empty_per_channel_affine_quantized_out_typed_handle(); |
14530 | return op.call(size, scales, zero_points, axis, memory_format, out); |
14531 | } |
14532 | |
14533 | // aten::_empty_per_channel_affine_quantized.out(int[] size, *, Tensor scales, Tensor zero_points, int axis, MemoryFormat? memory_format=contiguous_format, Tensor(a!) out) -> Tensor(a!) |
14534 | at::Tensor & _empty_per_channel_affine_quantized_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Tensor & scales, const at::Tensor & zero_points, int64_t axis, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14535 | |
14536 | static auto op = create__empty_per_channel_affine_quantized_out_typed_handle(); |
14537 | return op.redispatch(dispatchKeySet, size, scales, zero_points, axis, memory_format, out); |
14538 | } |
14539 | |
14540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_quantized_out, name, "aten::empty_quantized" ) |
14541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_quantized_out, overload_name, "out" ) |
14542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_quantized_out, schema_str, "empty_quantized.out(int[] size, Tensor qtensor, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)" ) |
14543 | |
14544 | // aten::empty_quantized.out(int[] size, Tensor qtensor, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14545 | static C10_NOINLINE c10::TypedOperatorHandle<empty_quantized_out::schema> create_empty_quantized_out_typed_handle() { |
14546 | return c10::Dispatcher::singleton() |
14547 | .findSchemaOrThrow(empty_quantized_out::name, empty_quantized_out::overload_name) |
14548 | .typed<empty_quantized_out::schema>(); |
14549 | } |
14550 | |
14551 | // aten::empty_quantized.out(int[] size, Tensor qtensor, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14552 | at::Tensor & empty_quantized_out::call(at::IntArrayRef size, const at::Tensor & qtensor, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14553 | |
14554 | static auto op = create_empty_quantized_out_typed_handle(); |
14555 | return op.call(size, qtensor, memory_format, out); |
14556 | } |
14557 | |
14558 | // aten::empty_quantized.out(int[] size, Tensor qtensor, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14559 | at::Tensor & empty_quantized_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::IntArrayRef size, const at::Tensor & qtensor, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14560 | |
14561 | static auto op = create_empty_quantized_out_typed_handle(); |
14562 | return op.redispatch(dispatchKeySet, size, qtensor, memory_format, out); |
14563 | } |
14564 | |
14565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_strided_out, name, "aten::empty_strided" ) |
14566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_strided_out, overload_name, "out" ) |
14567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(empty_strided_out, schema_str, "empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!)" ) |
14568 | |
14569 | // aten::empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) |
14570 | static C10_NOINLINE c10::TypedOperatorHandle<empty_strided_out::schema> create_empty_strided_out_typed_handle() { |
14571 | return c10::Dispatcher::singleton() |
14572 | .findSchemaOrThrow(empty_strided_out::name, empty_strided_out::overload_name) |
14573 | .typed<empty_strided_out::schema>(); |
14574 | } |
14575 | |
14576 | // aten::empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) |
14577 | at::Tensor & empty_strided_out::call(c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { |
14578 | |
14579 | static auto op = create_empty_strided_out_typed_handle(); |
14580 | return op.call(size, stride, out); |
14581 | } |
14582 | |
14583 | // aten::empty_strided.out(SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) |
14584 | at::Tensor & empty_strided_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { |
14585 | |
14586 | static auto op = create_empty_strided_out_typed_handle(); |
14587 | return op.redispatch(dispatchKeySet, size, stride, out); |
14588 | } |
14589 | |
14590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(from_file_out, name, "aten::from_file" ) |
14591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(from_file_out, overload_name, "out" ) |
14592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(from_file_out, schema_str, "from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!)" ) |
14593 | |
14594 | // aten::from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!) |
14595 | static C10_NOINLINE c10::TypedOperatorHandle<from_file_out::schema> create_from_file_out_typed_handle() { |
14596 | return c10::Dispatcher::singleton() |
14597 | .findSchemaOrThrow(from_file_out::name, from_file_out::overload_name) |
14598 | .typed<from_file_out::schema>(); |
14599 | } |
14600 | |
14601 | // aten::from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!) |
14602 | at::Tensor & from_file_out::call(c10::string_view filename, c10::optional<bool> shared, c10::optional<int64_t> size, at::Tensor & out) { |
14603 | |
14604 | static auto op = create_from_file_out_typed_handle(); |
14605 | return op.call(filename, shared, size, out); |
14606 | } |
14607 | |
14608 | // aten::from_file.out(str filename, bool? shared=None, int? size=0, *, Tensor(a!) out) -> Tensor(a!) |
14609 | at::Tensor & from_file_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::string_view filename, c10::optional<bool> shared, c10::optional<int64_t> size, at::Tensor & out) { |
14610 | |
14611 | static auto op = create_from_file_out_typed_handle(); |
14612 | return op.redispatch(dispatchKeySet, filename, shared, size, out); |
14613 | } |
14614 | |
14615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_layer_norm_backward_out, name, "aten::native_layer_norm_backward" ) |
14616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_layer_norm_backward_out, overload_name, "out" ) |
14617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_layer_norm_backward_out, schema_str, "native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))" ) |
14618 | |
14619 | // aten::native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
14620 | static C10_NOINLINE c10::TypedOperatorHandle<native_layer_norm_backward_out::schema> create_native_layer_norm_backward_out_typed_handle() { |
14621 | return c10::Dispatcher::singleton() |
14622 | .findSchemaOrThrow(native_layer_norm_backward_out::name, native_layer_norm_backward_out::overload_name) |
14623 | .typed<native_layer_norm_backward_out::schema>(); |
14624 | } |
14625 | |
14626 | // aten::native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
14627 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> native_layer_norm_backward_out::call(const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
14628 | |
14629 | static auto op = create_native_layer_norm_backward_out_typed_handle(); |
14630 | return op.call(grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask, out0, out1, out2); |
14631 | } |
14632 | |
14633 | // aten::native_layer_norm_backward.out(Tensor grad_out, Tensor input, SymInt[] normalized_shape, Tensor mean, Tensor rstd, Tensor? weight, Tensor? bias, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
14634 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> native_layer_norm_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_out, const at::Tensor & input, c10::SymIntArrayRef normalized_shape, const at::Tensor & mean, const at::Tensor & rstd, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
14635 | |
14636 | static auto op = create_native_layer_norm_backward_out_typed_handle(); |
14637 | return op.redispatch(dispatchKeySet, grad_out, input, normalized_shape, mean, rstd, weight, bias, output_mask, out0, out1, out2); |
14638 | } |
14639 | |
14640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_max_pool2d_backward_out, name, "aten::mps_max_pool2d_backward" ) |
14641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_max_pool2d_backward_out, overload_name, "out" ) |
14642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_max_pool2d_backward_out, schema_str, "mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
14643 | |
14644 | // aten::mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
14645 | static C10_NOINLINE c10::TypedOperatorHandle<mps_max_pool2d_backward_out::schema> create_mps_max_pool2d_backward_out_typed_handle() { |
14646 | return c10::Dispatcher::singleton() |
14647 | .findSchemaOrThrow(mps_max_pool2d_backward_out::name, mps_max_pool2d_backward_out::overload_name) |
14648 | .typed<mps_max_pool2d_backward_out::schema>(); |
14649 | } |
14650 | |
14651 | // aten::mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
14652 | at::Tensor & mps_max_pool2d_backward_out::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, at::Tensor & out) { |
14653 | |
14654 | static auto op = create_mps_max_pool2d_backward_out_typed_handle(); |
14655 | return op.call(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, out); |
14656 | } |
14657 | |
14658 | // aten::mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) |
14659 | at::Tensor & mps_max_pool2d_backward_out::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, at::Tensor & out) { |
14660 | |
14661 | static auto op = create_mps_max_pool2d_backward_out_typed_handle(); |
14662 | return op.redispatch(dispatchKeySet, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode, out); |
14663 | } |
14664 | |
14665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_out, name, "aten::mkldnn_max_pool3d" ) |
14666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_out, overload_name, "out" ) |
14667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_max_pool3d_out, schema_str, "mkldnn_max_pool3d.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(a!)" ) |
14668 | |
14669 | // aten::mkldnn_max_pool3d.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(a!) |
14670 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_max_pool3d_out::schema> create_mkldnn_max_pool3d_out_typed_handle() { |
14671 | return c10::Dispatcher::singleton() |
14672 | .findSchemaOrThrow(mkldnn_max_pool3d_out::name, mkldnn_max_pool3d_out::overload_name) |
14673 | .typed<mkldnn_max_pool3d_out::schema>(); |
14674 | } |
14675 | |
14676 | // aten::mkldnn_max_pool3d.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(a!) |
14677 | at::Tensor & mkldnn_max_pool3d_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) { |
14678 | |
14679 | static auto op = create_mkldnn_max_pool3d_out_typed_handle(); |
14680 | return op.call(self, kernel_size, stride, padding, dilation, ceil_mode, out); |
14681 | } |
14682 | |
14683 | // aten::mkldnn_max_pool3d.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(a!) |
14684 | at::Tensor & mkldnn_max_pool3d_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) { |
14685 | |
14686 | static auto op = create_mkldnn_max_pool3d_out_typed_handle(); |
14687 | return op.redispatch(dispatchKeySet, self, kernel_size, stride, padding, dilation, ceil_mode, out); |
14688 | } |
14689 | |
14690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_backward_out, name, "aten::mps_convolution_backward" ) |
14691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_backward_out, overload_name, "out" ) |
14692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mps_convolution_backward_out, schema_str, "mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!))" ) |
14693 | |
14694 | // aten::mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
14695 | static C10_NOINLINE c10::TypedOperatorHandle<mps_convolution_backward_out::schema> create_mps_convolution_backward_out_typed_handle() { |
14696 | return c10::Dispatcher::singleton() |
14697 | .findSchemaOrThrow(mps_convolution_backward_out::name, mps_convolution_backward_out::overload_name) |
14698 | .typed<mps_convolution_backward_out::schema>(); |
14699 | } |
14700 | |
14701 | // aten::mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
14702 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> mps_convolution_backward_out::call(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
14703 | |
14704 | static auto op = create_mps_convolution_backward_out_typed_handle(); |
14705 | return op.call(self, grad_output, weight, padding, stride, dilation, groups, output_mask, out0, out1, out2); |
14706 | } |
14707 | |
14708 | // aten::mps_convolution_backward.out(Tensor self, Tensor grad_output, Tensor weight, int[] padding, int[] stride, int[] dilation, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) |
14709 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &> mps_convolution_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, at::IntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, ::std::array<bool,3> output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { |
14710 | |
14711 | static auto op = create_mps_convolution_backward_out_typed_handle(); |
14712 | return op.redispatch(dispatchKeySet, self, grad_output, weight, padding, stride, dilation, groups, output_mask, out0, out1, out2); |
14713 | } |
14714 | |
14715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_rnn_layer_out, name, "aten::mkldnn_rnn_layer" ) |
14716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_rnn_layer_out, overload_name, "out" ) |
14717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(mkldnn_rnn_layer_out, schema_str, "mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))" ) |
14718 | |
14719 | // aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
14720 | static C10_NOINLINE c10::TypedOperatorHandle<mkldnn_rnn_layer_out::schema> create_mkldnn_rnn_layer_out_typed_handle() { |
14721 | return c10::Dispatcher::singleton() |
14722 | .findSchemaOrThrow(mkldnn_rnn_layer_out::name, mkldnn_rnn_layer_out::overload_name) |
14723 | .typed<mkldnn_rnn_layer_out::schema>(); |
14724 | } |
14725 | |
14726 | // aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
14727 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> mkldnn_rnn_layer_out::call(const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
14728 | |
14729 | static auto op = create_mkldnn_rnn_layer_out_typed_handle(); |
14730 | return op.call(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train, out0, out1, out2, out3); |
14731 | } |
14732 | |
14733 | // aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
14734 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> mkldnn_rnn_layer_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const at::Tensor & weight0, const at::Tensor & weight1, const at::Tensor & weight2, const at::Tensor & weight3, const at::Tensor & hx_, const at::Tensor & cx_, bool reverse, at::IntArrayRef batch_sizes, int64_t mode, int64_t hidden_size, int64_t num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
14735 | |
14736 | static auto op = create_mkldnn_rnn_layer_out_typed_handle(); |
14737 | return op.redispatch(dispatchKeySet, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train, out0, out1, out2, out3); |
14738 | } |
14739 | |
14740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_out, name, "aten::miopen_convolution" ) |
14741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_out, overload_name, "out" ) |
14742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_convolution_out, schema_str, "miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!)" ) |
14743 | |
14744 | // aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) |
14745 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_convolution_out::schema> create_miopen_convolution_out_typed_handle() { |
14746 | return c10::Dispatcher::singleton() |
14747 | .findSchemaOrThrow(miopen_convolution_out::name, miopen_convolution_out::overload_name) |
14748 | .typed<miopen_convolution_out::schema>(); |
14749 | } |
14750 | |
14751 | // aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) |
14752 | at::Tensor & miopen_convolution_out::call(const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { |
14753 | |
14754 | static auto op = create_miopen_convolution_out_typed_handle(); |
14755 | return op.call(self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); |
14756 | } |
14757 | |
14758 | // aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) |
14759 | at::Tensor & miopen_convolution_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & weight, const c10::optional<at::Tensor> & bias, c10::SymIntArrayRef padding, at::IntArrayRef stride, at::IntArrayRef dilation, int64_t groups, bool benchmark, bool deterministic, at::Tensor & out) { |
14760 | |
14761 | static auto op = create_miopen_convolution_out_typed_handle(); |
14762 | return op.redispatch(dispatchKeySet, self, weight, bias, padding, stride, dilation, groups, benchmark, deterministic, out); |
14763 | } |
14764 | |
14765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_out, name, "aten::miopen_rnn" ) |
14766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_out, overload_name, "out" ) |
14767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(miopen_rnn_out, schema_str, "miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))" ) |
14768 | |
14769 | // aten::miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
14770 | static C10_NOINLINE c10::TypedOperatorHandle<miopen_rnn_out::schema> create_miopen_rnn_out_typed_handle() { |
14771 | return c10::Dispatcher::singleton() |
14772 | .findSchemaOrThrow(miopen_rnn_out::name, miopen_rnn_out::overload_name) |
14773 | .typed<miopen_rnn_out::schema>(); |
14774 | } |
14775 | |
14776 | // aten::miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
14777 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> miopen_rnn_out::call(const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, 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, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { |
14778 | |
14779 | static auto op = create_miopen_rnn_out_typed_handle(); |
14780 | return op.call(input, weight, weight_stride0, hx, cx, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); |
14781 | } |
14782 | |
14783 | // aten::miopen_rnn.out(Tensor input, Tensor[] weight, int weight_stride0, Tensor hx, Tensor? cx, int mode, int hidden_size, int num_layers, bool batch_first, float dropout, bool train, bool bidirectional, int[] batch_sizes, Tensor? dropout_state, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
14784 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> miopen_rnn_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, at::TensorList weight, int64_t weight_stride0, const at::Tensor & hx, const c10::optional<at::Tensor> & cx, 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, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { |
14785 | |
14786 | static auto op = create_miopen_rnn_out_typed_handle(); |
14787 | return op.redispatch(dispatchKeySet, input, weight, weight_stride0, hx, cx, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, out0, out1, out2, out3, out4); |
14788 | } |
14789 | |
14790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sparse_matmul_out, name, "aten::_sparse_sparse_matmul" ) |
14791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sparse_matmul_out, overload_name, "out" ) |
14792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sparse_matmul_out, schema_str, "_sparse_sparse_matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!)" ) |
14793 | |
14794 | // aten::_sparse_sparse_matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
14795 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sparse_matmul_out::schema> create__sparse_sparse_matmul_out_typed_handle() { |
14796 | return c10::Dispatcher::singleton() |
14797 | .findSchemaOrThrow(_sparse_sparse_matmul_out::name, _sparse_sparse_matmul_out::overload_name) |
14798 | .typed<_sparse_sparse_matmul_out::schema>(); |
14799 | } |
14800 | |
14801 | // aten::_sparse_sparse_matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
14802 | at::Tensor & _sparse_sparse_matmul_out::call(const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
14803 | |
14804 | static auto op = create__sparse_sparse_matmul_out_typed_handle(); |
14805 | return op.call(self, other, out); |
14806 | } |
14807 | |
14808 | // aten::_sparse_sparse_matmul.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) |
14809 | at::Tensor & _sparse_sparse_matmul_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & other, at::Tensor & out) { |
14810 | |
14811 | static auto op = create__sparse_sparse_matmul_out_typed_handle(); |
14812 | return op.redispatch(dispatchKeySet, self, other, out); |
14813 | } |
14814 | |
14815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_functional, name, "aten::_native_batch_norm_legit_functional" ) |
14816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_functional, overload_name, "" ) |
14817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_batch_norm_legit_functional, schema_str, "_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out)" ) |
14818 | |
14819 | // aten::_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out) |
14820 | static C10_NOINLINE c10::TypedOperatorHandle<_native_batch_norm_legit_functional::schema> create__native_batch_norm_legit_functional_typed_handle() { |
14821 | return c10::Dispatcher::singleton() |
14822 | .findSchemaOrThrow(_native_batch_norm_legit_functional::name, _native_batch_norm_legit_functional::overload_name) |
14823 | .typed<_native_batch_norm_legit_functional::schema>(); |
14824 | } |
14825 | |
14826 | // aten::_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out) |
14827 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _native_batch_norm_legit_functional::call(const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & running_mean, const at::Tensor & running_var, bool training, double momentum, double eps) { |
14828 | |
14829 | static auto op = create__native_batch_norm_legit_functional_typed_handle(); |
14830 | return op.call(input, weight, bias, running_mean, running_var, training, momentum, eps); |
14831 | } |
14832 | |
14833 | // aten::_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out) |
14834 | ::std::tuple<at::Tensor,at::Tensor,at::Tensor,at::Tensor,at::Tensor> _native_batch_norm_legit_functional::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & weight, const c10::optional<at::Tensor> & bias, const at::Tensor & running_mean, const at::Tensor & running_var, bool training, double momentum, double eps) { |
14835 | |
14836 | static auto op = create__native_batch_norm_legit_functional_typed_handle(); |
14837 | return op.redispatch(dispatchKeySet, input, weight, bias, running_mean, running_var, training, momentum, eps); |
14838 | } |
14839 | |
14840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_update_stats_out, name, "aten::batch_norm_update_stats" ) |
14841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_update_stats_out, overload_name, "out" ) |
14842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(batch_norm_update_stats_out, schema_str, "batch_norm_update_stats.out(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))" ) |
14843 | |
14844 | // aten::batch_norm_update_stats.out(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
14845 | static C10_NOINLINE c10::TypedOperatorHandle<batch_norm_update_stats_out::schema> create_batch_norm_update_stats_out_typed_handle() { |
14846 | return c10::Dispatcher::singleton() |
14847 | .findSchemaOrThrow(batch_norm_update_stats_out::name, batch_norm_update_stats_out::overload_name) |
14848 | .typed<batch_norm_update_stats_out::schema>(); |
14849 | } |
14850 | |
14851 | // aten::batch_norm_update_stats.out(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
14852 | ::std::tuple<at::Tensor &,at::Tensor &> batch_norm_update_stats_out::call(const at::Tensor & input, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, double momentum, at::Tensor & out0, at::Tensor & out1) { |
14853 | |
14854 | static auto op = create_batch_norm_update_stats_out_typed_handle(); |
14855 | return op.call(input, running_mean, running_var, momentum, out0, out1); |
14856 | } |
14857 | |
14858 | // aten::batch_norm_update_stats.out(Tensor input, Tensor? running_mean, Tensor? running_var, float momentum, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
14859 | ::std::tuple<at::Tensor &,at::Tensor &> batch_norm_update_stats_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & input, const c10::optional<at::Tensor> & running_mean, const c10::optional<at::Tensor> & running_var, double momentum, at::Tensor & out0, at::Tensor & out1) { |
14860 | |
14861 | static auto op = create_batch_norm_update_stats_out_typed_handle(); |
14862 | return op.redispatch(dispatchKeySet, input, running_mean, running_var, momentum, out0, out1); |
14863 | } |
14864 | |
14865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ones_like_out, name, "aten::ones_like" ) |
14866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ones_like_out, overload_name, "out" ) |
14867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(ones_like_out, schema_str, "ones_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)" ) |
14868 | |
14869 | // aten::ones_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14870 | static C10_NOINLINE c10::TypedOperatorHandle<ones_like_out::schema> create_ones_like_out_typed_handle() { |
14871 | return c10::Dispatcher::singleton() |
14872 | .findSchemaOrThrow(ones_like_out::name, ones_like_out::overload_name) |
14873 | .typed<ones_like_out::schema>(); |
14874 | } |
14875 | |
14876 | // aten::ones_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14877 | at::Tensor & ones_like_out::call(const at::Tensor & self, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14878 | |
14879 | static auto op = create_ones_like_out_typed_handle(); |
14880 | return op.call(self, memory_format, out); |
14881 | } |
14882 | |
14883 | // aten::ones_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
14884 | at::Tensor & ones_like_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
14885 | |
14886 | static auto op = create_ones_like_out_typed_handle(); |
14887 | return op.redispatch(dispatchKeySet, self, memory_format, out); |
14888 | } |
14889 | |
14890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_euclidean_dist_out, name, "aten::_euclidean_dist" ) |
14891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_euclidean_dist_out, overload_name, "out" ) |
14892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_euclidean_dist_out, schema_str, "_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!)" ) |
14893 | |
14894 | // aten::_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!) |
14895 | static C10_NOINLINE c10::TypedOperatorHandle<_euclidean_dist_out::schema> create__euclidean_dist_out_typed_handle() { |
14896 | return c10::Dispatcher::singleton() |
14897 | .findSchemaOrThrow(_euclidean_dist_out::name, _euclidean_dist_out::overload_name) |
14898 | .typed<_euclidean_dist_out::schema>(); |
14899 | } |
14900 | |
14901 | // aten::_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!) |
14902 | at::Tensor & _euclidean_dist_out::call(const at::Tensor & x1, const at::Tensor & x2, at::Tensor & out) { |
14903 | |
14904 | static auto op = create__euclidean_dist_out_typed_handle(); |
14905 | return op.call(x1, x2, out); |
14906 | } |
14907 | |
14908 | // aten::_euclidean_dist.out(Tensor x1, Tensor x2, *, Tensor(a!) out) -> Tensor(a!) |
14909 | at::Tensor & _euclidean_dist_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & x1, const at::Tensor & x2, at::Tensor & out) { |
14910 | |
14911 | static auto op = create__euclidean_dist_out_typed_handle(); |
14912 | return op.redispatch(dispatchKeySet, x1, x2, out); |
14913 | } |
14914 | |
14915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cdist_backward_out, name, "aten::_cdist_backward" ) |
14916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cdist_backward_out, overload_name, "out" ) |
14917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cdist_backward_out, schema_str, "_cdist_backward.out(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist, *, Tensor(a!) out) -> Tensor(a!)" ) |
14918 | |
14919 | // aten::_cdist_backward.out(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist, *, Tensor(a!) out) -> Tensor(a!) |
14920 | static C10_NOINLINE c10::TypedOperatorHandle<_cdist_backward_out::schema> create__cdist_backward_out_typed_handle() { |
14921 | return c10::Dispatcher::singleton() |
14922 | .findSchemaOrThrow(_cdist_backward_out::name, _cdist_backward_out::overload_name) |
14923 | .typed<_cdist_backward_out::schema>(); |
14924 | } |
14925 | |
14926 | // aten::_cdist_backward.out(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist, *, Tensor(a!) out) -> Tensor(a!) |
14927 | at::Tensor & _cdist_backward_out::call(const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist, at::Tensor & out) { |
14928 | |
14929 | static auto op = create__cdist_backward_out_typed_handle(); |
14930 | return op.call(grad, x1, x2, p, cdist, out); |
14931 | } |
14932 | |
14933 | // aten::_cdist_backward.out(Tensor grad, Tensor x1, Tensor x2, float p, Tensor cdist, *, Tensor(a!) out) -> Tensor(a!) |
14934 | at::Tensor & _cdist_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & x1, const at::Tensor & x2, double p, const at::Tensor & cdist, at::Tensor & out) { |
14935 | |
14936 | static auto op = create__cdist_backward_out_typed_handle(); |
14937 | return op.redispatch(dispatchKeySet, grad, x1, x2, p, cdist, out); |
14938 | } |
14939 | |
14940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pdist_forward_out, name, "aten::_pdist_forward" ) |
14941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pdist_forward_out, overload_name, "out" ) |
14942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_pdist_forward_out, schema_str, "_pdist_forward.out(Tensor self, float p=2, *, Tensor(a!) out) -> Tensor(a!)" ) |
14943 | |
14944 | // aten::_pdist_forward.out(Tensor self, float p=2, *, Tensor(a!) out) -> Tensor(a!) |
14945 | static C10_NOINLINE c10::TypedOperatorHandle<_pdist_forward_out::schema> create__pdist_forward_out_typed_handle() { |
14946 | return c10::Dispatcher::singleton() |
14947 | .findSchemaOrThrow(_pdist_forward_out::name, _pdist_forward_out::overload_name) |
14948 | .typed<_pdist_forward_out::schema>(); |
14949 | } |
14950 | |
14951 | // aten::_pdist_forward.out(Tensor self, float p=2, *, Tensor(a!) out) -> Tensor(a!) |
14952 | at::Tensor & _pdist_forward_out::call(const at::Tensor & self, double p, at::Tensor & out) { |
14953 | |
14954 | static auto op = create__pdist_forward_out_typed_handle(); |
14955 | return op.call(self, p, out); |
14956 | } |
14957 | |
14958 | // aten::_pdist_forward.out(Tensor self, float p=2, *, Tensor(a!) out) -> Tensor(a!) |
14959 | at::Tensor & _pdist_forward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double p, at::Tensor & out) { |
14960 | |
14961 | static auto op = create__pdist_forward_out_typed_handle(); |
14962 | return op.redispatch(dispatchKeySet, self, p, out); |
14963 | } |
14964 | |
14965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scalar_tensor_out, name, "aten::scalar_tensor" ) |
14966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scalar_tensor_out, overload_name, "out" ) |
14967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(scalar_tensor_out, schema_str, "scalar_tensor.out(Scalar s, *, Tensor(a!) out) -> Tensor(a!)" ) |
14968 | |
14969 | // aten::scalar_tensor.out(Scalar s, *, Tensor(a!) out) -> Tensor(a!) |
14970 | static C10_NOINLINE c10::TypedOperatorHandle<scalar_tensor_out::schema> create_scalar_tensor_out_typed_handle() { |
14971 | return c10::Dispatcher::singleton() |
14972 | .findSchemaOrThrow(scalar_tensor_out::name, scalar_tensor_out::overload_name) |
14973 | .typed<scalar_tensor_out::schema>(); |
14974 | } |
14975 | |
14976 | // aten::scalar_tensor.out(Scalar s, *, Tensor(a!) out) -> Tensor(a!) |
14977 | at::Tensor & scalar_tensor_out::call(const at::Scalar & s, at::Tensor & out) { |
14978 | |
14979 | static auto op = create_scalar_tensor_out_typed_handle(); |
14980 | return op.call(s, out); |
14981 | } |
14982 | |
14983 | // aten::scalar_tensor.out(Scalar s, *, Tensor(a!) out) -> Tensor(a!) |
14984 | at::Tensor & scalar_tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Scalar & s, at::Tensor & out) { |
14985 | |
14986 | static auto op = create_scalar_tensor_out_typed_handle(); |
14987 | return op.redispatch(dispatchKeySet, s, out); |
14988 | } |
14989 | |
14990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_names_out, name, "aten::rand" ) |
14991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_names_out, overload_name, "names_out" ) |
14992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_names_out, schema_str, "rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)" ) |
14993 | |
14994 | // aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
14995 | static C10_NOINLINE c10::TypedOperatorHandle<rand_names_out::schema> create_rand_names_out_typed_handle() { |
14996 | return c10::Dispatcher::singleton() |
14997 | .findSchemaOrThrow(rand_names_out::name, rand_names_out::overload_name) |
14998 | .typed<rand_names_out::schema>(); |
14999 | } |
15000 | |
15001 | // aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
15002 | at::Tensor & rand_names_out::call(c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, at::Tensor & out) { |
15003 | |
15004 | static auto op = create_rand_names_out_typed_handle(); |
15005 | return op.call(size, names, out); |
15006 | } |
15007 | |
15008 | // aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
15009 | at::Tensor & rand_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::DimnameList> names, at::Tensor & out) { |
15010 | |
15011 | static auto op = create_rand_names_out_typed_handle(); |
15012 | return op.redispatch(dispatchKeySet, size, names, out); |
15013 | } |
15014 | |
15015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_with_names_out, name, "aten::rand" ) |
15016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_with_names_out, overload_name, "generator_with_names_out" ) |
15017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rand_generator_with_names_out, schema_str, "rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!)" ) |
15018 | |
15019 | // aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
15020 | static C10_NOINLINE c10::TypedOperatorHandle<rand_generator_with_names_out::schema> create_rand_generator_with_names_out_typed_handle() { |
15021 | return c10::Dispatcher::singleton() |
15022 | .findSchemaOrThrow(rand_generator_with_names_out::name, rand_generator_with_names_out::overload_name) |
15023 | .typed<rand_generator_with_names_out::schema>(); |
15024 | } |
15025 | |
15026 | // aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
15027 | at::Tensor & rand_generator_with_names_out::call(c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, at::Tensor & out) { |
15028 | |
15029 | static auto op = create_rand_generator_with_names_out_typed_handle(); |
15030 | return op.call(size, generator, names, out); |
15031 | } |
15032 | |
15033 | // aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) |
15034 | at::Tensor & rand_generator_with_names_out::redispatch(c10::DispatchKeySet dispatchKeySet, c10::SymIntArrayRef size, c10::optional<at::Generator> generator, c10::optional<at::DimnameList> names, at::Tensor & out) { |
15035 | |
15036 | static auto op = create_rand_generator_with_names_out_typed_handle(); |
15037 | return op.redispatch(dispatchKeySet, size, generator, names, out); |
15038 | } |
15039 | |
15040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_like_out, name, "aten::randn_like" ) |
15041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_like_out, overload_name, "out" ) |
15042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(randn_like_out, schema_str, "randn_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!)" ) |
15043 | |
15044 | // aten::randn_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
15045 | static C10_NOINLINE c10::TypedOperatorHandle<randn_like_out::schema> create_randn_like_out_typed_handle() { |
15046 | return c10::Dispatcher::singleton() |
15047 | .findSchemaOrThrow(randn_like_out::name, randn_like_out::overload_name) |
15048 | .typed<randn_like_out::schema>(); |
15049 | } |
15050 | |
15051 | // aten::randn_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
15052 | at::Tensor & randn_like_out::call(const at::Tensor & self, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
15053 | |
15054 | static auto op = create_randn_like_out_typed_handle(); |
15055 | return op.call(self, memory_format, out); |
15056 | } |
15057 | |
15058 | // aten::randn_like.out(Tensor self, *, MemoryFormat? memory_format=None, Tensor(a!) out) -> Tensor(a!) |
15059 | at::Tensor & randn_like_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::MemoryFormat> memory_format, at::Tensor & out) { |
15060 | |
15061 | static auto op = create_randn_like_out_typed_handle(); |
15062 | return op.redispatch(dispatchKeySet, self, memory_format, out); |
15063 | } |
15064 | |
15065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_out, name, "aten::repeat" ) |
15066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_out, overload_name, "out" ) |
15067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_out, schema_str, "repeat.out(Tensor self, SymInt[] repeats, *, Tensor(a!) out) -> Tensor(a!)" ) |
15068 | |
15069 | // aten::repeat.out(Tensor self, SymInt[] repeats, *, Tensor(a!) out) -> Tensor(a!) |
15070 | static C10_NOINLINE c10::TypedOperatorHandle<repeat_out::schema> create_repeat_out_typed_handle() { |
15071 | return c10::Dispatcher::singleton() |
15072 | .findSchemaOrThrow(repeat_out::name, repeat_out::overload_name) |
15073 | .typed<repeat_out::schema>(); |
15074 | } |
15075 | |
15076 | // aten::repeat.out(Tensor self, SymInt[] repeats, *, Tensor(a!) out) -> Tensor(a!) |
15077 | at::Tensor & repeat_out::call(const at::Tensor & self, c10::SymIntArrayRef repeats, at::Tensor & out) { |
15078 | |
15079 | static auto op = create_repeat_out_typed_handle(); |
15080 | return op.call(self, repeats, out); |
15081 | } |
15082 | |
15083 | // aten::repeat.out(Tensor self, SymInt[] repeats, *, Tensor(a!) out) -> Tensor(a!) |
15084 | at::Tensor & repeat_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef repeats, at::Tensor & out) { |
15085 | |
15086 | static auto op = create_repeat_out_typed_handle(); |
15087 | return op.redispatch(dispatchKeySet, self, repeats, out); |
15088 | } |
15089 | |
15090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_Tensor_out, name, "aten::repeat_interleave" ) |
15091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_Tensor_out, overload_name, "Tensor_out" ) |
15092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(repeat_interleave_Tensor_out, schema_str, "repeat_interleave.Tensor_out(Tensor repeats, *, int? output_size=None, Tensor(a!) out) -> Tensor(a!)" ) |
15093 | |
15094 | // aten::repeat_interleave.Tensor_out(Tensor repeats, *, int? output_size=None, Tensor(a!) out) -> Tensor(a!) |
15095 | static C10_NOINLINE c10::TypedOperatorHandle<repeat_interleave_Tensor_out::schema> create_repeat_interleave_Tensor_out_typed_handle() { |
15096 | return c10::Dispatcher::singleton() |
15097 | .findSchemaOrThrow(repeat_interleave_Tensor_out::name, repeat_interleave_Tensor_out::overload_name) |
15098 | .typed<repeat_interleave_Tensor_out::schema>(); |
15099 | } |
15100 | |
15101 | // aten::repeat_interleave.Tensor_out(Tensor repeats, *, int? output_size=None, Tensor(a!) out) -> Tensor(a!) |
15102 | at::Tensor & repeat_interleave_Tensor_out::call(const at::Tensor & repeats, c10::optional<int64_t> output_size, at::Tensor & out) { |
15103 | |
15104 | static auto op = create_repeat_interleave_Tensor_out_typed_handle(); |
15105 | return op.call(repeats, output_size, out); |
15106 | } |
15107 | |
15108 | // aten::repeat_interleave.Tensor_out(Tensor repeats, *, int? output_size=None, Tensor(a!) out) -> Tensor(a!) |
15109 | at::Tensor & repeat_interleave_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & repeats, c10::optional<int64_t> output_size, at::Tensor & out) { |
15110 | |
15111 | static auto op = create_repeat_interleave_Tensor_out_typed_handle(); |
15112 | return op.redispatch(dispatchKeySet, repeats, output_size, out); |
15113 | } |
15114 | |
15115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mkldnn_reshape_out, name, "aten::_mkldnn_reshape" ) |
15116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mkldnn_reshape_out, overload_name, "out" ) |
15117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_mkldnn_reshape_out, schema_str, "_mkldnn_reshape.out(Tensor self, int[] shape, *, Tensor(a!) out) -> Tensor(a!)" ) |
15118 | |
15119 | // aten::_mkldnn_reshape.out(Tensor self, int[] shape, *, Tensor(a!) out) -> Tensor(a!) |
15120 | static C10_NOINLINE c10::TypedOperatorHandle<_mkldnn_reshape_out::schema> create__mkldnn_reshape_out_typed_handle() { |
15121 | return c10::Dispatcher::singleton() |
15122 | .findSchemaOrThrow(_mkldnn_reshape_out::name, _mkldnn_reshape_out::overload_name) |
15123 | .typed<_mkldnn_reshape_out::schema>(); |
15124 | } |
15125 | |
15126 | // aten::_mkldnn_reshape.out(Tensor self, int[] shape, *, Tensor(a!) out) -> Tensor(a!) |
15127 | at::Tensor & _mkldnn_reshape_out::call(const at::Tensor & self, at::IntArrayRef shape, at::Tensor & out) { |
15128 | |
15129 | static auto op = create__mkldnn_reshape_out_typed_handle(); |
15130 | return op.call(self, shape, out); |
15131 | } |
15132 | |
15133 | // aten::_mkldnn_reshape.out(Tensor self, int[] shape, *, Tensor(a!) out) -> Tensor(a!) |
15134 | at::Tensor & _mkldnn_reshape_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef shape, at::Tensor & out) { |
15135 | |
15136 | static auto op = create__mkldnn_reshape_out_typed_handle(); |
15137 | return op.redispatch(dispatchKeySet, self, shape, out); |
15138 | } |
15139 | |
15140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_out, name, "aten::sum" ) |
15141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_out, overload_name, "out" ) |
15142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(sum_out, schema_str, "sum.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)" ) |
15143 | |
15144 | // aten::sum.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
15145 | static C10_NOINLINE c10::TypedOperatorHandle<sum_out::schema> create_sum_out_typed_handle() { |
15146 | return c10::Dispatcher::singleton() |
15147 | .findSchemaOrThrow(sum_out::name, sum_out::overload_name) |
15148 | .typed<sum_out::schema>(); |
15149 | } |
15150 | |
15151 | // aten::sum.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
15152 | at::Tensor & sum_out::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15153 | |
15154 | static auto op = create_sum_out_typed_handle(); |
15155 | return op.call(self, dtype, out); |
15156 | } |
15157 | |
15158 | // aten::sum.out(Tensor self, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
15159 | at::Tensor & sum_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15160 | |
15161 | static auto op = create_sum_out_typed_handle(); |
15162 | return op.redispatch(dispatchKeySet, self, dtype, out); |
15163 | } |
15164 | |
15165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rot90_out, name, "aten::rot90" ) |
15166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rot90_out, overload_name, "out" ) |
15167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(rot90_out, schema_str, "rot90.out(Tensor self, int k=1, int[] dims=[0,1], *, Tensor(a!) out) -> Tensor(a!)" ) |
15168 | |
15169 | // aten::rot90.out(Tensor self, int k=1, int[] dims=[0,1], *, Tensor(a!) out) -> Tensor(a!) |
15170 | static C10_NOINLINE c10::TypedOperatorHandle<rot90_out::schema> create_rot90_out_typed_handle() { |
15171 | return c10::Dispatcher::singleton() |
15172 | .findSchemaOrThrow(rot90_out::name, rot90_out::overload_name) |
15173 | .typed<rot90_out::schema>(); |
15174 | } |
15175 | |
15176 | // aten::rot90.out(Tensor self, int k=1, int[] dims=[0,1], *, Tensor(a!) out) -> Tensor(a!) |
15177 | at::Tensor & rot90_out::call(const at::Tensor & self, int64_t k, at::IntArrayRef dims, at::Tensor & out) { |
15178 | |
15179 | static auto op = create_rot90_out_typed_handle(); |
15180 | return op.call(self, k, dims, out); |
15181 | } |
15182 | |
15183 | // aten::rot90.out(Tensor self, int k=1, int[] dims=[0,1], *, Tensor(a!) out) -> Tensor(a!) |
15184 | at::Tensor & rot90_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t k, at::IntArrayRef dims, at::Tensor & out) { |
15185 | |
15186 | static auto op = create_rot90_out_typed_handle(); |
15187 | return op.redispatch(dispatchKeySet, self, k, dims, out); |
15188 | } |
15189 | |
15190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_strides_out, name, "aten::_nested_tensor_strides" ) |
15191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_strides_out, overload_name, "out" ) |
15192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_strides_out, schema_str, "_nested_tensor_strides.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
15193 | |
15194 | // aten::_nested_tensor_strides.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
15195 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_strides_out::schema> create__nested_tensor_strides_out_typed_handle() { |
15196 | return c10::Dispatcher::singleton() |
15197 | .findSchemaOrThrow(_nested_tensor_strides_out::name, _nested_tensor_strides_out::overload_name) |
15198 | .typed<_nested_tensor_strides_out::schema>(); |
15199 | } |
15200 | |
15201 | // aten::_nested_tensor_strides.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
15202 | at::Tensor & _nested_tensor_strides_out::call(const at::Tensor & self, at::Tensor & out) { |
15203 | |
15204 | static auto op = create__nested_tensor_strides_out_typed_handle(); |
15205 | return op.call(self, out); |
15206 | } |
15207 | |
15208 | // aten::_nested_tensor_strides.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
15209 | at::Tensor & _nested_tensor_strides_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
15210 | |
15211 | static auto op = create__nested_tensor_strides_out_typed_handle(); |
15212 | return op.redispatch(dispatchKeySet, self, out); |
15213 | } |
15214 | |
15215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction_out, name, "aten::var_mean" ) |
15216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction_out, overload_name, "correction_out" ) |
15217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(var_mean_correction_out, schema_str, "var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))" ) |
15218 | |
15219 | // aten::var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15220 | static C10_NOINLINE c10::TypedOperatorHandle<var_mean_correction_out::schema> create_var_mean_correction_out_typed_handle() { |
15221 | return c10::Dispatcher::singleton() |
15222 | .findSchemaOrThrow(var_mean_correction_out::name, var_mean_correction_out::overload_name) |
15223 | .typed<var_mean_correction_out::schema>(); |
15224 | } |
15225 | |
15226 | // aten::var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15227 | ::std::tuple<at::Tensor &,at::Tensor &> var_mean_correction_out::call(const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim, at::Tensor & out0, at::Tensor & out1) { |
15228 | |
15229 | static auto op = create_var_mean_correction_out_typed_handle(); |
15230 | return op.call(self, dim, correction, keepdim, out0, out1); |
15231 | } |
15232 | |
15233 | // aten::var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15234 | ::std::tuple<at::Tensor &,at::Tensor &> var_mean_correction_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::OptionalIntArrayRef dim, c10::optional<int64_t> correction, bool keepdim, at::Tensor & out0, at::Tensor & out1) { |
15235 | |
15236 | static auto op = create_var_mean_correction_out_typed_handle(); |
15237 | return op.redispatch(dispatchKeySet, self, dim, correction, keepdim, out0, out1); |
15238 | } |
15239 | |
15240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_grad_out, name, "aten::_standard_gamma_grad" ) |
15241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_grad_out, overload_name, "out" ) |
15242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_standard_gamma_grad_out, schema_str, "_standard_gamma_grad.out(Tensor self, Tensor output, *, Tensor(a!) out) -> Tensor(a!)" ) |
15243 | |
15244 | // aten::_standard_gamma_grad.out(Tensor self, Tensor output, *, Tensor(a!) out) -> Tensor(a!) |
15245 | static C10_NOINLINE c10::TypedOperatorHandle<_standard_gamma_grad_out::schema> create__standard_gamma_grad_out_typed_handle() { |
15246 | return c10::Dispatcher::singleton() |
15247 | .findSchemaOrThrow(_standard_gamma_grad_out::name, _standard_gamma_grad_out::overload_name) |
15248 | .typed<_standard_gamma_grad_out::schema>(); |
15249 | } |
15250 | |
15251 | // aten::_standard_gamma_grad.out(Tensor self, Tensor output, *, Tensor(a!) out) -> Tensor(a!) |
15252 | at::Tensor & _standard_gamma_grad_out::call(const at::Tensor & self, const at::Tensor & output, at::Tensor & out) { |
15253 | |
15254 | static auto op = create__standard_gamma_grad_out_typed_handle(); |
15255 | return op.call(self, output, out); |
15256 | } |
15257 | |
15258 | // aten::_standard_gamma_grad.out(Tensor self, Tensor output, *, Tensor(a!) out) -> Tensor(a!) |
15259 | at::Tensor & _standard_gamma_grad_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & output, at::Tensor & out) { |
15260 | |
15261 | static auto op = create__standard_gamma_grad_out_typed_handle(); |
15262 | return op.redispatch(dispatchKeySet, self, output, out); |
15263 | } |
15264 | |
15265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_out, name, "aten::native_norm" ) |
15266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_out, overload_name, "out" ) |
15267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_out, schema_str, "native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!)" ) |
15268 | |
15269 | // aten::native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
15270 | static C10_NOINLINE c10::TypedOperatorHandle<native_norm_out::schema> create_native_norm_out_typed_handle() { |
15271 | return c10::Dispatcher::singleton() |
15272 | .findSchemaOrThrow(native_norm_out::name, native_norm_out::overload_name) |
15273 | .typed<native_norm_out::schema>(); |
15274 | } |
15275 | |
15276 | // aten::native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
15277 | at::Tensor & native_norm_out::call(const at::Tensor & self, const at::Scalar & p, at::Tensor & out) { |
15278 | |
15279 | static auto op = create_native_norm_out_typed_handle(); |
15280 | return op.call(self, p, out); |
15281 | } |
15282 | |
15283 | // aten::native_norm.out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
15284 | at::Tensor & native_norm_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p, at::Tensor & out) { |
15285 | |
15286 | static auto op = create_native_norm_out_typed_handle(); |
15287 | return op.redispatch(dispatchKeySet, self, p, out); |
15288 | } |
15289 | |
15290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_ScalarOpt_dim_dtype_out, name, "aten::native_norm" ) |
15291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_ScalarOpt_dim_dtype_out, overload_name, "ScalarOpt_dim_dtype_out" ) |
15292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(native_norm_ScalarOpt_dim_dtype_out, schema_str, "native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!)" ) |
15293 | |
15294 | // aten::native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!) |
15295 | static C10_NOINLINE c10::TypedOperatorHandle<native_norm_ScalarOpt_dim_dtype_out::schema> create_native_norm_ScalarOpt_dim_dtype_out_typed_handle() { |
15296 | return c10::Dispatcher::singleton() |
15297 | .findSchemaOrThrow(native_norm_ScalarOpt_dim_dtype_out::name, native_norm_ScalarOpt_dim_dtype_out::overload_name) |
15298 | .typed<native_norm_ScalarOpt_dim_dtype_out::schema>(); |
15299 | } |
15300 | |
15301 | // aten::native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!) |
15302 | at::Tensor & native_norm_ScalarOpt_dim_dtype_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15303 | |
15304 | static auto op = create_native_norm_ScalarOpt_dim_dtype_out_typed_handle(); |
15305 | return op.call(self, p, dim, keepdim, dtype, out); |
15306 | } |
15307 | |
15308 | // aten::native_norm.ScalarOpt_dim_dtype_out(Tensor self, Scalar? p, int[1] dim, bool keepdim, ScalarType? dtype, *, Tensor(a!) out) -> Tensor(a!) |
15309 | at::Tensor & native_norm_ScalarOpt_dim_dtype_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15310 | |
15311 | static auto op = create_native_norm_ScalarOpt_dim_dtype_out_typed_handle(); |
15312 | return op.redispatch(dispatchKeySet, self, p, dim, keepdim, dtype, out); |
15313 | } |
15314 | |
15315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_backward_out, name, "aten::_sparse_sum_backward" ) |
15316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_backward_out, overload_name, "out" ) |
15317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_sum_backward_out, schema_str, "_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!)" ) |
15318 | |
15319 | // aten::_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) |
15320 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_sum_backward_out::schema> create__sparse_sum_backward_out_typed_handle() { |
15321 | return c10::Dispatcher::singleton() |
15322 | .findSchemaOrThrow(_sparse_sum_backward_out::name, _sparse_sum_backward_out::overload_name) |
15323 | .typed<_sparse_sum_backward_out::schema>(); |
15324 | } |
15325 | |
15326 | // aten::_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) |
15327 | at::Tensor & _sparse_sum_backward_out::call(const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { |
15328 | |
15329 | static auto op = create__sparse_sum_backward_out_typed_handle(); |
15330 | return op.call(grad, self, dim, out); |
15331 | } |
15332 | |
15333 | // aten::_sparse_sum_backward.out(Tensor grad, Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) |
15334 | at::Tensor & _sparse_sum_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad, const at::Tensor & self, at::IntArrayRef dim, at::Tensor & out) { |
15335 | |
15336 | static auto op = create__sparse_sum_backward_out_typed_handle(); |
15337 | return op.redispatch(dispatchKeySet, grad, self, dim, out); |
15338 | } |
15339 | |
15340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_sum_dim_dtype_out, name, "aten::_sparse_csr_sum" ) |
15341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_sum_dim_dtype_out, overload_name, "dim_dtype_out" ) |
15342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_csr_sum_dim_dtype_out, schema_str, "_sparse_csr_sum.dim_dtype_out(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)" ) |
15343 | |
15344 | // aten::_sparse_csr_sum.dim_dtype_out(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
15345 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_csr_sum_dim_dtype_out::schema> create__sparse_csr_sum_dim_dtype_out_typed_handle() { |
15346 | return c10::Dispatcher::singleton() |
15347 | .findSchemaOrThrow(_sparse_csr_sum_dim_dtype_out::name, _sparse_csr_sum_dim_dtype_out::overload_name) |
15348 | .typed<_sparse_csr_sum_dim_dtype_out::schema>(); |
15349 | } |
15350 | |
15351 | // aten::_sparse_csr_sum.dim_dtype_out(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
15352 | at::Tensor & _sparse_csr_sum_dim_dtype_out::call(const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15353 | |
15354 | static auto op = create__sparse_csr_sum_dim_dtype_out_typed_handle(); |
15355 | return op.call(self, dim, keepdim, dtype, out); |
15356 | } |
15357 | |
15358 | // aten::_sparse_csr_sum.dim_dtype_out(Tensor self, int[1] dim, bool keepdim=False, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!) |
15359 | at::Tensor & _sparse_csr_sum_dim_dtype_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef dim, bool keepdim, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15360 | |
15361 | static auto op = create__sparse_csr_sum_dim_dtype_out_typed_handle(); |
15362 | return op.redispatch(dispatchKeySet, self, dim, keepdim, dtype, out); |
15363 | } |
15364 | |
15365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_out, name, "aten::_sparse_softmax" ) |
15366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_out, overload_name, "out" ) |
15367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_softmax_out, schema_str, "_sparse_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!)" ) |
15368 | |
15369 | // aten::_sparse_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!) |
15370 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_softmax_out::schema> create__sparse_softmax_out_typed_handle() { |
15371 | return c10::Dispatcher::singleton() |
15372 | .findSchemaOrThrow(_sparse_softmax_out::name, _sparse_softmax_out::overload_name) |
15373 | .typed<_sparse_softmax_out::schema>(); |
15374 | } |
15375 | |
15376 | // aten::_sparse_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!) |
15377 | at::Tensor & _sparse_softmax_out::call(const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out) { |
15378 | |
15379 | static auto op = create__sparse_softmax_out_typed_handle(); |
15380 | return op.call(self, dim, half_to_float, out); |
15381 | } |
15382 | |
15383 | // aten::_sparse_softmax.out(Tensor self, int dim, bool half_to_float, *, Tensor(a!) out) -> Tensor(a!) |
15384 | at::Tensor & _sparse_softmax_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim, bool half_to_float, at::Tensor & out) { |
15385 | |
15386 | static auto op = create__sparse_softmax_out_typed_handle(); |
15387 | return op.redispatch(dispatchKeySet, self, dim, half_to_float, out); |
15388 | } |
15389 | |
15390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dtype_out, name, "aten::norm" ) |
15391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dtype_out, overload_name, "ScalarOpt_dtype_out" ) |
15392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_ScalarOpt_dtype_out, schema_str, "norm.ScalarOpt_dtype_out(Tensor self, Scalar? p, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!)" ) |
15393 | |
15394 | // aten::norm.ScalarOpt_dtype_out(Tensor self, Scalar? p, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
15395 | static C10_NOINLINE c10::TypedOperatorHandle<norm_ScalarOpt_dtype_out::schema> create_norm_ScalarOpt_dtype_out_typed_handle() { |
15396 | return c10::Dispatcher::singleton() |
15397 | .findSchemaOrThrow(norm_ScalarOpt_dtype_out::name, norm_ScalarOpt_dtype_out::overload_name) |
15398 | .typed<norm_ScalarOpt_dtype_out::schema>(); |
15399 | } |
15400 | |
15401 | // aten::norm.ScalarOpt_dtype_out(Tensor self, Scalar? p, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
15402 | at::Tensor & norm_ScalarOpt_dtype_out::call(const at::Tensor & self, const c10::optional<at::Scalar> & p, at::ScalarType dtype, at::Tensor & out) { |
15403 | |
15404 | static auto op = create_norm_ScalarOpt_dtype_out_typed_handle(); |
15405 | return op.call(self, p, dtype, out); |
15406 | } |
15407 | |
15408 | // aten::norm.ScalarOpt_dtype_out(Tensor self, Scalar? p, *, ScalarType dtype, Tensor(a!) out) -> Tensor(a!) |
15409 | at::Tensor & norm_ScalarOpt_dtype_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const c10::optional<at::Scalar> & p, at::ScalarType dtype, at::Tensor & out) { |
15410 | |
15411 | static auto op = create_norm_ScalarOpt_dtype_out_typed_handle(); |
15412 | return op.redispatch(dispatchKeySet, self, p, dtype, out); |
15413 | } |
15414 | |
15415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_Scalar_out, name, "aten::norm" ) |
15416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_Scalar_out, overload_name, "Scalar_out" ) |
15417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(norm_Scalar_out, schema_str, "norm.Scalar_out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!)" ) |
15418 | |
15419 | // aten::norm.Scalar_out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
15420 | static C10_NOINLINE c10::TypedOperatorHandle<norm_Scalar_out::schema> create_norm_Scalar_out_typed_handle() { |
15421 | return c10::Dispatcher::singleton() |
15422 | .findSchemaOrThrow(norm_Scalar_out::name, norm_Scalar_out::overload_name) |
15423 | .typed<norm_Scalar_out::schema>(); |
15424 | } |
15425 | |
15426 | // aten::norm.Scalar_out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
15427 | at::Tensor & norm_Scalar_out::call(const at::Tensor & self, const at::Scalar & p, at::Tensor & out) { |
15428 | |
15429 | static auto op = create_norm_Scalar_out_typed_handle(); |
15430 | return op.call(self, p, out); |
15431 | } |
15432 | |
15433 | // aten::norm.Scalar_out(Tensor self, Scalar p=2, *, Tensor(a!) out) -> Tensor(a!) |
15434 | at::Tensor & norm_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Scalar & p, at::Tensor & out) { |
15435 | |
15436 | static auto op = create_norm_Scalar_out_typed_handle(); |
15437 | return op.redispatch(dispatchKeySet, self, p, out); |
15438 | } |
15439 | |
15440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_with_dims_and_tensors_out, name, "aten::_sparse_coo_tensor_with_dims_and_tensors" ) |
15441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_with_dims_and_tensors_out, overload_name, "out" ) |
15442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_coo_tensor_with_dims_and_tensors_out, schema_str, "_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!)" ) |
15443 | |
15444 | // aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) |
15445 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_coo_tensor_with_dims_and_tensors_out::schema> create__sparse_coo_tensor_with_dims_and_tensors_out_typed_handle() { |
15446 | return c10::Dispatcher::singleton() |
15447 | .findSchemaOrThrow(_sparse_coo_tensor_with_dims_and_tensors_out::name, _sparse_coo_tensor_with_dims_and_tensors_out::overload_name) |
15448 | .typed<_sparse_coo_tensor_with_dims_and_tensors_out::schema>(); |
15449 | } |
15450 | |
15451 | // aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) |
15452 | at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_out::call(int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, at::Tensor & out) { |
15453 | |
15454 | static auto op = create__sparse_coo_tensor_with_dims_and_tensors_out_typed_handle(); |
15455 | return op.call(sparse_dim, dense_dim, size, indices, values, out); |
15456 | } |
15457 | |
15458 | // aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) |
15459 | at::Tensor & _sparse_coo_tensor_with_dims_and_tensors_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t sparse_dim, int64_t dense_dim, c10::SymIntArrayRef size, const at::Tensor & indices, const at::Tensor & values, at::Tensor & out) { |
15460 | |
15461 | static auto op = create__sparse_coo_tensor_with_dims_and_tensors_out_typed_handle(); |
15462 | return op.redispatch(dispatchKeySet, sparse_dim, dense_dim, size, indices, values, out); |
15463 | } |
15464 | |
15465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_dense_out, name, "aten::_to_dense" ) |
15466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_dense_out, overload_name, "out" ) |
15467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_to_dense_out, schema_str, "_to_dense.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
15468 | |
15469 | // aten::_to_dense.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
15470 | static C10_NOINLINE c10::TypedOperatorHandle<_to_dense_out::schema> create__to_dense_out_typed_handle() { |
15471 | return c10::Dispatcher::singleton() |
15472 | .findSchemaOrThrow(_to_dense_out::name, _to_dense_out::overload_name) |
15473 | .typed<_to_dense_out::schema>(); |
15474 | } |
15475 | |
15476 | // aten::_to_dense.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
15477 | at::Tensor & _to_dense_out::call(const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15478 | |
15479 | static auto op = create__to_dense_out_typed_handle(); |
15480 | return op.call(self, dtype, out); |
15481 | } |
15482 | |
15483 | // aten::_to_dense.out(Tensor self, ScalarType? dtype=None, *, Tensor(a!) out) -> Tensor(a!) |
15484 | at::Tensor & _to_dense_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::optional<at::ScalarType> dtype, at::Tensor & out) { |
15485 | |
15486 | static auto op = create__to_dense_out_typed_handle(); |
15487 | return op.redispatch(dispatchKeySet, self, dtype, out); |
15488 | } |
15489 | |
15490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced_out, name, "aten::_coalesced" ) |
15491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced_out, overload_name, "out" ) |
15492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced_out, schema_str, "_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!)" ) |
15493 | |
15494 | // aten::_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!) |
15495 | static C10_NOINLINE c10::TypedOperatorHandle<_coalesced_out::schema> create__coalesced_out_typed_handle() { |
15496 | return c10::Dispatcher::singleton() |
15497 | .findSchemaOrThrow(_coalesced_out::name, _coalesced_out::overload_name) |
15498 | .typed<_coalesced_out::schema>(); |
15499 | } |
15500 | |
15501 | // aten::_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!) |
15502 | at::Tensor & _coalesced_out::call(const at::Tensor & self, bool coalesced, at::Tensor & out) { |
15503 | |
15504 | static auto op = create__coalesced_out_typed_handle(); |
15505 | return op.call(self, coalesced, out); |
15506 | } |
15507 | |
15508 | // aten::_coalesced.out(Tensor self, bool coalesced, *, Tensor(a!) out) -> Tensor(a!) |
15509 | at::Tensor & _coalesced_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool coalesced, at::Tensor & out) { |
15510 | |
15511 | static auto op = create__coalesced_out_typed_handle(); |
15512 | return op.redispatch(dispatchKeySet, self, coalesced, out); |
15513 | } |
15514 | |
15515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced, name, "aten::_coalesced" ) |
15516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced, overload_name, "" ) |
15517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_coalesced, schema_str, "_coalesced(Tensor self, bool coalesced) -> Tensor" ) |
15518 | |
15519 | // aten::_coalesced(Tensor self, bool coalesced) -> Tensor |
15520 | static C10_NOINLINE c10::TypedOperatorHandle<_coalesced::schema> create__coalesced_typed_handle() { |
15521 | return c10::Dispatcher::singleton() |
15522 | .findSchemaOrThrow(_coalesced::name, _coalesced::overload_name) |
15523 | .typed<_coalesced::schema>(); |
15524 | } |
15525 | |
15526 | // aten::_coalesced(Tensor self, bool coalesced) -> Tensor |
15527 | at::Tensor _coalesced::call(const at::Tensor & self, bool coalesced) { |
15528 | |
15529 | static auto op = create__coalesced_typed_handle(); |
15530 | return op.call(self, coalesced); |
15531 | } |
15532 | |
15533 | // aten::_coalesced(Tensor self, bool coalesced) -> Tensor |
15534 | at::Tensor _coalesced::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, bool coalesced) { |
15535 | |
15536 | static auto op = create__coalesced_typed_handle(); |
15537 | return op.redispatch(dispatchKeySet, self, coalesced); |
15538 | } |
15539 | |
15540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsc_out, name, "aten::to_sparse_bsc" ) |
15541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsc_out, overload_name, "out" ) |
15542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(to_sparse_bsc_out, schema_str, "to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
15543 | |
15544 | // aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
15545 | static C10_NOINLINE c10::TypedOperatorHandle<to_sparse_bsc_out::schema> create_to_sparse_bsc_out_typed_handle() { |
15546 | return c10::Dispatcher::singleton() |
15547 | .findSchemaOrThrow(to_sparse_bsc_out::name, to_sparse_bsc_out::overload_name) |
15548 | .typed<to_sparse_bsc_out::schema>(); |
15549 | } |
15550 | |
15551 | // aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
15552 | at::Tensor & to_sparse_bsc_out::call(const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
15553 | |
15554 | static auto op = create_to_sparse_bsc_out_typed_handle(); |
15555 | return op.call(self, blocksize, dense_dim, out); |
15556 | } |
15557 | |
15558 | // aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) |
15559 | at::Tensor & to_sparse_bsc_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef blocksize, c10::optional<int64_t> dense_dim, at::Tensor & out) { |
15560 | |
15561 | static auto op = create_to_sparse_bsc_out_typed_handle(); |
15562 | return op.redispatch(dispatchKeySet, self, blocksize, dense_dim, out); |
15563 | } |
15564 | |
15565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_dynamic_out, name, "aten::quantize_per_tensor_dynamic" ) |
15566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_dynamic_out, overload_name, "out" ) |
15567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_dynamic_out, schema_str, "quantize_per_tensor_dynamic.out(Tensor self, ScalarType dtype, bool reduce_range, *, Tensor(a!) out) -> Tensor(a!)" ) |
15568 | |
15569 | // aten::quantize_per_tensor_dynamic.out(Tensor self, ScalarType dtype, bool reduce_range, *, Tensor(a!) out) -> Tensor(a!) |
15570 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor_dynamic_out::schema> create_quantize_per_tensor_dynamic_out_typed_handle() { |
15571 | return c10::Dispatcher::singleton() |
15572 | .findSchemaOrThrow(quantize_per_tensor_dynamic_out::name, quantize_per_tensor_dynamic_out::overload_name) |
15573 | .typed<quantize_per_tensor_dynamic_out::schema>(); |
15574 | } |
15575 | |
15576 | // aten::quantize_per_tensor_dynamic.out(Tensor self, ScalarType dtype, bool reduce_range, *, Tensor(a!) out) -> Tensor(a!) |
15577 | at::Tensor & quantize_per_tensor_dynamic_out::call(const at::Tensor & self, at::ScalarType dtype, bool reduce_range, at::Tensor & out) { |
15578 | |
15579 | static auto op = create_quantize_per_tensor_dynamic_out_typed_handle(); |
15580 | return op.call(self, dtype, reduce_range, out); |
15581 | } |
15582 | |
15583 | // aten::quantize_per_tensor_dynamic.out(Tensor self, ScalarType dtype, bool reduce_range, *, Tensor(a!) out) -> Tensor(a!) |
15584 | at::Tensor & quantize_per_tensor_dynamic_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype, bool reduce_range, at::Tensor & out) { |
15585 | |
15586 | static auto op = create_quantize_per_tensor_dynamic_out_typed_handle(); |
15587 | return op.redispatch(dispatchKeySet, self, dtype, reduce_range, out); |
15588 | } |
15589 | |
15590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_out, name, "aten::quantize_per_tensor" ) |
15591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_out, overload_name, "out" ) |
15592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_out, schema_str, "quantize_per_tensor.out(Tensor self, float scale, int zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)" ) |
15593 | |
15594 | // aten::quantize_per_tensor.out(Tensor self, float scale, int zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
15595 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor_out::schema> create_quantize_per_tensor_out_typed_handle() { |
15596 | return c10::Dispatcher::singleton() |
15597 | .findSchemaOrThrow(quantize_per_tensor_out::name, quantize_per_tensor_out::overload_name) |
15598 | .typed<quantize_per_tensor_out::schema>(); |
15599 | } |
15600 | |
15601 | // aten::quantize_per_tensor.out(Tensor self, float scale, int zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
15602 | at::Tensor & quantize_per_tensor_out::call(const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype, at::Tensor & out) { |
15603 | |
15604 | static auto op = create_quantize_per_tensor_out_typed_handle(); |
15605 | return op.call(self, scale, zero_point, dtype, out); |
15606 | } |
15607 | |
15608 | // aten::quantize_per_tensor.out(Tensor self, float scale, int zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
15609 | at::Tensor & quantize_per_tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, at::ScalarType dtype, at::Tensor & out) { |
15610 | |
15611 | static auto op = create_quantize_per_tensor_out_typed_handle(); |
15612 | return op.redispatch(dispatchKeySet, self, scale, zero_point, dtype, out); |
15613 | } |
15614 | |
15615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensor_qparams_out, name, "aten::quantize_per_tensor" ) |
15616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensor_qparams_out, overload_name, "tensor_qparams_out" ) |
15617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensor_qparams_out, schema_str, "quantize_per_tensor.tensor_qparams_out(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)" ) |
15618 | |
15619 | // aten::quantize_per_tensor.tensor_qparams_out(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
15620 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor_tensor_qparams_out::schema> create_quantize_per_tensor_tensor_qparams_out_typed_handle() { |
15621 | return c10::Dispatcher::singleton() |
15622 | .findSchemaOrThrow(quantize_per_tensor_tensor_qparams_out::name, quantize_per_tensor_tensor_qparams_out::overload_name) |
15623 | .typed<quantize_per_tensor_tensor_qparams_out::schema>(); |
15624 | } |
15625 | |
15626 | // aten::quantize_per_tensor.tensor_qparams_out(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
15627 | at::Tensor & quantize_per_tensor_tensor_qparams_out::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype, at::Tensor & out) { |
15628 | |
15629 | static auto op = create_quantize_per_tensor_tensor_qparams_out_typed_handle(); |
15630 | return op.call(self, scale, zero_point, dtype, out); |
15631 | } |
15632 | |
15633 | // aten::quantize_per_tensor.tensor_qparams_out(Tensor self, Tensor scale, Tensor zero_point, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
15634 | at::Tensor & quantize_per_tensor_tensor_qparams_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, at::ScalarType dtype, at::Tensor & out) { |
15635 | |
15636 | static auto op = create_quantize_per_tensor_tensor_qparams_out_typed_handle(); |
15637 | return op.redispatch(dispatchKeySet, self, scale, zero_point, dtype, out); |
15638 | } |
15639 | |
15640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensors_out, name, "aten::quantize_per_tensor" ) |
15641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensors_out, overload_name, "tensors_out" ) |
15642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(quantize_per_tensor_tensors_out, schema_str, "quantize_per_tensor.tensors_out(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype, *, Tensor(a!)[] out) -> ()" ) |
15643 | |
15644 | // aten::quantize_per_tensor.tensors_out(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype, *, Tensor(a!)[] out) -> () |
15645 | static C10_NOINLINE c10::TypedOperatorHandle<quantize_per_tensor_tensors_out::schema> create_quantize_per_tensor_tensors_out_typed_handle() { |
15646 | return c10::Dispatcher::singleton() |
15647 | .findSchemaOrThrow(quantize_per_tensor_tensors_out::name, quantize_per_tensor_tensors_out::overload_name) |
15648 | .typed<quantize_per_tensor_tensors_out::schema>(); |
15649 | } |
15650 | |
15651 | // aten::quantize_per_tensor.tensors_out(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype, *, Tensor(a!)[] out) -> () |
15652 | void quantize_per_tensor_tensors_out::call(at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype, at::TensorList out) { |
15653 | |
15654 | static auto op = create_quantize_per_tensor_tensors_out_typed_handle(); |
15655 | return op.call(tensors, scales, zero_points, dtype, out); |
15656 | } |
15657 | |
15658 | // aten::quantize_per_tensor.tensors_out(Tensor[] tensors, Tensor scales, Tensor zero_points, ScalarType dtype, *, Tensor(a!)[] out) -> () |
15659 | void quantize_per_tensor_tensors_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList tensors, const at::Tensor & scales, const at::Tensor & zero_points, at::ScalarType dtype, at::TensorList out) { |
15660 | |
15661 | static auto op = create_quantize_per_tensor_tensors_out_typed_handle(); |
15662 | return op.redispatch(dispatchKeySet, tensors, scales, zero_points, dtype, out); |
15663 | } |
15664 | |
15665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask_out, name, "aten::fake_quantize_per_tensor_affine_cachemask" ) |
15666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask_out, overload_name, "out" ) |
15667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(fake_quantize_per_tensor_affine_cachemask_out, schema_str, "fake_quantize_per_tensor_affine_cachemask.out(Tensor self, float scale, int zero_point, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))" ) |
15668 | |
15669 | // aten::fake_quantize_per_tensor_affine_cachemask.out(Tensor self, float scale, int zero_point, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15670 | static C10_NOINLINE c10::TypedOperatorHandle<fake_quantize_per_tensor_affine_cachemask_out::schema> create_fake_quantize_per_tensor_affine_cachemask_out_typed_handle() { |
15671 | return c10::Dispatcher::singleton() |
15672 | .findSchemaOrThrow(fake_quantize_per_tensor_affine_cachemask_out::name, fake_quantize_per_tensor_affine_cachemask_out::overload_name) |
15673 | .typed<fake_quantize_per_tensor_affine_cachemask_out::schema>(); |
15674 | } |
15675 | |
15676 | // aten::fake_quantize_per_tensor_affine_cachemask.out(Tensor self, float scale, int zero_point, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15677 | ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_tensor_affine_cachemask_out::call(const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { |
15678 | |
15679 | static auto op = create_fake_quantize_per_tensor_affine_cachemask_out_typed_handle(); |
15680 | return op.call(self, scale, zero_point, quant_min, quant_max, out0, out1); |
15681 | } |
15682 | |
15683 | // aten::fake_quantize_per_tensor_affine_cachemask.out(Tensor self, float scale, int zero_point, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15684 | ::std::tuple<at::Tensor &,at::Tensor &> fake_quantize_per_tensor_affine_cachemask_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double scale, int64_t zero_point, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { |
15685 | |
15686 | static auto op = create_fake_quantize_per_tensor_affine_cachemask_out_typed_handle(); |
15687 | return op.redispatch(dispatchKeySet, self, scale, zero_point, quant_min, quant_max, out0, out1); |
15688 | } |
15689 | |
15690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out, name, "aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams" ) |
15691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out, overload_name, "out" ) |
15692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out, schema_str, "_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.out(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!))" ) |
15693 | |
15694 | // aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.out(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15695 | static C10_NOINLINE c10::TypedOperatorHandle<_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::schema> create__fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out_typed_handle() { |
15696 | return c10::Dispatcher::singleton() |
15697 | .findSchemaOrThrow(_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::name, _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::overload_name) |
15698 | .typed<_fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::schema>(); |
15699 | } |
15700 | |
15701 | // aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.out(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15702 | ::std::tuple<at::Tensor &,at::Tensor &> _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { |
15703 | |
15704 | static auto op = create__fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out_typed_handle(); |
15705 | return op.call(self, scale, zero_point, fake_quant_enabled, quant_min, quant_max, out0, out1); |
15706 | } |
15707 | |
15708 | // aten::_fake_quantize_per_tensor_affine_cachemask_tensor_qparams.out(Tensor self, Tensor scale, Tensor zero_point, Tensor fake_quant_enabled, int quant_min, int quant_max, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) |
15709 | ::std::tuple<at::Tensor &,at::Tensor &> _fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, const at::Tensor & fake_quant_enabled, int64_t quant_min, int64_t quant_max, at::Tensor & out0, at::Tensor & out1) { |
15710 | |
15711 | static auto op = create__fake_quantize_per_tensor_affine_cachemask_tensor_qparams_out_typed_handle(); |
15712 | return op.redispatch(dispatchKeySet, self, scale, zero_point, fake_quant_enabled, quant_min, quant_max, out0, out1); |
15713 | } |
15714 | |
15715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_learnable_per_tensor_affine_out, name, "aten::_fake_quantize_learnable_per_tensor_affine" ) |
15716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_learnable_per_tensor_affine_out, overload_name, "out" ) |
15717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fake_quantize_learnable_per_tensor_affine_out, schema_str, "_fake_quantize_learnable_per_tensor_affine.out(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!)" ) |
15718 | |
15719 | // aten::_fake_quantize_learnable_per_tensor_affine.out(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!) |
15720 | static C10_NOINLINE c10::TypedOperatorHandle<_fake_quantize_learnable_per_tensor_affine_out::schema> create__fake_quantize_learnable_per_tensor_affine_out_typed_handle() { |
15721 | return c10::Dispatcher::singleton() |
15722 | .findSchemaOrThrow(_fake_quantize_learnable_per_tensor_affine_out::name, _fake_quantize_learnable_per_tensor_affine_out::overload_name) |
15723 | .typed<_fake_quantize_learnable_per_tensor_affine_out::schema>(); |
15724 | } |
15725 | |
15726 | // aten::_fake_quantize_learnable_per_tensor_affine.out(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!) |
15727 | at::Tensor & _fake_quantize_learnable_per_tensor_affine_out::call(const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor, at::Tensor & out) { |
15728 | |
15729 | static auto op = create__fake_quantize_learnable_per_tensor_affine_out_typed_handle(); |
15730 | return op.call(self, scale, zero_point, quant_min, quant_max, grad_factor, out); |
15731 | } |
15732 | |
15733 | // aten::_fake_quantize_learnable_per_tensor_affine.out(Tensor self, Tensor scale, Tensor zero_point, int quant_min, int quant_max, float grad_factor=1.0, *, Tensor(a!) out) -> Tensor(a!) |
15734 | at::Tensor & _fake_quantize_learnable_per_tensor_affine_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & scale, const at::Tensor & zero_point, int64_t quant_min, int64_t quant_max, double grad_factor, at::Tensor & out) { |
15735 | |
15736 | static auto op = create__fake_quantize_learnable_per_tensor_affine_out_typed_handle(); |
15737 | return op.redispatch(dispatchKeySet, self, scale, zero_point, quant_min, quant_max, grad_factor, out); |
15738 | } |
15739 | |
15740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_gru_cell_backward_out, name, "aten::_thnn_fused_gru_cell_backward" ) |
15741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_gru_cell_backward_out, overload_name, "out" ) |
15742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_thnn_fused_gru_cell_backward_out, schema_str, "_thnn_fused_gru_cell_backward.out(Tensor grad_hy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!))" ) |
15743 | |
15744 | // aten::_thnn_fused_gru_cell_backward.out(Tensor grad_hy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
15745 | static C10_NOINLINE c10::TypedOperatorHandle<_thnn_fused_gru_cell_backward_out::schema> create__thnn_fused_gru_cell_backward_out_typed_handle() { |
15746 | return c10::Dispatcher::singleton() |
15747 | .findSchemaOrThrow(_thnn_fused_gru_cell_backward_out::name, _thnn_fused_gru_cell_backward_out::overload_name) |
15748 | .typed<_thnn_fused_gru_cell_backward_out::schema>(); |
15749 | } |
15750 | |
15751 | // aten::_thnn_fused_gru_cell_backward.out(Tensor grad_hy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
15752 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _thnn_fused_gru_cell_backward_out::call(const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { |
15753 | |
15754 | static auto op = create__thnn_fused_gru_cell_backward_out_typed_handle(); |
15755 | return op.call(grad_hy, workspace, has_bias, out0, out1, out2, out3, out4); |
15756 | } |
15757 | |
15758 | // aten::_thnn_fused_gru_cell_backward.out(Tensor grad_hy, Tensor workspace, bool has_bias, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) |
15759 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _thnn_fused_gru_cell_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_hy, const at::Tensor & workspace, bool has_bias, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3, at::Tensor & out4) { |
15760 | |
15761 | static auto op = create__thnn_fused_gru_cell_backward_out_typed_handle(); |
15762 | return op.redispatch(dispatchKeySet, grad_hy, workspace, has_bias, out0, out1, out2, out3, out4); |
15763 | } |
15764 | |
15765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_out, name, "aten::set" ) |
15766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_out, overload_name, "source_Storage_out" ) |
15767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_out, schema_str, "set.source_Storage_out(Tensor self, Storage source, *, Tensor(a!) out) -> Tensor(a!)" ) |
15768 | |
15769 | // aten::set.source_Storage_out(Tensor self, Storage source, *, Tensor(a!) out) -> Tensor(a!) |
15770 | static C10_NOINLINE c10::TypedOperatorHandle<set_source_Storage_out::schema> create_set_source_Storage_out_typed_handle() { |
15771 | return c10::Dispatcher::singleton() |
15772 | .findSchemaOrThrow(set_source_Storage_out::name, set_source_Storage_out::overload_name) |
15773 | .typed<set_source_Storage_out::schema>(); |
15774 | } |
15775 | |
15776 | // aten::set.source_Storage_out(Tensor self, Storage source, *, Tensor(a!) out) -> Tensor(a!) |
15777 | at::Tensor & set_source_Storage_out::call(const at::Tensor & self, at::Storage source, at::Tensor & out) { |
15778 | |
15779 | static auto op = create_set_source_Storage_out_typed_handle(); |
15780 | return op.call(self, source, out); |
15781 | } |
15782 | |
15783 | // aten::set.source_Storage_out(Tensor self, Storage source, *, Tensor(a!) out) -> Tensor(a!) |
15784 | at::Tensor & set_source_Storage_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source, at::Tensor & out) { |
15785 | |
15786 | static auto op = create_set_source_Storage_out_typed_handle(); |
15787 | return op.redispatch(dispatchKeySet, self, source, out); |
15788 | } |
15789 | |
15790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage, name, "aten::set" ) |
15791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage, overload_name, "source_Storage" ) |
15792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage, schema_str, "set.source_Storage(Tensor self, Storage source) -> Tensor" ) |
15793 | |
15794 | // aten::set.source_Storage(Tensor self, Storage source) -> Tensor |
15795 | static C10_NOINLINE c10::TypedOperatorHandle<set_source_Storage::schema> create_set_source_Storage_typed_handle() { |
15796 | return c10::Dispatcher::singleton() |
15797 | .findSchemaOrThrow(set_source_Storage::name, set_source_Storage::overload_name) |
15798 | .typed<set_source_Storage::schema>(); |
15799 | } |
15800 | |
15801 | // aten::set.source_Storage(Tensor self, Storage source) -> Tensor |
15802 | at::Tensor set_source_Storage::call(const at::Tensor & self, at::Storage source) { |
15803 | |
15804 | static auto op = create_set_source_Storage_typed_handle(); |
15805 | return op.call(self, source); |
15806 | } |
15807 | |
15808 | // aten::set.source_Storage(Tensor self, Storage source) -> Tensor |
15809 | at::Tensor set_source_Storage::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source) { |
15810 | |
15811 | static auto op = create_set_source_Storage_typed_handle(); |
15812 | return op.redispatch(dispatchKeySet, self, source); |
15813 | } |
15814 | |
15815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_storage_offset_out, name, "aten::set" ) |
15816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_storage_offset_out, overload_name, "source_Storage_storage_offset_out" ) |
15817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_storage_offset_out, schema_str, "set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!)" ) |
15818 | |
15819 | // aten::set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!) |
15820 | static C10_NOINLINE c10::TypedOperatorHandle<set_source_Storage_storage_offset_out::schema> create_set_source_Storage_storage_offset_out_typed_handle() { |
15821 | return c10::Dispatcher::singleton() |
15822 | .findSchemaOrThrow(set_source_Storage_storage_offset_out::name, set_source_Storage_storage_offset_out::overload_name) |
15823 | .typed<set_source_Storage_storage_offset_out::schema>(); |
15824 | } |
15825 | |
15826 | // aten::set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!) |
15827 | at::Tensor & set_source_Storage_storage_offset_out::call(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { |
15828 | |
15829 | static auto op = create_set_source_Storage_storage_offset_out_typed_handle(); |
15830 | return op.call(self, source, storage_offset, size, stride, out); |
15831 | } |
15832 | |
15833 | // aten::set.source_Storage_storage_offset_out(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[], *, Tensor(a!) out) -> Tensor(a!) |
15834 | at::Tensor & set_source_Storage_storage_offset_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride, at::Tensor & out) { |
15835 | |
15836 | static auto op = create_set_source_Storage_storage_offset_out_typed_handle(); |
15837 | return op.redispatch(dispatchKeySet, self, source, storage_offset, size, stride, out); |
15838 | } |
15839 | |
15840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_storage_offset, name, "aten::set" ) |
15841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_storage_offset, overload_name, "source_Storage_storage_offset" ) |
15842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Storage_storage_offset, schema_str, "set.source_Storage_storage_offset(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor" ) |
15843 | |
15844 | // aten::set.source_Storage_storage_offset(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor |
15845 | static C10_NOINLINE c10::TypedOperatorHandle<set_source_Storage_storage_offset::schema> create_set_source_Storage_storage_offset_typed_handle() { |
15846 | return c10::Dispatcher::singleton() |
15847 | .findSchemaOrThrow(set_source_Storage_storage_offset::name, set_source_Storage_storage_offset::overload_name) |
15848 | .typed<set_source_Storage_storage_offset::schema>(); |
15849 | } |
15850 | |
15851 | // aten::set.source_Storage_storage_offset(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor |
15852 | at::Tensor set_source_Storage_storage_offset::call(const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { |
15853 | |
15854 | static auto op = create_set_source_Storage_storage_offset_typed_handle(); |
15855 | return op.call(self, source, storage_offset, size, stride); |
15856 | } |
15857 | |
15858 | // aten::set.source_Storage_storage_offset(Tensor self, Storage source, SymInt storage_offset, SymInt[] size, SymInt[] stride=[]) -> Tensor |
15859 | at::Tensor set_source_Storage_storage_offset::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Storage source, c10::SymInt storage_offset, c10::SymIntArrayRef size, c10::SymIntArrayRef stride) { |
15860 | |
15861 | static auto op = create_set_source_Storage_storage_offset_typed_handle(); |
15862 | return op.redispatch(dispatchKeySet, self, source, storage_offset, size, stride); |
15863 | } |
15864 | |
15865 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Tensor_out, name, "aten::set" ) |
15866 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Tensor_out, overload_name, "source_Tensor_out" ) |
15867 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Tensor_out, schema_str, "set.source_Tensor_out(Tensor self, Tensor source, *, Tensor(a!) out) -> Tensor(a!)" ) |
15868 | |
15869 | // aten::set.source_Tensor_out(Tensor self, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
15870 | static C10_NOINLINE c10::TypedOperatorHandle<set_source_Tensor_out::schema> create_set_source_Tensor_out_typed_handle() { |
15871 | return c10::Dispatcher::singleton() |
15872 | .findSchemaOrThrow(set_source_Tensor_out::name, set_source_Tensor_out::overload_name) |
15873 | .typed<set_source_Tensor_out::schema>(); |
15874 | } |
15875 | |
15876 | // aten::set.source_Tensor_out(Tensor self, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
15877 | at::Tensor & set_source_Tensor_out::call(const at::Tensor & self, const at::Tensor & source, at::Tensor & out) { |
15878 | |
15879 | static auto op = create_set_source_Tensor_out_typed_handle(); |
15880 | return op.call(self, source, out); |
15881 | } |
15882 | |
15883 | // aten::set.source_Tensor_out(Tensor self, Tensor source, *, Tensor(a!) out) -> Tensor(a!) |
15884 | at::Tensor & set_source_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & source, at::Tensor & out) { |
15885 | |
15886 | static auto op = create_set_source_Tensor_out_typed_handle(); |
15887 | return op.redispatch(dispatchKeySet, self, source, out); |
15888 | } |
15889 | |
15890 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Tensor, name, "aten::set" ) |
15891 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Tensor, overload_name, "source_Tensor" ) |
15892 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_source_Tensor, schema_str, "set.source_Tensor(Tensor self, Tensor source) -> Tensor" ) |
15893 | |
15894 | // aten::set.source_Tensor(Tensor self, Tensor source) -> Tensor |
15895 | static C10_NOINLINE c10::TypedOperatorHandle<set_source_Tensor::schema> create_set_source_Tensor_typed_handle() { |
15896 | return c10::Dispatcher::singleton() |
15897 | .findSchemaOrThrow(set_source_Tensor::name, set_source_Tensor::overload_name) |
15898 | .typed<set_source_Tensor::schema>(); |
15899 | } |
15900 | |
15901 | // aten::set.source_Tensor(Tensor self, Tensor source) -> Tensor |
15902 | at::Tensor set_source_Tensor::call(const at::Tensor & self, const at::Tensor & source) { |
15903 | |
15904 | static auto op = create_set_source_Tensor_typed_handle(); |
15905 | return op.call(self, source); |
15906 | } |
15907 | |
15908 | // aten::set.source_Tensor(Tensor self, Tensor source) -> Tensor |
15909 | at::Tensor set_source_Tensor::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & source) { |
15910 | |
15911 | static auto op = create_set_source_Tensor_typed_handle(); |
15912 | return op.redispatch(dispatchKeySet, self, source); |
15913 | } |
15914 | |
15915 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_out, name, "aten::set" ) |
15916 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_out, overload_name, "out" ) |
15917 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set_out, schema_str, "set.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
15918 | |
15919 | // aten::set.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
15920 | static C10_NOINLINE c10::TypedOperatorHandle<set_out::schema> create_set_out_typed_handle() { |
15921 | return c10::Dispatcher::singleton() |
15922 | .findSchemaOrThrow(set_out::name, set_out::overload_name) |
15923 | .typed<set_out::schema>(); |
15924 | } |
15925 | |
15926 | // aten::set.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
15927 | at::Tensor & set_out::call(const at::Tensor & self, at::Tensor & out) { |
15928 | |
15929 | static auto op = create_set_out_typed_handle(); |
15930 | return op.call(self, out); |
15931 | } |
15932 | |
15933 | // aten::set.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
15934 | at::Tensor & set_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
15935 | |
15936 | static auto op = create_set_out_typed_handle(); |
15937 | return op.redispatch(dispatchKeySet, self, out); |
15938 | } |
15939 | |
15940 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set, name, "aten::set" ) |
15941 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set, overload_name, "" ) |
15942 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(set, schema_str, "set(Tensor self) -> Tensor" ) |
15943 | |
15944 | // aten::set(Tensor self) -> Tensor |
15945 | static C10_NOINLINE c10::TypedOperatorHandle<set::schema> create_set_typed_handle() { |
15946 | return c10::Dispatcher::singleton() |
15947 | .findSchemaOrThrow(set::name, set::overload_name) |
15948 | .typed<set::schema>(); |
15949 | } |
15950 | |
15951 | // aten::set(Tensor self) -> Tensor |
15952 | at::Tensor set::call(const at::Tensor & self) { |
15953 | |
15954 | static auto op = create_set_typed_handle(); |
15955 | return op.call(self); |
15956 | } |
15957 | |
15958 | // aten::set(Tensor self) -> Tensor |
15959 | at::Tensor set::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self) { |
15960 | |
15961 | static auto op = create_set_typed_handle(); |
15962 | return op.redispatch(dispatchKeySet, self); |
15963 | } |
15964 | |
15965 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put_out, name, "aten::put" ) |
15966 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put_out, overload_name, "out" ) |
15967 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(put_out, schema_str, "put.out(Tensor self, Tensor index, Tensor source, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!)" ) |
15968 | |
15969 | // aten::put.out(Tensor self, Tensor index, Tensor source, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) |
15970 | static C10_NOINLINE c10::TypedOperatorHandle<put_out::schema> create_put_out_typed_handle() { |
15971 | return c10::Dispatcher::singleton() |
15972 | .findSchemaOrThrow(put_out::name, put_out::overload_name) |
15973 | .typed<put_out::schema>(); |
15974 | } |
15975 | |
15976 | // aten::put.out(Tensor self, Tensor index, Tensor source, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) |
15977 | at::Tensor & put_out::call(const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate, at::Tensor & out) { |
15978 | |
15979 | static auto op = create_put_out_typed_handle(); |
15980 | return op.call(self, index, source, accumulate, out); |
15981 | } |
15982 | |
15983 | // aten::put.out(Tensor self, Tensor index, Tensor source, bool accumulate=False, *, Tensor(a!) out) -> Tensor(a!) |
15984 | at::Tensor & put_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & index, const at::Tensor & source, bool accumulate, at::Tensor & out) { |
15985 | |
15986 | static auto op = create_put_out_typed_handle(); |
15987 | return op.redispatch(dispatchKeySet, self, index, source, accumulate, out); |
15988 | } |
15989 | |
15990 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform_out, name, "aten::uniform" ) |
15991 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform_out, overload_name, "out" ) |
15992 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform_out, schema_str, "uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!)" ) |
15993 | |
15994 | // aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
15995 | static C10_NOINLINE c10::TypedOperatorHandle<uniform_out::schema> create_uniform_out_typed_handle() { |
15996 | return c10::Dispatcher::singleton() |
15997 | .findSchemaOrThrow(uniform_out::name, uniform_out::overload_name) |
15998 | .typed<uniform_out::schema>(); |
15999 | } |
16000 | |
16001 | // aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
16002 | at::Tensor & uniform_out::call(const at::Tensor & self, double from, double to, c10::optional<at::Generator> generator, at::Tensor & out) { |
16003 | |
16004 | static auto op = create_uniform_out_typed_handle(); |
16005 | return op.call(self, from, to, generator, out); |
16006 | } |
16007 | |
16008 | // aten::uniform.out(Tensor self, float from=0, float to=1, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) |
16009 | at::Tensor & uniform_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double from, double to, c10::optional<at::Generator> generator, at::Tensor & out) { |
16010 | |
16011 | static auto op = create_uniform_out_typed_handle(); |
16012 | return op.redispatch(dispatchKeySet, self, from, to, generator, out); |
16013 | } |
16014 | |
16015 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform, name, "aten::uniform" ) |
16016 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform, overload_name, "" ) |
16017 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(uniform, schema_str, "uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor" ) |
16018 | |
16019 | // aten::uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor |
16020 | static C10_NOINLINE c10::TypedOperatorHandle<uniform::schema> create_uniform_typed_handle() { |
16021 | return c10::Dispatcher::singleton() |
16022 | .findSchemaOrThrow(uniform::name, uniform::overload_name) |
16023 | .typed<uniform::schema>(); |
16024 | } |
16025 | |
16026 | // aten::uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor |
16027 | at::Tensor uniform::call(const at::Tensor & self, double from, double to, c10::optional<at::Generator> generator) { |
16028 | |
16029 | static auto op = create_uniform_typed_handle(); |
16030 | return op.call(self, from, to, generator); |
16031 | } |
16032 | |
16033 | // aten::uniform(Tensor self, float from=0, float to=1, *, Generator? generator=None) -> Tensor |
16034 | at::Tensor uniform::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, double from, double to, c10::optional<at::Generator> generator) { |
16035 | |
16036 | static auto op = create_uniform_typed_handle(); |
16037 | return op.redispatch(dispatchKeySet, self, from, to, generator); |
16038 | } |
16039 | |
16040 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_indices_out, name, "aten::tril_indices" ) |
16041 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_indices_out, overload_name, "out" ) |
16042 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(tril_indices_out, schema_str, "tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!)" ) |
16043 | |
16044 | // aten::tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!) |
16045 | static C10_NOINLINE c10::TypedOperatorHandle<tril_indices_out::schema> create_tril_indices_out_typed_handle() { |
16046 | return c10::Dispatcher::singleton() |
16047 | .findSchemaOrThrow(tril_indices_out::name, tril_indices_out::overload_name) |
16048 | .typed<tril_indices_out::schema>(); |
16049 | } |
16050 | |
16051 | // aten::tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!) |
16052 | at::Tensor & tril_indices_out::call(int64_t row, int64_t col, int64_t offset, at::Tensor & out) { |
16053 | |
16054 | static auto op = create_tril_indices_out_typed_handle(); |
16055 | return op.call(row, col, offset, out); |
16056 | } |
16057 | |
16058 | // aten::tril_indices.out(int row, int col, int offset=0, *, Tensor(a!) out) -> Tensor(a!) |
16059 | at::Tensor & tril_indices_out::redispatch(c10::DispatchKeySet dispatchKeySet, int64_t row, int64_t col, int64_t offset, at::Tensor & out) { |
16060 | |
16061 | static auto op = create_tril_indices_out_typed_handle(); |
16062 | return op.redispatch(dispatchKeySet, row, col, offset, out); |
16063 | } |
16064 | |
16065 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cholesky_solve_helper_out, name, "aten::_cholesky_solve_helper" ) |
16066 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cholesky_solve_helper_out, overload_name, "out" ) |
16067 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_cholesky_solve_helper_out, schema_str, "_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!)" ) |
16068 | |
16069 | // aten::_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!) |
16070 | static C10_NOINLINE c10::TypedOperatorHandle<_cholesky_solve_helper_out::schema> create__cholesky_solve_helper_out_typed_handle() { |
16071 | return c10::Dispatcher::singleton() |
16072 | .findSchemaOrThrow(_cholesky_solve_helper_out::name, _cholesky_solve_helper_out::overload_name) |
16073 | .typed<_cholesky_solve_helper_out::schema>(); |
16074 | } |
16075 | |
16076 | // aten::_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!) |
16077 | at::Tensor & _cholesky_solve_helper_out::call(const at::Tensor & self, const at::Tensor & A, bool upper, at::Tensor & out) { |
16078 | |
16079 | static auto op = create__cholesky_solve_helper_out_typed_handle(); |
16080 | return op.call(self, A, upper, out); |
16081 | } |
16082 | |
16083 | // aten::_cholesky_solve_helper.out(Tensor self, Tensor A, bool upper, *, Tensor(a!) out) -> Tensor(a!) |
16084 | at::Tensor & _cholesky_solve_helper_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & A, bool upper, at::Tensor & out) { |
16085 | |
16086 | static auto op = create__cholesky_solve_helper_out_typed_handle(); |
16087 | return op.redispatch(dispatchKeySet, self, A, upper, out); |
16088 | } |
16089 | |
16090 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale_out, name, "aten::_amp_update_scale" ) |
16091 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale_out, overload_name, "out" ) |
16092 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale_out, schema_str, "_amp_update_scale.out(Tensor self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval, *, Tensor(a!) out) -> Tensor(a!)" ) |
16093 | |
16094 | // aten::_amp_update_scale.out(Tensor self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval, *, Tensor(a!) out) -> Tensor(a!) |
16095 | static C10_NOINLINE c10::TypedOperatorHandle<_amp_update_scale_out::schema> create__amp_update_scale_out_typed_handle() { |
16096 | return c10::Dispatcher::singleton() |
16097 | .findSchemaOrThrow(_amp_update_scale_out::name, _amp_update_scale_out::overload_name) |
16098 | .typed<_amp_update_scale_out::schema>(); |
16099 | } |
16100 | |
16101 | // aten::_amp_update_scale.out(Tensor self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval, *, Tensor(a!) out) -> Tensor(a!) |
16102 | at::Tensor & _amp_update_scale_out::call(const at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval, at::Tensor & out) { |
16103 | |
16104 | static auto op = create__amp_update_scale_out_typed_handle(); |
16105 | return op.call(self, growth_tracker, found_inf, scale_growth_factor, scale_backoff_factor, growth_interval, out); |
16106 | } |
16107 | |
16108 | // aten::_amp_update_scale.out(Tensor self, Tensor(b!) growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval, *, Tensor(a!) out) -> Tensor(a!) |
16109 | at::Tensor & _amp_update_scale_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval, at::Tensor & out) { |
16110 | |
16111 | static auto op = create__amp_update_scale_out_typed_handle(); |
16112 | return op.redispatch(dispatchKeySet, self, growth_tracker, found_inf, scale_growth_factor, scale_backoff_factor, growth_interval, out); |
16113 | } |
16114 | |
16115 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale, name, "aten::_amp_update_scale" ) |
16116 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale, overload_name, "" ) |
16117 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_amp_update_scale, schema_str, "_amp_update_scale(Tensor self, Tensor growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> (Tensor, Tensor growth_tracker_out)" ) |
16118 | |
16119 | // aten::_amp_update_scale(Tensor self, Tensor growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> (Tensor, Tensor growth_tracker_out) |
16120 | static C10_NOINLINE c10::TypedOperatorHandle<_amp_update_scale::schema> create__amp_update_scale_typed_handle() { |
16121 | return c10::Dispatcher::singleton() |
16122 | .findSchemaOrThrow(_amp_update_scale::name, _amp_update_scale::overload_name) |
16123 | .typed<_amp_update_scale::schema>(); |
16124 | } |
16125 | |
16126 | // aten::_amp_update_scale(Tensor self, Tensor growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> (Tensor, Tensor growth_tracker_out) |
16127 | ::std::tuple<at::Tensor,at::Tensor> _amp_update_scale::call(const at::Tensor & self, const at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval) { |
16128 | |
16129 | static auto op = create__amp_update_scale_typed_handle(); |
16130 | return op.call(self, growth_tracker, found_inf, scale_growth_factor, scale_backoff_factor, growth_interval); |
16131 | } |
16132 | |
16133 | // aten::_amp_update_scale(Tensor self, Tensor growth_tracker, Tensor found_inf, float scale_growth_factor, float scale_backoff_factor, int growth_interval) -> (Tensor, Tensor growth_tracker_out) |
16134 | ::std::tuple<at::Tensor,at::Tensor> _amp_update_scale::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, const at::Tensor & growth_tracker, const at::Tensor & found_inf, double scale_growth_factor, double scale_backoff_factor, int64_t growth_interval) { |
16135 | |
16136 | static auto op = create__amp_update_scale_typed_handle(); |
16137 | return op.redispatch(dispatchKeySet, self, growth_tracker, found_inf, scale_growth_factor, scale_backoff_factor, growth_interval); |
16138 | } |
16139 | |
16140 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp_out, name, "aten::_foreach_exp" ) |
16141 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp_out, overload_name, "out" ) |
16142 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_exp_out, schema_str, "_foreach_exp.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16143 | |
16144 | // aten::_foreach_exp.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16145 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_exp_out::schema> create__foreach_exp_out_typed_handle() { |
16146 | return c10::Dispatcher::singleton() |
16147 | .findSchemaOrThrow(_foreach_exp_out::name, _foreach_exp_out::overload_name) |
16148 | .typed<_foreach_exp_out::schema>(); |
16149 | } |
16150 | |
16151 | // aten::_foreach_exp.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16152 | void _foreach_exp_out::call(at::TensorList self, at::TensorList out) { |
16153 | |
16154 | static auto op = create__foreach_exp_out_typed_handle(); |
16155 | return op.call(self, out); |
16156 | } |
16157 | |
16158 | // aten::_foreach_exp.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16159 | void _foreach_exp_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16160 | |
16161 | static auto op = create__foreach_exp_out_typed_handle(); |
16162 | return op.redispatch(dispatchKeySet, self, out); |
16163 | } |
16164 | |
16165 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt_out, name, "aten::_foreach_sqrt" ) |
16166 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt_out, overload_name, "out" ) |
16167 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sqrt_out, schema_str, "_foreach_sqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16168 | |
16169 | // aten::_foreach_sqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16170 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sqrt_out::schema> create__foreach_sqrt_out_typed_handle() { |
16171 | return c10::Dispatcher::singleton() |
16172 | .findSchemaOrThrow(_foreach_sqrt_out::name, _foreach_sqrt_out::overload_name) |
16173 | .typed<_foreach_sqrt_out::schema>(); |
16174 | } |
16175 | |
16176 | // aten::_foreach_sqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16177 | void _foreach_sqrt_out::call(at::TensorList self, at::TensorList out) { |
16178 | |
16179 | static auto op = create__foreach_sqrt_out_typed_handle(); |
16180 | return op.call(self, out); |
16181 | } |
16182 | |
16183 | // aten::_foreach_sqrt.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16184 | void _foreach_sqrt_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16185 | |
16186 | static auto op = create__foreach_sqrt_out_typed_handle(); |
16187 | return op.redispatch(dispatchKeySet, self, out); |
16188 | } |
16189 | |
16190 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log_out, name, "aten::_foreach_log" ) |
16191 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log_out, overload_name, "out" ) |
16192 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log_out, schema_str, "_foreach_log.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16193 | |
16194 | // aten::_foreach_log.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16195 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log_out::schema> create__foreach_log_out_typed_handle() { |
16196 | return c10::Dispatcher::singleton() |
16197 | .findSchemaOrThrow(_foreach_log_out::name, _foreach_log_out::overload_name) |
16198 | .typed<_foreach_log_out::schema>(); |
16199 | } |
16200 | |
16201 | // aten::_foreach_log.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16202 | void _foreach_log_out::call(at::TensorList self, at::TensorList out) { |
16203 | |
16204 | static auto op = create__foreach_log_out_typed_handle(); |
16205 | return op.call(self, out); |
16206 | } |
16207 | |
16208 | // aten::_foreach_log.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16209 | void _foreach_log_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16210 | |
16211 | static auto op = create__foreach_log_out_typed_handle(); |
16212 | return op.redispatch(dispatchKeySet, self, out); |
16213 | } |
16214 | |
16215 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p_out, name, "aten::_foreach_log1p" ) |
16216 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p_out, overload_name, "out" ) |
16217 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_log1p_out, schema_str, "_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16218 | |
16219 | // aten::_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16220 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_log1p_out::schema> create__foreach_log1p_out_typed_handle() { |
16221 | return c10::Dispatcher::singleton() |
16222 | .findSchemaOrThrow(_foreach_log1p_out::name, _foreach_log1p_out::overload_name) |
16223 | .typed<_foreach_log1p_out::schema>(); |
16224 | } |
16225 | |
16226 | // aten::_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16227 | void _foreach_log1p_out::call(at::TensorList self, at::TensorList out) { |
16228 | |
16229 | static auto op = create__foreach_log1p_out_typed_handle(); |
16230 | return op.call(self, out); |
16231 | } |
16232 | |
16233 | // aten::_foreach_log1p.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16234 | void _foreach_log1p_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16235 | |
16236 | static auto op = create__foreach_log1p_out_typed_handle(); |
16237 | return op.redispatch(dispatchKeySet, self, out); |
16238 | } |
16239 | |
16240 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg_out, name, "aten::_foreach_neg" ) |
16241 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg_out, overload_name, "out" ) |
16242 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_neg_out, schema_str, "_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16243 | |
16244 | // aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16245 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_neg_out::schema> create__foreach_neg_out_typed_handle() { |
16246 | return c10::Dispatcher::singleton() |
16247 | .findSchemaOrThrow(_foreach_neg_out::name, _foreach_neg_out::overload_name) |
16248 | .typed<_foreach_neg_out::schema>(); |
16249 | } |
16250 | |
16251 | // aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16252 | void _foreach_neg_out::call(at::TensorList self, at::TensorList out) { |
16253 | |
16254 | static auto op = create__foreach_neg_out_typed_handle(); |
16255 | return op.call(self, out); |
16256 | } |
16257 | |
16258 | // aten::_foreach_neg.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16259 | void _foreach_neg_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16260 | |
16261 | static auto op = create__foreach_neg_out_typed_handle(); |
16262 | return op.redispatch(dispatchKeySet, self, out); |
16263 | } |
16264 | |
16265 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin_out, name, "aten::_foreach_sin" ) |
16266 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin_out, overload_name, "out" ) |
16267 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sin_out, schema_str, "_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16268 | |
16269 | // aten::_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16270 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sin_out::schema> create__foreach_sin_out_typed_handle() { |
16271 | return c10::Dispatcher::singleton() |
16272 | .findSchemaOrThrow(_foreach_sin_out::name, _foreach_sin_out::overload_name) |
16273 | .typed<_foreach_sin_out::schema>(); |
16274 | } |
16275 | |
16276 | // aten::_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16277 | void _foreach_sin_out::call(at::TensorList self, at::TensorList out) { |
16278 | |
16279 | static auto op = create__foreach_sin_out_typed_handle(); |
16280 | return op.call(self, out); |
16281 | } |
16282 | |
16283 | // aten::_foreach_sin.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16284 | void _foreach_sin_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16285 | |
16286 | static auto op = create__foreach_sin_out_typed_handle(); |
16287 | return op.redispatch(dispatchKeySet, self, out); |
16288 | } |
16289 | |
16290 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal_out, name, "aten::_foreach_reciprocal" ) |
16291 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal_out, overload_name, "out" ) |
16292 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_reciprocal_out, schema_str, "_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16293 | |
16294 | // aten::_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16295 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_reciprocal_out::schema> create__foreach_reciprocal_out_typed_handle() { |
16296 | return c10::Dispatcher::singleton() |
16297 | .findSchemaOrThrow(_foreach_reciprocal_out::name, _foreach_reciprocal_out::overload_name) |
16298 | .typed<_foreach_reciprocal_out::schema>(); |
16299 | } |
16300 | |
16301 | // aten::_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16302 | void _foreach_reciprocal_out::call(at::TensorList self, at::TensorList out) { |
16303 | |
16304 | static auto op = create__foreach_reciprocal_out_typed_handle(); |
16305 | return op.call(self, out); |
16306 | } |
16307 | |
16308 | // aten::_foreach_reciprocal.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16309 | void _foreach_reciprocal_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16310 | |
16311 | static auto op = create__foreach_reciprocal_out_typed_handle(); |
16312 | return op.redispatch(dispatchKeySet, self, out); |
16313 | } |
16314 | |
16315 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid_out, name, "aten::_foreach_sigmoid" ) |
16316 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid_out, overload_name, "out" ) |
16317 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_sigmoid_out, schema_str, "_foreach_sigmoid.out(Tensor[] self, *, Tensor(a!)[] out) -> ()" ) |
16318 | |
16319 | // aten::_foreach_sigmoid.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16320 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_sigmoid_out::schema> create__foreach_sigmoid_out_typed_handle() { |
16321 | return c10::Dispatcher::singleton() |
16322 | .findSchemaOrThrow(_foreach_sigmoid_out::name, _foreach_sigmoid_out::overload_name) |
16323 | .typed<_foreach_sigmoid_out::schema>(); |
16324 | } |
16325 | |
16326 | // aten::_foreach_sigmoid.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16327 | void _foreach_sigmoid_out::call(at::TensorList self, at::TensorList out) { |
16328 | |
16329 | static auto op = create__foreach_sigmoid_out_typed_handle(); |
16330 | return op.call(self, out); |
16331 | } |
16332 | |
16333 | // aten::_foreach_sigmoid.out(Tensor[] self, *, Tensor(a!)[] out) -> () |
16334 | void _foreach_sigmoid_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList out) { |
16335 | |
16336 | static auto op = create__foreach_sigmoid_out_typed_handle(); |
16337 | return op.redispatch(dispatchKeySet, self, out); |
16338 | } |
16339 | |
16340 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Scalar_out, name, "aten::_foreach_addcdiv" ) |
16341 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Scalar_out, overload_name, "Scalar_out" ) |
16342 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Scalar_out, schema_str, "_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> ()" ) |
16343 | |
16344 | // aten::_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> () |
16345 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv_Scalar_out::schema> create__foreach_addcdiv_Scalar_out_typed_handle() { |
16346 | return c10::Dispatcher::singleton() |
16347 | .findSchemaOrThrow(_foreach_addcdiv_Scalar_out::name, _foreach_addcdiv_Scalar_out::overload_name) |
16348 | .typed<_foreach_addcdiv_Scalar_out::schema>(); |
16349 | } |
16350 | |
16351 | // aten::_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> () |
16352 | void _foreach_addcdiv_Scalar_out::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out) { |
16353 | |
16354 | static auto op = create__foreach_addcdiv_Scalar_out_typed_handle(); |
16355 | return op.call(self, tensor1, tensor2, value, out); |
16356 | } |
16357 | |
16358 | // aten::_foreach_addcdiv.Scalar_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1, *, Tensor(a!)[] out) -> () |
16359 | void _foreach_addcdiv_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Scalar & value, at::TensorList out) { |
16360 | |
16361 | static auto op = create__foreach_addcdiv_Scalar_out_typed_handle(); |
16362 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, value, out); |
16363 | } |
16364 | |
16365 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_ScalarList_out, name, "aten::_foreach_addcdiv" ) |
16366 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_ScalarList_out, overload_name, "ScalarList_out" ) |
16367 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_ScalarList_out, schema_str, "_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> ()" ) |
16368 | |
16369 | // aten::_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
16370 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv_ScalarList_out::schema> create__foreach_addcdiv_ScalarList_out_typed_handle() { |
16371 | return c10::Dispatcher::singleton() |
16372 | .findSchemaOrThrow(_foreach_addcdiv_ScalarList_out::name, _foreach_addcdiv_ScalarList_out::overload_name) |
16373 | .typed<_foreach_addcdiv_ScalarList_out::schema>(); |
16374 | } |
16375 | |
16376 | // aten::_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
16377 | void _foreach_addcdiv_ScalarList_out::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
16378 | |
16379 | static auto op = create__foreach_addcdiv_ScalarList_out_typed_handle(); |
16380 | return op.call(self, tensor1, tensor2, scalars, out); |
16381 | } |
16382 | |
16383 | // aten::_foreach_addcdiv.ScalarList_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars, *, Tensor(a!)[] out) -> () |
16384 | void _foreach_addcdiv_ScalarList_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, at::ArrayRef<at::Scalar> scalars, at::TensorList out) { |
16385 | |
16386 | static auto op = create__foreach_addcdiv_ScalarList_out_typed_handle(); |
16387 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, scalars, out); |
16388 | } |
16389 | |
16390 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Tensor_out, name, "aten::_foreach_addcdiv" ) |
16391 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Tensor_out, overload_name, "Tensor_out" ) |
16392 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_addcdiv_Tensor_out, schema_str, "_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> ()" ) |
16393 | |
16394 | // aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () |
16395 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_addcdiv_Tensor_out::schema> create__foreach_addcdiv_Tensor_out_typed_handle() { |
16396 | return c10::Dispatcher::singleton() |
16397 | .findSchemaOrThrow(_foreach_addcdiv_Tensor_out::name, _foreach_addcdiv_Tensor_out::overload_name) |
16398 | .typed<_foreach_addcdiv_Tensor_out::schema>(); |
16399 | } |
16400 | |
16401 | // aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () |
16402 | void _foreach_addcdiv_Tensor_out::call(at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out) { |
16403 | |
16404 | static auto op = create__foreach_addcdiv_Tensor_out_typed_handle(); |
16405 | return op.call(self, tensor1, tensor2, scalars, out); |
16406 | } |
16407 | |
16408 | // aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () |
16409 | void _foreach_addcdiv_Tensor_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList tensor1, at::TensorList tensor2, const at::Tensor & scalars, at::TensorList out) { |
16410 | |
16411 | static auto op = create__foreach_addcdiv_Tensor_out_typed_handle(); |
16412 | return op.redispatch(dispatchKeySet, self, tensor1, tensor2, scalars, out); |
16413 | } |
16414 | |
16415 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_norm_Scalar_out, name, "aten::_foreach_norm" ) |
16416 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_norm_Scalar_out, overload_name, "Scalar_out" ) |
16417 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_foreach_norm_Scalar_out, schema_str, "_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> ()" ) |
16418 | |
16419 | // aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () |
16420 | static C10_NOINLINE c10::TypedOperatorHandle<_foreach_norm_Scalar_out::schema> create__foreach_norm_Scalar_out_typed_handle() { |
16421 | return c10::Dispatcher::singleton() |
16422 | .findSchemaOrThrow(_foreach_norm_Scalar_out::name, _foreach_norm_Scalar_out::overload_name) |
16423 | .typed<_foreach_norm_Scalar_out::schema>(); |
16424 | } |
16425 | |
16426 | // aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () |
16427 | void _foreach_norm_Scalar_out::call(at::TensorList self, const at::Scalar & ord, at::TensorList out) { |
16428 | |
16429 | static auto op = create__foreach_norm_Scalar_out_typed_handle(); |
16430 | return op.call(self, ord, out); |
16431 | } |
16432 | |
16433 | // aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () |
16434 | void _foreach_norm_Scalar_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, const at::Scalar & ord, at::TensorList out) { |
16435 | |
16436 | static auto op = create__foreach_norm_Scalar_out_typed_handle(); |
16437 | return op.redispatch(dispatchKeySet, self, ord, out); |
16438 | } |
16439 | |
16440 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_jvp_out, name, "aten::glu_jvp" ) |
16441 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_jvp_out, overload_name, "out" ) |
16442 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(glu_jvp_out, schema_str, "glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!)" ) |
16443 | |
16444 | // aten::glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!) |
16445 | static C10_NOINLINE c10::TypedOperatorHandle<glu_jvp_out::schema> create_glu_jvp_out_typed_handle() { |
16446 | return c10::Dispatcher::singleton() |
16447 | .findSchemaOrThrow(glu_jvp_out::name, glu_jvp_out::overload_name) |
16448 | .typed<glu_jvp_out::schema>(); |
16449 | } |
16450 | |
16451 | // aten::glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!) |
16452 | at::Tensor & glu_jvp_out::call(const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out) { |
16453 | |
16454 | static auto op = create_glu_jvp_out_typed_handle(); |
16455 | return op.call(glu, x, dx, dim, out); |
16456 | } |
16457 | |
16458 | // aten::glu_jvp.out(Tensor glu, Tensor x, Tensor dx, int dim, *, Tensor(a!) out) -> Tensor(a!) |
16459 | at::Tensor & glu_jvp_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & glu, const at::Tensor & x, const at::Tensor & dx, int64_t dim, at::Tensor & out) { |
16460 | |
16461 | static auto op = create_glu_jvp_out_typed_handle(); |
16462 | return op.redispatch(dispatchKeySet, glu, x, dx, dim, out); |
16463 | } |
16464 | |
16465 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_backward_out, name, "aten::_adaptive_avg_pool2d_backward" ) |
16466 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_backward_out, overload_name, "out" ) |
16467 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_adaptive_avg_pool2d_backward_out, schema_str, "_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
16468 | |
16469 | // aten::_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16470 | static C10_NOINLINE c10::TypedOperatorHandle<_adaptive_avg_pool2d_backward_out::schema> create__adaptive_avg_pool2d_backward_out_typed_handle() { |
16471 | return c10::Dispatcher::singleton() |
16472 | .findSchemaOrThrow(_adaptive_avg_pool2d_backward_out::name, _adaptive_avg_pool2d_backward_out::overload_name) |
16473 | .typed<_adaptive_avg_pool2d_backward_out::schema>(); |
16474 | } |
16475 | |
16476 | // aten::_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16477 | at::Tensor & _adaptive_avg_pool2d_backward_out::call(const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { |
16478 | |
16479 | static auto op = create__adaptive_avg_pool2d_backward_out_typed_handle(); |
16480 | return op.call(grad_output, self, out); |
16481 | } |
16482 | |
16483 | // aten::_adaptive_avg_pool2d_backward.out(Tensor grad_output, Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16484 | at::Tensor & _adaptive_avg_pool2d_backward_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & grad_output, const at::Tensor & self, at::Tensor & out) { |
16485 | |
16486 | static auto op = create__adaptive_avg_pool2d_backward_out_typed_handle(); |
16487 | return op.redispatch(dispatchKeySet, grad_output, self, out); |
16488 | } |
16489 | |
16490 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_dilated3d_out, name, "aten::slow_conv_dilated3d" ) |
16491 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_dilated3d_out, overload_name, "out" ) |
16492 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(slow_conv_dilated3d_out, schema_str, "slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!)" ) |
16493 | |
16494 | // aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) |
16495 | static C10_NOINLINE c10::TypedOperatorHandle<slow_conv_dilated3d_out::schema> create_slow_conv_dilated3d_out_typed_handle() { |
16496 | return c10::Dispatcher::singleton() |
16497 | .findSchemaOrThrow(slow_conv_dilated3d_out::name, slow_conv_dilated3d_out::overload_name) |
16498 | .typed<slow_conv_dilated3d_out::schema>(); |
16499 | } |
16500 | |
16501 | // aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) |
16502 | at::Tensor & slow_conv_dilated3d_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, at::IntArrayRef dilation, at::Tensor & out) { |
16503 | |
16504 | static auto op = create_slow_conv_dilated3d_out_typed_handle(); |
16505 | return op.call(self, weight, kernel_size, bias, stride, padding, dilation, out); |
16506 | } |
16507 | |
16508 | // aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) |
16509 | at::Tensor & slow_conv_dilated3d_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, at::IntArrayRef dilation, at::Tensor & out) { |
16510 | |
16511 | static auto op = create_slow_conv_dilated3d_out_typed_handle(); |
16512 | return op.redispatch(dispatchKeySet, self, weight, kernel_size, bias, stride, padding, dilation, out); |
16513 | } |
16514 | |
16515 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isinf_out, name, "aten::isinf" ) |
16516 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isinf_out, overload_name, "out" ) |
16517 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(isinf_out, schema_str, "isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
16518 | |
16519 | // aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16520 | static C10_NOINLINE c10::TypedOperatorHandle<isinf_out::schema> create_isinf_out_typed_handle() { |
16521 | return c10::Dispatcher::singleton() |
16522 | .findSchemaOrThrow(isinf_out::name, isinf_out::overload_name) |
16523 | .typed<isinf_out::schema>(); |
16524 | } |
16525 | |
16526 | // aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16527 | at::Tensor & isinf_out::call(const at::Tensor & self, at::Tensor & out) { |
16528 | |
16529 | static auto op = create_isinf_out_typed_handle(); |
16530 | return op.call(self, out); |
16531 | } |
16532 | |
16533 | // aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16534 | at::Tensor & isinf_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
16535 | |
16536 | static auto op = create_isinf_out_typed_handle(); |
16537 | return op.redispatch(dispatchKeySet, self, out); |
16538 | } |
16539 | |
16540 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_floatlist_out, name, "aten::_test_optional_floatlist" ) |
16541 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_floatlist_out, overload_name, "out" ) |
16542 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_test_optional_floatlist_out, schema_str, "_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!)" ) |
16543 | |
16544 | // aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) |
16545 | static C10_NOINLINE c10::TypedOperatorHandle<_test_optional_floatlist_out::schema> create__test_optional_floatlist_out_typed_handle() { |
16546 | return c10::Dispatcher::singleton() |
16547 | .findSchemaOrThrow(_test_optional_floatlist_out::name, _test_optional_floatlist_out::overload_name) |
16548 | .typed<_test_optional_floatlist_out::schema>(); |
16549 | } |
16550 | |
16551 | // aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) |
16552 | at::Tensor & _test_optional_floatlist_out::call(const at::Tensor & values, c10::optional<at::ArrayRef<double>> addends, at::Tensor & out) { |
16553 | |
16554 | static auto op = create__test_optional_floatlist_out_typed_handle(); |
16555 | return op.call(values, addends, out); |
16556 | } |
16557 | |
16558 | // aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) |
16559 | at::Tensor & _test_optional_floatlist_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & values, c10::optional<at::ArrayRef<double>> addends, at::Tensor & out) { |
16560 | |
16561 | static auto op = create__test_optional_floatlist_out_typed_handle(); |
16562 | return op.redispatch(dispatchKeySet, values, addends, out); |
16563 | } |
16564 | |
16565 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_tensor_list_out, name, "aten::_nested_tensor_from_tensor_list" ) |
16566 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_tensor_list_out, overload_name, "out" ) |
16567 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_nested_tensor_from_tensor_list_out, schema_str, "_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!)" ) |
16568 | |
16569 | // aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) |
16570 | static C10_NOINLINE c10::TypedOperatorHandle<_nested_tensor_from_tensor_list_out::schema> create__nested_tensor_from_tensor_list_out_typed_handle() { |
16571 | return c10::Dispatcher::singleton() |
16572 | .findSchemaOrThrow(_nested_tensor_from_tensor_list_out::name, _nested_tensor_from_tensor_list_out::overload_name) |
16573 | .typed<_nested_tensor_from_tensor_list_out::schema>(); |
16574 | } |
16575 | |
16576 | // aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) |
16577 | at::Tensor & _nested_tensor_from_tensor_list_out::call(at::TensorList list, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, at::Tensor & out) { |
16578 | |
16579 | static auto op = create__nested_tensor_from_tensor_list_out_typed_handle(); |
16580 | return op.call(list, dtype, layout, device, pin_memory, out); |
16581 | } |
16582 | |
16583 | // aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) |
16584 | at::Tensor & _nested_tensor_from_tensor_list_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList list, c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout, c10::optional<at::Device> device, c10::optional<bool> pin_memory, at::Tensor & out) { |
16585 | |
16586 | static auto op = create__nested_tensor_from_tensor_list_out_typed_handle(); |
16587 | return op.redispatch(dispatchKeySet, list, dtype, layout, device, pin_memory, out); |
16588 | } |
16589 | |
16590 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_broadcast_to_copy_out, name, "aten::_sparse_broadcast_to_copy" ) |
16591 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_broadcast_to_copy_out, overload_name, "out" ) |
16592 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_sparse_broadcast_to_copy_out, schema_str, "_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!)" ) |
16593 | |
16594 | // aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) |
16595 | static C10_NOINLINE c10::TypedOperatorHandle<_sparse_broadcast_to_copy_out::schema> create__sparse_broadcast_to_copy_out_typed_handle() { |
16596 | return c10::Dispatcher::singleton() |
16597 | .findSchemaOrThrow(_sparse_broadcast_to_copy_out::name, _sparse_broadcast_to_copy_out::overload_name) |
16598 | .typed<_sparse_broadcast_to_copy_out::schema>(); |
16599 | } |
16600 | |
16601 | // aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) |
16602 | at::Tensor & _sparse_broadcast_to_copy_out::call(const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { |
16603 | |
16604 | static auto op = create__sparse_broadcast_to_copy_out_typed_handle(); |
16605 | return op.call(self, size, out); |
16606 | } |
16607 | |
16608 | // aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) |
16609 | at::Tensor & _sparse_broadcast_to_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::IntArrayRef size, at::Tensor & out) { |
16610 | |
16611 | static auto op = create__sparse_broadcast_to_copy_out_typed_handle(); |
16612 | return op.redispatch(dispatchKeySet, self, size, out); |
16613 | } |
16614 | |
16615 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(transpose_copy_int_out, name, "aten::transpose_copy" ) |
16616 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(transpose_copy_int_out, overload_name, "int_out" ) |
16617 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(transpose_copy_int_out, schema_str, "transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!)" ) |
16618 | |
16619 | // aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) |
16620 | static C10_NOINLINE c10::TypedOperatorHandle<transpose_copy_int_out::schema> create_transpose_copy_int_out_typed_handle() { |
16621 | return c10::Dispatcher::singleton() |
16622 | .findSchemaOrThrow(transpose_copy_int_out::name, transpose_copy_int_out::overload_name) |
16623 | .typed<transpose_copy_int_out::schema>(); |
16624 | } |
16625 | |
16626 | // aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) |
16627 | at::Tensor & transpose_copy_int_out::call(const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out) { |
16628 | |
16629 | static auto op = create_transpose_copy_int_out_typed_handle(); |
16630 | return op.call(self, dim0, dim1, out); |
16631 | } |
16632 | |
16633 | // aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) |
16634 | at::Tensor & transpose_copy_int_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dim0, int64_t dim1, at::Tensor & out) { |
16635 | |
16636 | static auto op = create_transpose_copy_int_out_typed_handle(); |
16637 | return op.redispatch(dispatchKeySet, self, dim0, dim1, out); |
16638 | } |
16639 | |
16640 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_indices_copy_out, name, "aten::_indices_copy" ) |
16641 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_indices_copy_out, overload_name, "out" ) |
16642 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_indices_copy_out, schema_str, "_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
16643 | |
16644 | // aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16645 | static C10_NOINLINE c10::TypedOperatorHandle<_indices_copy_out::schema> create__indices_copy_out_typed_handle() { |
16646 | return c10::Dispatcher::singleton() |
16647 | .findSchemaOrThrow(_indices_copy_out::name, _indices_copy_out::overload_name) |
16648 | .typed<_indices_copy_out::schema>(); |
16649 | } |
16650 | |
16651 | // aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16652 | at::Tensor & _indices_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
16653 | |
16654 | static auto op = create__indices_copy_out_typed_handle(); |
16655 | return op.call(self, out); |
16656 | } |
16657 | |
16658 | // aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16659 | at::Tensor & _indices_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
16660 | |
16661 | static auto op = create__indices_copy_out_typed_handle(); |
16662 | return op.redispatch(dispatchKeySet, self, out); |
16663 | } |
16664 | |
16665 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_values_copy_out, name, "aten::_values_copy" ) |
16666 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_values_copy_out, overload_name, "out" ) |
16667 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_values_copy_out, schema_str, "_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
16668 | |
16669 | // aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16670 | static C10_NOINLINE c10::TypedOperatorHandle<_values_copy_out::schema> create__values_copy_out_typed_handle() { |
16671 | return c10::Dispatcher::singleton() |
16672 | .findSchemaOrThrow(_values_copy_out::name, _values_copy_out::overload_name) |
16673 | .typed<_values_copy_out::schema>(); |
16674 | } |
16675 | |
16676 | // aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16677 | at::Tensor & _values_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
16678 | |
16679 | static auto op = create__values_copy_out_typed_handle(); |
16680 | return op.call(self, out); |
16681 | } |
16682 | |
16683 | // aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16684 | at::Tensor & _values_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
16685 | |
16686 | static auto op = create__values_copy_out_typed_handle(); |
16687 | return op.redispatch(dispatchKeySet, self, out); |
16688 | } |
16689 | |
16690 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values_copy_out, name, "aten::values_copy" ) |
16691 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values_copy_out, overload_name, "out" ) |
16692 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(values_copy_out, schema_str, "values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!)" ) |
16693 | |
16694 | // aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16695 | static C10_NOINLINE c10::TypedOperatorHandle<values_copy_out::schema> create_values_copy_out_typed_handle() { |
16696 | return c10::Dispatcher::singleton() |
16697 | .findSchemaOrThrow(values_copy_out::name, values_copy_out::overload_name) |
16698 | .typed<values_copy_out::schema>(); |
16699 | } |
16700 | |
16701 | // aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16702 | at::Tensor & values_copy_out::call(const at::Tensor & self, at::Tensor & out) { |
16703 | |
16704 | static auto op = create_values_copy_out_typed_handle(); |
16705 | return op.call(self, out); |
16706 | } |
16707 | |
16708 | // aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) |
16709 | at::Tensor & values_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::Tensor & out) { |
16710 | |
16711 | static auto op = create_values_copy_out_typed_handle(); |
16712 | return op.redispatch(dispatchKeySet, self, out); |
16713 | } |
16714 | |
16715 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_out, name, "aten::view_copy" ) |
16716 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_out, overload_name, "out" ) |
16717 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_out, schema_str, "view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!)" ) |
16718 | |
16719 | // aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
16720 | static C10_NOINLINE c10::TypedOperatorHandle<view_copy_out::schema> create_view_copy_out_typed_handle() { |
16721 | return c10::Dispatcher::singleton() |
16722 | .findSchemaOrThrow(view_copy_out::name, view_copy_out::overload_name) |
16723 | .typed<view_copy_out::schema>(); |
16724 | } |
16725 | |
16726 | // aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
16727 | at::Tensor & view_copy_out::call(const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
16728 | |
16729 | static auto op = create_view_copy_out_typed_handle(); |
16730 | return op.call(self, size, out); |
16731 | } |
16732 | |
16733 | // aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) |
16734 | at::Tensor & view_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, c10::SymIntArrayRef size, at::Tensor & out) { |
16735 | |
16736 | static auto op = create_view_copy_out_typed_handle(); |
16737 | return op.redispatch(dispatchKeySet, self, size, out); |
16738 | } |
16739 | |
16740 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_dtype_out, name, "aten::view_copy" ) |
16741 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_dtype_out, overload_name, "dtype_out" ) |
16742 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(view_copy_dtype_out, schema_str, "view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!)" ) |
16743 | |
16744 | // aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
16745 | static C10_NOINLINE c10::TypedOperatorHandle<view_copy_dtype_out::schema> create_view_copy_dtype_out_typed_handle() { |
16746 | return c10::Dispatcher::singleton() |
16747 | .findSchemaOrThrow(view_copy_dtype_out::name, view_copy_dtype_out::overload_name) |
16748 | .typed<view_copy_dtype_out::schema>(); |
16749 | } |
16750 | |
16751 | // aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
16752 | at::Tensor & view_copy_dtype_out::call(const at::Tensor & self, at::ScalarType dtype, at::Tensor & out) { |
16753 | |
16754 | static auto op = create_view_copy_dtype_out_typed_handle(); |
16755 | return op.call(self, dtype, out); |
16756 | } |
16757 | |
16758 | // aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) |
16759 | at::Tensor & view_copy_dtype_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, at::ScalarType dtype, at::Tensor & out) { |
16760 | |
16761 | static auto op = create_view_copy_dtype_out_typed_handle(); |
16762 | return op.redispatch(dispatchKeySet, self, dtype, out); |
16763 | } |
16764 | |
16765 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold_copy_out, name, "aten::unfold_copy" ) |
16766 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold_copy_out, overload_name, "out" ) |
16767 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(unfold_copy_out, schema_str, "unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!)" ) |
16768 | |
16769 | // aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) |
16770 | static C10_NOINLINE c10::TypedOperatorHandle<unfold_copy_out::schema> create_unfold_copy_out_typed_handle() { |
16771 | return c10::Dispatcher::singleton() |
16772 | .findSchemaOrThrow(unfold_copy_out::name, unfold_copy_out::overload_name) |
16773 | .typed<unfold_copy_out::schema>(); |
16774 | } |
16775 | |
16776 | // aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) |
16777 | at::Tensor & unfold_copy_out::call(const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out) { |
16778 | |
16779 | static auto op = create_unfold_copy_out_typed_handle(); |
16780 | return op.call(self, dimension, size, step, out); |
16781 | } |
16782 | |
16783 | // aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) |
16784 | at::Tensor & unfold_copy_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & self, int64_t dimension, int64_t size, int64_t step, at::Tensor & out) { |
16785 | |
16786 | static auto op = create_unfold_copy_out_typed_handle(); |
16787 | return op.redispatch(dispatchKeySet, self, dimension, size, step, out); |
16788 | } |
16789 | |
16790 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_decoder_only_multi_head_attention_out, name, "aten::_native_decoder_only_multi_head_attention" ) |
16791 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_decoder_only_multi_head_attention_out, overload_name, "out" ) |
16792 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_native_decoder_only_multi_head_attention_out, schema_str, "_native_decoder_only_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!))" ) |
16793 | |
16794 | // aten::_native_decoder_only_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
16795 | static C10_NOINLINE c10::TypedOperatorHandle<_native_decoder_only_multi_head_attention_out::schema> create__native_decoder_only_multi_head_attention_out_typed_handle() { |
16796 | return c10::Dispatcher::singleton() |
16797 | .findSchemaOrThrow(_native_decoder_only_multi_head_attention_out::name, _native_decoder_only_multi_head_attention_out::overload_name) |
16798 | .typed<_native_decoder_only_multi_head_attention_out::schema>(); |
16799 | } |
16800 | |
16801 | // aten::_native_decoder_only_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
16802 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _native_decoder_only_multi_head_attention_out::call(const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, const c10::optional<at::Tensor> & incr_key, const c10::optional<at::Tensor> & incr_value, bool need_weights, bool average_attn_weights, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
16803 | |
16804 | static auto op = create__native_decoder_only_multi_head_attention_out_typed_handle(); |
16805 | return op.call(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, incr_key, incr_value, need_weights, average_attn_weights, out0, out1, out2, out3); |
16806 | } |
16807 | |
16808 | // aten::_native_decoder_only_multi_head_attention.out(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, Tensor? incr_key=None, Tensor? incr_value=None, bool need_weights=True, bool average_attn_weights=True, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) |
16809 | ::std::tuple<at::Tensor &,at::Tensor &,at::Tensor &,at::Tensor &> _native_decoder_only_multi_head_attention_out::redispatch(c10::DispatchKeySet dispatchKeySet, const at::Tensor & query, const at::Tensor & key, const at::Tensor & value, int64_t embed_dim, int64_t num_head, const at::Tensor & qkv_weight, const at::Tensor & qkv_bias, const at::Tensor & proj_weight, const at::Tensor & proj_bias, const c10::optional<at::Tensor> & mask, const c10::optional<at::Tensor> & incr_key, const c10::optional<at::Tensor> & incr_value, bool need_weights, bool average_attn_weights, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, at::Tensor & out3) { |
16810 | |
16811 | static auto op = create__native_decoder_only_multi_head_attention_out_typed_handle(); |
16812 | return op.redispatch(dispatchKeySet, query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, incr_key, incr_value, need_weights, average_attn_weights, out0, out1, out2, out3); |
16813 | } |
16814 | |
16815 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam_out, name, "aten::_fused_adam" ) |
16816 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam_out, overload_name, "out" ) |
16817 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam_out, schema_str, "_fused_adam.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> ()" ) |
16818 | |
16819 | // aten::_fused_adam.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () |
16820 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_adam_out::schema> create__fused_adam_out_typed_handle() { |
16821 | return c10::Dispatcher::singleton() |
16822 | .findSchemaOrThrow(_fused_adam_out::name, _fused_adam_out::overload_name) |
16823 | .typed<_fused_adam_out::schema>(); |
16824 | } |
16825 | |
16826 | // aten::_fused_adam.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () |
16827 | void _fused_adam_out::call(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional<at::Tensor> & grad_scale, const c10::optional<at::Tensor> & found_inf, at::TensorList out) { |
16828 | |
16829 | static auto op = create__fused_adam_out_typed_handle(); |
16830 | return op.call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); |
16831 | } |
16832 | |
16833 | // aten::_fused_adam.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () |
16834 | void _fused_adam_out::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional<at::Tensor> & grad_scale, const c10::optional<at::Tensor> & found_inf, at::TensorList out) { |
16835 | |
16836 | static auto op = create__fused_adam_out_typed_handle(); |
16837 | return op.redispatch(dispatchKeySet, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf, out); |
16838 | } |
16839 | |
16840 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam, name, "aten::_fused_adam" ) |
16841 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam, overload_name, "" ) |
16842 | STATIC_CONST_STR_OUT_OF_LINE_FOR_WIN_CUDA(_fused_adam, schema_str, "_fused_adam(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out)" ) |
16843 | |
16844 | // aten::_fused_adam(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) |
16845 | static C10_NOINLINE c10::TypedOperatorHandle<_fused_adam::schema> create__fused_adam_typed_handle() { |
16846 | return c10::Dispatcher::singleton() |
16847 | .findSchemaOrThrow(_fused_adam::name, _fused_adam::overload_name) |
16848 | .typed<_fused_adam::schema>(); |
16849 | } |
16850 | |
16851 | // aten::_fused_adam(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) |
16852 | ::std::tuple<::std::vector<at::Tensor>,::std::vector<at::Tensor>,::std::vector<at::Tensor>,::std::vector<at::Tensor>,::std::vector<at::Tensor>> _fused_adam::call(at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional<at::Tensor> & grad_scale, const c10::optional<at::Tensor> & found_inf) { |
16853 | |
16854 | static auto op = create__fused_adam_typed_handle(); |
16855 | return op.call(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); |
16856 | } |
16857 | |
16858 | // aten::_fused_adam(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) |
16859 | ::std::tuple<::std::vector<at::Tensor>,::std::vector<at::Tensor>,::std::vector<at::Tensor>,::std::vector<at::Tensor>,::std::vector<at::Tensor>> _fused_adam::redispatch(c10::DispatchKeySet dispatchKeySet, at::TensorList self, at::TensorList grads, at::TensorList exp_avgs, at::TensorList exp_avg_sqs, at::TensorList max_exp_avg_sqs, at::TensorList state_steps, double lr, double beta1, double beta2, double weight_decay, double eps, bool amsgrad, bool maximize, const c10::optional<at::Tensor> & grad_scale, const c10::optional<at::Tensor> & found_inf) { |
16860 | |
16861 | static auto op = create__fused_adam_typed_handle(); |
16862 | return op.redispatch(dispatchKeySet, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); |
16863 | } |
16864 | |
16865 | }} // namespace at::_ops |
16866 | |