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/aosp_15_r20/external/pytorch/test/inductor/
H A Dtest_auto_functionalize.py46 out.copy_(x)
87 o.copy_(all_gather_output)
407 … copy_: "f32[s0][1]cpu" = torch.ops.aten.copy_.default(arg2_1, arg2_1); arg2_1 = copy_ = None
408 … copy__1: "f32[s0][1]cpu" = torch.ops.aten.copy_.default(arg5_1, arg5_1); arg5_1 = copy__1 = None
419 copy_: "f32[3][1]cpu" = torch.ops.aten.copy_.default(arg1_1, arg1_1); arg1_1 = copy_ = None
420 … copy__1: "f32[3][1]cpu" = torch.ops.aten.copy_.default(arg4_1, arg4_1); arg4_1 = copy__1 = None
511 copy_: "f32[3][1]cpu" = torch.ops.aten.copy_.default(arg1_1, arg1_1); arg1_1 = copy_ = None
512 … copy__1: "f32[3][1]cpu" = torch.ops.aten.copy_.default(arg4_1, arg4_1); arg4_1 = copy__1 = None
571 …copy_: "f32[s0][1]cpu" = torch.ops.aten.copy_.default(arg1_1, getitem_2); arg1_1 = getitem_2 = co…
572 …copy__1: "f32[s0][1]cpu" = torch.ops.aten.copy_.default(arg2_1, getitem_1); arg2_1 = getitem_1 = …
[all …]
H A Ds429861_repro.py4442 copy_: "f32[50][1]cuda:0" = torch.ops.aten.copy_.default(arg1_1, getitem_7031)
4444 copy__1: "f32[23][1]cuda:0" = torch.ops.aten.copy_.default(arg2_1, getitem_7032)
4446 copy__2: "f32[38][1]cuda:0" = torch.ops.aten.copy_.default(arg3_1, getitem_7033)
4448 copy__3: "f32[5][1]cuda:0" = torch.ops.aten.copy_.default(arg4_1, getitem_7034)
4450 copy__4: "f32[100][1]cuda:0" = torch.ops.aten.copy_.default(arg5_1, getitem_7035)
4452 copy__5: "f32[50][1]cuda:0" = torch.ops.aten.copy_.default(arg6_1, getitem_7036)
4454 copy__6: "f32[77][1]cuda:0" = torch.ops.aten.copy_.default(arg7_1, getitem_7037)
4456 copy__7: "f32[100][1]cuda:0" = torch.ops.aten.copy_.default(arg8_1, getitem_7038)
4458 copy__8: "f32[100][1]cuda:0" = torch.ops.aten.copy_.default(arg9_1, getitem_7039)
4460 copy__9: "f32[96][1]cuda:0" = torch.ops.aten.copy_.default(arg10_1, getitem_7040)
[all …]
H A Dtest_inplacing_pass.py39 result.copy_(x.sin())
44 out_sin.copy_(x.sin())
45 out_cos.copy_(x.cos())
206 copy_ = torch.ops.aten.copy_.default(arg0_1, getitem_1)
229 copy_ = torch.ops.aten.copy_.default(arg0_1, getitem_1)
253 copy_ = torch.ops.aten.copy_.default(arg0_1, getitem_1)
H A Dtest_distributed_patterns.py30 … # torch.ops.fsdp.set_ doesn't work well in eager mode, so use the slow copy_ path instead.
37 mod.unsharded_weight.copy_(all_gather(mod.sharded_weight))
62 … # torch.ops.fsdp.set_ doesn't work well in eager mode, so use the slow copy_ path instead.
69 mod.unsharded_weight.copy_(all_gather(mod.sharded_weight))
199 out.copy_(y.cos())
225 w.copy_(x + 1)
249 w.copy_(x)
269 w.copy_(x + 1)
287 w.copy_(x)
/aosp_15_r20/external/pytorch/test/
H A Dtest_functionalization.py70 inpt.copy_(inpt_new)
187 y.copy_(x)
298 copy_ = torch.ops.aten.copy_.default(arg0_1, view_copy_1); arg0_1 = view_copy_1 = copy_ = None
319 copy_ = torch.ops.aten.copy_.default(arg0_1, view_1); arg0_1 = view_1 = copy_ = None
513 copy_ = torch.ops.aten.copy_.default(arg0_1, add); arg0_1 = copy_ = None
532 copy_ = torch.ops.aten.copy_.default(arg0_1, add); arg0_1 = copy_ = None
561 copy_ = torch.ops.aten.copy_.default(arg0_1, getitem_5); arg0_1 = getitem_5 = copy_ = None
585 copy_ = torch.ops.aten.copy_.default(arg0_1, as_strided_scatter); arg0_1 = copy_ = None
605 copy_ = torch.ops.aten.copy_.default(arg0_1, as_strided_scatter); arg0_1 = copy_ = None
739 copy_ = torch.ops.aten.copy_.default(arg0_1, diagonal_scatter); arg0_1 = copy_ = None
[all …]
/aosp_15_r20/external/google-cloud-java/java-aiplatform/proto-google-cloud-aiplatform-v1beta1/src/main/java/com/google/cloud/aiplatform/v1beta1/
H A DModelSourceInfo.java335 private boolean copy_ = false; field in ModelSourceInfo
351 return copy_; in getCopy()
374 if (copy_ != false) { in writeTo()
375 output.writeBool(2, copy_); in writeTo()
392 if (copy_ != false) { in getSerializedSize()
393 size += com.google.protobuf.CodedOutputStream.computeBoolSize(2, copy_); in getSerializedSize()
568 copy_ = false; in clear()
609 result.copy_ = copy_; in buildPartial0()
699 copy_ = input.readBool(); in mergeFrom()
821 private boolean copy_; field in ModelSourceInfo.Builder
[all …]
/aosp_15_r20/external/google-cloud-java/java-aiplatform/proto-google-cloud-aiplatform-v1/src/main/java/com/google/cloud/aiplatform/v1/
H A DModelSourceInfo.java333 private boolean copy_ = false; field in ModelSourceInfo
349 return copy_; in getCopy()
372 if (copy_ != false) { in writeTo()
373 output.writeBool(2, copy_); in writeTo()
390 if (copy_ != false) { in getSerializedSize()
391 size += com.google.protobuf.CodedOutputStream.computeBoolSize(2, copy_); in getSerializedSize()
566 copy_ = false; in clear()
607 result.copy_ = copy_; in buildPartial0()
696 copy_ = input.readBool(); in mergeFrom()
812 private boolean copy_; field in ModelSourceInfo.Builder
[all …]
/aosp_15_r20/external/pytorch/torch/_inductor/fx_passes/
H A Dreinplace.py76 tmp.copy_(src)
145 slice2.copy_(src)
159 graph_call_function(graph, aten.copy_.default, tmp, src)
196 user.target is aten.copy_.default and user.args[0] is inp for user in node.users
232 tmp.copy_(src)
382 be inplaced if the above condition is true and there's a copy_ in the
391 # maps argument to the first copy_ node that mutates it.
399 if node.target == aten.copy_.default and node.args[0].op in (
437 # Ignore uses after the copy_ epilogue node, where the input
446 # mutated_arg.copy_(other)
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/
H A DCopy.cpp88 _AT_DISPATCH_CP_TYPES(self.scalar_type(), "copy_", [&] { in copy_same_type_transpose_()
130 // (e.g. XLA) may be supported by overriding copy_ and _copy_from.
221 // cpu_tensor.copy_(xla_tensor) => xla_tensor._copy_from(cpu_tensor) in copy_impl()
222 // xla_tensor.copy_(cpu_tensor) => cpu_tensor._copy_from(xla_tensor) in copy_impl()
247 return vulkan::ops::copy_(self, src); in copy_impl()
317 r.copy_(src, non_blocking); in copy_meta()
323 …// copy() is the "functional" form of copy_(). It exists so we can properly functionalize copy_(),… in copy()
329 // that copy_() will fully overwrite all data with that of src in copy()
335 r.copy_(src, non_blocking); in copy()
353 Tensor& copy_(Tensor& self, const Tensor& src, bool non_blocking) { in copy_() function
/aosp_15_r20/external/pytorch/aten/src/ATen/native/cuda/
H A DScanKernels.cpp38 values.copy_(*values_); in cummax_helper_cuda()
41 indices.copy_(*indices_); in cummax_helper_cuda()
55 values.copy_(*values_); in cummin_helper_cuda()
58 indices.copy_(*indices_); in cummin_helper_cuda()
81 result.copy_(*result_); in _logcumsumexp_out_cuda()
100 result.copy_(*result_); in cumsum_cuda_kernel()
108 result.copy_(*result_); in cumprod_cuda_kernel()
H A DCopy.cu145 AT_DISPATCH_QINT_TYPES(dtype, "copy_", [&] { in direct_copy_kernel_cuda()
151 TORCH_CHECK(dtype == iter.dtype(1), "copy_() does not support casting " in direct_copy_kernel_cuda()
153 AT_DISPATCH_BIT_TYPES(dtype, "copy_", [&] { in direct_copy_kernel_cuda()
158 dtype, "copy_", AT_WRAP([&] { in direct_copy_kernel_cuda()
328 dst_contig.copy_(src_contig, non_blocking); in copy_kernel_cuda()
333 dst.copy_(dst_contig, non_blocking); in copy_kernel_cuda()
354 TORCH_INTERNAL_ASSERT(false, "unsupported devices in GPU copy_()"); in copy_kernel_cuda()
H A DSort.cpp34 t.copy_(rangeview); in fillSliceWithIndex()
78 values.copy_(self); in sort_cuda_kernel()
93 self_.copy_(self); in sort_cuda_kernel()
115 values.copy_(*values_tmp); in sort_cuda_kernel()
118 indices.copy_(*indices_tmp); in sort_cuda_kernel()
/aosp_15_r20/external/pytorch/aten/src/ATen/native/cpu/
H A DAdaptiveMaxPoolKernel.cpp77 output_.copy_(output); in cpu_adaptive_max_pool2d()
80 indices_.copy_(indices); in cpu_adaptive_max_pool2d()
194 output_.copy_(output); in cpu_adaptive_max_pool2d_channels_last()
197 indices_.copy_(indices); in cpu_adaptive_max_pool2d_channels_last()
334 output_.copy_(output); in cpu_adaptive_max_pool2d_channels_last()
337 indices_.copy_(indices); in cpu_adaptive_max_pool2d_channels_last()
383 grad_input_.copy_(grad_input); in cpu_adaptive_max_pool2d_backward()
432 grad_input_.copy_(grad_input); in cpu_adaptive_max_pool2d_backward_channels_last()
551 output_.copy_(output); in cpu_adaptive_max_pool3d()
554 indices_.copy_(indices); in cpu_adaptive_max_pool3d()
[all …]
/aosp_15_r20/external/pytorch/test/profiler/
H A Dtest_profiler_tree.py292 aten::copy_
298 aten::copy_
309 aten::copy_
351 aten::copy_
363 aten::copy_""",
403 aten::copy_
411 aten::copy_
432 aten::copy_
512 aten::copy_
520 aten::copy_
[all …]
/aosp_15_r20/external/pytorch/torch/optim/
H A Drprop.py266 sign.copy_(torch.where(sign.gt(0), etaplus, sign))
267 sign.copy_(torch.where(sign.lt(0), etaminus, sign))
268 sign.copy_(torch.where(sign.eq(0), 1, sign))
281 grad.copy_(torch.where(sign.eq(etaminus), 0, grad))
287 prev.copy_(grad)
368 sign.copy_(torch.where(sign.gt(0), etaplus, sign))
369 sign.copy_(torch.where(sign.lt(0), etaminus, sign))
370 sign.copy_(torch.where(sign.eq(0), 1, sign))
386 grouped_grads[i].copy_(
/aosp_15_r20/external/pytorch/torch/ao/quantization/
H A Dobserver.py539 self.min_val.copy_(min_val)
540 self.max_val.copy_(max_val)
555 self.min_val.copy_(torch.tensor(float("inf")))
556 self.max_val.copy_(torch.tensor(float("-inf")))
653 self.min_val.copy_(min_val)
654 self.max_val.copy_(max_val)
761 self.min_val.copy_(min_val)
762 self.max_val.copy_(max_val)
811 self.min_val.copy_(val)
813 self.max_val.copy_(val)
[all …]
/aosp_15_r20/external/pytorch/torch/csrc/distributed/c10d/
H A Dreducer.cpp394 "torch::distributed::reducer::copy_", in mark_variable_ready_dense()
396 bucket_view.copy_(div_result); in mark_variable_ready_dense()
400 "torch::distributed::reducer::copy_", in mark_variable_ready_dense()
402 bucket_view.copy_(grad); in mark_variable_ready_dense()
741 // essential. The H2D copy_ is stream ordered, while the host's in all_reduce_local_used_map()
743 // cuda/privateuseone-stream work pushes the copy_ far into the future, and in all_reduce_local_used_map()
746 // before the stream executes the copy_, copy_ will read those zeros in all_reduce_local_used_map()
770 local_used_map_tmp.copy_(local_used_map_); in all_reduce_local_used_map()
771 local_used_map_dev_.copy_(local_used_map_tmp, true); in all_reduce_local_used_map()
782 local_used_map_tmp.copy_(local_used_map_); in all_reduce_local_used_map()
[all …]
/aosp_15_r20/external/pytorch/torch/ao/quantization/fx/_model_report/
H A Dmodel_report_observer.py101 self.epoch_activation_min.copy_(epoch_min_val)
102 self.epoch_activation_max.copy_(epoch_max_val)
147 self.min_val.copy_(min_val)
148 self.max_val.copy_(max_val)
247 self.percentile_batches_tracked.copy_(new_number_of_batches)
248 self.average_percentile_ratio.copy_(new_ratios)
249 self.constant_channels.copy_(new_constant_count)
/aosp_15_r20/external/pytorch/torch/csrc/autograd/
H A DVariableTypeManual.cpp190 Tensor& copy_( in copy_() function
210 at::redispatch::copy_( in copy_()
222 new_fw_grad = self_fw_grad.copy_(src_fw_grad); in copy_()
362 "copy_", in TORCH_LIBRARY_IMPL()
363 torch::dispatch(DispatchKey::Autograd, TORCH_FN(VariableType::copy_))); in TORCH_LIBRARY_IMPL()
384 static Tensor& copy_( in copy_() function
391 at::redispatch::copy_( in copy_()
536 "copy_", in TORCH_LIBRARY_IMPL()
538 DispatchKey::ADInplaceOrView, TORCH_FN(ADInplaceOrView::copy_))); in TORCH_LIBRARY_IMPL()
H A Dautograd_meta.cpp29 // foo.copy_(bar)
33 // view.copy_(bar)
37 // foo.copy_(bar)
67 // view.copy_(bar)
73 // base.copy_(bar)
242 new_fw_grad_value.copy_(new_grad); in set_fw_grad()
262 res.copy_(new_grad); in set_fw_grad()
/aosp_15_r20/external/executorch/examples/models/llama/source_transformation/
H A Dquantized_kv_cache.py125 narrowed_k.copy_(quantized_k_val)
126 narrowed_k_scales.copy_(k_scales)
127 narrowed_k_zp.copy_(k_zero_points)
135 narrowed_v.copy_(quantized_v_val)
136 narrowed_v_scales.copy_(v_scales)
137 narrowed_v_zp.copy_(v_zero_points)
/aosp_15_r20/external/pytorch/torch/_functorch/_aot_autograd/
H A Dtraced_function_transforms.py383 # and performing copy_() calls at the end of the function if `keep_input_mutations` is set.
466 … # Add node meta for copy_ for partitioner that this node should be in backward graph.
468 before.copy_(after)
489 … # (2) For keep_input_mutations, we support tracing a call to copy_() directly on mutated inputs.
504 …# It would be much better to add copy_() calls into the graph for the two tiny slices, instead of …
571 … # Even if we marked the input as having a data mutation (thus needing a copy_()),
576 … # Optimization: if the copy_() is a no-op then don't include it in the graph.
578 # param.copy_(param), where param is a zero-storage-size tensor,
586 # Since keep_input_mutations is set, we need to faithfully apply a copy_()
601 inpt_old.copy_(inpt_new)
[all …]
/aosp_15_r20/external/pytorch/torch/testing/_internal/distributed/
H A Dmulti_threaded_pg.py77 output_tensor_list[src_rank].copy_(input_tensor_list[dest_rank])
92 output_buffer[output_indexes[src_rank]:output_indexes[src_rank + 1]].copy_(
139 data[src_rank][i].copy_(res.to(data[src_rank][i].device))
153 dest_tensor.copy_(src_tensor)
172 dest_tensor.copy_(src_in_tensors[rank])
189 dest_tensor.copy_(src_in_tensor_list[0])
210 dest_tensor_on_rank_i[0].copy_(to_scatter[i].to(dst_tensor_device))
230 out_tensor_list[j].copy_(in_tensor_list[j])
/aosp_15_r20/external/pytorch/torch/csrc/jit/passes/
H A Dconcat_opt.cpp262 // %22 = aten::copy_(%21, %2) // copy %2
264 // %24 = aten::copy_(%23, %3) // copy %3
351 auto copy = graph_->create(aten::copy_, {slice->output(), cat_inp}); in expandCat()
434 // %22 = aten::copy_(%21, %2)
436 // %24 = aten::copy_(%23, %3)
440 // %32 = aten::copy_(%31, %20) // src of copy is aten::empty
443 // %34 = aten::copy_(%33, %4)
449 // %22 = aten::copy_(%21, %2)
451 // %24 = aten::copy_(%23, %3)
455 // %34 = aten::copy_(%33, %4)
/aosp_15_r20/external/pytorch/torch/fx/passes/
H A Dreinplace.py65 # copy_() doesn't read from its first argument; it writes to it, overwriting previous data.
68 if node.target is torch.ops.aten.copy_.default:
308 there is a node that looks like "a.copy_(...)",
310 which will later be overwritten by the copy_() call.
412 a_slice.copy_(b)
430 slice.copy_(mutated_slice)
538 # TODO: later, add the optimization for handling `copy_()` calls in the graph.
567 # and instead copy_() the slice directly into the larger tensor.
575 # slice.copy_(mutated_slice)
582 … 'call_function', torch.ops.aten.copy_.default, (slice_node, mutated_slice_node,), {})

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