| /external/pytorch/test/inductor/ |
| D | test_auto_functionalize.py | 46 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 …]
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| D | s429861_repro.py | 4442 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 …]
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| D | test_inplacing_pass.py | 39 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)
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| D | test_distributed_patterns.py | 30 … # 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)
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| /external/pytorch/aten/src/ATen/native/cuda/ |
| D | ScanKernels.cpp | 38 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()
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| D | Sort.cpp | 34 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()
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| D | TensorTopK.cpp | 30 values.copy_(sorted_values.narrow(dim, 0, k)); in topk_out_with_sort()
31 indices.copy_(sorted_indices.narrow(dim, 0, k)); in topk_out_with_sort()
90 indices.copy_(indices.gather(dim, sortedIndices)); in TORCH_IMPL_FUNC()
91 values.copy_(sortedValues); in TORCH_IMPL_FUNC()
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| D | Copy.cu | 145 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()
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| /external/pytorch/test/ |
| D | test_functionalization.py | 70 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 …]
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| /external/executorch/examples/models/llama/source_transformation/ |
| D | quantized_kv_cache.py | 125 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)
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| /external/pytorch/aten/src/ATen/native/ |
| D | Copy.cpp | 88 _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
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| D | AffineGridGenerator.cpp | 39 base_grid.select(-1, 0).copy_(linspace_from_neg_one(theta, W, align_corners)); in make_base_grid_4D()
40 base_grid.select(-1, 1).copy_(linspace_from_neg_one(theta, H, align_corners).unsqueeze_(-1)); in make_base_grid_4D()
56 base_grid.select(-1, 0).copy_(linspace_from_neg_one(theta, W, align_corners)); in make_base_grid_5D()
57 base_grid.select(-1, 1).copy_(linspace_from_neg_one(theta, H, align_corners).unsqueeze_(-1)); in make_base_grid_5D()
58 …base_grid.select(-1, 2).copy_(linspace_from_neg_one(theta, D, align_corners).unsqueeze_(-1).unsque… in make_base_grid_5D()
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| D | Fill.cpp | 42 // Trust the `copy_` to handle the quantization and the boundary checks. in fill_out_quantized()
43 self.copy_(out); in fill_out_quantized()
63 self.copy_(value.clone()); in fill_()
65 self.copy_(value); in fill_()
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| /external/pytorch/torch/ao/quantization/fx/_model_report/ |
| D | model_report_observer.py | 101 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)
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| /external/pytorch/aten/src/ATen/test/ |
| D | undefined_tensor_test.cpp | 55 // copy_ in TEST()
57 ASSERT_ANY_THROW(und.copy_(und)); in TEST()
59 ASSERT_ANY_THROW(und.copy_(ft)); in TEST()
61 ASSERT_ANY_THROW(ft.copy_(und)); in TEST()
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| /external/pytorch/torch/_inductor/fx_passes/ |
| D | reinplace.py | 76 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 …]
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| D | README.md | 10 …acing and before Inductor, we have no mutation in our graph, except for a copy_ epilogue at the en…
23 In addition, AOTDispatch can introduce a copy_ epilogue into the graph. For example, we may have a …
27 x.copy_(y)
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| /external/google-cloud-java/java-aiplatform/proto-google-cloud-aiplatform-v1/src/main/java/com/google/cloud/aiplatform/v1/ |
| D | ModelSourceInfo.java | 333 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 …]
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| /external/google-cloud-java/java-aiplatform/proto-google-cloud-aiplatform-v1beta1/src/main/java/com/google/cloud/aiplatform/v1beta1/ |
| D | ModelSourceInfo.java | 335 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 …]
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| /external/pytorch/torch/optim/ |
| D | rprop.py | 266 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_(
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| /external/pytorch/torch/onnx/_internal/fx/passes/ |
| D | functionalization.py | 54 a.copy_(new_a)
136 """Remove `aten.copy_.default` nodes that mutate module inputs.
139 ``Functionalization`` pass adds `aten.copy_.default` nodes to the graph
148 and node.target == torch.ops.aten.copy_.default
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| /external/pytorch/torch/csrc/autograd/ |
| D | autograd_meta.cpp | 29 // 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()
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| D | VariableTypeManual.cpp | 190 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()
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| /external/executorch/kernels/portable/cpu/ |
| D | op_copy.cpp | 64 Tensor& copy_( in copy_() function
80 static constexpr const char op_name[] = "copy_"; in copy_()
82 ET_SWITCH_REALHBBF16_TYPES(in.scalar_type(), ctx, "copy_", CTYPE, [&]() { in copy_()
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| /external/pytorch/torch/testing/_internal/distributed/ |
| D | multi_threaded_pg.py | 77 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])
|