| /external/pytorch/test/inductor/ |
| D | test_pattern_matcher.py | 837 split_with_sizes = torch.ops.aten.split_with_sizes.default(a, [8, 24], 1)
838 getitem = split_with_sizes[0]
839 getitem_1 = split_with_sizes[1]
850 split_with_sizes = torch.ops.aten.split_with_sizes.default(a, [8, 8, 16], 1)
851 getitem = split_with_sizes[0]
852 getitem_1 = split_with_sizes[1]
853 getitem_2 = split_with_sizes[2]
864 split_with_sizes = torch.ops.aten.split_with_sizes.default(
867 cat = torch.ops.aten.cat.default(split_with_sizes, 0)
877 x = torch.ops.aten.split_with_sizes.default(a, [3, 2, 3], dim=1)
[all …]
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| /external/pytorch/aten/src/ATen/native/nested/ |
| D | NestedTensorUtils.cpp | 119 TORCH_CHECK_INDEX(false, "split_with_sizes() cannot be applied to a 0-dim tensor."); in split_with_sizes_nested()
123 … "split_with_sizes for nested tensors is currently only supported for the last dimension."); in split_with_sizes_nested()
126 "split_with_sizes expects number of splits to be greater than 0, got: ", num_splits); in split_with_sizes_nested()
127 TORCH_CHECK(self.is_contiguous(), "split_with_sizes expects `self` to be contiguous."); in split_with_sizes_nested()
137 "split_with_sizes expects split_sizes to sum exactly to ", self_size, in split_with_sizes_nested()
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| /external/pytorch/test/jit/ |
| D | test_autodiff_subgraph_slicing.py | 462 # to merge both split_with_sizes in relu in one graph
476 # Case 2: aliasing between relu and split_with_sizes
478 # to merge both split_with_sizes in relu in one graph
479 # i.e. relu and split_with_sizes should be in different
486 %2 : Tensor[] = aten::split_with_sizes(%b, %0, %1)
495 ).check("Tensor = aten::relu").check_not("aten::split_with_sizes").run(
500 # Both `split_with_sizes` should be unfused
507 %2 : Tensor[] = aten::split_with_sizes(%b, %s1, %1)
508 %3 : Tensor[] = aten::split_with_sizes(%b, %s2, %1)
517 ).check("Tensor = aten::relu").check_not("aten::split_with_sizes").run(
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| /external/executorch/backends/qualcomm/builders/ |
| D | op_split_with_sizes.py | 20 target = ["aten.split_with_sizes.default"]
43 # split_with_sizes will return a tuple since it has multiple outputs
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| /external/pytorch/torch/csrc/jit/passes/onnx/ |
| D | preprocess_for_onnx.cpp | 41 // split_with_sizes(Tensor self, int[] split_sizes, int dim=0) -> Tensor[]
46 // %8 : Tensor[] = aten::split_with_sizes(%input, %13, %7)
59 // aten::split_with_sizes(%input, %13, %7, %8) return (%14, %15, %16)
96 case aten::split_with_sizes: in FuseWithListUnpack()
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| /external/pytorch/torch/csrc/cuda/ |
| D | comm.cpp | 285 tensor.split_with_sizes(/*split_sizes=*/chunk_sizes, /*dim=*/dim); in _broadcast_out_impl()
332 ? tensor.split_with_sizes(/*split_sizes=*/*chunk_sizes, /*dim=*/dim) in _broadcast_out_impl()
384 out_tensor.split_with_sizes(/*split_sizes=*/chunk_sizes, /*dim=*/dim); in _broadcast_out_impl()
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| /external/executorch/backends/arm/quantizer/quantization_annotation/ |
| D | generic_annotator.py | 49 torch.ops.aten.split_with_sizes.default,
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| /external/pytorch/torch/_inductor/fx_passes/ |
| D | post_grad.py | 607 split_nodes = filter_nodes(match.nodes, aten.split_with_sizes)
625 # For example, if the split_node like split_with_sizes(input, [2, 2, 3], 1),
902 aten.split_with_sizes,
922 split_nodes = filter_nodes(match.nodes, aten.split_with_sizes)
957 aten.split_with_sizes,
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| /external/executorch/backends/arm/test/ops/ |
| D | test_split.py | 38 return x.split_with_sizes(split_sizes=split_sizes, dim=dim)
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| /external/pytorch/functorch/op_analysis/ |
| D | public_api | 202 split_with_sizes
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| D | annotated_ops | 253 split_with_sizes, view/reshape
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| /external/pytorch/docs/source/ |
| D | tensor_view.rst | 81 - :meth:`~torch.Tensor.split_with_sizes`
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| /external/pytorch/aten/src/ATen/native/ |
| D | MathBitFallThroughLists.h | 37 m.impl("split_with_sizes", torch::CppFunction::makeFallthrough()); \
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| /external/pytorch/torch/csrc/jit/runtime/ |
| D | register_special_ops.cpp | 248 RECORD_FUNCTION("split_with_sizes", last(stack, 3)); in __anon0ef288b80202()
250 auto result = at::split_with_sizes( in __anon0ef288b80202()
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| /external/pytorch/test/ |
| D | test_functionalization.py | 858 # test: view ops that return multiple tensors (split_with_sizes)
860 y1, y2 = x.split_with_sizes([2, 2])
908 split_with_sizes = torch.ops.aten.split_with_sizes.default(arg0_1, [2, 2])
909 getitem = split_with_sizes[0]
910 getitem_1 = split_with_sizes[1]; split_with_sizes = getitem_1 = None
913 split_with_sizes_1 = torch.ops.aten.split_with_sizes.default(arg0_1, [2, 2])
918 split_with_sizes_2 = torch.ops.aten.split_with_sizes.default(slice_scatter, [2, 2])
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| D | test_proxy_tensor.py | 1572 …split_with_sizes = torch.ops.aten.split_with_sizes.default(values_1, [_local_scalar_dense, _local_…
1573 getitem = split_with_sizes[0]
1574 getitem_1 = split_with_sizes[1]
1575 getitem_2 = split_with_sizes[2]; split_with_sizes = None
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| /external/pytorch/torch/csrc/jit/runtime/static/ |
| D | native_ops.cpp | 736 at::native::split_with_sizes(self, split_sizes.vec(), dim); in __anon69571ad14602()
745 aten::split_with_sizes,
749 … "aten::split_with_sizes(Tensor(a -> *) self, int[] split_sizes, int dim=0) -> Tensor(a)[]")) && in __anon69571ad14902()
751 … "aten::split_with_sizes(Tensor(a -> *) self, int[] split_sizes, int dim=0) -> (Tensor[])"))) { in __anon69571ad14902()
760 at::native::split_with_sizes(self, split_sizes.vec(), dim); in __anon69571ad14902()
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| /external/pytorch/test/cpp/api/ |
| D | inference_mode.cpp | 482 b = s_view.split_with_sizes({1, 1}); in TEST()
485 c = s.split_with_sizes({1, 1}); in TEST()
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| /external/executorch/backends/qualcomm/_passes/ |
| D | layout_transform.py | 72 exir_ops.edge.aten.split_with_sizes.default,
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| /external/executorch/exir/tests/ |
| D | test_delegate.py | 292 …# TODO(ssjia): split.Tensor now gets decomposed to split_with_sizes. Due to how executorch uses a …
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| /external/pytorch/torch/onnx/ |
| D | symbolic_opset13.py | 118 @_onnx_symbolic("aten::split_with_sizes")
119 def split_with_sizes(g: jit_utils.GraphContext, self, split_sizes, dim, _outputs=None): function
134 return split_with_sizes(g, self, split_sizes, dim, _outputs)
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| /external/pytorch/aten/src/ATen/native/nested/cuda/ |
| D | NestedTensorTransformerFunctions.cpp | 196 at::split_with_sizes(metadata, {offsets.numel(), nt_sizes.numel()}, 0); in NestedTensor_to_padded_tensor_cuda()
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| /external/pytorch/test/expect/ |
| D | HasDecompTest.test_aten_core_operators.expect | 483 aten::split_with_sizes
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| /external/pytorch/aten/src/ATen/native/cuda/ |
| D | TensorShape.cu | 728 "split_with_sizes expects split_sizes have only non-negative ", in split_with_sizes_copy_out_cuda()
735 "split_with_sizes expects split_sizes to sum exactly to ", in split_with_sizes_copy_out_cuda()
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| /external/pytorch/test/mobile/model_test/ |
| D | model_ops.yaml | 337 aten::split_with_sizes: 1
|