| /external/pytorch/torch/distributed/tensor/_ops/ |
| D | _experimental_ops.py | 24 slice_backward is a new_zeros + slice_scatter, we only allow replication
25 on the input/output for now since new_zeros would produce replication
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| /external/pytorch/torch/_decomp/ |
| D | decompositions_for_jvp.py | 108 min = torch.minimum(self.new_zeros(()), self)
111 buffer = self.new_zeros((0,))
159 input.new_zeros(input_shape),
160 input.new_zeros(input_shape[axis:]),
161 input.new_zeros(input_shape[axis:]),
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| D | decompositions.py | 737 grad_input = grad_output.new_zeros(input_sizes)
866 grad_input = grad_output.new_zeros(input_sizes)
875 grad_input = grad_output.new_zeros(input_sizes)
1105 output = input.new_zeros(
1146 grad_input = grad.new_zeros(input_size)
1282 counts = indices.new_zeros((num_weights,))
1290 grad_weight = grad_output.new_zeros(
1721 input.new_zeros(input_shape) if output_mask[0] else None,
1722 input.new_zeros(input_shape[axis:]) if output_mask[1] else None,
1723 input.new_zeros(input_shape[axis:]) if output_mask[2] else None,
[all …]
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| /external/pytorch/aten/src/ATen/functorch/ |
| D | BatchRulesFactory.cpp | 50 // USAGE: NEW_BLAH_BATCH_RULE(at::new_zeros)
51 // INCORRECT USAGE: NEW_BLAH_BATCH_RULE(&at::new_zeros)
234 VMAP_SUPPORT(new_zeros, NEW_BLAH_BATCH_RULE_SYMINT(ATEN_FN(new_zeros))); in TORCH_LIBRARY_IMPL()
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| /external/pytorch/torch/csrc/jit/passes/onnx/ |
| D | preprocess_for_onnx.cpp | 123 // %8 : Tensor = aten::new_zeros(%x.1, %7, %2, %2, %2, %2)
135 // %8 : Tensor = aten::new_zeros(%x.1, %9, %2, %2, %2, %2)
175 // %6 : Tensor = aten::new_zeros(%x.1, %5, %1, %1, %1, %1)
187 // %6 : Tensor = aten::new_zeros(%x.1, %5, %1, %1, %1, %1)
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| /external/pytorch/torch/testing/_internal/ |
| D | autograd_function_db.py | 379 result = grad_output.new_zeros(ctx.x_shape)
408 result = grad_output.new_zeros(ctx.x_shape)
454 # Intentionally returning torch.zeros instead of zeros_like or new_zeros.
464 # Intentionally returning torch.zeros instead of zeros_like or new_zeros.
490 result = grad_output.new_zeros(ctx.x_shape)
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| /external/pytorch/functorch/op_analysis/ |
| D | public_api | 379 new_zeros
380 new_zeros
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| D | annotated_ops | 106 new_zeros, factory
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| /external/pytorch/torch/_prims/ |
| D | context.py | 45 torch.Tensor.new_zeros: torch._refs.new_zeros,
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| /external/pytorch/docs/source/ |
| D | func.ux_limitations.rst | 170 - Replace :func:`torch.zeros` with :meth:`Tensor.new_zeros`
198 result = vec.new_zeros(vec.shape[0], vec.shape[0])
205 Replacing :func:`torch.zeros` with :meth:`Tensor.new_zeros` makes it so that
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| /external/pytorch/test/inductor/ |
| D | indirect_assert_helper.py | 43 b = x.new_zeros((), dtype=torch.int64)
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| D | test_padding.py | 416 pad = x.new_zeros(*x.shape[:dim], padded_length, *x.shape[dim + 1 :])
637 pad = x.new_zeros(x.size(0), 6)
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| /external/pytorch/aten/src/ATen/native/vulkan/ops/ |
| D | Sum.cpp | 140 return self.new_zeros({}, at::device(at::kVulkan).dtype(self.dtype())); in sum()
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| /external/pytorch/torch/ |
| D | _lobpcg.py | 48 poly_coeffs = roots.new_zeros(poly_coeffs_shape)
176 # res = A.new_zeros(A.shape)
177 # p_res = A.new_zeros(*A.shape[:-1], D.size(-1))
200 series_acc = U_grad_projected.new_zeros(U_grad_projected.shape)
208 # chr_poly_D_at_A = A.new_zeros(A.shape)
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| /external/pytorch/torch/masked/ |
| D | _ops.py | 487 flat_indices = indices.new_zeros(indices.size(1))
606 where_input_values.new_zeros((n,) + where_input_values.shape[1:]),
787 crow_indices.new_zeros(1),
793 new_col_indices = col_indices.new_zeros(new_nnz)
807 new_col_indices = col_indices.new_zeros(nnz)
1639 count = torch.maximum(count, count.new_zeros([]))
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| /external/pytorch/torch/distributions/ |
| D | lkj_cholesky.py | 79 offset = torch.cat([offset.new_zeros((1,)), offset])
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| D | utils.py | 196 mat = vec.new_zeros(vec.shape[:-1] + torch.Size((n, n)))
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| /external/pytorch/test/nn/ |
| D | test_packed_sequence.py | 123 extra_pad = no_extra_pad.new_zeros(
128 extra_pad = no_extra_pad.new_zeros(
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| /external/pytorch/test/ |
| D | test_masked.py | 270 strided = torch.where(mask, strided, strided.new_zeros([]))
271 expected = torch.where(mask, expected, expected.new_zeros([]))
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| /external/pytorch/test/distributions/ |
| D | test_transforms.py | 413 expected = x.new_zeros(x.shape[x.dim() - transform.domain.event_dim])
414 expected = x.new_zeros(x.shape[x.dim() - transform.domain.event_dim])
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| /external/tensorflow/tensorflow/c/eager/ |
| D | tape.h | 1052 std::vector<Gradient*> new_zeros; in Accumulate() local
1053 auto delete_new_zeros = gtl::MakeCleanup([&new_zeros, this] { in Accumulate()
1054 for (Gradient* tensor : new_zeros) { in Accumulate()
1069 new_zeros.push_back(zero); in Accumulate()
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| /external/pytorch/torch/csrc/api/src/nn/modules/ |
| D | adaptive.cpp | 108 Tensor output = input.new_zeros(batch_size); in forward()
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| /external/pytorch/benchmarks/dynamo/microbenchmarks/operator_inp_logs/torchbench_train/ |
| D | pytorch_struct_training.txt | 45 Operator: aten.new_zeros.default
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| /external/pytorch/test/onnx/ |
| D | test_fx_to_onnx.py | 169 return input.new_zeros(())
178 expected_node="aten.new_zeros.default",
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| /external/pytorch/benchmarks/dynamo/microbenchmarks/operator_inp_logs/hf_train/ |
| D | XGLMForCausalLM_training.txt | 80 Operator: aten.new_zeros.default
|