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/aosp_15_r20/external/pytorch/test/functorch/
H A Dtest_ops.py227 return tree_map(torch.randn_like, output)
270 tree_map(lambda x: torch.randn_like(x, requires_grad=True), result)
292 tangents = _as_tuple(tree_map(lambda x: torch.randn_like(x), primals))
315 tangents = _as_tuple(tree_map(lambda x: torch.randn_like(x), primals))
323 tangents = _as_tuple(tree_map(lambda x: torch.randn_like(x), primals))
693 orig_tangents = tree_map(lambda x: torch.randn_like(x), primals)
808 cotangents = tree_map(lambda x: torch.randn_like(x), result)
903 cotangents = tree_map(lambda x: torch.randn_like(x), result)
1088 cotangents = tree_map(lambda x: torch.randn_like(x), result)
1726 cotangents = tree_map(lambda x: torch.randn_like(x), result)
[all …]
H A Ddiscover_coverage.py597 "torch.randn_like", # randomness
680 "randn_like", # randomness
/aosp_15_r20/external/pytorch/aten/src/ATen/native/vulkan/ops/
H A DRandom.cpp123 static Tensor randn_like( in randn_like() function
139 m.impl(TORCH_SELECTIVE_NAME("aten::randn_like"), TORCH_FN(randn_like)); in TORCH_LIBRARY_IMPL()
/aosp_15_r20/external/pytorch/test/nn/
H A Dtest_embedding.py802 torch.randn_like(idx1, device=device, dtype=w_dtype),
884 per_sample_weights = torch.randn_like(input, dtype=torch.double, device=device)
1012 per_sample_weights = torch.randn_like(
1028 grad = torch.randn_like(expected)
1076 per_sample_weights = torch.randn_like(
1092 grad = torch.randn_like(expected).to(dtype=dtypes[2], device=device)
1152 per_sample_weights = torch.randn_like(
1177 grad = torch.randn_like(expected)
H A Dtest_pooling.py1471 g = torch.randn_like(y, dtype=torch.half)
1667 res.backward(torch.randn_like(res))
1681 res2.backward(torch.randn_like(res2))
1798 res.backward(torch.randn_like(res))
1809 res2.backward(torch.randn_like(res2))
/aosp_15_r20/external/pytorch/test/optim/
H A Dtest_swa_utils.py97 p.detach().add_(torch.randn_like(p))
146 p.detach().add_(torch.randn_like(p))
201 p.detach().add_(torch.randn_like(p))
/aosp_15_r20/external/pytorch/test/typing/reveal/
H A Dtensor_sampling.py51 # randn_like
53 reveal_type(torch.randn_like(c)) # E: {Tensor}
/aosp_15_r20/external/pytorch/torch/distributed/_shard/sharded_tensor/_ops/
H A Dinit.py121 torch.randn_like: sharded_tensor.randn,
151 register_tensor_creation_op(torch.randn_like)
/aosp_15_r20/external/pytorch/aten/src/ATen/functorch/
H A DBatchRulesRandomness.cpp477 …m.impl("randn_like", tensor_like_random_batch_rule<decltype(&ATEN_FN(randn_like)), &ATEN_FN(randn_… in TORCH_LIBRARY_IMPL()
H A DBatchRulesFactory.cpp230 VMAP_SUPPORT(randn_like, BASIC_UNARY_BATCH_RULE(ATEN_FN(randn_like))); in TORCH_LIBRARY_IMPL()
/aosp_15_r20/external/pytorch/torch/testing/_internal/opinfo/definitions/
H A Dnested.py161 njt2 = torch.randn_like(njt1)
248 njt, kwargs={"mask": (torch.randn_like(njt, requires_grad=False) < 0.0)}
/aosp_15_r20/external/pytorch/docs/source/
H A Dtorch.rst38 :func:`torch.randn_like`
210 randn_like
H A Djit_unsupported.rst63 * :func:`torch.randn_like`
/aosp_15_r20/external/pytorch/test/
H A Dtest_bundled_inputs.py376 output[k] = torch.randn_like(v)
391 output.append(torch.randn_like(v))
H A Dtest_ops.py663 grad_for_expected = torch.randn_like(expected)
675 grad_for_expected = [torch.randn_like(t) for t in expected]
1470 grad = torch.randn_like(backward_tensor)
1953 grad = torch.randn_like(expected_forward)
/aosp_15_r20/external/pytorch/benchmarks/transformer/
H A Dscore_mod.py206 dOut = torch.randn_like(out_eager)
219 dOut = torch.randn_like(out_compile)
H A Dsdpa.py111 dOut = torch.randn_like(out_torch)
/aosp_15_r20/external/pytorch/benchmarks/fastrnns/
H A Dfactory.py50 grad_output = torch.randn_like(output)
239 grad = torch.randn_like(padded)
/aosp_15_r20/external/executorch/docs/source/
H A Dextension-tensor.md396 | `at::randn_like(tensor)` | `randn_like(tensor)` |
/aosp_15_r20/external/pytorch/torch/testing/_internal/
H A Dcomposite_compliance.py512 return torch.randn_like(t)
514 return [torch.randn_like(e) if e.requires_grad else None for e in t]
/aosp_15_r20/external/pytorch/torch/_inductor/fx_passes/
H A Dpad_mm.py437 return torch.randn_like(t)
495 input_pad = torch.randn_like(input)
/aosp_15_r20/external/pytorch/test/mobile/model_test/
H A Dsampling_ops.py25 torch.randn_like(a),
/aosp_15_r20/external/pytorch/torch/_subclasses/
H A Dfake_impls.py68 aten.randn_like.default,
69 aten.randn_like.out,
/aosp_15_r20/external/pytorch/test/jit/
H A Dtest_models.py563 eps = torch.randn_like(std)
578 # eval() is present because randn_like makes this nondeterministic
/aosp_15_r20/external/pytorch/torch/utils/benchmark/utils/
H A Dsparse_fuzzer.py85 v = torch.cat([v, torch.randn_like(v)], 0)

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