| /external/tensorflow/tensorflow/compiler/xla/service/ |
| D | eigh_expander.cc | 388 // frobenius_norm = np.sqrt(np.sum(np.square(tl) + np.square(tr) +
392 // off_diag_norm = np.sqrt(frobenius_norm - diag_norm) * np.sqrt(
393 // frobenius_norm + diag_norm)
394 // while off_diag_norm > 1e-6 * frobenius_norm:
422 // frobenius_norm = np.sqrt(np.sum(np.square(tl) + np.square(tr) +
426 // off_diag_norm = np.sqrt(frobenius_norm - diag_norm) * np.sqrt(
427 // frobenius_norm + diag_norm)
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| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| D | svd.cc | 803 // frobenius_norm = np.linalg.norm(D)
806 // frobenius_norm - diag_norm) * np.sqrt(frobenius_norm + diag_norm)
807 // while off_diag_norm > 1e-6 * frobenius_norm and iter < max_iter:
816 // frobenius_norm = np.linalg.norm(D)
819 // frobenius_norm - diag_norm) * np.sqrt(frobenius_norm + diag_norm)
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| /external/pytorch/torch/jit/ |
| D | _builtins.py | 113 (torch._VF.frobenius_norm, "aten::frobenius_norm"),
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| /external/pytorch/functorch/op_analysis/ |
| D | public_api | 239 frobenius_norm
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| D | annotated_ops | 307 frobenius_norm, reduction
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| /external/pytorch/test/functorch/ |
| D | test_vmap_registrations.py | 83 "aten::frobenius_norm",
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| /external/pytorch/aten/src/ATen/functorch/ |
| D | BatchRulesDecompositions.cpp | 214 OP_DECOMPOSE2(frobenius_norm, dim); in TORCH_LIBRARY_IMPL()
|
| /external/pytorch/test/mobile/model_test/ |
| D | model_ops.yaml | 157 aten::frobenius_norm.dim: 1
|
| D | coverage.yaml | 250 - aten::frobenius_norm.dim
251 - aten::frobenius_norm.out
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| /external/pytorch/aten/src/ATen/ |
| D | autocast_mode.cpp | 262 KERNEL_MPS2(frobenius_norm, dim, fp32) in TORCH_LIBRARY_IMPL()
|
| D | autocast_mode.h | 832 _(frobenius_norm, dim) \
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| /external/pytorch/torch/onnx/ |
| D | symbolic_opset13.py | 50 @_onnx_symbolic("aten::frobenius_norm")
52 def frobenius_norm(g: jit_utils.GraphContext, self, dim=None, keepdim=False): function
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| D | symbolic_opset9.py | 107 "frobenius_norm",
5538 return frobenius_norm(g, self, dim, keepdim)
5544 return frobenius_norm(g, self, dim, keepdim)
5592 @_onnx_symbolic("aten::frobenius_norm")
5594 def frobenius_norm(g: jit_utils.GraphContext, self, dim=None, keepdim=False): function
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| /external/pytorch/torch/csrc/jit/passes/ |
| D | autocast.cpp | 418 case aten::frobenius_norm: in handleBlock()
|
| /external/pytorch/torch/ |
| D | functional.py | 1834 return _VF.frobenius_norm(input, dim=(), keepdim=keepdim)
1858 return _VF.frobenius_norm(input, _dim, keepdim=keepdim) # type: ignore[arg-type]
1860 … return _VF.frobenius_norm(input, _dim, keepdim=keepdim, out=out) # type: ignore[arg-type]
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| D | overrides.py | 643 torch.frobenius_norm: lambda input, dim=None, keepdim=False, out=None: -1,
|
| /external/pytorch/docs/source/ |
| D | conf.py | 1384 "frobenius_norm",
1532 "frobenius_norm",
|
| /external/pytorch/aten/src/ATen/native/ |
| D | LinearAlgebra.cpp | 3060 Tensor frobenius_norm(const Tensor& self, IntArrayRef dim, bool keepdim) { in frobenius_norm() function
3064 "at::frobenius_norm is deprecated and it is just left for JIT compatibility. ", in frobenius_norm()
3084 "at::frobenius_norm is deprecated and it is just left for JIT compatibility. ", in frobenius_norm_out()
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| D | native_functions.yaml | 6755 - func: frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor
6759 - func: frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tenso…
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| /external/pytorch/torch/_dynamo/ |
| D | trace_rules.py | 1836 "torch.frobenius_norm",
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| /external/pytorch/test/cpp/lazy/ |
| D | test_lazy_ops.cpp | 2002 torch::Tensor b = torch::frobenius_norm(a, {dim}, /*keepdim=*/false); in TEST_F()
2006 torch::frobenius_norm(lazy_a, {dim}, /*keepdim=*/false); in TEST_F()
2016 torch::Tensor b = torch::frobenius_norm(a, dims, /*keepdim=*/false); in TEST_F()
2020 torch::frobenius_norm(lazy_a, dims, /*keepdim=*/false); in TEST_F()
|