| /aosp_15_r20/external/pytorch/test/ |
| H A D | test_linalg.py | 5628 lu_data, lu_pivots = torch.linalg.lu_factor(x)
5631 torch.lu_unpack(lu_data, lu_pivots.long())
5634 p, l, u = torch.lu_unpack(lu_data, lu_pivots, unpack_data=False)
5636 p, l, u = torch.lu_unpack(lu_data, lu_pivots, unpack_pivots=False)
5638 p, l, u = torch.lu_unpack(lu_data, lu_pivots, unpack_data=False, unpack_pivots=False)
7997 LU_data, LU_pivots, info = torch.linalg.lu_factor_ex(A)
7999 return b, A, LU_data, LU_pivots
8009 … b, A, LU_data, LU_pivots = self.lu_solve_test_helper((n, n), (n, k), pivot, device, dtype)
8010 x = torch.lu_solve(b, LU_data, LU_pivots)
8025 … b, A, LU_data, LU_pivots = self.lu_solve_test_helper(A_dims, b_dims, pivot, device, dtype)
[all …]
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| /aosp_15_r20/external/pytorch/torch/csrc/inductor/aoti_torch/generated/ |
| H A D | c_shim_cpu.h | 78 …ror aoti_torch_cpu_lu_unpack(AtenTensorHandle LU_data, AtenTensorHandle LU_pivots, int32_t unpack_…
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| H A D | c_shim_cuda.h | 87 …or aoti_torch_cuda_lu_unpack(AtenTensorHandle LU_data, AtenTensorHandle LU_pivots, int32_t unpack_…
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| /aosp_15_r20/external/pytorch/aten/src/ATen/native/ |
| H A D | BatchLinearAlgebra.cpp | 699 "torch.lu_unpack: LU_pivots is expected to be a contiguous tensor of torch.int32 dtype.\n" in TORCH_META_FUNC()
2146 Tensor lu_solve(const Tensor& self, const Tensor& LU_data, const Tensor& LU_pivots) { in lu_solve() argument
2155 return at::linalg_lu_solve(LU_data, LU_pivots, self); in lu_solve()
2158 Tensor& lu_solve_out(const Tensor& self, const Tensor& LU_data, const Tensor& LU_pivots, Tensor& re… in lu_solve_out() argument
2167 return at::linalg_lu_solve_out(result, LU_data, LU_pivots, self); in lu_solve_out()
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| H A D | native_functions.yaml | 9411 - func: lu_solve.out(Tensor self, Tensor LU_data, Tensor LU_pivots, *, Tensor(a!) out) -> Tensor(a!)
9413 - func: lu_solve(Tensor self, Tensor LU_data, Tensor LU_pivots) -> Tensor
9417 - func: lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True)…
9421 - func: lu_unpack.out(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=T…
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| /aosp_15_r20/external/pytorch/torch/csrc/jit/tensorexpr/ |
| H A D | external_functions_codegen.cpp | 1877 const at::Tensor& LU_pivots = tensors[3]; in nnc_aten_lu_solve() local
1879 at::lu_solve_out(r, self, LU_data, LU_pivots); in nnc_aten_lu_solve()
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| /aosp_15_r20/external/pytorch/torch/ |
| H A D | overrides.py | 652 torch.lu_unpack: lambda LU_data, LU_pivots, unpack_data=True, unpack_pivots=True: -1,
752 torch.lu_solve: lambda b, LU_data, LU_pivots, out=None: -1,
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| H A D | _torch_docs.py | 6280 lu_unpack(LU_data, LU_pivots, unpack_data=True, unpack_pivots=True, *, out=None) -> (Tensor, Tensor…
6291 LU_pivots (Tensor): the packed LU factorization pivots
6339 lu_solve(b, LU_data, LU_pivots, *, out=None) -> Tensor
6361 …LU_pivots (IntTensor): the pivots of the LU factorization from :meth:`~linalg.lu_factor` of size :…
6363 … The batch dimensions of :attr:`LU_pivots` must be equal to the batch dimensions of
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| H A D | _tensor_docs.py | 3119 lu_solve(LU_data, LU_pivots) -> Tensor
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| H A D | _meta_registrations.py | 1220 … "torch.lu_unpack: LU_pivots is expected to be a contiguous tensor of torch.int32 dtype.\n"
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| /aosp_15_r20/external/pytorch/tools/autograd/ |
| H A D | derivatives.yaml | 1052 - name: lu_unpack(Tensor LU_data, Tensor LU_pivots, bool unpack_data=True, bool unpack_pivots=True)…
1054 LU_pivots: non_differentiable
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| /aosp_15_r20/external/pytorch/torch/csrc/autograd/ |
| H A D | FunctionsManual.cpp | 5693 // B_grad = P L^{-H} U^{-H} X_grad = lu_solve(X_grad, LU_data, LU_pivots,
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