| /external/eigen/Eigen/src/Eigenvalues/ |
| D | SelfAdjointEigenSolver.h | 24 ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag, const Index maxIt…
238 …omputeFromTridiagonal(const RealVectorType& diag, const SubDiagonalType& subdiag , int options=Com…
393 static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scal…
451 ::computeFromTridiagonal(const RealVectorType& diag, const SubDiagonalType& subdiag , int options)
457 m_subdiag = subdiag;
482 ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag, const Index maxIt…
501 …if (internal::isMuchSmallerThan(abs(subdiag[i]),(abs(diag[i])+abs(diag[i+1])),precision) || abs(su…
502 subdiag[i] = 0;
505 while (end>0 && subdiag[end-1]==RealScalar(0))
517 while (start>0 && subdiag[start-1]!=0)
[all …]
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| D | Tridiagonalization.h | 427 void tridiagonalization_inplace(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, bool…
429 eigen_assert(mat.cols()==mat.rows() && diag.size()==mat.rows() && subdiag.size()==mat.rows()-1);
430 tridiagonalization_inplace_selector<MatrixType>::run(mat, diag, subdiag, extractQ);
442 static void run(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, bool extractQ)
447 subdiag = mat.template diagonal<-1>().real();
466 static void run(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, bool extractQ)
476 subdiag[0] = mat(1,0);
477 subdiag[1] = mat(2,1);
490 subdiag[0] = beta;
491 subdiag[1] = mat(2,1) - m01 * q;
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| /external/tensorflow/tensorflow/core/kernels/linalg/ |
| D | tridiagonal_solve_op.cc | 109 const auto& subdiag = diagonals.row(2); in ComputeMatrix() local
129 subdiag, rhs, x); in ComputeMatrix()
131 SolveWithThomasAlgorithm(context, superdiag, diag, subdiag, rhs, x); in ComputeMatrix()
141 const MatrixMapRow& subdiag, in SolveWithGaussianEliminationWithPivoting() argument
159 if (std::abs(u(i)) >= std::abs(subdiag(i + 1))) { in SolveWithGaussianEliminationWithPivoting()
163 const Scalar factor = subdiag(i + 1) / u(i, 0); in SolveWithGaussianEliminationWithPivoting()
172 const Scalar factor = u(i, 0) / subdiag(i + 1); in SolveWithGaussianEliminationWithPivoting()
173 u(i, 0) = subdiag(i + 1); in SolveWithGaussianEliminationWithPivoting()
197 const MatrixMapRow& subdiag, in SolveWithThomasAlgorithm() argument
212 auto denom = diag(i) - subdiag(i) * u(i - 1); in SolveWithThomasAlgorithm()
[all …]
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| D | tridiagonal_matmul_op_gpu.cu.cc | 40 const Scalar* __restrict__ subdiag, in TridiagonalMatMulKernel() argument
47 result = result + subdiag[row_id] * rhs[i - n]; in TridiagonalMatMulKernel()
65 const Tensor& subdiag = context->input(2); in Compute() local
85 maindiag.flat<Scalar>().data(), subdiag.flat<Scalar>().data(), in Compute()
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| D | tridiagonal_solve_op_gpu.cu.cc | 143 const auto& subdiag = diagonals.row(2); in ComputeMatrix() local
165 subdiag.data(), x.data(), m, 1); in ComputeMatrix()
179 subdiag.data(), temp.flat<Scalar>().data(), m, k); in ComputeMatrix()
201 const Scalar* subdiag, Scalar* rhs, const int num_eqs, in SolveWithGtsv() argument
208 num_eqs, num_rhs, subdiag, diag, superdiag, rhs, in SolveWithGtsv()
219 num_eqs, num_rhs, subdiag, diag, superdiag, rhs, in SolveWithGtsv()
300 const Scalar* subdiag = lhs_data + 2 * matrix_size * batch_size; in ComputeWithGtsvBatched() local
316 matrix_size, subdiag, diag, superdiag, x, in ComputeWithGtsvBatched()
324 matrix_size, subdiag, diag, superdiag, x, in ComputeWithGtsvBatched()
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| D | tridiagonal_matmul_op.cc | 94 const auto& subdiag = inputs[2].row(0); in ComputeMatrix() local
104 ConstVectorMap subdiag_map(subdiag.data() + 1, m - 1); in ComputeMatrix()
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| /external/eigen/doc/snippets/ |
| D | Tridiagonalization_decomposeInPlace.cpp | 6 VectorXd subdiag(4); variable
7 internal::tridiagonalization_inplace(A, diag, subdiag, true);
10 cout << "The subdiagonal of the tridiagonal matrix T is:" << endl << subdiag << endl;
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| D | Tridiagonalization_diagonal.cpp | 12 VectorXd subdiag = triOfA.subDiagonal(); variable
13 cout << "The subdiagonal is:" << endl << subdiag << endl;
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| /external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
| D | linear_operator_tridiag_test.py | 45 subdiag = linear_operator_test_util.random_sign_uniform(
52 superdiag = math_ops.conj(subdiag)
59 [superdiag, diag, subdiag], axis=-2)
69 diagonals = [superdiag, diag, subdiag]
71 diagonals = array_ops.stack([superdiag, diag, subdiag], axis=-2)
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | tridiagonal_matmul_op_test.py | 44 subdiag, argument
49 subdiag_extended = np.pad(subdiag, [1, 0], 'constant')
52 subdiag, -1)
94 def _makeTridiagonalMatrix(self, superdiag, maindiag, subdiag): argument
100 sub_part = array_ops.pad(array_ops.matrix_diag(subdiag), sub_pad)
147 subdiag = self._randomComplexArray((b, m - 1))
151 np.diag(subdiag[i], -1) for i in range(b)])
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| D | tridiagonal_solve_op_test.py | 644 subdiag = array_ops.placeholder(dtypes.float64, shape=[None])
647 x = linalg_impl.tridiagonal_solve((superdiag, diag, subdiag),
655 subdiag: [20, 1, -1, 1],
683 subdiag = 2 * np.abs(np.random.randn(matrix_size - 1))
685 matrix = sparse.diags([superdiag, diag, subdiag], [1, 0, -1]).toarray()
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| /external/tensorflow/tensorflow/python/ops/linalg/ |
| D | linear_operator_tridiag.py | 263 subdiag = manip_ops.roll(diagonals[..., 2, :], shift=-1, axis=-1)
265 math_ops.conj(subdiag[..., :-1]),
271 subdiag = manip_ops.roll(self.diagonals[2], shift=-1, axis=-1)
273 math_ops.conj(subdiag[..., :-1]),
291 superdiag, diag, subdiag = array_ops.unstack(
295 new_superdiag = manip_ops.roll(subdiag, shift=-1, axis=-1)
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| D | linalg_impl.py | 555 superdiag, maindiag, subdiag = diagonals
556 if (not subdiag.shape[:-1].is_compatible_with(maindiag.shape[:-1]) or
561 subdiag.shape, maindiag.shape, superdiag.shape))
576 subdiag = pad_if_necessary(subdiag, 'subdiagonal', [1, 0])
579 diagonals = array_ops.stack((superdiag, maindiag, subdiag), axis=-2)
702 subdiag = diagonals[..., 2, :]
704 superdiag, maindiag, subdiag = diagonals
716 subdiag = diags[..., 2, :]
724 subdiag = array_ops.expand_dims(subdiag, -2)
726 return linalg_ops.tridiagonal_mat_mul(superdiag, maindiag, subdiag, rhs, name)
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | TridiagonalMatMul.pbtxt | 12 name: "subdiag"
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
| D | TridiagonalMatMul.pbtxt | 12 name: "subdiag"
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| /external/tensorflow/tensorflow/core/ops/ |
| D | linalg_ops.cc | 287 ShapeHandle subdiag; in TridiagonalMatMulShapeFn() local
293 TF_RETURN_IF_ERROR(c->WithRankAtLeast(c->input(2), 2, &subdiag)); in TridiagonalMatMulShapeFn()
303 TF_RETURN_IF_ERROR(c->Subshape(subdiag, 0, -2, &subdiag_batch_shape)); in TridiagonalMatMulShapeFn()
313 TF_RETURN_IF_ERROR(c->Merge(subdiag, maindiag, &maindiag)); in TridiagonalMatMulShapeFn()
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| D | ops.pbtxt | 56785 name: "subdiag"
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_TridiagonalMatMul.pbtxt | 19 name: "subdiag"
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| /external/tensorflow/tensorflow/python/ops/ |
| D | linalg_grad.py | 1015 subdiag = array_ops.concat((zeros, diags[..., 0, :-1]), axis=-1)
1024 subdiag = array_ops.pad(diags[..., 0, :-1], subdiag_pad)
1025 return array_ops.stack([superdiag, diag, subdiag], axis=-2)
1051 subdiag = math_ops.reduce_sum(
1062 subdiag = math_ops.reduce_sum(
1064 return array_ops.stack([superdiag, diag, subdiag], axis=-2)
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.raw_ops.pbtxt | 5157 …argspec: "args=[\'superdiag\', \'maindiag\', \'subdiag\', \'rhs\', \'name\'], varargs=None, keywor…
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.raw_ops.pbtxt | 5157 …argspec: "args=[\'superdiag\', \'maindiag\', \'subdiag\', \'rhs\', \'name\'], varargs=None, keywor…
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| /external/tensorflow/tensorflow/go/op/ |
| D | wrappers.go | 15036 func TridiagonalMatMul(scope *Scope, superdiag tf.Output, maindiag tf.Output, subdiag tf.Output, rh…
15043 superdiag, maindiag, subdiag, rhs,
|