Searched refs:Cholesky (Results 1 – 25 of 53) sorted by relevance
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| /external/eigen/Eigen/ |
| D | Cholesky | 15 /** \defgroup Cholesky_Module Cholesky module
19 …* This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matr…
27 * #include <Eigen/Cholesky>
31 #include "src/Cholesky/LLT.h"
32 #include "src/Cholesky/LDLT.h"
35 #include "src/Cholesky/LLT_LAPACKE.h"
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| D | PaStiXSupport | 30 * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization.
31 * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization.
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| D | CholmodSupport | 24 * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
25 …* - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit…
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| D | Dense | 3 #include "Cholesky"
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| D | QR | 15 #include "Cholesky"
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| D | SparseCholesky | 21 …* This module currently provides two variants of the direct sparse Cholesky decomposition for self…
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| D | Eigenvalues | 15 #include "Cholesky"
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| D | OrderingMethods | 25 * Using for instance the sparse Cholesky decomposition, it is expected that
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SparseMatrixSparseCholesky.pbtxt | 14 description: "The sparse Cholesky decompsition of `input`."
16 summary: "Computes the sparse Cholesky decomposition of `input`."
18 Computes the Sparse Cholesky decomposition of a sparse matrix, with the given
37 sparse matrix represents `L`, the lower triangular Cholesky factor satisfying
67 # Obtain the Sparse Cholesky factor using AMD Ordering for reducing zero
68 # fill-in (number of structural non-zeros in the sparse Cholesky factor).
74 # Convert the CSRSparseMatrix Cholesky factor to a dense Tensor
82 `dense_cholesky_value` stores the dense Cholesky factor:
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| D | api_def_CholeskyGrad.pbtxt | 6 Output of batch Cholesky algorithm l = cholesky(A). Shape is `[..., M, M]`.
25 summary: "Computes the reverse mode backpropagated gradient of the Cholesky algorithm."
27 For an explanation see "Differentiation of the Cholesky algorithm" by
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| D | api_def_Cholesky.pbtxt | 2 graph_op_name: "Cholesky"
15 summary: "Computes the Cholesky decomposition of one or more square matrices."
25 containing the Cholesky decompositions for all input submatrices `[..., :, :]`.
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| D | api_def_SparseMatrixOrderingAMD.pbtxt | 18 Cholesky (or other decompositions) in having fewer zero fill-in compared to
29 reused for the Cholesky decompositions of sparse matrices with the same sparsity
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| D | api_def_MatrixSolveLs.pbtxt | 50 equations using Cholesky decomposition. Specifically, if \\(m \ge n\\) then
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| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| D | cholesky_test.cc | 51 Cholesky(a, /*lower=*/true); in XLA_TEST_F()
82 Cholesky(a, /*lower=*/true); in XLA_TEST_F()
115 LowerTriangle(Cholesky(a, /*lower=*/true)); in XLA_TEST_F()
141 UpperTriangle(Cholesky(a, /*lower=*/false)); in XLA_TEST_F()
166 LowerTriangle(Cholesky(a, /*lower=*/true)); in XLA_TEST_F()
197 LowerTriangle(Cholesky(a, /*lower=*/true)); in XLA_TEST_F()
241 auto cholesky = Triangle(Cholesky(matrix, lower), lower); in XLA_TEST_P()
286 auto cholesky = Triangle(Cholesky(matrix, lower), lower); in XLA_TEST_P()
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
| D | Cholesky.pbtxt | 2 name: "Cholesky"
23 name: "Cholesky"
46 name: "Cholesky"
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | Cholesky.pbtxt | 2 name: "Cholesky"
23 name: "Cholesky"
46 name: "Cholesky"
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| /external/tensorflow/tensorflow/core/api_def/java_api/ |
| D | api_def_Cholesky.pbtxt | 2 graph_op_name: "Cholesky"
4 name: "linalg.Cholesky"
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| /external/tensorflow/tensorflow/core/api_def/python_api/ |
| D | api_def_Cholesky.pbtxt | 2 graph_op_name: "Cholesky"
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| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | cholesky_op.cc | 29 xla::Triangle(xla::Cholesky(ctx->Input(0), /*lower=*/true), in Compile()
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| /external/eigen/bench/btl/data/ |
| D | action_settings.txt | 11 cholesky ; "{/*1.5 Cholesky decomposition}" ; "matrix size" ; 4:5000
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| /external/tensorflow/third_party/eigen3/ |
| D | BUILD | 19 "Eigen/Cholesky",
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| /external/eigen/doc/ |
| D | DenseDecompositionBenchmark.dox | 12 …ric covariance matrix \f$ A^T A \f$ for the first four solvers based on Cholesky and LU, as denote…
34 …+ For largely over-constrained problems, the cost of Cholesky/LU decompositions is dominated by th…
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| D | B01_Experimental.dox | 25 \li Cholesky
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| D | QuickReference.dox | 19 …t"><td>\link Cholesky_Module Cholesky \endlink</td><td>\code#include <Eigen/Cholesky>\endcode</td>…
25 …code#include <Eigen/Dense>\endcode</td><td>Includes Core, Geometry, LU, Cholesky, SVD, QR, and Eig…
717 // via a standard Cholesky factorization
719 // via a Cholesky factorization with pivoting
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| D | InplaceDecomposition.dox | 5 Starting from %Eigen 3.3, the LU, Cholesky, and QR decompositions can operate \em inplace, that is,…
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