| /external/eigen/lapack/ |
| svd.cpp | 19 int diag_size = (std::min)(*m,*n); local
30 || (*jobz=='S' && *ldvt<diag_size)
58 make_vector(s,diag_size) = svd.singularValues().head(diag_size);
67 matrix(u,*m,diag_size,*ldu) = svd.matrixU();
68 matrix(vt,diag_size,*n,*ldvt) = svd.matrixV().adjoint();
78 matrix(a,diag_size,*n,*lda) = svd.matrixV().adjoint();
90 int diag_size = (std::min)(*m,*n); local
101 || (*jobv=='S' && *ldvt<diag_size)) *info = -11;
126 make_vector(s,diag_size) = svd.singularValues().head(diag_size)
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| linalg_ops_impl.py | 51 diag_size = math_ops.minimum(num_rows, num_columns)
59 diag_size = np.minimum(num_rows, num_columns)
62 if isinstance(batch_shape, ops.Tensor) or isinstance(diag_size, ops.Tensor):
65 diag_shape = array_ops.concat((batch_shape, [diag_size]), axis=0)
71 diag_shape = batch_shape + [diag_size]
|
| sparse_ops.py | 182 diag_size = math_ops.minimum(num_rows, num_columns)
183 diag_range = math_ops.range(diag_size, dtype=dtypes.int64)
187 values=array_ops.ones(diag_size, dtype=dtype),
[all...] |
| /external/tensorflow/tensorflow/python/ops/linalg/ |
| linear_operator_circulant.py | 447 diag_size = self.domain_dimension.value
450 diag_size = self.domain_dimension_tensor()
464 diag_value = self.trace() / math_ops.cast(diag_size, self.dtype)
[all...] |
| /external/eigen/test/ |
| main.h | 584 const Index diag_size = (std::min)(d.rows(),d.cols());
585 if(diag_size != desired_rank)
586 d.diagonal().segment(desired_rank, diag_size-desired_rank) = VectorType::Zero(diag_size-desired_rank);
|
| /external/eigen/Eigen/src/Core/util/ |
| XprHelper.h | 611 enum { diag_size = EIGEN_SIZE_MIN_PREFER_DYNAMIC(ExpressionType::RowsAtCompileTime, ExpressionType::ColsAtCompileTime),
614 typedef Matrix<Scalar, diag_size, 1, ExpressionType::PlainObject::Options & ~RowMajor, max_diag_size, 1> MatrixDiagType;
615 typedef Array<Scalar, diag_size, 1, ExpressionType::PlainObject::Options & ~RowMajor, max_diag_size, 1> ArrayDiagType;
[all...] |
