# tensorflow::ops::MatrixDiagV3 Class Reference # tensorflow::ops::MatrixDiagV3 `#include ` Returns a batched diagonal tensor with given batched diagonal values. ## Summary Returns a tensor with the contents in `diagonal` as `k[0]`-th to `k[1]`-th diagonals of a matrix, with everything else padded with `padding`. `num_rows` and `num_cols` specify the dimension of the innermost matrix of the output. If both are not specified, the op assumes the innermost matrix is square and infers its size from `k` and the innermost dimension of `diagonal`. If only one of them is specified, the op assumes the unspecified value is the smallest possible based on other criteria. Let `diagonal` have `r` dimensions `[I, J, ..., L, M, N]`. The output tensor has rank `r+1` with shape `[I, J, ..., L, M, num_rows, num_cols]` when only one diagonal is given (`k` is an integer or `k[0] == k[1]`). Otherwise, it has rank `r` with shape `[I, J, ..., L, num_rows, num_cols]`. The second innermost dimension of `diagonal` has double meaning. When `k` is scalar or `k[0] == k[1]`, `M` is part of the batch size \[I, J, ..., M\], and the output tensor is: ``` output[i, j, ..., l, m, n] = diagonal[i, j, ..., l, n-max(d_upper, 0)] ; if n - m == d_upper padding_value ; otherwise ```
Otherwise, `M` is treated as the number of diagonals for the matrix in the same batch (`M = k[1]-k[0]+1`), and the output tensor is:
``` output[i, j, ..., l, m, n] = diagonal[i, j, ..., l, diag_index, index_in_diag] ; if k[0] <= d <= k[1] padding_value ; otherwise ``` where `d = n - m`, `diag_index = [k] - d`, and `index_in_diag = n - max(d, 0) + offset`.
`offset` is zero except when the alignment of the diagonal is to the right. ``` offset = max_diag_len - diag_len(d) ; if (`align` in {RIGHT_LEFT, RIGHT_RIGHT} and `d >= 0`) or (`align` in {LEFT_RIGHT, RIGHT_RIGHT} and `d <= 0`) 0 ; otherwise ``` where `diag_len(d) = min(cols - max(d, 0), rows + min(d, 0))`.
For example: ``` # The main diagonal. diagonal = np.array([[1, 2, 3, 4], # Input shape: (2, 4) [5, 6, 7, 8]]) tf.matrix_diag(diagonal) ==> [[[1, 0, 0, 0], # Output shape: (2, 4, 4) [0, 2, 0, 0], [0, 0, 3, 0], [0, 0, 0, 4]], [[5, 0, 0, 0], [0, 6, 0, 0], [0, 0, 7, 0], [0, 0, 0, 8]]] ```
``` # A superdiagonal (per batch). diagonal = np.array([[1, 2, 3], # Input shape: (2, 3) [4, 5, 6]]) tf.matrix_diag(diagonal, k = 1) ==> [[[0, 1, 0, 0], # Output shape: (2, 4, 4) [0, 0, 2, 0], [0, 0, 0, 3], [0, 0, 0, 0]], [[0, 4, 0, 0], [0, 0, 5, 0], [0, 0, 0, 6], [0, 0, 0, 0]]] ```
``` # A tridiagonal band (per batch). diagonals = np.array([[[0, 8, 9], # Input shape: (2, 2, 3) [1, 2, 3], [4, 5, 0]], [[0, 2, 3], [6, 7, 9], [9, 1, 0]]]) tf.matrix_diag(diagonals, k = (-1, 1)) ==> [[[1, 8, 0], # Output shape: (2, 3, 3) [4, 2, 9], [0, 5, 3]], [[6, 2, 0], [9, 7, 3], [0, 1, 9]]] ```
``` # LEFT_RIGHT alignment. diagonals = np.array([[[8, 9, 0], # Input shape: (2, 2, 3) [1, 2, 3], [0, 4, 5]], [[2, 3, 0], [6, 7, 9], [0, 9, 1]]]) tf.matrix_diag(diagonals, k = (-1, 1), align="LEFT_RIGHT") ==> [[[1, 8, 0], # Output shape: (2, 3, 3) [4, 2, 9], [0, 5, 3]], [[6, 2, 0], [9, 7, 3], [0, 1, 9]]] ```
``` # Rectangular matrix. diagonal = np.array([1, 2]) # Input shape: (2) tf.matrix_diag(diagonal, k = -1, num_rows = 3, num_cols = 4) ==> [[0, 0, 0, 0], # Output shape: (3, 4) [1, 0, 0, 0], [0, 2, 0, 0]] ```
``` # Rectangular matrix with inferred num_cols and padding_value = 9. tf.matrix_diag(diagonal, k = -1, num_rows = 3, padding_value = 9) ==> [[9, 9], # Output shape: (3, 2) [1, 9], [9, 2]] ```
```` Arguments: - scope: A https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope object - diagonal: Rank `r`, where `r >= 1` - k: Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main diagonal, and negative value means subdiagonals. `k` can be a single integer (for a single diagonal) or a pair of integers specifying the low and high ends of a matrix band. `k[0]` must not be larger than `k[1]`. - num_rows: The number of rows of the output matrix. If it is not provided, the op assumes the output matrix is a square matrix and infers the matrix size from k and the innermost dimension of `diagonal`. - num_cols: The number of columns of the output matrix. If it is not provided, the op assumes the output matrix is a square matrix and infers the matrix size from k and the innermost dimension of `diagonal`. - padding_value: The number to fill the area outside the specified diagonal band with. Default is 0. Optional attributes (see `https://www.tensorflow.org/versions/r2.3/api_docs/cc/struct/tensorflow/ops/matrix-diag-v3/attrs#structtensorflow_1_1ops_1_1_matrix_diag_v3_1_1_attrs`): - align: Some diagonals are shorter than `max_diag_len` and need to be padded. `align` is a string specifying how superdiagonals and subdiagonals should be aligned, respectively. There are four possible alignments: "RIGHT_LEFT" (default), "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals to the right (left-pads the row) and subdiagonals to the left (right-pads the row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is the opposite alignment. Returns: - `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output`: Has rank `r+1` when `k` is an integer or `k[0] == k[1]`, rank `r` otherwise. ### Constructors and Destructors `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1ae15f2ceb99ae691a2f9b52311ceb67ee(const ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input diagonal, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input k, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input num_rows, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input num_cols, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input padding_value)` `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1ac8140fdd73a0274d929e97471a92bcf6(const ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input diagonal, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input k, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input num_rows, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input num_cols, ::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input padding_value, const https://www.tensorflow.org/versions/r2.3/api_docs/cc/struct/tensorflow/ops/matrix-diag-v3/attrs#structtensorflow_1_1ops_1_1_matrix_diag_v3_1_1_attrs & attrs)` ### Public attributes `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1a8470b34b4891814a4ba0fee33124c406` `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation` `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1a5909ed23456448d4060a36f3efa969d1` `::https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output` ### Public functions `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1ad867e695b350f6aabb4d7fded813638f() const ` `::tensorflow::Node *` `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1a62f98c657022427d95dd0420bcacd6f9() const ` ` `` ` `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1a7ffe2ed277a437e26729efef42f58e0a() const ` ` `` ` ### Public static functions `https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3_1abd0ab9e473db3bcb437524898b0232d6(StringPiece x)` `https://www.tensorflow.org/versions/r2.3/api_docs/cc/struct/tensorflow/ops/matrix-diag-v3/attrs#structtensorflow_1_1ops_1_1_matrix_diag_v3_1_1_attrs` ### Structs https://www.tensorflow.org/versions/r2.3/api_docs/cc/struct/tensorflow/ops/matrix-diag-v3/attrs Optional attribute setters for https://www.tensorflow.org/versions/r2.3/api_docs/cc/class/tensorflow/ops/matrix-diag-v3#classtensorflow_1_1ops_1_1_matrix_diag_v3. Public attributes ### operation ``` Operation operation ``` ### output ``` ::tensorflow::Output output ``` Public functions ### MatrixDiagV3 ``` MatrixDiagV3( const ::tensorflow::Scope & scope, ::tensorflow::Input diagonal, ::tensorflow::Input k, ::tensorflow::Input num_rows, ::tensorflow::Input num_cols, ::tensorflow::Input padding_value ) ``` ### MatrixDiagV3 ``` MatrixDiagV3( const ::tensorflow::Scope & scope, ::tensorflow::Input diagonal, ::tensorflow::Input k, ::tensorflow::Input num_rows, ::tensorflow::Input num_cols, ::tensorflow::Input padding_value, const MatrixDiagV3::Attrs & attrs ) ``` ### node ``` ::tensorflow::Node * node() const ``` ### operator::tensorflow::Input ``` operator::tensorflow::Input() const ``` ### operator::tensorflow::Output ``` operator::tensorflow::Output() const ``` Public static functions ### Align ``` Attrs Align( StringPiece x ) ``` ````