tensorflow::ops::MatrixDiagV3
#include <array_ops.h>Renvoie un tenseur diagonal par lots avec les valeurs diagonales par lots données.
Résumé
Renvoie un tenseur dont les éléments diagonal correspondent aux éléments de la diagonale k[0] à k[1] d'une matrice, le reste étant complété par padding . Les paramètres num_rows et num_cols spécifient la dimension de la matrice interne du résultat. Si les deux ne sont pas spécifiés, l'opération considère que la matrice interne est carrée et déduit sa taille à partir de k et de la dimension de la diagonal interne. Si un seul de ces paramètres est spécifié, l'opération considère que la valeur non spécifiée est la plus petite possible selon d'autres critères.
Soit diagonal de dimension r [I, J, ..., L, M, N] . Le tenseur de sortie est de rang r+1 et de forme [I, J, ..., L, M, num_rows, num_cols] lorsqu'une seule diagonale est donnée ( k est un entier ou k[0] == k[1] ). Sinon, il est de rang r et de forme [I, J, ..., L, num_rows, num_cols] .
La deuxième dimension la plus interne de la diagonal a une double signification. Lorsque k est un scalaire ou k[0] == k[1] , M fait partie de la taille du lot [I, J, ..., M], et le tenseur de sortie est :
output[i, j, ..., l, m, n]
= diagonal[i, j, ..., l, n-max(d_upper, 0)] ; if n - m == d_upper
padding_value ; otherwise Sinon, M est traité comme le nombre de diagonales de la matrice dans le même lot ( M = k[1]-k[0]+1 ), et le tenseur de sortie est :
output[i, j, ..., l, m, n]
= diagonal[i, j, ..., l, diag_index, index_in_diag] ; if k[0] <= d <= k[1]
padding_value ; otherwised = n - m , diag_index = [k] - d , et index_in_diag = n - max(d, 0) + offset . offset est nul sauf lorsque l'alignement de la diagonale est à droite.
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
diag_len(d) = min(cols - max(d, 0), rows + min(d, 0)) .Par exemple:
# 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 Scope object
- diagonal: Rank
r, wherer >= 1 - k: Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main diagonal, and negative value means subdiagonals.
kcan 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 thank[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 Attrs):
- align: Some diagonals are shorter than
max_diag_lenand need to be padded.alignis 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:
Output: Has rankr+1whenkis an integer ork[0] == k[1], rankrotherwise.
Constructors and Destructors |
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MatrixDiagV3(const ::tensorflow::Scope & scope, ::tensorflow::Input diagonal, ::tensorflow::Input k, ::tensorflow::Input num_rows, ::tensorflow::Input num_cols, ::tensorflow::Input padding_value)
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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)
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Public attributes |
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operation
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output
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Public functions |
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node() const
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::tensorflow::Node *
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operator::tensorflow::Input() const
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operator::tensorflow::Output() const
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Public static functions |
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Align(StringPiece x)
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Structs |
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tensorflow:: |
Optional attribute setters for MatrixDiagV3. |
Public attributes
sortir
::tensorflow::Output output
fonctions publiques
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 )
nœud
::tensorflow::Node * node() const
opérateur::tensorflow::Entrée
operator::tensorflow::Input() const
opérateur::tensorflow::Sortie
operator::tensorflow::Output() const
fonctions statiques publiques
Aligner
Attrs Align( StringPiece x )