flux tensoriel : : opérations : : MatriceDiagV3
#include <array_ops.h>
Renvoie un tenseur diagonal par lots avec des valeurs diagonales par lots données.
Résumé
Renvoie un tenseur avec le contenu en diagonal
comme k[0]
-th à k[1]
-th diagonales d'une matrice, avec tout le reste complété par padding
. num_rows
et num_cols
spécifient la dimension de la matrice la plus interne de la sortie. Si les deux ne sont pas spécifiés, l'opération suppose que la matrice la plus interne est carrée et déduit sa taille de k
et de la dimension la plus interne de diagonal
. Si un seul d'entre eux est spécifié, l'opération suppose que la valeur non spécifiée est la plus petite possible en fonction d'autres critères.
Soit diagonal
avoir r
dimensions [I, J, ..., L, M, N]
. Le tenseur de sortie a le rang r+1
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 a le rang r
avec la forme [I, J, ..., L, num_rows, num_cols]
.
La deuxième dimension la plus intérieure de la diagonal
a une double signification. Lorsque k
est 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 ; otherwiseoù
d = 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 vers la 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 ; otherwiseoù
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.
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 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_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:
Output
: Has rankr+1
whenk
is an integer ork[0] == k[1]
, rankr
otherwise.
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
operation
Operation operation
sortir
::tensorflow::Output output
Fonctions publiques
MatriceDiagV3
MatrixDiagV3( const ::tensorflow::Scope & scope, ::tensorflow::Input diagonal, ::tensorflow::Input k, ::tensorflow::Input num_rows, ::tensorflow::Input num_cols, ::tensorflow::Input padding_value )
MatriceDiagV3
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 )