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flux tensoriel : : opérations : : MatrixDiagPartV3
#include <array_ops.h> Renvoie la partie diagonale groupée d'un tenseur groupé.
Résumé
Renvoie un tenseur avec les k[0] -ème à k[1] -ème diagonales de l' input groupée.
Supposons que input ait r dimensions [I, J, ..., L, M, N] . Soit max_diag_len la longueur maximale parmi toutes les diagonales à extraire, max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0)) Soit num_diags le nombre de diagonales à extrait, num_diags = k[1] - k[0] + 1 .
Si num_diags == 1 , le tenseur de sortie est de rang r - 1 de forme [I, J, ..., L, max_diag_len] et valeurs :
diagonal[i, j, ..., l, n]
= input[i, j, ..., l, n+y, n+x] ; if 0 <= n+y < M and 0 <= n+x < N,
padding_value ; otherwise. où
y = max(-k[1], 0) ,
x = max(k[1], 0) .
Sinon, le tenseur de sortie a un rang r de dimensions [I, J, ..., L, num_diags, max_diag_len] avec des valeurs :
diagonal[i, j, ..., l, m, n]
= input[i, j, ..., l, n+y, n+x] ; if 0 <= n+y < M and 0 <= n+x < N,
padding_value ; otherwise. où
d = k[1] - m ,
y = max(-d, 0) - offset et
x = 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 ; otherwise où
diag_len(d) = min(cols - max(d, 0), rows + min(d, 0)) .
L'entrée doit être au moins une matrice.
Par exemple:
input = np.array([[[1, 2, 3, 4], # Input shape: (2, 3, 4)
[5, 6, 7, 8],
[9, 8, 7, 6]],
[[5, 4, 3, 2],
[1, 2, 3, 4],
[5, 6, 7, 8]]])# A main diagonal from each batch.
tf.matrix_diag_part(input) ==> [[1, 6, 7], # Output shape: (2, 3)
[5, 2, 7]]# A superdiagonal from each batch.
tf.matrix_diag_part(input, k = 1)
==> [[2, 7, 6], # Output shape: (2, 3)
[4, 3, 8]]# A band from each batch.
tf.matrix_diag_part(input, k = (-1, 2))
==> [[[0, 3, 8], # Output shape: (2, 4, 3)
[2, 7, 6],
[1, 6, 7],
[5, 8, 0]],
[[0, 3, 4],
[4, 3, 8],
[5, 2, 7],
[1, 6, 0]]]# LEFT_RIGHT alignment.
tf.matrix_diag_part(input, k = (-1, 2), align="LEFT_RIGHT")
==> [[[3, 8, 0], # Output shape: (2, 4, 3)
[2, 7, 6],
[1, 6, 7],
[0, 5, 8]],
[[3, 4, 0],
[4, 3, 8],
[5, 2, 7],
[0, 1, 6]]]# max_diag_len can be shorter than the main diagonal.
tf.matrix_diag_part(input, k = (-2, -1))
==> [[[5, 8],
[9, 0]],
[[1, 6],
[5, 0]]]# padding_value = 9
tf.matrix_diag_part(input, k = (1, 3), padding_value = 9)
==> [[[9, 9, 4], # Output shape: (2, 3, 3)
[9, 3, 8],
[2, 7, 6]],
[[9, 9, 2],
[9, 3, 4],
[4, 3, 8]]]
Arguments:
- scope: A Scope object
- input: Rank
r tensor where r >= 2.
- 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].
- padding_value: The value 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: The extracted diagonal(s).
Public static functions
|
Align(StringPiece x)
|
|
Public attributes
Fonctions publiques
nœud
::tensorflow::Node * node() const
operator::tensorflow::Input() const
opérateur :: tensorflow :: Sortie
operator::tensorflow::Output() const
Fonctions statiques publiques
Aligner
Attrs Align(
StringPiece x
)
Sauf indication contraire, le contenu de cette page est régi par une licence Creative Commons Attribution 4.0, et les échantillons de code sont régis par une licence Apache 2.0. Pour en savoir plus, consultez les Règles du site Google Developers. Java est une marque déposée d'Oracle et/ou de ses sociétés affiliées.
Dernière mise à jour le 2025/07/27 (UTC).
[null,null,["Dernière mise à jour le 2025/07/27 (UTC)."],[],[],null,["# tensorflow::ops::MatrixDiagPartV3 Class Reference\n\ntensorflow::ops::MatrixDiagPartV3\n=================================\n\n`#include \u003carray_ops.h\u003e`\n\nReturns the batched diagonal part of a batched tensor.\n\nSummary\n-------\n\nReturns a tensor with the `k[0]`-th to `k[1]`-th diagonals of the batched `input`.\n\nAssume `input` has `r` dimensions `[I, J, ..., L, M, N]`. Let `max_diag_len` be the maximum length among all diagonals to be extracted, `max_diag_len = min(M + min(k[1], 0), N + min(-k[0], 0))` Let `num_diags` be the number of diagonals to extract, `num_diags = k[1] - k[0] + 1`.\n\nIf `num_diags == 1`, the output tensor is of rank `r - 1` with shape `[I, J, ..., L, max_diag_len]` and values:\n\n\u003cbr /\u003e\n\n```scdoc\ndiagonal[i, j, ..., l, n]\n = input[i, j, ..., l, n+y, n+x] ; if 0 \u003c= n+y \u003c M and 0 \u003c= n+x \u003c N,\n padding_value ; otherwise.\n```\nwhere `y = max(-k[1], 0)`, `x = max(k[1], 0)`.\n\n\u003cbr /\u003e\n\nOtherwise, the output tensor has rank `r` with dimensions `[I, J, ..., L, num_diags, max_diag_len]` with values:\n\n\u003cbr /\u003e\n\n```scdoc\ndiagonal[i, j, ..., l, m, n]\n = input[i, j, ..., l, n+y, n+x] ; if 0 \u003c= n+y \u003c M and 0 \u003c= n+x \u003c N,\n padding_value ; otherwise.\n```\nwhere `d = k[1] - m`, `y = max(-d, 0) - offset`, and `x = max(d, 0) - offset`.\n\n\u003cbr /\u003e\n\n`offset` is zero except when the alignment of the diagonal is to the right. \n\n```mysql\noffset = max_diag_len - diag_len(d) ; if (`align` in {RIGHT_LEFT, RIGHT_RIGHT}\n and `d \u003e= 0`) or\n (`align` in {LEFT_RIGHT, RIGHT_RIGHT}\n and `d \u003c= 0`)\n 0 ; otherwise\n```\nwhere `diag_len(d) = min(cols - max(d, 0), rows + min(d, 0))`.\n\n\u003cbr /\u003e\n\nThe input must be at least a matrix.\n\nFor example:\n\n\n```text\ninput = np.array([[[1, 2, 3, 4], # Input shape: (2, 3, 4)\n [5, 6, 7, 8],\n [9, 8, 7, 6]],\n [[5, 4, 3, 2],\n [1, 2, 3, 4],\n [5, 6, 7, 8]]])\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\n# A main diagonal from each batch.\ntf.matrix_diag_part(input) ==\u003e [[1, 6, 7], # Output shape: (2, 3)\n [5, 2, 7]]\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\n# A superdiagonal from each batch.\ntf.matrix_diag_part(input, k = 1)\n ==\u003e [[2, 7, 6], # Output shape: (2, 3)\n [4, 3, 8]]\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\n# A band from each batch.\ntf.matrix_diag_part(input, k = (-1, 2))\n ==\u003e [[[0, 3, 8], # Output shape: (2, 4, 3)\n [2, 7, 6],\n [1, 6, 7],\n [5, 8, 0]],\n [[0, 3, 4],\n [4, 3, 8],\n [5, 2, 7],\n [1, 6, 0]]]\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\n# LEFT_RIGHT alignment.\ntf.matrix_diag_part(input, k = (-1, 2), align=\"LEFT_RIGHT\")\n ==\u003e [[[3, 8, 0], # Output shape: (2, 4, 3)\n [2, 7, 6],\n [1, 6, 7],\n [0, 5, 8]],\n [[3, 4, 0],\n [4, 3, 8],\n [5, 2, 7],\n [0, 1, 6]]]\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\n# max_diag_len can be shorter than the main diagonal.\ntf.matrix_diag_part(input, k = (-2, -1))\n ==\u003e [[[5, 8],\n [9, 0]],\n [[1, 6],\n [5, 0]]]\n```\n\n\u003cbr /\u003e\n\n\n```scdoc\n# padding_value = 9\ntf.matrix_diag_part(input, k = (1, 3), padding_value = 9)\n ==\u003e [[[9, 9, 4], # Output shape: (2, 3, 3)\n [9, 3, 8],\n [2, 7, 6]],\n [[9, 9, 2],\n [9, 3, 4],\n [4, 3, 8]]]\n```\n\n\u003cbr /\u003e\n\n\n````gdscript\n \n Arguments:\n \n- scope: A /versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope object\n\n \n- input: Rank r tensor where r \u003e= 2.\n\n \n- 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].\n\n \n- padding_value: The value to fill the area outside the specified diagonal band with. Default is 0.\n\n \n\n Optional attributes (see /versions/r2.2/api_docs/cc/struct/tensorflow/ops/matrix-diag-part-v3/attrs#structtensorflow_1_1ops_1_1_matrix_diag_part_v3_1_1_attrs):\n \n- 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.\n\n \n\n Returns:\n \n- /versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output: The extracted diagonal(s). \n\n \n\n \n\n\n \n### Constructors and Destructors\n\n\n \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1abda51edecba9f012bd9118b2b4e4eb39(const ::/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input input, ::/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input k, ::/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input padding_value)\n \n\n \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1ab2a7181a88ac68c2c1f8aa8e54d94f36(const ::/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input input, ::/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input k, ::/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input padding_value, const /versions/r2.2/api_docs/cc/struct/tensorflow/ops/matrix-diag-part-v3/attrs#structtensorflow_1_1ops_1_1_matrix_diag_part_v3_1_1_attrs & attrs)\n \n\n \n\n\n \n\n\n \n### Public attributes\n\n\n \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1ab5b1ebb490b4c3ac451095ad9c2860ce\n \n\n \n\n ::/versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output\n \n\n \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1aab8e9d1b13b2fafd7954d2acc89077f3\n \n\n \n\n /versions/r2.2/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation\n \n\n \n\n\n \n\n\n \n### Public functions\n\n\n \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1a42ebd82d85100f3cae0b90acce7c7d41() const \n \n\n \n\n ::tensorflow::Node *\n \n\n \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1a077796bdba19bb0c51a49a758b47b2f7() const \n \n\n \n\n `\n` \n`\n` \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1aad6d6537777dd1424e046801937d308c() const \n \n\n \n\n `\n` \n`\n` \n\n\n \n\n\n \n### Public static functions\n\n\n \n\n\n\n #classtensorflow_1_1ops_1_1_matrix_diag_part_v3_1a2bd0085f20db6aaa612f12494bfd9c6e(StringPiece x)\n \n\n \n\n /versions/r2.2/api_docs/cc/struct/tensorflow/ops/matrix-diag-part-v3/attrs#structtensorflow_1_1ops_1_1_matrix_diag_part_v3_1_1_attrs\n \n\n \n\n\n \n\n\n \n### Structs\n\n\n \n\n\n\n /versions/r2.2/api_docs/cc/struct/tensorflow/ops/matrix-diag-part-v3/attrs\n \n\n \nOptional attribute setters for /versions/r2.2/api_docs/cc/class/tensorflow/ops/matrix-diag-part-v3#classtensorflow_1_1ops_1_1_matrix_diag_part_v3. \n\n \n\n\n Public attributes\n \n \n### diagonal\n\n\n \n```\n::tensorflow::Output diagonal\n```\n\n \n\n \n \n \n### operation\n\n\n \n\n\n```text\nOperation operation\n```\n\n \n\n \n Public functions\n \n \n### MatrixDiagPartV3\n\n\n \n\n\n```gdscript\n MatrixDiagPartV3(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input k,\n ::tensorflow::Input padding_value\n)\n```\n\n \n\n \n \n \n### MatrixDiagPartV3\n\n\n \n\n\n```gdscript\n MatrixDiagPartV3(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input input,\n ::tensorflow::Input k,\n ::tensorflow::Input padding_value,\n const MatrixDiagPartV3::Attrs & attrs\n)\n```\n\n \n\n \n \n \n### node\n\n\n \n\n\n```gdscript\n::tensorflow::Node * node() const \n```\n\n \n\n \n \n \n### operator::tensorflow::Input\n\n\n \n\n\n```gdscript\n operator::tensorflow::Input() const \n```\n\n \n\n \n \n \n### operator::tensorflow::Output\n\n\n \n\n\n```gdscript\n operator::tensorflow::Output() const \n```\n\n \n\n \n Public static functions\n \n \n### Align\n\n\n \n\n\n```text\nAttrs Align(\n StringPiece x\n)\n```\n\n \n\n \n\n \n\n \n````"]]
