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flux tensoriel : : opérations : : Où3
#include <math_ops.h>
Sélectionne les éléments de x
ou y
, selon condition
.
Résumé
Les tenseurs x
et y
doivent tous avoir la même forme, et la sortie aura également cette forme.
Le tenseur condition
doit être un scalaire si x
et y
sont des scalaires. Si x
et y
sont des vecteurs ou un rang supérieur, alors condition
doit être soit un scalaire, un vecteur dont la taille correspond à la première dimension de x
, soit avoir la même forme que x
.
Le tenseur condition
agit comme un masque qui choisit, en fonction de la valeur de chaque élément, si l'élément/la ligne correspondant dans la sortie doit être extrait de x
(si vrai) ou y
(si faux).
Si condition
est un vecteur et que x
et y
sont des matrices de rang supérieur, alors il choisit quelle ligne (dimension extérieure) copier à partir de x
et y
. Si condition
a la même forme que x
et y
, alors elle choisit quel élément copier à partir de x
et y
.
Par exemple:
# 'condition' tensor is [[True, False]
# [False, True]]
# 't' is [[1, 2],
# [3, 4]]
# 'e' is [[5, 6],
# [7, 8]]
select(condition, t, e) # => [[1, 6], [7, 4]]
# 'condition' tensor is [True, False]
# 't' is [[1, 2],
# [3, 4]]
# 'e' is [[5, 6],
# [7, 8]]
select(condition, t, e) ==> [[1, 2],
[7, 8]]
Arguments:
- scope: A Scope object
- x: = A
Tensor
which may have the same shape as condition
. If condition
is rank 1, x
may have higher rank, but its first dimension must match the size of condition
.
- y: = A
Tensor
with the same type and shape as x
.
Returns:
Public attributes
Fonctions publiques
nœud
::tensorflow::Node * node() const
operator::tensorflow::Input() const
opérateur :: tensorflow :: Sortie
operator::tensorflow::Output() const
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 2025/07/26 (UTC).
[null,null,["Dernière mise à jour le 2025/07/26 (UTC)."],[],[],null,["# tensorflow::ops::Where3 Class Reference\n\ntensorflow::ops::Where3\n=======================\n\n`#include \u003cmath_ops.h\u003e`\n\nSelects elements from `x` or `y`, depending on `condition`.\n\nSummary\n-------\n\nThe `x`, and `y` tensors must all have the same shape, and the output will also have that shape.\n\nThe `condition` tensor must be a scalar if `x` and `y` are scalars. If `x` and `y` are vectors or higher rank, then `condition` must be either a scalar, a vector with size matching the first dimension of `x`, or must have the same shape as `x`.\n\nThe `condition` tensor acts as a mask that chooses, based on the value at each element, whether the corresponding element / row in the output should be taken from `x` (if true) or `y` (if false).\n\nIf `condition` is a vector and `x` and `y` are higher rank matrices, then it chooses which row (outer dimension) to copy from `x` and `y`. If `condition` has the same shape as `x` and `y`, then it chooses which element to copy from `x` and `y`.\n\nFor example:\n\n\n```text\n# 'condition' tensor is [[True, False]\n# [False, True]]\n# 't' is [[1, 2],\n# [3, 4]]\n# 'e' is [[5, 6],\n# [7, 8]]\nselect(condition, t, e) # =\u003e [[1, 6], [7, 4]]\n```\n\n\u003cbr /\u003e\n\n\n```text\n# 'condition' tensor is [True, False]\n# 't' is [[1, 2],\n# [3, 4]]\n# 'e' is [[5, 6],\n# [7, 8]]\nselect(condition, t, e) ==\u003e [[1, 2],\n [7, 8]]\n```\n\n\u003cbr /\u003e\n\n\n````gdscript\n \n Arguments:\n \n- scope: A /versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope object\n\n \n- x: = A /versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor which may have the same shape as condition. If condition is rank 1, x may have higher rank, but its first dimension must match the size of condition.\n\n \n- y: = A /versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor with the same type and shape as x.\n\n \n\n Returns:\n \n- /versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output: = A /versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor with the same type and shape as x and y. \n\n \n\n \n\n\n \n### Constructors and Destructors\n\n\n \n\n\n\n #classtensorflow_1_1ops_1_1_where3_1a1e043e7f8493b555a94d106084a64a32(const ::/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope & scope, ::/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input condition, ::/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input x, ::/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input y)\n \n\n \n\n\n \n\n\n \n### Public attributes\n\n\n \n\n\n\n #classtensorflow_1_1ops_1_1_where3_1a9b749e1046fbe4c39075a2b037391cf2\n \n\n \n\n /versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation\n \n\n \n\n\n\n #classtensorflow_1_1ops_1_1_where3_1a07742c7ad2705b0fa9b9cc9e59eca41b\n \n\n \n\n ::/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output\n \n\n \n\n\n \n\n\n \n### Public functions\n\n\n \n\n\n\n #classtensorflow_1_1ops_1_1_where3_1aacfd2a5bd041b46bc2179d3e9ac5c0c6() const \n \n\n \n\n ::tensorflow::Node *\n \n\n \n\n\n\n #classtensorflow_1_1ops_1_1_where3_1a7fcabeeb211b239288d028b587a88e54() const \n \n\n \n\n `\n` \n`\n` \n\n\n\n #classtensorflow_1_1ops_1_1_where3_1aedd6e529c7127af0c5af333ded627ab3() const \n \n\n \n\n `\n` \n`\n` \n\n\n Public attributes\n \n \n### operation\n\n\n \n```\nOperation operation\n```\n\n \n\n \n \n \n### output\n\n\n \n\n\n```text\n::tensorflow::Output output\n```\n\n \n\n \n Public functions\n \n \n### Where3\n\n\n \n\n\n```gdscript\n Where3(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input condition,\n ::tensorflow::Input x,\n ::tensorflow::Input y\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\n \n\n \n````"]]