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flujo tensor:: operaciones:: DispersiónNdActualización
#include <state_ops.h>
Aplica updates
dispersas a valores individuales o sectores dentro de un determinado.
Resumen
variable según indices
.
ref
es un Tensor
con rango P
y indices
son un Tensor
de rango Q
indices
deben ser tensores enteros y contener índices en ref
. debe tener forma \([d_0, ..., d_{Q-2}, K]\) donde 0 < K <= P
.
La dimensión más interna de indices
(con longitud K
) corresponde a índices en elementos (si K = P
) o cortes (si K < P
) a lo largo de la K
-ésima dimensión de ref
.
updates
es Tensor
de rango Q-1+PK
con forma:
$$[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].$$
Por ejemplo, digamos que queremos actualizar 4 elementos dispersos a un tensor de rango 1 a 8 elementos. En Python, esa actualización se vería así:
ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])
indices = tf.constant([[4], [3], [1] ,[7]])
updates = tf.constant([9, 10, 11, 12])
update = tf.scatter_nd_update(ref, indices, updates)
with tf.Session() as sess:
print sess.run(update)
La actualización resultante de ref se vería así:
[1, 11, 3, 10, 9, 6, 7, 12]
Consulte tf.scatter_nd
para obtener más detalles sobre cómo realizar actualizaciones en los sectores.
Consulte también tf.scatter_update
y tf.batch_scatter_update
.
Argumentos:
- alcance: un objeto de alcance
- ref: Un tensor mutable. Debe ser de un nodo Variable .
- índices: Un tensor . Debe ser uno de los siguientes tipos: int32, int64. Un tensor de índices en ref.
- actualizaciones: Un tensor . Debe ser del mismo tipo que la ref. Un tensor de valores actualizados para agregar a la referencia.
Atributos opcionales (ver Attrs
):
- use_locking: un bool opcional. El valor predeterminado es Verdadero. Si es Verdadero, la asignación estará protegida por un candado; de lo contrario, el comportamiento no está definido, pero puede presentar menos contención.
Devoluciones:
-
Output
: Igual que la ref. Se devuelve para comodidad de las operaciones que desean utilizar los valores actualizados una vez realizada la actualización.
Atributos públicos
Funciones públicas
nodo
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operador::tensorflow::Salida
operator::tensorflow::Output() const
Funciones estáticas públicas
UsoBloqueo
Attrs UseLocking(
bool x
)
A menos que se indique lo contrario, el contenido de esta página está sujeto a la licencia Reconocimiento 4.0 de Creative Commons y las muestras de código están sujetas a la licencia Apache 2.0. Para obtener más información, consulta las políticas del sitio web de Google Developers. Java es una marca registrada de Oracle o sus afiliados.
Última actualización: 2025-07-26 (UTC).
[null,null,["Última actualización: 2025-07-26 (UTC)."],[],[],null,["# tensorflow::ops::ScatterNdUpdate Class Reference\n\ntensorflow::ops::ScatterNdUpdate\n================================\n\n`#include \u003cstate_ops.h\u003e`\n\nApplies sparse `updates` to individual values or slices within a given.\n\nSummary\n-------\n\nvariable according to `indices`.\n\n`ref` is a [Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) with rank `P` and `indices` is a [Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) of rank `Q`.\n\n`indices` must be integer tensor, containing indices into `ref`. It must be shape \\\\(\\[d_0, ..., d_{Q-2}, K\\]\\\\) where `0 \u003c K \u003c= P`.\n\nThe innermost dimension of `indices` (with length `K`) corresponds to indices into elements (if `K = P`) or slices (if `K \u003c P`) along the `K`th dimension of `ref`.\n\n`updates` is [Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor) of rank `Q-1+P-K` with shape:\n\n$$\\[d_0, ..., d_{Q-2}, ref.shape\\[K\\], ..., ref.shape\\[P-1\\]\\].$$\n\nFor example, say we want to update 4 scattered elements to a rank-1 tensor to 8 elements. In Python, that update would look like this:\n\n\n```gdscript\n ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])\n indices = tf.constant([[4], [3], [1] ,[7]])\n updates = tf.constant([9, 10, 11, 12])\n update = tf.scatter_nd_update(ref, indices, updates)\n with tf.Session() as sess:\n print sess.run(update)\n```\n\n\u003cbr /\u003e\n\nThe resulting update to ref would look like this: \n\n```text\n[1, 11, 3, 10, 9, 6, 7, 12]\n```\n\n\u003cbr /\u003e\n\nSee `tf.scatter_nd` for more details about how to make updates to slices.\n\nSee also `tf.scatter_update` and `tf.batch_scatter_update`.\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- ref: A mutable [Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor). Should be from a [Variable](/versions/r1.15/api_docs/cc/class/tensorflow/ops/variable#classtensorflow_1_1ops_1_1_variable) node.\n- indices: A [Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor). Must be one of the following types: int32, int64. A tensor of indices into ref.\n- updates: A [Tensor](/versions/r1.15/api_docs/cc/class/tensorflow/tensor#classtensorflow_1_1_tensor). Must have the same type as ref. A tensor of updated values to add to ref.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/scatter-nd-update/attrs#structtensorflow_1_1ops_1_1_scatter_nd_update_1_1_attrs)):\n\n- use_locking: An optional bool. Defaults to True. If True, the assignment will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Same as ref. Returned as a convenience for operations that want to use the updated values after the update is done.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ScatterNdUpdate](#classtensorflow_1_1ops_1_1_scatter_nd_update_1acb6b3b44045199decc158f661ed16c3f)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ref, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` updates)` ||\n| [ScatterNdUpdate](#classtensorflow_1_1ops_1_1_scatter_nd_update_1ae3aa0b51b9e1787da8db1bf0b0eff7a2)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ref, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` updates, const `[ScatterNdUpdate::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/scatter-nd-update/attrs#structtensorflow_1_1ops_1_1_scatter_nd_update_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_scatter_nd_update_1a8d113d05ce297b3fbdfe5ec0108a9d2a) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output_ref](#classtensorflow_1_1ops_1_1_scatter_nd_update_1a3207186292f8bca8cf869bc6a6aa2f82) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_scatter_nd_update_1aa755e0d558f6d9154ad504413b815c87)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_scatter_nd_update_1aaf1431785e8afb4ad1f0498144a12e6b)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_scatter_nd_update_1a2e39eab6b05cd85493c30752a36ca1ea)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|----------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_scatter_nd_update_1aecb251dcdebad69c21d53f5980d0dd80)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/scatter-nd-update/attrs#structtensorflow_1_1ops_1_1_scatter_nd_update_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ScatterNdUpdate::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/scatter-nd-update/attrs) | Optional attribute setters for [ScatterNdUpdate](/versions/r1.15/api_docs/cc/class/tensorflow/ops/scatter-nd-update#classtensorflow_1_1ops_1_1_scatter_nd_update). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output_ref\n\n```scdoc\n::tensorflow::Output output_ref\n``` \n\nPublic functions\n----------------\n\n### ScatterNdUpdate\n\n```gdscript\n ScatterNdUpdate(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input ref,\n ::tensorflow::Input indices,\n ::tensorflow::Input updates\n)\n``` \n\n### ScatterNdUpdate\n\n```gdscript\n ScatterNdUpdate(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input ref,\n ::tensorflow::Input indices,\n ::tensorflow::Input updates,\n const ScatterNdUpdate::Attrs & attrs\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n``` \n\nPublic static functions\n-----------------------\n\n### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n```"]]