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tensorflow :: operaciones :: ResourceSparseApplyAdagrad
#include <training_ops.h>
Actualice las entradas relevantes en '* var' y '* acumula' de acuerdo con el esquema adagrad.
Resumen
Es decir, para las filas para las que tenemos grad, actualizamos var y acumulamos de la siguiente manera: acum + = grad * grad var - = lr * grad * (1 / sqrt (acum))
Argumentos:
- alcance: un objeto de alcance
- var: debe ser de una variable ().
- acum: debe ser de una variable ().
- lr: tasa de aprendizaje. Debe ser un escalar.
- grad: El gradiente.
- índices: Un vector de índices en la primera dimensión de var y acum.
Atributos opcionales (consulte Attrs
):
- use_locking: Si es
True
, la actualización de los tensores var y acumuladores estará protegida por un bloqueo; de lo contrario, el comportamiento no está definido, pero puede mostrar menos contención.
Devoluciones:
Constructores y Destructores |
---|
ResourceSparseApplyAdagrad (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input lr, :: tensorflow::Input grad, :: tensorflow::Input indices)
|
ResourceSparseApplyAdagrad (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input lr, :: tensorflow::Input grad, :: tensorflow::Input indices, const ResourceSparseApplyAdagrad::Attrs & attrs) |
Atributos públicos
Funciones publicas
operador :: tensorflow :: Operación
operator::tensorflow::Operation() const
Funciones estáticas públicas
UpdateSlots
Attrs UpdateSlots(
bool x
)
UseLocking
Attrs UseLocking(
bool x
)
Salvo que se indique lo contrario, el contenido de esta página está sujeto a la licencia Atribución 4.0 de Creative Commons, y los ejemplos de código están sujetos a la licencia Apache 2.0. Para obtener más información, consulta las políticas del sitio de Google Developers. Java es una marca registrada de Oracle o sus afiliados.
Última actualización: 2020-06-29 (UTC)
[null,null,["Última actualización: 2020-06-29 (UTC)"],[],[],null,["# tensorflow::ops::ResourceSparseApplyAdagrad Class Reference\n\ntensorflow::ops::ResourceSparseApplyAdagrad\n===========================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate relevant entries in '\\*var' and '\\*accum' according to the adagrad scheme.\n\nSummary\n-------\n\nThat is for rows we have grad for, we update var and accum as follows: accum += grad \\* grad var -= lr \\* grad \\* (1 / sqrt(accum))\n\nArguments:\n\n- scope: A [Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- var: Should be from a Variable().\n- accum: Should be from a Variable().\n- lr: Learning rate. Must be a scalar.\n- grad: The gradient.\n- indices: A vector of indices into the first dimension of var and accum.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1_1_attrs)):\n\n- use_locking: If `True`, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.\n\n\u003cbr /\u003e\n\nReturns:\n\n- the created [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ResourceSparseApplyAdagrad](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a3ecfebc42a69601af17e27c4f487996a)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices)` ||\n| [ResourceSparseApplyAdagrad](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a88b42cc212cd10a0b52d433a9116ee59)`(const ::`[tensorflow::Scope](/versions/r2.3/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.3/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[ResourceSparseApplyAdagrad::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a917b533fe528936609ff652edec54b97) | [Operation](/versions/r2.3/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n\n| ### Public functions ||\n|--------------------------------------------------------------------------------------------------------------------------------------------|---------|\n| [operator::tensorflow::Operation](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1ab312e9a5253a41e2d2a895f9c50a9b17)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-----------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UpdateSlots](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a8e0a9ebe58e73522e657cd3fa6d2f4e1)`(bool x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1_1_attrs) |\n| [UseLocking](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1ab305f9b0860b1d2a24a1d314d486ed82)`(bool x)` | [Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1_1_attrs) |\n\n| ### Structs ||\n|--------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResourceSparseApplyAdagrad::Attrs](/versions/r2.3/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs) | Optional attribute setters for [ResourceSparseApplyAdagrad](/versions/r2.3/api_docs/cc/class/tensorflow/ops/resource-sparse-apply-adagrad#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### ResourceSparseApplyAdagrad\n\n```gdscript\n ResourceSparseApplyAdagrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input lr,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices\n)\n``` \n\n### ResourceSparseApplyAdagrad\n\n```gdscript\n ResourceSparseApplyAdagrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input lr,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices,\n const ResourceSparseApplyAdagrad::Attrs & attrs\n)\n``` \n\n### operator::tensorflow::Operation\n\n```gdscript\n operator::tensorflow::Operation() const \n``` \n\nPublic static functions\n-----------------------\n\n### UpdateSlots\n\n```text\nAttrs UpdateSlots(\n bool x\n)\n``` \n\n### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n```"]]