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tensoreflusso:: ops:: ResourceSparseApplyAdagrad
#include <training_ops.h>
Aggiorna le voci rilevanti in '*var' e '*accum' secondo lo schema adagrad.
Riepilogo
Questo è per le righe per le quali abbiamo grad, aggiorniamo var e accum come segue: accum += grad * grad var -= lr * grad * (1 / sqrt(accum))
Argomenti:
- scope: un oggetto Scope
- var: dovrebbe provenire da una variabile().
- accum: dovrebbe provenire da una variabile().
- lr: tasso di apprendimento. Deve essere uno scalare.
- grad: il gradiente.
- indici: un vettore di indici nella prima dimensione di var e accum.
Attributi facoltativi (vedi Attrs
):
- use_locking: Se
True
, l'aggiornamento dei tensori var e accum sarà protetto da un lock; altrimenti il comportamento non è definito, ma può mostrare meno contesa.
Resi:
Costruttori e distruttori |
---|
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) |
Attributi pubblici
Funzioni pubbliche
operator::tensorflow::Operazione
operator::tensorflow::Operation() const
Funzioni pubbliche statiche
Aggiorna Slot
Attrs UpdateSlots(
bool x
)
UsaLocking
Attrs UseLocking(
bool x
)
Salvo quando diversamente specificato, i contenuti di questa pagina sono concessi in base alla licenza Creative Commons Attribution 4.0, mentre gli esempi di codice sono concessi in base alla licenza Apache 2.0. Per ulteriori dettagli, consulta le norme del sito di Google Developers. Java è un marchio registrato di Oracle e/o delle sue consociate.
Ultimo aggiornamento 2025-07-27 UTC.
[null,null,["Ultimo aggiornamento 2025-07-27 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/r2.2/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/r2.2/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/r2.2/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/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.2/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/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[ResourceSparseApplyAdagrad::Attrs](/versions/r2.2/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/r2.2/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/r2.2/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/r2.2/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/r2.2/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs) | Optional attribute setters for [ResourceSparseApplyAdagrad](/versions/r2.2/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```"]]