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tensoreflusso:: ops:: ResourceApplyRMSProp
#include <training_ops.h>
Aggiorna '*var' in base all'algoritmo RMSProp.
Riepilogo
Si noti che nell'implementazione densa di questo algoritmo, ms e mom si aggiorneranno anche se il grad è zero, ma in questa implementazione sparsa, ms e mom non si aggiorneranno nelle iterazioni durante le quali il grad è zero.
quadrato_medio = decadimento * quadrato_medio + (1-decadimento) * gradiente ** 2 Delta = tasso_di_apprendimento * gradiente / sqrt(quadrato_medio + epsilon)
ms <- rho * ms_{t-1} + (1-rho) * grad * grad mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) var <- var - mom
Argomenti:
- scope: un oggetto Scope
- var: dovrebbe provenire da una variabile().
- ms: dovrebbe provenire da una variabile().
- mamma: Dovrebbe provenire da una Variabile().
- lr: fattore di scala. Deve essere uno scalare.
- rho: tasso di decadimento. Deve essere uno scalare.
- epsilon: termine di cresta. Deve essere uno scalare.
- grad: il gradiente.
Attributi facoltativi (vedi Attrs
):
- use_locking: Se
True
, l'aggiornamento dei tensori var, ms e mom è protetto da un blocco; altrimenti il comportamento non è definito, ma può mostrare meno contesa.
Resi:
Costruttori e distruttori |
---|
ResourceApplyRMSProp (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input ms, :: tensorflow::Input mom, :: tensorflow::Input lr, :: tensorflow::Input rho, :: tensorflow::Input momentum, :: tensorflow::Input epsilon, :: tensorflow::Input grad)
|
ResourceApplyRMSProp (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input ms, :: tensorflow::Input mom, :: tensorflow::Input lr, :: tensorflow::Input rho, :: tensorflow::Input momentum, :: tensorflow::Input epsilon, :: tensorflow::Input grad, const ResourceApplyRMSProp::Attrs & attrs) |
Attributi pubblici
Funzioni pubbliche
operator::tensorflow::Operazione
operator::tensorflow::Operation() const
Funzioni pubbliche statiche
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 2025-07-25 UTC.
[null,null,["Ultimo aggiornamento 2025-07-25 UTC."],[],[],null,["# tensorflow::ops::ResourceApplyRMSProp Class Reference\n\ntensorflow::ops::ResourceApplyRMSProp\n=====================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate '\\*var' according to the RMSProp algorithm.\n\nSummary\n-------\n\nNote that in dense implementation of this algorithm, ms and mom will update even if the grad is zero, but in this sparse implementation, ms and mom will not update in iterations during which the grad is zero.\n\nmean_square = decay \\* mean_square + (1-decay) \\* gradient \\*\\* 2 Delta = learning_rate \\* gradient / sqrt(mean_square + epsilon)\n\nms \\\u003c- rho \\* ms_{t-1} + (1-rho) \\* grad \\* grad mom \\\u003c- momentum \\* mom_{t-1} + lr \\* grad / sqrt(ms + epsilon) var \\\u003c- var - mom\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- var: Should be from a Variable().\n- ms: Should be from a Variable().\n- mom: Should be from a Variable().\n- lr: Scaling factor. Must be a scalar.\n- rho: Decay rate. Must be a scalar.\n- epsilon: Ridge term. Must be a scalar.\n- grad: The gradient.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop_1_1_attrs)):\n\n- use_locking: If `True`, updating of the var, ms, and mom tensors is 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/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ResourceApplyRMSProp](#classtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop_1ae91eb1e2b6b3e0c166963715954c5122)`(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)` var, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ms, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` mom, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` momentum, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad)` ||\n| [ResourceApplyRMSProp](#classtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop_1a75df67ab1eea661cf727de50a0a7fb98)`(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)` var, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ms, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` mom, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` momentum, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, const `[ResourceApplyRMSProp::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop_1a48b8adc2f5de282222027a49c23ff42d) | [Operation](/versions/r1.15/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_apply_r_m_s_prop_1afe6e89eae46d27e22c2ac94cc2c7aadc)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop_1aacf915d8791a673d2e19b0af3d86af3a)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop_1_1_attrs) |\n\n| ### Structs ||\n|-----------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResourceApplyRMSProp::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/resource-apply-r-m-s-prop/attrs) | Optional attribute setters for [ResourceApplyRMSProp](/versions/r1.15/api_docs/cc/class/tensorflow/ops/resource-apply-r-m-s-prop#classtensorflow_1_1ops_1_1_resource_apply_r_m_s_prop). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### ResourceApplyRMSProp\n\n```gdscript\n ResourceApplyRMSProp(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input ms,\n ::tensorflow::Input mom,\n ::tensorflow::Input lr,\n ::tensorflow::Input rho,\n ::tensorflow::Input momentum,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad\n)\n``` \n\n### ResourceApplyRMSProp\n\n```gdscript\n ResourceApplyRMSProp(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input ms,\n ::tensorflow::Input mom,\n ::tensorflow::Input lr,\n ::tensorflow::Input rho,\n ::tensorflow::Input momentum,\n ::tensorflow::Input epsilon,\n ::tensorflow::Input grad,\n const ResourceApplyRMSProp::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### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n```"]]