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fluxo tensor:: ops:: Aplicar RMSProp
#include <training_ops.h>
Atualize '*var' de acordo com o algoritmo RMSProp.
Resumo
Observe que na implementação densa desse algoritmo, ms e mom serão atualizados mesmo se o grad for zero, mas nesta implementação esparsa, ms e mom não serão atualizados em iterações durante as quais o grad for zero.
quadrado_médio = decaimento * quadrado_médio + (1-decaimento) * gradiente ** 2 Delta = taxa de aprendizagem * gradiente / sqrt (quadrado_médio + épsilon)
ms <- rho * ms_{t-1} + (1-rho) * grad * grad mãe <- momentum * mom_{t-1} + lr * grad / sqrt(ms + épsilon) var <- var - mãe
Argumentos:
- escopo: um objeto Escopo
- var: Deve ser de uma variável().
- ms: Deve ser de uma variável().
- mãe: Deve ser de uma variável().
- lr: Fator de escala. Deve ser um escalar.
- rho: Taxa de decaimento. Deve ser um escalar.
- épsilon: termo Ridge. Deve ser um escalar.
- graduação: O gradiente.
Atributos opcionais (veja Attrs
):
- use_locking: Se
True
, a atualização dos tensores var, ms e mom é protegida por um bloqueio; caso contrário, o comportamento será indefinido, mas poderá apresentar menos contenção.
Retorna:
Construtores e Destruidores |
---|
ApplyRMSProp (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)
|
ApplyRMSProp (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 ApplyRMSProp::Attrs & attrs) |
Atributos públicos
Funções públicas
nó
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operador::tensorflow::Saída
operator::tensorflow::Output() const
Funções estáticas públicas
UseLocking
Attrs UseLocking(
bool x
)
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Última atualização 2025-07-26 UTC.
[null,null,["Última atualização 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::ApplyRMSProp Class Reference\n\ntensorflow::ops::ApplyRMSProp\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/apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_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- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Same as \"var\".\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ApplyRMSProp](#classtensorflow_1_1ops_1_1_apply_r_m_s_prop_1a590f878f7698fa0f56a0b5226d658855)`(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| [ApplyRMSProp](#classtensorflow_1_1ops_1_1_apply_r_m_s_prop_1a4d5ef1aee8f989dbbe2c16e3538482b2)`(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 `[ApplyRMSProp::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_apply_r_m_s_prop_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|----------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_apply_r_m_s_prop_1a412619ace9b4ff26ec14ae0ecfb8ac11) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_apply_r_m_s_prop_1a72a4daee4e9ef1d2a3f3d4a088ed010f) | `::`[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_apply_r_m_s_prop_1a82fe90ad87c393e443f8459e9b0158db)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_apply_r_m_s_prop_1aabbb7630a5cd439e4694eda0021d694d)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_apply_r_m_s_prop_1a4e664360fbdde8291f80a08b2347fdf0)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|---------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_apply_r_m_s_prop_1ae0d5824bd2a81852e1e2185346adb9c3)`(bool x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_apply_r_m_s_prop_1_1_attrs) |\n\n| ### Structs ||\n|------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ApplyRMSProp::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/apply-r-m-s-prop/attrs) | Optional attribute setters for [ApplyRMSProp](/versions/r1.15/api_docs/cc/class/tensorflow/ops/apply-r-m-s-prop#classtensorflow_1_1ops_1_1_apply_r_m_s_prop). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### out\n\n```text\n::tensorflow::Output out\n``` \n\nPublic functions\n----------------\n\n### ApplyRMSProp\n\n```gdscript\n ApplyRMSProp(\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### ApplyRMSProp\n\n```gdscript\n ApplyRMSProp(\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 ApplyRMSProp::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```"]]