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텐서플로우:: 작전:: 자원적용RMSProp
#include <training_ops.h>
RMSProp 알고리즘에 따라 '*var'를 업데이트합니다.
요약
이 알고리즘의 밀집 구현에서 ms와 mom은 grad가 0인 경우에도 업데이트되지만 이 희소 구현에서는 ms와 mom은 grad가 0인 동안 반복에서 업데이트되지 않습니다.
평균 제곱 = 붕괴 * 평균 제곱 + (1-감쇠) * 기울기 ** 2 델타 = 학습 속도 * 기울기 / sqrt(평균 제곱 + 엡실론)
ms <- rho * ms_{t-1} + (1-rho) * grad * grad mom <- 모멘텀 * mom_{t-1} + lr * grad / sqrt(ms + epsilon) var <- var - 엄마
인수:
- 범위: 범위 개체
- var: Variable()에서 가져와야 합니다.
- ms: Variable()에서 가져와야 합니다.
- mom: Variable()에서 가져와야 합니다.
- lr: 스케일링 팩터. 스칼라여야 합니다.
- rho: 감쇠율. 스칼라여야 합니다.
- 엡실론: 능선 항. 스칼라여야 합니다.
- grad: 그라데이션입니다.
선택적 속성( Attrs
참조):
- use_locking:
True
인 경우 var, ms 및 mom 텐서 업데이트는 잠금으로 보호됩니다. 그렇지 않으면 동작이 정의되지 않지만 경합이 덜 나타날 수 있습니다.
보고:
생성자와 소멸자 |
---|
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) |
공개 속성
공공 기능
연산자::텐서플로우::작업
operator::tensorflow::Operation() const
공개 정적 함수
사용잠금
Attrs UseLocking(
bool x
)
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최종 업데이트: 2025-07-25(UTC)
[null,null,["최종 업데이트: 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```"]]