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tensor akışı:: işlem:: KaynakSparseApplyRMSProp
#include <training_ops.h>
'*var'ı RMSProp algoritmasına göre güncelleyin.
Özet
Bu algoritmanın yoğun uygulanmasında ms ve mom'in derece sıfır olsa bile güncelleneceğini, ancak bu seyrek uygulamada ms ve mom'in derecenin sıfır olduğu yinelemelerde güncellenmeyeceğini unutmayın.
ortalama_kare = bozunma * ortalama_kare + (1-bozunma) * gradyan ** 2 Delta = öğrenme_oranı * gradyan / sqrt(ortalama_kare + epsilon)
ms <- rho * ms_{t-1} + (1-rho) * grad * grad mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) var <- var - mom
Argümanlar:
- kapsam: Bir Kapsam nesnesi
- var: Bir Variable()'dan olmalıdır.
- ms: Bir Variable()'dan olmalıdır.
- anne: Bir Variable()'dan olmalı.
- lr: Ölçeklendirme faktörü. Bir skaler olmalı.
- rho: Bozunma oranı. Bir skaler olmalı.
- epsilon: Ridge terimi. Bir skaler olmalı.
- grad: Gradyan.
- indeksler: var, ms ve mom'un birinci boyutuna ait indekslerin bir vektörü.
İsteğe bağlı özellikler (bkz. Attrs
):
- use_locking:
True
ise var, ms ve mom tensörlerinin güncellenmesi bir kilitle korunur; aksi takdirde davranış tanımsızdır ancak daha az çekişme sergileyebilir.
İade:
Yapıcılar ve Yıkıcılar |
---|
ResourceSparseApplyRMSProp (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, :: tensorflow::Input indices)
|
ResourceSparseApplyRMSProp (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, :: tensorflow::Input indices, const ResourceSparseApplyRMSProp::Attrs & attrs) |
Genel özellikler
Kamu işlevleri
KaynakSparseApplyRMSProp
ResourceSparseApplyRMSProp(
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,
::tensorflow::Input indices,
const ResourceSparseApplyRMSProp::Attrs & attrs
)
operatör::tensorflow::İşlem
operator::tensorflow::Operation() const
Genel statik işlevler
KullanımKilitleme
Attrs UseLocking(
bool x
)
Aksi belirtilmediği sürece bu sayfanın içeriği Creative Commons Atıf 4.0 Lisansı altında ve kod örnekleri Apache 2.0 Lisansı altında lisanslanmıştır. Ayrıntılı bilgi için Google Developers Site Politikaları'na göz atın. Java, Oracle ve/veya satış ortaklarının tescilli ticari markasıdır.
Son güncelleme tarihi: 2025-07-26 UTC.
[null,null,["Son güncelleme tarihi: 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::ResourceSparseApplyRMSProp Class Reference\n\ntensorflow::ops::ResourceSparseApplyRMSProp\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/r2.1/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- indices: A vector of indices into the first dimension of var, ms and mom.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_resource_sparse_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/r2.1/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ResourceSparseApplyRMSProp](#classtensorflow_1_1ops_1_1_resource_sparse_apply_r_m_s_prop_1aff53e99b8e6dc505fb48976158d11f39)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ms, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` mom, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` momentum, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices)` ||\n| [ResourceSparseApplyRMSProp](#classtensorflow_1_1ops_1_1_resource_sparse_apply_r_m_s_prop_1aba358e7d7c7d78bfcdc5eaed2530fa16)`(const ::`[tensorflow::Scope](/versions/r2.1/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` ms, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` mom, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rho, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` momentum, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` epsilon, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.1/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[ResourceSparseApplyRMSProp::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_r_m_s_prop_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resource_sparse_apply_r_m_s_prop_1abcff2e138b5825b7fe66d8d9e68c9b7f) | [Operation](/versions/r2.1/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_r_m_s_prop_1ae4f96774d9e75c094f13f6ea8d5ca0b6)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_resource_sparse_apply_r_m_s_prop_1a19ab4ce72ae4d3db4e8b7daa0c72ff60)`(bool x)` | [Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-r-m-s-prop/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_r_m_s_prop_1_1_attrs) |\n\n| ### Structs ||\n|-----------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResourceSparseApplyRMSProp::Attrs](/versions/r2.1/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-r-m-s-prop/attrs) | Optional attribute setters for [ResourceSparseApplyRMSProp](/versions/r2.1/api_docs/cc/class/tensorflow/ops/resource-sparse-apply-r-m-s-prop#classtensorflow_1_1ops_1_1_resource_sparse_apply_r_m_s_prop). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### ResourceSparseApplyRMSProp\n\n```gdscript\n ResourceSparseApplyRMSProp(\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 ::tensorflow::Input indices\n)\n``` \n\n### ResourceSparseApplyRMSProp\n\n```gdscript\n ResourceSparseApplyRMSProp(\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 ::tensorflow::Input indices,\n const ResourceSparseApplyRMSProp::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```"]]