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aliran tensor:: operasi:: ResourceSparseApplyRMSProp
#include <training_ops.h>
Perbarui '*var' sesuai dengan algoritma RMSProp.
Ringkasan
Perhatikan bahwa dalam penerapan algoritma ini yang padat, ms dan mom akan memperbarui meskipun gradasinya nol, tetapi dalam implementasi yang jarang ini, ms dan mom tidak akan memperbarui dalam iterasi yang gradannya nol.
mean_square = peluruhan * mean_square + (1-decay) * gradien ** 2 Delta = learning_rate * gradien / sqrt(mean_square + epsilon)
ms <- rho * ms_{t-1} + (1-rho) * lulusan * lulusan ibu <- momentum * ibu_{t-1} + lr * lulusan / sqrt(ms + epsilon) var <- var - ibu
Argumen:
- ruang lingkup: Objek Lingkup
- var: Harus dari Variabel().
- ms: Harus dari Variabel().
- ibu: Harus dari Variabel().
- lr: Faktor penskalaan. Pasti skalar.
- rho : Tingkat pembusukan. Pasti skalar.
- epsilon: Istilah punggungan. Pasti skalar.
- lulusan: Gradien.
- indeks: Vektor indeks ke dalam dimensi pertama var, ms, dan ibu.
Atribut opsional (lihat Attrs
):
- use_locking: Jika
True
, pembaruan tensor var, ms, dan mom dilindungi oleh kunci; jika tidak, perilaku tersebut tidak terdefinisikan, namun mungkin menunjukkan lebih sedikit pertentangan.
Pengembalian:
Konstruktor dan Destruktor |
---|
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) |
Atribut publik
Fungsi publik
ResourceSparseApplyRMSProp
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
)
operator::tensorflow::Operasi
operator::tensorflow::Operation() const
Fungsi statis publik
Gunakan Penguncian
Attrs UseLocking(
bool x
)
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
Terakhir diperbarui pada 2025-07-25 UTC.
[null,null,["Terakhir diperbarui pada 2025-07-25 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/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- indices: A vector of indices into the first dimension of var, ms and mom.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/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/r1.15/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/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, ::`[tensorflow::Input](/versions/r1.15/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/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, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[ResourceSparseApplyRMSProp::Attrs](/versions/r1.15/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/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_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/r1.15/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/r1.15/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-r-m-s-prop/attrs) | Optional attribute setters for [ResourceSparseApplyRMSProp](/versions/r1.15/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```"]]