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flux tensoriel : : opérations : : SparseApplyAdagrad
#include <training_ops.h> Mettez à jour les entrées pertinentes dans '*var' et '*accum' selon le schéma adagrad.
Résumé
C'est pour les lignes pour lesquelles nous avons grad, nous mettons à jour var et accumulons comme suit :
$$accum += grad * grad$$
$$var -= lr * grad * (1 / sqrt(accum))$$
Arguments :
- scope : un objet Scope
- var : doit provenir d'une variable ().
- cumul : doit provenir d'une variable ().
- gd : Taux d’apprentissage. Ça doit être un scalaire.
- grad : Le dégradé.
- indices : Un vecteur d'indices dans la première dimension de var et cumul.
Attributs facultatifs (voir Attrs ) :
- use_locking : Si
True , la mise à jour des tenseurs var et accum sera protégée par un verrou ; sinon, le comportement n'est pas défini, mais peut présenter moins de conflits.
Retours :
Constructeurs et Destructeurs |
|---|
SparseApplyAdagrad (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input lr, :: tensorflow::Input grad, :: tensorflow::Input indices)
|
SparseApplyAdagrad (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input lr, :: tensorflow::Input grad, :: tensorflow::Input indices, const SparseApplyAdagrad::Attrs & attrs)
|
Attributs publics
Fonctions publiques
nœud
::tensorflow::Node * node() const
operator::tensorflow::Input() const
opérateur :: tensorflow :: Sortie
operator::tensorflow::Output() const
Fonctions statiques publiques
Emplacements de mise à jour
Attrs UpdateSlots(
bool x
)
UtiliserVerrouillage
Attrs UseLocking(
bool x
)
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Dernière mise à jour le 2025/07/27 (UTC).
[null,null,["Dernière mise à jour le 2025/07/27 (UTC)."],[],[],null,["# tensorflow::ops::SparseApplyAdagrad Class Reference\n\ntensorflow::ops::SparseApplyAdagrad\n===================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate relevant entries in '\\*var' and '\\*accum' according to the adagrad scheme.\n\nSummary\n-------\n\nThat is for rows we have grad for, we update var and accum as follows: \n$$accum += grad \\* grad$$ \n$$var -= lr \\* grad \\* (1 / sqrt(accum))$$\n\n\u003cbr /\u003e\n\nArguments:\n\n- scope: A [Scope](/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- var: Should be from a Variable().\n- accum: Should be from a Variable().\n- lr: Learning rate. Must be a scalar.\n- grad: The gradient.\n- indices: A vector of indices into the first dimension of var and accum.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_sparse_apply_adagrad_1_1_attrs)):\n\n- use_locking: If `True`, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): Same as \"var\".\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [SparseApplyAdagrad](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1a8654c81ae7fb822d3d68cf07933298c5)`(const ::`[tensorflow::Scope](/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices)` ||\n| [SparseApplyAdagrad](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1a065426b919fd035ddb0cff7f0d0383b2)`(const ::`[tensorflow::Scope](/versions/r2.2/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.2/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[SparseApplyAdagrad::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_sparse_apply_adagrad_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1a583fccf8242cbba9ca0966f1f164f279) | [Operation](/versions/r2.2/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1acfcb53bfa0178d5f4531764444a70568) | `::`[tensorflow::Output](/versions/r2.2/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|--------------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1a82b4ae6551f4a0d9456891da05823903)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1a1bd37515accb4c3505c3432dbcaaff2d)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1ab850cf3221b4383f0d773d8211173ac7)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UpdateSlots](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1afa53af54d646c0cd056c3e5d9ae19970)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_sparse_apply_adagrad_1_1_attrs) |\n| [UseLocking](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1ab561ae2919f29d971d0c0b28448f1695)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_sparse_apply_adagrad_1_1_attrs) |\n\n| ### Structs ||\n|---------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::SparseApplyAdagrad::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/sparse-apply-adagrad/attrs) | Optional attribute setters for [SparseApplyAdagrad](/versions/r2.2/api_docs/cc/class/tensorflow/ops/sparse-apply-adagrad#classtensorflow_1_1ops_1_1_sparse_apply_adagrad). |\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### SparseApplyAdagrad\n\n```gdscript\n SparseApplyAdagrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input lr,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices\n)\n``` \n\n### SparseApplyAdagrad\n\n```gdscript\n SparseApplyAdagrad(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input lr,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices,\n const SparseApplyAdagrad::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### UpdateSlots\n\n```text\nAttrs UpdateSlots(\n bool x\n)\n``` \n\n### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n```"]]
