تدفق التوتر:: العمليات:: ResourceSparseApplyAdagrad
#include <training_ops.h>
قم بتحديث الإدخالات ذات الصلة في '*var' و'*accum' وفقًا لمخطط adagrad.
ملخص
هذا بالنسبة للصفوف التي لدينا غراد لها، نقوم بتحديث var وaccum على النحو التالي: accum += grad * grad var -= lr * grad * (1 / sqrt(accum))
الحجج:
- النطاق: كائن النطاق
- فار: يجب أن يكون من متغير ().
- تراكم: يجب أن يكون من متغير ().
- ل: معدل التعلم. يجب أن يكون العددية.
- غراد: التدرج.
- المؤشرات: متجه للمؤشرات في البعد الأول من var وaccum.
السمات الاختيارية (انظر Attrs
):
- use_locking: إذا كان
True
، فسيتم حماية تحديث موترتي var وaccum بواسطة قفل؛ وإلا فإن السلوك غير محدد، ولكنه قد يحمل قدرًا أقل من الخلاف.
العوائد:
-
Operation
التي تم إنشاؤها
البنائين والمدمرين | |
---|---|
ResourceSparseApplyAdagrad (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input lr, :: tensorflow::Input grad, :: tensorflow::Input indices) | |
ResourceSparseApplyAdagrad (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input lr, :: tensorflow::Input grad, :: tensorflow::Input indices, const ResourceSparseApplyAdagrad::Attrs & attrs) |
الصفات العامة | |
---|---|
operation |
الوظائف العامة | |
---|---|
operator::tensorflow::Operation () const |
وظائف ثابتة العامة | |
---|---|
UpdateSlots (bool x) | |
UseLocking (bool x) |
الهياكل | |
---|---|
Tensorflow:: ops:: ResourceSparseApplyAdagrad:: Attrs | محددات السمات الاختيارية لـ ResourceSparseApplyAdagrad . |
الصفات العامة
عملية
Operation operation
الوظائف العامة
ResourceSparseApplyAdagrad
ResourceSparseApplyAdagrad( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices )
ResourceSparseApplyAdagrad
ResourceSparseApplyAdagrad( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, const ResourceSparseApplyAdagrad::Attrs & attrs )
المشغل::tensorflow::Operation
operator::tensorflow::Operation() const
وظائف ثابتة العامة
فتحات التحديث
Attrs UpdateSlots( bool x )
UseLocking
Attrs UseLocking( bool x )
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تاريخ التعديل الأخير: 2025-07-27 (حسب التوقيت العالمي المتفَّق عليه)
[null,null,["تاريخ التعديل الأخير: 2025-07-27 (حسب التوقيت العالمي المتفَّق عليه)"],[],[],null,["# tensorflow::ops::ResourceSparseApplyAdagrad Class Reference\n\ntensorflow::ops::ResourceSparseApplyAdagrad\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: accum += grad \\* grad var -= lr \\* grad \\* (1 / sqrt(accum))\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/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_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- the created [Operation](/versions/r2.2/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ResourceSparseApplyAdagrad](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a3ecfebc42a69601af17e27c4f487996a)`(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| [ResourceSparseApplyAdagrad](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a88b42cc212cd10a0b52d433a9116ee59)`(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 `[ResourceSparseApplyAdagrad::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a917b533fe528936609ff652edec54b97) | [Operation](/versions/r2.2/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_adagrad_1ab312e9a5253a41e2d2a895f9c50a9b17)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-----------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UpdateSlots](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1a8e0a9ebe58e73522e657cd3fa6d2f4e1)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1_1_attrs) |\n| [UseLocking](#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1ab305f9b0860b1d2a24a1d314d486ed82)`(bool x)` | [Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad_1_1_attrs) |\n\n| ### Structs ||\n|--------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResourceSparseApplyAdagrad::Attrs](/versions/r2.2/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-adagrad/attrs) | Optional attribute setters for [ResourceSparseApplyAdagrad](/versions/r2.2/api_docs/cc/class/tensorflow/ops/resource-sparse-apply-adagrad#classtensorflow_1_1ops_1_1_resource_sparse_apply_adagrad). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### ResourceSparseApplyAdagrad\n\n```gdscript\n ResourceSparseApplyAdagrad(\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### ResourceSparseApplyAdagrad\n\n```gdscript\n ResourceSparseApplyAdagrad(\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 ResourceSparseApplyAdagrad::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### UpdateSlots\n\n```text\nAttrs UpdateSlots(\n bool x\n)\n``` \n\n### UseLocking\n\n```text\nAttrs UseLocking(\n bool x\n)\n```"]]