تدفق التوتر:: العمليات:: SparseApplyAdagrad
#include <training_ops.h>
قم بتحديث الإدخالات ذات الصلة في '*var' و'*accum' وفقًا لمخطط adagrad.
ملخص
هذا بالنسبة للصفوف التي لدينا grad 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:
-
Output
: نفس "فار".
البنائين والمدمرين | |
---|---|
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) |
الصفات العامة | |
---|---|
operation | |
out |
الوظائف العامة | |
---|---|
node () const | ::tensorflow::Node * |
operator::tensorflow::Input () const | |
operator::tensorflow::Output () const |
وظائف ثابتة العامة | |
---|---|
UpdateSlots (bool x) | |
UseLocking (bool x) |
الهياكل | |
---|---|
Tensorflow:: ops:: SparseApplyAdagrad:: Attrs | محددات السمات الاختيارية لـ SparseApplyAdagrad . |
الصفات العامة
عملية
Operation operation
خارج
::tensorflow::Output out
الوظائف العامة
SparseApplyAdagrad
SparseApplyAdagrad( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices )
SparseApplyAdagrad
SparseApplyAdagrad( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, const SparseApplyAdagrad::Attrs & attrs )
العقدة
::tensorflow::Node * node() const
المشغل::tensorflow::الإدخال
operator::tensorflow::Input() const
المشغل::tensorflow::الإخراج
operator::tensorflow::Output() const
وظائف ثابتة العامة
فتحات التحديث
Attrs UpdateSlots( bool x )
UseLocking
Attrs UseLocking( bool x )
إنّ محتوى هذه الصفحة مرخّص بموجب ترخيص Creative Commons Attribution 4.0 ما لم يُنصّ على خلاف ذلك، ونماذج الرموز مرخّصة بموجب ترخيص Apache 2.0. للاطّلاع على التفاصيل، يُرجى مراجعة سياسات موقع Google Developers. إنّ Java هي علامة تجارية مسجَّلة لشركة Oracle و/أو شركائها التابعين.
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::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```"]]