tensorflow:: אופס:: SparseApplyAdagrad
#include <training_ops.h>
עדכן את הערכים הרלוונטיים ב-'*var' ו-'*accum' בהתאם לתכנית adgrad.
תַקצִיר
כלומר, עבור שורות שיש לנו גראד עבורן, אנו מעדכנים את var ומצטברים באופן הבא: $$accum += grad * grad$$ $$var -= lr * grad * (1 / sqrt(accum))$$
טיעונים:
- scope: אובייקט Scope
- var: צריך להיות מ-Variable().
- acum: צריך להיות מ-Variable().
- lr: קצב למידה. חייב להיות סקלר.
- grad: השיפוע.
- מדדים: וקטור של מדדים למימד הראשון של var ו-acum.
מאפיינים אופציונליים (ראה Attrs
):
- use_locking: אם
True
, עדכון של טנסור ה-var ו-acum יהיה מוגן על ידי מנעול; אחרת ההתנהגות אינה מוגדרת, אך עלולה להפגין פחות מחלוקת.
החזרות:
-
Output
: זהה ל-"var".
בנאים והורסים | |
---|---|
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) |
תכונות ציבוריות | |
---|---|
operation | |
out |
תפקידים ציבוריים | |
---|---|
node () const | ::tensorflow::Node * |
operator::tensorflow::Input () const | |
operator::tensorflow::Output () const |
פונקציות סטטיות ציבוריות | |
---|---|
UpdateSlots (bool x) | |
UseLocking (bool x) |
מבנים | |
---|---|
tensorflow:: ops:: SparseApplyAdagrad:: Attrs | קובעי תכונות אופציונליים עבור SparseApplyAdagrad . |
תכונות ציבוריות
מִבצָע
Operation operation
הַחוּצָה
::tensorflow::Output out
תפקידים ציבוריים
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 )
צוֹמֶת
::tensorflow::Node * node() const
מפעיל::tensorflow::קלט
operator::tensorflow::Input() const
אופרטור::tensorflow::פלט
operator::tensorflow::Output() const
פונקציות סטטיות ציבוריות
UpdateSlots
Attrs UpdateSlots( bool x )
השתמש בנעילה
Attrs UseLocking( bool x )
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עדכון אחרון: 2025-07-26 (שעון UTC).
[null,null,["עדכון אחרון: 2025-07-26 (שעון 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: $$accum += grad \\* grad$$ $$var -= lr \\* grad \\* (1 / sqrt(accum))$$\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/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/r2.0/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/r2.0/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/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.0/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/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` var, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` accum, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` grad, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` indices, const `[SparseApplyAdagrad::Attrs](/versions/r2.0/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/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [out](#classtensorflow_1_1ops_1_1_sparse_apply_adagrad_1acfcb53bfa0178d5f4531764444a70568) | `::`[tensorflow::Output](/versions/r2.0/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/r2.0/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/r2.0/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/r2.0/api_docs/cc/struct/tensorflow/ops/sparse-apply-adagrad/attrs) | Optional attribute setters for [SparseApplyAdagrad](/versions/r2.0/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```"]]