tensorflow:: אופס:: ResourceApplyFtrl
#include <training_ops.h>
עדכן את '*var' לפי סכימת Ftrl-proximal.
תַקצִיר
accum_new = accum + grad * grad linear += grad - (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2 var = (סימן(ליניארי) * l1 - ליניארי) / ריבועי אם |ליניארי| > l1 אחר 0.0 accum = accum_new
טיעונים:
- scope: אובייקט Scope
- var: צריך להיות מ-Variable().
- acum: צריך להיות מ-Variable().
- ליניארי: צריך להיות ממשתנה().
- grad: השיפוע.
- lr: גורם קנה מידה. חייב להיות סקלר.
- l1: הסדרת L1. חייב להיות סקלר.
- l2: הסדרת L2. חייב להיות סקלר.
- lr_power: גורם קנה מידה. חייב להיות סקלר.
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:
-
Operation
שנוצר
בנאים והורסים | |
---|---|
ResourceApplyFtrl (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input lr_power) | |
ResourceApplyFtrl (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input lr_power, const ResourceApplyFtrl::Attrs & attrs) |
תכונות ציבוריות | |
---|---|
operation |
תפקידים ציבוריים | |
---|---|
operator::tensorflow::Operation () const |
פונקציות סטטיות ציבוריות | |
---|---|
UseLocking (bool x) |
מבנים | |
---|---|
tensorflow:: ops:: ResourceApplyFtrl:: Attrs | קובעי תכונות אופציונליים עבור ResourceApplyFtrl . |
תכונות ציבוריות
מִבצָע
Operation operation
תפקידים ציבוריים
ResourceApplyFtrl
ResourceApplyFtrl( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input linear, ::tensorflow::Input grad, ::tensorflow::Input lr, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input lr_power )
ResourceApplyFtrl
ResourceApplyFtrl( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input linear, ::tensorflow::Input grad, ::tensorflow::Input lr, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input lr_power, const ResourceApplyFtrl::Attrs & attrs )
אופרטור::tensorflow::פעולה
operator::tensorflow::Operation() const
פונקציות סטטיות ציבוריות
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::ResourceApplyFtrl Class Reference\n\ntensorflow::ops::ResourceApplyFtrl\n==================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate '\\*var' according to the Ftrl-proximal scheme.\n\nSummary\n-------\n\naccum_new = accum + grad \\* grad linear += grad - (accum_new\\^(-lr_power) - accum\\^(-lr_power)) / lr \\* var quadratic = 1.0 / (accum_new\\^(lr_power) \\* lr) + 2 \\* l2 var = (sign(linear) \\* l1 - linear) / quadratic if \\|linear\\| \\\u003e l1 else 0.0 accum = accum_new\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- linear: Should be from a Variable().\n- grad: The gradient.\n- lr: Scaling factor. Must be a scalar.\n- l1: L1 regulariation. Must be a scalar.\n- l2: L2 regulariation. Must be a scalar.\n- lr_power: Scaling factor. Must be a scalar.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/resource-apply-ftrl/attrs#structtensorflow_1_1ops_1_1_resource_apply_ftrl_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/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation)\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [ResourceApplyFtrl](#classtensorflow_1_1ops_1_1_resource_apply_ftrl_1aad4d85a2e638469dbe3155f147f018c8)`(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)` linear, ::`[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)` lr, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l1, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr_power)` ||\n| [ResourceApplyFtrl](#classtensorflow_1_1ops_1_1_resource_apply_ftrl_1ae2f90848aff4185a26250531866329e0)`(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)` linear, ::`[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)` lr, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l1, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` l2, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` lr_power, const `[ResourceApplyFtrl::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/resource-apply-ftrl/attrs#structtensorflow_1_1ops_1_1_resource_apply_ftrl_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resource_apply_ftrl_1a0de68aae1932c1c4d5dcf3a839665558) | [Operation](/versions/r2.0/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_apply_ftrl_1a602f7fb326f32fb3fe3101d65380b45d)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_resource_apply_ftrl_1a9acb1a5775d104b181717db97bf46f54)`(bool x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/resource-apply-ftrl/attrs#structtensorflow_1_1ops_1_1_resource_apply_ftrl_1_1_attrs) |\n\n| ### Structs ||\n|-------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResourceApplyFtrl::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/resource-apply-ftrl/attrs) | Optional attribute setters for [ResourceApplyFtrl](/versions/r2.0/api_docs/cc/class/tensorflow/ops/resource-apply-ftrl#classtensorflow_1_1ops_1_1_resource_apply_ftrl). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### ResourceApplyFtrl\n\n```gdscript\n ResourceApplyFtrl(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input linear,\n ::tensorflow::Input grad,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input lr_power\n)\n``` \n\n### ResourceApplyFtrl\n\n```gdscript\n ResourceApplyFtrl(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input linear,\n ::tensorflow::Input grad,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input lr_power,\n const ResourceApplyFtrl::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```"]]