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тензорный поток:: опс:: ResourceSparseApplyFtrl
#include <training_ops.h>
Обновите соответствующие записи в '*var' по схеме Ftrl-proximal.
Краткое содержание
То есть для строк, для которых у нас есть grad, мы обновляем var, accum и Linear следующим образом: accum_new = accum + grad * grad linear += grad - (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var квадратичный = 1,0 / (accum_new^(lr_power) * lr) + 2 * l2 var = (sign(линейный) * l1 - линейный) / квадратичный, если |linear| > l1 еще 0,0 аккум = аккум_новый
Аргументы:
- область: объект области.
- var: Должно быть из переменной().
- accum: Должно быть из переменной().
- линейный: должен быть из переменной().
- град: Градиент.
- индексы: вектор индексов в первом измерении var и accum.
- lr: Коэффициент масштабирования. Должно быть скаляр.
- l1: регуляризация L1. Должно быть скаляр.
- l2: регуляризация L2. Должно быть скаляр.
- lr_power: Коэффициент масштабирования. Должно быть скаляр.
Необязательные атрибуты (см. Attrs
):
- use_locking: если
True
, обновление тензоров var и accum будет защищено блокировкой; в противном случае поведение не определено, но может вызывать меньше конфликтов.
Возврат:
Конструкторы и деструкторы |
---|
ResourceSparseApplyFtrl (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input indices, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input lr_power)
|
ResourceSparseApplyFtrl (const :: tensorflow::Scope & scope, :: tensorflow::Input var, :: tensorflow::Input accum, :: tensorflow::Input linear, :: tensorflow::Input grad, :: tensorflow::Input indices, :: tensorflow::Input lr, :: tensorflow::Input l1, :: tensorflow::Input l2, :: tensorflow::Input lr_power, const ResourceSparseApplyFtrl::Attrs & attrs) |
Публичные атрибуты
Общественные функции
ResourceSparseApplyFtrl
ResourceSparseApplyFtrl(
const ::tensorflow::Scope & scope,
::tensorflow::Input var,
::tensorflow::Input accum,
::tensorflow::Input linear,
::tensorflow::Input grad,
::tensorflow::Input indices,
::tensorflow::Input lr,
::tensorflow::Input l1,
::tensorflow::Input l2,
::tensorflow::Input lr_power,
const ResourceSparseApplyFtrl::Attrs & attrs
)
оператор::tensorflow::Операция
operator::tensorflow::Operation() const
Публичные статические функции
Использование блокировки
Attrs UseLocking(
bool x
)
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Последнее обновление: 2025-07-26 UTC.
[null,null,["Последнее обновление: 2025-07-26 UTC."],[],[],null,["# tensorflow::ops::ResourceSparseApplyFtrl Class Reference\n\ntensorflow::ops::ResourceSparseApplyFtrl\n========================================\n\n`#include \u003ctraining_ops.h\u003e`\n\nUpdate relevant entries in '\\*var' according to the Ftrl-proximal scheme.\n\nSummary\n-------\n\nThat is for rows we have grad for, we update var, accum and linear as follows: 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 = (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- indices: A vector of indices into the first dimension of var and accum.\n- lr: Scaling factor. Must be a scalar.\n- l1: L1 regularization. Must be a scalar.\n- l2: L2 regularization. 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-sparse-apply-ftrl/attrs#structtensorflow_1_1ops_1_1_resource_sparse_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| [ResourceSparseApplyFtrl](#classtensorflow_1_1ops_1_1_resource_sparse_apply_ftrl_1aee900421c9006251c84f6dd00fb1892d)`(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)` indices, ::`[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| [ResourceSparseApplyFtrl](#classtensorflow_1_1ops_1_1_resource_sparse_apply_ftrl_1aca1e9533dccd71ef1217f5b21b2429ae)`(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)` indices, ::`[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 `[ResourceSparseApplyFtrl::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-ftrl/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_ftrl_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|--------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_resource_sparse_apply_ftrl_1a8c62c5bad64bbb58ad975e6e6d6e7510) | [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_sparse_apply_ftrl_1ad6adcd76de214e2887864742642d04a9)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|-------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [UseLocking](#classtensorflow_1_1ops_1_1_resource_sparse_apply_ftrl_1ad1edb0a2e7e8c453477bb22f82046f29)`(bool x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-ftrl/attrs#structtensorflow_1_1ops_1_1_resource_sparse_apply_ftrl_1_1_attrs) |\n\n| ### Structs ||\n|--------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::ResourceSparseApplyFtrl::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/resource-sparse-apply-ftrl/attrs) | Optional attribute setters for [ResourceSparseApplyFtrl](/versions/r2.0/api_docs/cc/class/tensorflow/ops/resource-sparse-apply-ftrl#classtensorflow_1_1ops_1_1_resource_sparse_apply_ftrl). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### ResourceSparseApplyFtrl\n\n```gdscript\n ResourceSparseApplyFtrl(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input linear,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input lr_power\n)\n``` \n\n### ResourceSparseApplyFtrl\n\n```gdscript\n ResourceSparseApplyFtrl(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input var,\n ::tensorflow::Input accum,\n ::tensorflow::Input linear,\n ::tensorflow::Input grad,\n ::tensorflow::Input indices,\n ::tensorflow::Input lr,\n ::tensorflow::Input l1,\n ::tensorflow::Input l2,\n ::tensorflow::Input lr_power,\n const ResourceSparseApplyFtrl::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```"]]