#include <training_ops.h>
Update relevant entries in '*var' according to the Ftrl-proximal scheme.
That is for rows we have grad for, we update var, accum and linear as follows: $$accum_new = accum + grad * grad$$ $$linear += grad + (accum_{new}^{-lr_{power} } - accum^{-lr_{power} } / lr * var$$ $$quadratic = 1.0 / (accum_{new}^{lr_{power} } * lr) + 2 * l2$$ $$var = (sign(linear) * l1 - linear) / quadratic\ if\ |linear| > l1\ else\ 0.0$$ $$accum = accum_{new}$$
Args:
Optional attributes (see Attrs
):
True
, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.Returns:
Output
: Same as "var". Constructors and Destructors | |
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SparseApplyFtrl(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) | |
SparseApplyFtrl(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 SparseApplyFtrl::Attrs & attrs) |
Public attributes | |
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operation | |
out |
Public functions | |
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node() const | ::tensorflow::Node * |
operator::tensorflow::Input() const | |
operator::tensorflow::Output() const |
Public static functions | |
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MultiplyLinearByLr(bool x) | |
UseLocking(bool x) |
Structs | |
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tensorflow::ops::SparseApplyFtrl::Attrs | Optional attribute setters for SparseApplyFtrl. |
Operation operation
::tensorflow::Output out
SparseApplyFtrl( 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 )
SparseApplyFtrl( 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 SparseApplyFtrl::Attrs & attrs )
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output() const
Attrs MultiplyLinearByLr( bool x )
Attrs UseLocking( bool x )
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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/cc/class/tensorflow/ops/sparse-apply-ftrl