tensorflow::ops::SparseApplyFtrl
#include <training_ops.h>
Update relevant entries in '*var' according to the Ftrl-proximal scheme.
Summary
That is for rows we have grad for, we update var, accum and linear as follows: accumnew=accum+grad∗grad
linear+=grad+(accum−lrpowernew−accum−lrpower/lr∗var
quadratic=1.0/(accumlrpowernew∗lr)+2∗l2
var=(sign(linear)∗l1−linear)/quadratic if |linear|>l1 else 0.0
accum=accumnew
Args:
- scope: A Scope object
- var: Should be from a Variable().
- accum: Should be from a Variable().
- linear: Should be from a Variable().
- grad: The gradient.
- indices: A vector of indices into the first dimension of var and accum.
- lr: Scaling factor. Must be a scalar.
- l1: L1 regularization. Must be a scalar.
- l2: L2 regularization. Must be a scalar.
- lr_power: Scaling factor. Must be a scalar.
Optional attributes (see Attrs
):
- 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.
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)
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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, const SparseApplyFtrl::Attrs & attrs)
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Public functions |
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node() const
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::tensorflow::Node *
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operator::tensorflow::Input() const
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operator::tensorflow::Output() const
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Public static functions |
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MultiplyLinearByLr(bool x)
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UseLocking(bool x)
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Structs |
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tensorflow:: |
Optional attribute setters for SparseApplyFtrl. |
Public attributes
operation
Operation operation
out
::tensorflow::Output out
Public functions
SparseApplyFtrl
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
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 )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
MultiplyLinearByLr
Attrs MultiplyLinearByLr( bool x )
UseLocking
Attrs UseLocking( bool x )