tensorflow:: ops:: SparseApplyProximalGradientDescent
#include <training_ops.h>
Sparse update '*var' as FOBOS algorithm with fixed learning rate.
Summary
That is for rows we have grad for, we update var as follows: $$prox_v = var - alpha * grad$$ $$var = sign(prox_v)/(1+alpha*l2) * max{|prox_v|-alpha*l1,0}$$
Args:
- scope: A Scope object
- var: Should be from a Variable().
- alpha: Scaling factor. Must be a scalar.
- l1: L1 regularization. Must be a scalar.
- l2: L2 regularization. Must be a scalar.
- grad: The gradient.
- indices: A vector of indices into the first dimension of var and accum.
Optional attributes (see Attrs
):
- use_locking: If True, the subtraction will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
Returns:
Output
: Same as "var".
Constructors and Destructors |
|
---|---|
SparseApplyProximalGradientDescent(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input alpha, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices)
|
|
SparseApplyProximalGradientDescent(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input alpha, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices, const SparseApplyProximalGradientDescent::Attrs & attrs)
|
Public attributes |
|
---|---|
operation
|
|
out
|
Public functions |
|
---|---|
node() const
|
::tensorflow::Node *
|
operator::tensorflow::Input() const
|
|
operator::tensorflow::Output() const
|
|
Public static functions |
|
---|---|
UseLocking(bool x)
|
Structs |
|
---|---|
tensorflow:: |
Optional attribute setters for SparseApplyProximalGradientDescent. |
Public attributes
operation
Operation operation
out
::tensorflow::Output out
Public functions
SparseApplyProximalGradientDescent
SparseApplyProximalGradientDescent( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input alpha, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices )
SparseApplyProximalGradientDescent
SparseApplyProximalGradientDescent( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input alpha, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices, const SparseApplyProximalGradientDescent::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
UseLocking
Attrs UseLocking( bool x )