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:

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:: ops:: SparseApplyProximalGradientDescent:: Attrs

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
)