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: $$prox_v = var - alpha * grad$$ $$var = sign(prox_v)/(1+alpha*l2) * max{|prox_v|-alpha*l1,0}$$

Arguments:

  • 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

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

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
)