tensorflow::ops::SparseApplyMomentum

#include <training_ops.h>

Update relevant entries in '*var' and '*accum' according to the momentum scheme.

Summary

Set use_nesterov = True if you want to use Nesterov momentum.

That is for rows we have grad for, we update var and accum as follows:

$$accum = accum * momentum + grad$$ $$var -= lr * accum$$

Arguments:

  • scope: A Scope object
  • var: Should be from a Variable().
  • accum: Should be from a Variable().
  • lr: Learning rate. Must be a scalar.
  • grad: The gradient.
  • indices: A vector of indices into the first dimension of var and accum.
  • momentum: Momentum. 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.
  • use_nesterov: If True, the tensor passed to compute grad will be var - lr * momentum * accum, so in the end, the var you get is actually var - lr * momentum * accum.

Returns:

Constructors and Destructors

SparseApplyMomentum(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, ::tensorflow::Input momentum)
SparseApplyMomentum(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, ::tensorflow::Input momentum, const SparseApplyMomentum::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)
UseNesterov(bool x)

Structs

tensorflow::ops::SparseApplyMomentum::Attrs

Optional attribute setters for SparseApplyMomentum.

Public attributes

out

::tensorflow::Output out

Public functions

SparseApplyMomentum

 SparseApplyMomentum(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input accum,
  ::tensorflow::Input lr,
  ::tensorflow::Input grad,
  ::tensorflow::Input indices,
  ::tensorflow::Input momentum
)

SparseApplyMomentum

 SparseApplyMomentum(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input accum,
  ::tensorflow::Input lr,
  ::tensorflow::Input grad,
  ::tensorflow::Input indices,
  ::tensorflow::Input momentum,
  const SparseApplyMomentum::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
)

UseNesterov

Attrs UseNesterov(
  bool x
)