tensorflow::ops::ApplyMomentum

#include <training_ops.h>

Update '*var' according to the momentum scheme.

Summary

Set use_nesterov = True if you

want to use Nesterov momentum.

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: Scaling factor. Must be a scalar.
• grad: The gradient.
• 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:

• Output: Same as "var".

Public attributes

::tensorflow::Output out

Public functions

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

 ApplyMomentum(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input accum,
  ::tensorflow::Input lr,
  ::tensorflow::Input grad,
  ::tensorflow::Input momentum,
  const ApplyMomentum::Attrs & attrs
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs UseLocking(
  bool x
)

Attrs UseNesterov(
  bool x
)