tensorflow::ops::ApplyGradientDescent

#include <training_ops.h>

Update '*var' by subtracting 'alpha' * 'delta' from it.

Summary

Arguments:

• scope: A Scope object
• var: Should be from a Variable().
• alpha: Scaling factor. Must be a scalar.
• delta: The change.

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".

Public attributes

::tensorflow::Output out

Public functions

 ApplyGradientDescent(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input alpha,
  ::tensorflow::Input delta
)

 ApplyGradientDescent(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input alpha,
  ::tensorflow::Input delta,
  const ApplyGradientDescent::Attrs & attrs
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs UseLocking(
  bool x
)