tensorflow:: ops:: ApplyGradientDescent

#include <training_ops.h>

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

Summary

Args:

  • 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:

Constructors and Destructors

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)

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:: ApplyGradientDescent:: Attrs

Optional attribute setters for ApplyGradientDescent .

Public attributes

operation 

Operation operation

out 

::tensorflow::Output out

Public functions

ApplyGradientDescent 

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

ApplyGradientDescent 

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