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:

• Output: Same as "var".

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	Operation
out	::tensorflow::Output

Public functions
node() const	::tensorflow::Node *
operator::tensorflow::Input() const
operator::tensorflow::Output() const

Public static functions
UseLocking(bool x)	Attrs

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
)