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tensorflow::ops::ResourceApplyGradientDescent

#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:

Constructors and Destructors

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

Public attributes

operation

Public functions

operator::tensorflow::Operation() const

Public static functions

UseLocking(bool x)

Structs

tensorflow::ops::ResourceApplyGradientDescent::Attrs

Optional attribute setters for ResourceApplyGradientDescent.

Public attributes

operation

Operation operation

Public functions

ResourceApplyGradientDescent

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

ResourceApplyGradientDescent

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

operator::tensorflow::Operation

 operator::tensorflow::Operation() const 

Public static functions

UseLocking

Attrs UseLocking(
  bool x
)