tensorflow::ops::ResourceSparseApplyAdadelta

#include <training_ops.h>

var: Should be from a Variable().

Summary

Arguments:

• scope: A Scope object
• accum: Should be from a Variable().
• accum_update: : Should be from a Variable().
• lr: Learning rate. Must be a scalar.
• rho: Decay factor. Must be a scalar.
• epsilon: Constant factor. Must be a scalar.
• grad: The gradient.
• indices: A vector of indices into the first dimension of var and accum.

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.

Returns:

• the created Operation

Public attributes

Operation operation

Public functions

 ResourceSparseApplyAdadelta(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input accum,
  ::tensorflow::Input accum_update,
  ::tensorflow::Input lr,
  ::tensorflow::Input rho,
  ::tensorflow::Input epsilon,
  ::tensorflow::Input grad,
  ::tensorflow::Input indices
)

 ResourceSparseApplyAdadelta(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input accum,
  ::tensorflow::Input accum_update,
  ::tensorflow::Input lr,
  ::tensorflow::Input rho,
  ::tensorflow::Input epsilon,
  ::tensorflow::Input grad,
  ::tensorflow::Input indices,
  const ResourceSparseApplyAdadelta::Attrs & attrs
)

operator::tensorflow::Operation() const 

Public static functions

Attrs UseLocking(
  bool x
)