tensorflow::ops::ApplyRMSProp

#include <training_ops.h>

Update '*var' according to the RMSProp algorithm.

Summary

Note that in dense implementation of this algorithm, ms and mom will update even if the grad is zero, but in this sparse implementation, ms and mom will not update in iterations during which the grad is zero.

mean_square = decay * mean_square + (1-decay) * gradient ** 2 Delta = learning_rate * gradient / sqrt(mean_square + epsilon)

ms <- rho * ms_{t-1} + (1-rho) * grad * grad mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) var <- var - mom

Arguments:

  • scope: A Scope object
  • var: Should be from a Variable().
  • ms: Should be from a Variable().
  • mom: Should be from a Variable().
  • lr: Scaling factor. Must be a scalar.
  • rho: Decay rate. Must be a scalar.
  • epsilon: Ridge term. Must be a scalar.
  • grad: The gradient.

Optional attributes (see Attrs):

  • use_locking: If True, updating of the var, ms, and mom tensors is protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.

Returns:

Constructors and Destructors

ApplyRMSProp(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input ms, ::tensorflow::Input mom, ::tensorflow::Input lr, ::tensorflow::Input rho, ::tensorflow::Input momentum, ::tensorflow::Input epsilon, ::tensorflow::Input grad)
ApplyRMSProp(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input ms, ::tensorflow::Input mom, ::tensorflow::Input lr, ::tensorflow::Input rho, ::tensorflow::Input momentum, ::tensorflow::Input epsilon, ::tensorflow::Input grad, const ApplyRMSProp::Attrs & attrs)

Public attributes

out

Public functions

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

Public static functions

UseLocking(bool x)

Structs

tensorflow::ops::ApplyRMSProp::Attrs

Optional attribute setters for ApplyRMSProp.

Public attributes

out

::tensorflow::Output out

Public functions

ApplyRMSProp

 ApplyRMSProp(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input ms,
  ::tensorflow::Input mom,
  ::tensorflow::Input lr,
  ::tensorflow::Input rho,
  ::tensorflow::Input momentum,
  ::tensorflow::Input epsilon,
  ::tensorflow::Input grad
)

ApplyRMSProp

 ApplyRMSProp(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input ms,
  ::tensorflow::Input mom,
  ::tensorflow::Input lr,
  ::tensorflow::Input rho,
  ::tensorflow::Input momentum,
  ::tensorflow::Input epsilon,
  ::tensorflow::Input grad,
  const ApplyRMSProp::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
)