tensorflow::ops::SparseApplyAdagrad

#include <training_ops.h>

Update relevant entries in '*var' and '*accum' according to the adagrad scheme.

Summary

That is for rows we have grad for, we update var and accum as follows:

$$accum += grad * grad$$

$$var -= lr * grad * (1 / sqrt(accum))$$

Arguments:

• scope: A Scope object
• var: Should be from a Variable().
• accum: Should be from a Variable().
• lr: Learning rate. 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:

• Output: Same as "var".

Constructors and Destructors
SparseApplyAdagrad(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices)
SparseApplyAdagrad(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, const SparseApplyAdagrad::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
UpdateSlots(bool x)	Attrs
UseLocking(bool x)	Attrs

Structs
tensorflow::ops::SparseApplyAdagrad::Attrs	Optional attribute setters for SparseApplyAdagrad.

Public attributes

operation

Operation operation

out

::tensorflow::Output out

Public functions

SparseApplyAdagrad

 SparseApplyAdagrad(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input accum,
  ::tensorflow::Input lr,
  ::tensorflow::Input grad,
  ::tensorflow::Input indices
)

SparseApplyAdagrad

 SparseApplyAdagrad(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input var,
  ::tensorflow::Input accum,
  ::tensorflow::Input lr,
  ::tensorflow::Input grad,
  ::tensorflow::Input indices,
  const SparseApplyAdagrad::Attrs & attrs
)

node

::tensorflow::Node * node() const 

operator::tensorflow::Input

 operator::tensorflow::Input() const 

operator::tensorflow::Output

 operator::tensorflow::Output() const 

Public static functions

UpdateSlots

Attrs UpdateSlots(
  bool x
)

UseLocking

Attrs UseLocking(
  bool x
)