tensorflow::
#include <training_ops.h>
Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.
Summary
That is for rows we have grad for, we update var and accum as follows: $$accum += grad * grad$$ $$prox_v = var$$ $$prox_v -= lr * grad * (1 / sqrt(accum))$$ $$var = sign(prox_v)/(1+lr*l2) * max{|prox_v|-lr*l1,0}$$
Args:
- scope: A Scope object
- var: Should be from a Variable().
- accum: Should be from a Variable().
- lr: Learning rate. Must be a scalar.
- l1: L1 regularization. Must be a scalar.
- l2: L2 regularization. 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 | |
|---|---|
| SparseApplyProximalAdagrad(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices) | |
| SparseApplyProximalAdagrad(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices, const SparseApplyProximalAdagrad::Attrs & attrs) | 
| Public attributes | |
|---|---|
| operation | |
| out | |
| Public functions | |
|---|---|
| node() const  | ::tensorflow::Node * | 
| operator::tensorflow::Input() const  |  | 
| operator::tensorflow::Output() const  |  | 
| Public static functions | |
|---|---|
| UseLocking(bool x) | |
| Structs | |
|---|---|
| tensorflow:: | Optional attribute setters for SparseApplyProximalAdagrad. | 
Public attributes
operation
Operation operation
out
::tensorflow::Output out
Public functions
SparseApplyProximalAdagrad
SparseApplyProximalAdagrad( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices )
SparseApplyProximalAdagrad
SparseApplyProximalAdagrad( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input grad, ::tensorflow::Input indices, const SparseApplyProximalAdagrad::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 )