ApplyMomentum

public final class ApplyMomentum

Update '*var' according to the momentum scheme.

Set use_nesterov = True if you want to use Nesterov momentum.

accum = accum * momentum + grad var -= lr * accum

Nested Classes

class ApplyMomentum.Options Optional attributes for ApplyMomentum  

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of the tensor.
static <T extends TType> ApplyMomentum<T>
create(Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Operand<T> momentum, Options... options)
Factory method to create a class wrapping a new ApplyMomentum operation.
Output<T>
out()
Same as "var".
static ApplyMomentum.Options
useLocking(Boolean useLocking)
static ApplyMomentum.Options
useNesterov(Boolean useNesterov)

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "ApplyMomentum"

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static ApplyMomentum<T> create (Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Operand<T> momentum, Options... options)

Factory method to create a class wrapping a new ApplyMomentum operation.

Parameters
scope current scope
var Should be from a Variable().
accum Should be from a Variable().
lr Scaling factor. Must be a scalar.
grad The gradient.
momentum Momentum. Must be a scalar.
options carries optional attributes values
Returns
  • a new instance of ApplyMomentum

public Output<T> out ()

Same as "var".

public static ApplyMomentum.Options useLocking (Boolean useLocking)

Parameters
useLocking 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.

public static ApplyMomentum.Options useNesterov (Boolean useNesterov)

Parameters
useNesterov If `True`, the tensor passed to compute grad will be var - lr * momentum * accum, so in the end, the var you get is actually var - lr * momentum * accum.