T
- data type for out()
output@Operator(group="train") public final class ApplyMomentum<T> extends PrimitiveOp implements Operand<T>
want to use Nesterov momentum.
accum = accum * momentum + grad var -= lr * accum
Modifier and Type | Class and Description |
---|---|
static class |
ApplyMomentum.Options
Optional attributes for
ApplyMomentum |
operation
Modifier and Type | Method and Description |
---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T> ApplyMomentum<T> |
create(Scope scope,
Operand<T> var,
Operand<T> accum,
Operand<T> lr,
Operand<T> grad,
Operand<T> momentum,
ApplyMomentum.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) |
equals, hashCode, op, toString
public static <T> ApplyMomentum<T> create(Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Operand<T> momentum, ApplyMomentum.Options... options)
scope
- current scopevar
- 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 valuespublic static ApplyMomentum.Options useLocking(Boolean useLocking)
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)
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.public Output<T> asOutput()
Operand
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.
asOutput
in interface Operand<T>
OperationBuilder.addInput(Output)
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