T
- data type for out()
output@Operator(group="train") public final class ApplyAddSign<T> extends PrimitiveOp implements Operand<T>
m_t <- beta1 * m_{t-1} + (1 - beta1) * g update <- (alpha + sign_decay * sign(g) *sign(m)) * g variable <- variable - lr_t * update
Modifier and Type | Class and Description |
---|---|
static class |
ApplyAddSign.Options
Optional attributes for
ApplyAddSign |
operation
Modifier and Type | Method and Description |
---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T> ApplyAddSign<T> |
create(Scope scope,
Operand<T> var,
Operand<T> m,
Operand<T> lr,
Operand<T> alpha,
Operand<T> signDecay,
Operand<T> beta,
Operand<T> grad,
ApplyAddSign.Options... options)
Factory method to create a class wrapping a new ApplyAddSign operation.
|
Output<T> |
out()
Same as "var".
|
static ApplyAddSign.Options |
useLocking(Boolean useLocking) |
equals, hashCode, op, toString
public static <T> ApplyAddSign<T> create(Scope scope, Operand<T> var, Operand<T> m, Operand<T> lr, Operand<T> alpha, Operand<T> signDecay, Operand<T> beta, Operand<T> grad, ApplyAddSign.Options... options)
scope
- current scopevar
- Should be from a Variable().m
- Should be from a Variable().lr
- Scaling factor. Must be a scalar.alpha
- Must be a scalar.signDecay
- Must be a scalar.beta
- Must be a scalar.grad
- The gradient.options
- carries optional attributes valuespublic static ApplyAddSign.Options useLocking(Boolean useLocking)
useLocking
- If `True`, updating of the var and m tensors is
protected by a lock; otherwise the behavior is undefined, but may exhibit less
contention.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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