T
- data type for out()
outputpublic final class ApplyAdaMax<T> extends PrimitiveOp implements Operand<T>
m_t <- beta1 * m_{t-1} + (1 - beta1) * g v_t <- max(beta2 * v_{t-1}, abs(g)) variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon)
Modifier and Type | Class and Description |
---|---|
static class |
ApplyAdaMax.Options
Optional attributes for
ApplyAdaMax |
operation
Modifier and Type | Method and Description |
---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T> ApplyAdaMax<T> |
create(Scope scope,
Operand<T> var,
Operand<T> m,
Operand<T> v,
Operand<T> beta1Power,
Operand<T> lr,
Operand<T> beta1,
Operand<T> beta2,
Operand<T> epsilon,
Operand<T> grad,
ApplyAdaMax.Options... options)
Factory method to create a class wrapping a new ApplyAdaMax operation.
|
Output<T> |
out()
Same as "var".
|
static ApplyAdaMax.Options |
useLocking(Boolean useLocking) |
equals, hashCode, op, toString
public static <T> ApplyAdaMax<T> create(Scope scope, Operand<T> var, Operand<T> m, Operand<T> v, Operand<T> beta1Power, Operand<T> lr, Operand<T> beta1, Operand<T> beta2, Operand<T> epsilon, Operand<T> grad, ApplyAdaMax.Options... options)
scope
- current scopevar
- Should be from a Variable().m
- Should be from a Variable().v
- Should be from a Variable().beta1Power
- Must be a scalar.lr
- Scaling factor. Must be a scalar.beta1
- Momentum factor. Must be a scalar.beta2
- Momentum factor. Must be a scalar.epsilon
- Ridge term. Must be a scalar.grad
- The gradient.options
- carries optional attributes valuespublic static ApplyAdaMax.Options useLocking(Boolean useLocking)
useLocking
- If `True`, updating of the var, m, and v tensors will be 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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