T - data type for out() output@Operator public final class ApplyRMSProp<T> extends PrimitiveOp implements Operand<T>
Note that in dense implementation of this algorithm, ms and mom will update even if the grad is zero, but in this sparse implementation, ms and mom will not update in iterations during which the grad is zero.
mean_square = decay * mean_square + (1-decay) * gradient ** 2 Delta = learning_rate * gradient / sqrt(mean_square + epsilon)
ms <- rho * ms_{t-1} + (1-rho) * grad * grad mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) var <- var - mom
| Modifier and Type | Class and Description |
|---|---|
static class |
ApplyRMSProp.Options
Optional attributes for
ApplyRMSProp |
operation| Modifier and Type | Method and Description |
|---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T> ApplyRMSProp<T> |
create(Scope scope,
Operand<T> var,
Operand<T> ms,
Operand<T> mom,
Operand<T> lr,
Operand<T> rho,
Operand<T> momentum,
Operand<T> epsilon,
Operand<T> grad,
ApplyRMSProp.Options... options)
Factory method to create a class to wrap a new ApplyRMSProp operation to the graph.
|
Output<T> |
out()
Same as "var".
|
static ApplyRMSProp.Options |
useLocking(Boolean useLocking) |
equals, hashCode, toStringpublic static <T> ApplyRMSProp<T> create(Scope scope, Operand<T> var, Operand<T> ms, Operand<T> mom, Operand<T> lr, Operand<T> rho, Operand<T> momentum, Operand<T> epsilon, Operand<T> grad, ApplyRMSProp.Options... options)
scope - current graph scopevar - Should be from a Variable().ms - Should be from a Variable().mom - Should be from a Variable().lr - Scaling factor. Must be a scalar.rho - Decay rate. Must be a scalar.momentum - epsilon - Ridge term. Must be a scalar.grad - The gradient.options - carries optional attributes valuespublic static ApplyRMSProp.Options useLocking(Boolean useLocking)
useLocking - If `True`, updating of the var, ms, and mom tensors is protected
by a lock; otherwise the behavior is undefined, but may exhibit less
contention.public Output<T> asOutput()
OperandInputs 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)Copyright © 2015–2019. All rights reserved.