T
- data type for out()
output@Operator(group="train") public final class SparseApplyProximalGradientDescent<T> extends PrimitiveOp implements Operand<T>
That is for rows we have grad for, we update var as follows: $$prox_v = var - alpha grad$$ $$var = sign(prox_v)/(1+alphal2) max{|prox_v|-alphal1,0}$$
Modifier and Type | Class and Description |
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static class |
SparseApplyProximalGradientDescent.Options
Optional attributes for
SparseApplyProximalGradientDescent |
operation
Modifier and Type | Method and Description |
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Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T,U extends Number> |
create(Scope scope,
Operand<T> var,
Operand<T> alpha,
Operand<T> l1,
Operand<T> l2,
Operand<T> grad,
Operand<U> indices,
SparseApplyProximalGradientDescent.Options... options)
Factory method to create a class wrapping a new SparseApplyProximalGradientDescent operation.
|
Output<T> |
out()
Same as "var".
|
static SparseApplyProximalGradientDescent.Options |
useLocking(Boolean useLocking) |
equals, hashCode, op, toString
public static <T,U extends Number> SparseApplyProximalGradientDescent<T> create(Scope scope, Operand<T> var, Operand<T> alpha, Operand<T> l1, Operand<T> l2, Operand<T> grad, Operand<U> indices, SparseApplyProximalGradientDescent.Options... options)
scope
- current scopevar
- Should be from a Variable().alpha
- Scaling factor. Must be a scalar.l1
- L1 regularization. Must be a scalar.l2
- L2 regularization. Must be a scalar.grad
- The gradient.indices
- A vector of indices into the first dimension of var and accum.options
- carries optional attributes valuespublic static SparseApplyProximalGradientDescent.Options useLocking(Boolean useLocking)
useLocking
- If True, the subtraction 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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