tensorflow::
ops::
ResourceApplyProximalGradientDescent
#include <training_ops.h>
Update '*var' as FOBOS algorithm with fixed learning rate.
Summary
prox_v = var - alpha * delta var = sign(prox_v)/(1+alpha*l2) * max{|prox_v|-alpha*l1,0}
Args:
- scope: A Scope object
- var: 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.
- delta: The change.
Optional attributes (see
Attrs
):
- use_locking: If True, the subtraction will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.
Returns:
-
the created
Operation
Constructors and Destructors |
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ResourceApplyProximalGradientDescent
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
var, ::
tensorflow::Input
alpha, ::
tensorflow::Input
l1, ::
tensorflow::Input
l2, ::
tensorflow::Input
delta)
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ResourceApplyProximalGradientDescent
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
var, ::
tensorflow::Input
alpha, ::
tensorflow::Input
l1, ::
tensorflow::Input
l2, ::
tensorflow::Input
delta, const
ResourceApplyProximalGradientDescent::Attrs
& attrs)
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Public attributes |
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operation
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Public functions |
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operator::tensorflow::Operation
() const
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Public static functions |
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UseLocking
(bool x)
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Structs |
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tensorflow::
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Optional attribute setters for ResourceApplyProximalGradientDescent . |
Public attributes
Public functions
ResourceApplyProximalGradientDescent
ResourceApplyProximalGradientDescent( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input alpha, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input delta )
ResourceApplyProximalGradientDescent
ResourceApplyProximalGradientDescent( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input alpha, ::tensorflow::Input l1, ::tensorflow::Input l2, ::tensorflow::Input delta, const ResourceApplyProximalGradientDescent::Attrs & attrs )
operator::tensorflow::Operation
operator::tensorflow::Operation() const