tensorflow::
ops::
ApplyMomentum
#include <training_ops.h>
Update '*var' according to the momentum scheme.
Summary
Set use_nesterov = True if you want to use Nesterov momentum.
accum = accum * momentum + grad var -= lr * accum
Args:
- scope: A Scope object
- var: Should be from a Variable().
- accum: Should be from a Variable().
- lr: Scaling factor. Must be a scalar.
- grad: The gradient.
- momentum: Momentum. Must be a scalar.
Optional attributes (see
Attrs
):
-
use_locking: If
True
, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention. -
use_nesterov: If
True
, the tensor passed to compute grad will be var - lr * momentum * accum, so in the end, the var you get is actually var - lr * momentum * accum.
Returns:
-
Output
: Same as "var".
Constructors and Destructors |
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ApplyMomentum
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
var, ::
tensorflow::Input
accum, ::
tensorflow::Input
lr, ::
tensorflow::Input
grad, ::
tensorflow::Input
momentum)
|
|
ApplyMomentum
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
var, ::
tensorflow::Input
accum, ::
tensorflow::Input
lr, ::
tensorflow::Input
grad, ::
tensorflow::Input
momentum, const
ApplyMomentum::Attrs
& attrs)
|
Public attributes |
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operation
|
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out
|
Public functions |
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node
() const
|
::tensorflow::Node *
|
operator::tensorflow::Input
() const
|
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operator::tensorflow::Output
() const
|
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Public static functions |
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UseLocking
(bool x)
|
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UseNesterov
(bool x)
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Structs |
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tensorflow::
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Optional attribute setters for ApplyMomentum . |
Public attributes
Public functions
ApplyMomentum
ApplyMomentum( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input momentum )
ApplyMomentum
ApplyMomentum( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input momentum, const ApplyMomentum::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const