tensorflow::
ops::
ApplyRMSProp
#include <training_ops.h>
Update '*var' according to the RMSProp algorithm.
Summary
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
Args:
- scope: A Scope object
- var: 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.
- epsilon: Ridge term. Must be a scalar.
- grad: The gradient.
Optional attributes (see
Attrs
):
-
use_locking: 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.
Returns:
-
Output
: Same as "var".
Constructors and Destructors |
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ApplyRMSProp
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
var, ::
tensorflow::Input
ms, ::
tensorflow::Input
mom, ::
tensorflow::Input
lr, ::
tensorflow::Input
rho, ::
tensorflow::Input
momentum, ::
tensorflow::Input
epsilon, ::
tensorflow::Input
grad)
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ApplyRMSProp
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
var, ::
tensorflow::Input
ms, ::
tensorflow::Input
mom, ::
tensorflow::Input
lr, ::
tensorflow::Input
rho, ::
tensorflow::Input
momentum, ::
tensorflow::Input
epsilon, ::
tensorflow::Input
grad, const
ApplyRMSProp::Attrs
& attrs)
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Public attributes |
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operation
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out
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Public functions |
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node
() const
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::tensorflow::Node *
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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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Structs |
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tensorflow::
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Optional attribute setters for ApplyRMSProp . |
Public attributes
Public functions
ApplyRMSProp
ApplyRMSProp( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input ms, ::tensorflow::Input mom, ::tensorflow::Input lr, ::tensorflow::Input rho, ::tensorflow::Input momentum, ::tensorflow::Input epsilon, ::tensorflow::Input grad )
ApplyRMSProp
ApplyRMSProp( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input ms, ::tensorflow::Input mom, ::tensorflow::Input lr, ::tensorflow::Input rho, ::tensorflow::Input momentum, ::tensorflow::Input epsilon, ::tensorflow::Input grad, const ApplyRMSProp::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const