tensorflow:: ops:: SparseApplyMomentum
#include <training_ops.h>
Update relevant entries in '*var' and '*accum' according to the momentum scheme.
Summary
Set use_nesterov = True if you want to use Nesterov momentum.
That is for rows we have grad for, we update var and accum as follows:
$$accum = accum * momentum + grad$$ $$var -= lr * accum$$
Args:
- scope: A Scope object
- var: Should be from a Variable().
- accum: Should be from a Variable().
- lr: Learning rate. Must be a scalar.
- grad: The gradient.
- indices: A vector of indices into the first dimension of var and accum.
- 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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SparseApplyMomentum(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, ::tensorflow::Input momentum)
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SparseApplyMomentum(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, ::tensorflow::Input momentum, const SparseApplyMomentum::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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UseNesterov(bool x)
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Structs |
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tensorflow:: |
Optional attribute setters for SparseApplyMomentum. |
Public attributes
operation
Operation operation
out
::tensorflow::Output out
Public functions
SparseApplyMomentum
SparseApplyMomentum( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, ::tensorflow::Input momentum )
SparseApplyMomentum
SparseApplyMomentum( const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input accum, ::tensorflow::Input lr, ::tensorflow::Input grad, ::tensorflow::Input indices, ::tensorflow::Input momentum, const SparseApplyMomentum::Attrs & attrs )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
UseLocking
Attrs UseLocking( bool x )
UseNesterov
Attrs UseNesterov( bool x )