tensorflow::ops::ApplyAddSign
#include <training_ops.h>
Update '*var' according to the AddSign update.
Summary
m_t <- beta1 * m_{t-1} + (1 - beta1) * g update <- (alpha + sign_decay * sign(g) *sign(m)) * g variable <- variable - lr_t * update
Args:
- scope: A Scope object
- var: Should be from a Variable().
- m: Should be from a Variable().
- lr: Scaling factor. Must be a scalar.
- alpha: Must be a scalar.
- sign_decay: Must be a scalar.
- beta: Must be a scalar.
- grad: The gradient.
Optional attributes (see Attrs
):
- use_locking: If
True
, updating of the var and m 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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ApplyAddSign(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input m, ::tensorflow::Input lr, ::tensorflow::Input alpha, ::tensorflow::Input sign_decay, ::tensorflow::Input beta, ::tensorflow::Input grad) | |
ApplyAddSign(const ::tensorflow::Scope & scope, ::tensorflow::Input var, ::tensorflow::Input m, ::tensorflow::Input lr, ::tensorflow::Input alpha, ::tensorflow::Input sign_decay, ::tensorflow::Input beta, ::tensorflow::Input grad, const ApplyAddSign::Attrs & attrs) |
Public attributes | |
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operation | |
out |
Public functions | |
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node() const | ::tensorflow::Node * |
operator::tensorflow::Input() const |
|
operator::tensorflow::Output() const |
|
Public static functions | |
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UseLocking(bool x) |
Structs | |
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tensorflow:: | Optional attribute setters for ApplyAddSign. |