tf.raw_ops.ResourceApplyKerasMomentum
Update '*var' according to the momentum scheme.
tf.raw_ops.ResourceApplyKerasMomentum(
var,
accum,
lr,
grad,
momentum,
use_locking=False,
use_nesterov=False,
name=None
)
Set use_nesterov = True if you want to use Nesterov momentum.
accum = accum * momentum - lr * grad
var += accum
Args |
var
|
A Tensor of type resource . Should be from a Variable().
|
accum
|
A Tensor of type resource . Should be from a Variable().
|
lr
|
A Tensor . Must be one of the following types: float32 , float64 , int32 , uint8 , int16 , int8 , complex64 , int64 , qint8 , quint8 , qint32 , bfloat16 , qint16 , quint16 , uint16 , complex128 , half , uint32 , uint64 .
Scaling factor. Must be a scalar.
|
grad
|
A Tensor . Must have the same type as lr . The gradient.
|
momentum
|
A Tensor . Must have the same type as lr .
Momentum. Must be a scalar.
|
use_locking
|
An optional bool . Defaults to False .
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
|
An optional bool . Defaults to False .
If True , the tensor passed to compute grad will be
var + momentum * accum, so in the end, the var you get is actually
var + momentum * accum.
|
name
|
A name for the operation (optional).
|
Returns |
The created Operation.
|
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Last updated 2024-01-23 UTC.
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