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, 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. |