tf.raw_ops.ResourceApplyMomentum
Update '*var' according to the momentum scheme.
tf.raw_ops.ResourceApplyMomentum(
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 + grad var -= lr * 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 - lr * momentum * accum, so in the end, the var you get is actually var - lr * momentum * accum. |
name | A name for the operation (optional). |
| Returns | |
|---|---|
| The created Operation. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/ResourceApplyMomentum