tf.raw_ops.ResourceApplyMomentum
    
    
      
    
    
      
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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 Tensorof typeresource. Should be from a Variable(). | 
| accum | A Tensorof typeresource. 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 aslr. The gradient. | 
| momentum | A Tensor. Must have the same type aslr.
Momentum. Must be a scalar. | 
| use_locking | An optional bool. Defaults toFalse.
IfTrue, 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 toFalse.
IfTrue, 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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  Last updated 2022-10-27 UTC.
  
  
  
    
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