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scalation/scalation/scalation.modeling/scalation.modeling.forecasting/scalation.modeling.forecasting.neuralforecasting/RMSNorm

RMSNorm

scalation.modeling.forecasting.neuralforecasting.RMSNorm
case class RMSNorm()

The RMSNorm class will, in computing the output, normalize by dividing by the Root Mean Square (RMS).

Attributes

Graph
Supertypes
trait Serializable
trait Product
trait Equals
class Object
trait Matchable
class Any
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Members list

Inherited
  • Not inherited
  • Product

Value members

Concrete methods

def apply(u: VectorD): VectorD

Forward pass: calculate the output of this layer given the values sent to all its neurons: u = W x where W is a weight matrix

Forward pass: calculate the output of this layer given the values sent to all its neurons: u = W x where W is a weight matrix

Value parameters

u

the input vector to the given layer

Attributes

Inherited methods

def productElementNames: Iterator[String]

Attributes

Inherited from:
Product
def productIterator: Iterator[Any]

Attributes

Inherited from:
Product
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