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docs/torch/torch.nn/torch.nn.modules/torch.nn.modules.normalization/LayerNorm

LayerNorm

torch.nn.modules.normalization.LayerNorm
final class LayerNorm[ParamType <: DType](normalizedShape: Seq[Int] | Int, eps: Double, elementwiseAffine: Boolean)(implicit evidence$1: Default[ParamType]) extends TensorModule[ParamType]

Applies Layer Normalization over a mini-batch of inputs as described in the paper Layer Normalization // TODO Add docs

Attributes

Source
LayerNorm.scala
Graph
Supertypes
trait TensorModule[ParamType]
trait Tensor[ParamType] => Tensor[ParamType]
class Module
class Object
trait Matchable
class Any
Show all

Members list

Value members

Concrete methods

def apply(t: Tensor[ParamType]): Tensor[ParamType]

Attributes

Source
LayerNorm.scala

Inherited methods

def andThen[A](g: Tensor[ParamType] => A): T1 => A

Attributes

Inherited from:
Function1
def compose[A](g: A => Tensor[ParamType]): A => R

Attributes

Inherited from:
Function1
def eval(): Unit

Attributes

Inherited from:
Module
Source
Module.scala
def isTraining: Boolean

Attributes

Inherited from:
Module
Source
Module.scala
def load(inputArchive: InputArchive): Unit

Attributes

Inherited from:
Module
Source
Module.scala
def loadStateDict(stateDict: Map[String, Tensor[DType]]): Unit

Attributes

Inherited from:
Module
Source
Module.scala
def modules: Seq[Module]

Attributes

Inherited from:
Module
Source
Module.scala
def modules(recurse: Boolean): Seq[Module]

Attributes

Inherited from:
Module
Source
Module.scala
def namedBuffers(recurse: Boolean): SeqMap[String, Tensor[_]]

Attributes

Inherited from:
Module
Source
Module.scala
def namedChildren: SeqMap[String, Module]

Attributes

Inherited from:
Module
Source
Module.scala
def namedModules: SeqMap[String, Module]

Attributes

Inherited from:
Module
Source
Module.scala
def namedParameters(recurse: Boolean): SeqMap[String, Tensor[_]]

Attributes

Inherited from:
Module
Source
Module.scala
def parameters(recurse: Boolean): Seq[Tensor[_]]

Attributes

Inherited from:
Module
Source
Module.scala
def parameters: Seq[Tensor[_]]

Attributes

Inherited from:
Module
Source
Module.scala
def register[D <: DType](t: Tensor[D], requiresGrad: Boolean)(using name: Name): Tensor[D]

Attributes

Inherited from:
Module
Source
Module.scala
def register[M <: Module](child: M)(using name: Name): M

Attributes

Inherited from:
Module
Source
Module.scala
def registerBuffer[D <: DType](name: String, tensor: Tensor[D]): Tensor[D]

Adds a buffer to the module.

Adds a buffer to the module.

Attributes

Inherited from:
Module
Source
Module.scala
def save(outputArchive: OutputArchive): Unit

Attributes

Inherited from:
Module
Source
Module.scala
def summarize: String

Attributes

Inherited from:
Module
Source
Module.scala
def to(device: Device): Module.this.type

Attributes

Inherited from:
Module
Source
Module.scala
override def toString(): String

Returns a string representation of the object.

Returns a string representation of the object.

The default representation is platform dependent.

Attributes

Returns

a string representation of the object.

Definition Classes
Inherited from:
TensorModule
Source
Module.scala
def train(on: Boolean): Unit

Attributes

Inherited from:
Module
Source
Module.scala

Concrete fields

val bias: Tensor[ParamType]

Attributes

Source
LayerNorm.scala
val weight: Tensor[ParamType]

Attributes

Source
LayerNorm.scala
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