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docs/torch/torch.nn/torch.nn.modules/torch.nn.modules.normalization/GroupNorm

GroupNorm

torch.nn.modules.normalization.GroupNorm
final class GroupNorm[ParamType <: FloatNN | ComplexNN](numGroups: Int, numChannels: Int, eps: Double, affine: Boolean)(implicit evidence$1: Default[ParamType]) extends HasWeight[ParamType], TensorModule[ParamType]

Applies Group Normalization over a mini-batch of inputs

Value parameters

affine

a boolean value that when set to true, this module has learnable per-channel affine parameters initialized to ones (for weights) and zeros (for biases)

eps

a value added to the denominator for numerical stability

numChannels

number of channels expected in input

numGroups

number of groups to separate the channels into

Attributes

Source
GroupNorm.scala
Graph
Supertypes
trait TensorModule[ParamType]
trait Tensor[ParamType] => Tensor[ParamType]
trait HasWeight[ParamType]
class Module
class Object
trait Matchable
class Any
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Members list

Value members

Concrete methods

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

Attributes

Source
GroupNorm.scala
override def hasBias(): Boolean

Attributes

Definition Classes
Source
GroupNorm.scala

Inherited methods

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

Attributes

Inherited from:
Function1
def apply(fn: Module => Unit): Module.this.type

Attributes

Inherited from:
Module
Source
Module.scala
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[M <: Module](child: M, n: String)(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 registerBuffer[D <: DType](t: Tensor[D], n: String)(using name: Name): Tensor[D]

Attributes

Inherited from:
Module
Source
Module.scala
def registerModule[M <: Module](child: M, n: String)(using name: Name): M

Attributes

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

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
GroupNorm.scala
val weight: Tensor[ParamType]

Attributes

Source
GroupNorm.scala
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