torch.nn.modules.normalization
package torch.nn.modules.normalization
Members list
Type members
Classlikes
Applies Group Normalization over a mini-batch of inputs
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
- Supertypes
-
trait TensorModule[ParamType]trait HasWeight[ParamType]class Moduleclass Objecttrait Matchableclass AnyShow all
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
Applies Layer Normalization over a mini-batch of inputs as described in the paper Layer Normalization // TODO Add docs
Attributes
- Source
- LayerNorm.scala
- Supertypes
In this article