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layer_norm

allennlp.modules.layer_norm

[SOURCE]

LayerNorm#

class LayerNorm(torch.nn.Module):
 | def __init__(self, dimension: int) -> None

An implementation of Layer Normalization.

Layer Normalization stabilises the training of deep neural networks by normalising the outputs of neurons from a particular layer. It computes:

output = (gamma * (tensor - mean) / (std + eps)) + beta

Parameters

  • dimension : int
    The dimension of the layer output to normalize.

Returns

  • The normalized layer output.

forward#

class LayerNorm(torch.nn.Module):
 | ...
 | def forward(self, tensor: torch.Tensor)