Source code for modelzoo.common.pytorch.layers.AdaLayerNorm

# Copyright 2022 Cerebras Systems.
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# Licensed under the Apache License, Version 2.0 (the "License");
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import torch.nn as nn


[docs]class AdaLayerNorm(nn.Module):
[docs] def __init__(self, normalized_shape, eps=1e-05, device=None, dtype=None): factory_kwargs = {"device": device, "dtype": dtype} super(AdaLayerNorm, self).__init__() self.layernorm = nn.LayerNorm( normalized_shape=normalized_shape, eps=eps, elementwise_affine=False, **factory_kwargs, ) self.scale_linear = nn.Sequential( nn.SiLU(), nn.Linear(normalized_shape, normalized_shape, bias=True) ) self.shift_linear = nn.Sequential( nn.SiLU(), nn.Linear(normalized_shape, normalized_shape, bias=True) ) self.reset_parameters()
def reset_parameters(self): for param in self.parameters(): param.data.zero_() def forward(self, input, context): shift = self.shift_linear(context) scale = self.scale_linear(context) output = (1 + scale.unsqueeze(1)) * self.layernorm( input ) + shift.unsqueeze(1) return output