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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
"""Normalization modules."""
import typing as tp
import einops
import torch
from torch import nn
class ConvLayerNorm(nn.LayerNorm):
"""
Convolution-friendly LayerNorm that moves channels to last dimensions
before running the normalization and moves them back to original position right after.
"""
def __init__(self,
normalized_shape: tp.Union[int, tp.List[int], torch.Size],
**kwargs):
super().__init__(normalized_shape, **kwargs)
def forward(self, x):
x = einops.rearrange(x, 'b ... t -> b t ...')
x = super().forward(x)
x = einops.rearrange(x, 'b t ... -> b ... t')
return
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