# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
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"""Layer normalization module."""
import paddle
from paddle import nn
[docs]class LayerNorm(nn.LayerNorm):
"""Layer normalization module.
Args:
nout (int):
Output dim size.
dim (int):
Dimension to be normalized.
"""
def __init__(self, nout, dim=-1):
"""Construct an LayerNorm object."""
super().__init__(nout)
self.dim = dim
[docs] def forward(self, x):
"""Apply layer normalization.
Args:
x (Tensor):
Input tensor.
Returns:
Tensor: Normalized tensor.
"""
if self.dim == -1:
return super(LayerNorm, self).forward(x)
else:
len_dim = len(x.shape)
if self.dim < 0:
self.dim = len_dim + self.dim
assert self.dim >= 0
orig_perm = list(range(len_dim))
new_perm = orig_perm[:]
# Python style item change is not able when converting dygraph to static graph.
# new_perm[self.dim], new_perm[len_dim -1] = new_perm[len_dim -1], new_perm[self.dim]
# use C++ style item change here
temp = new_perm[self.dim]
new_perm[self.dim] = new_perm[len_dim - 1]
new_perm[len_dim - 1] = temp
return paddle.transpose(
super(LayerNorm, self).forward(paddle.transpose(x, new_perm)),
new_perm)