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- # Copyright (c) 2022 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
- # limitations under the License.
- import paddle
- import paddle.nn as nn
- import paddle.nn.functional as F
- def avg_max_reduce_channel_helper(x, use_concat=True):
- # Reduce hw by avg and max, only support single input
- assert not isinstance(x, (list, tuple))
- mean_value = paddle.mean(x, axis=1, keepdim=True)
- max_value = paddle.max(x, axis=1, keepdim=True)
- if use_concat:
- res = paddle.concat([mean_value, max_value], axis=1)
- else:
- res = [mean_value, max_value]
- return res
- def avg_max_reduce_channel(x):
- # Reduce hw by avg and max
- # Return cat([avg_ch_0, max_ch_0, avg_ch_1, max_ch_1, ...])
- if not isinstance(x, (list, tuple)):
- return avg_max_reduce_channel_helper(x)
- elif len(x) == 1:
- return avg_max_reduce_channel_helper(x[0])
- else:
- res = []
- for xi in x:
- res.extend(avg_max_reduce_channel_helper(xi, False))
- return paddle.concat(res, axis=1)
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