52 lines
1.6 KiB
Python
52 lines
1.6 KiB
Python
# 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
|
|
# limitations under the License.
|
|
|
|
from __future__ import absolute_import, division, print_function
|
|
|
|
import paddle
|
|
import paddle.nn as nn
|
|
|
|
from ..utils import get_param_attr_dict
|
|
|
|
|
|
class BNNeck(nn.Layer):
|
|
def __init__(self, num_features, **kwargs):
|
|
super().__init__()
|
|
weight_attr = paddle.ParamAttr(
|
|
initializer=paddle.nn.initializer.Constant(value=1.0))
|
|
bias_attr = paddle.ParamAttr(
|
|
initializer=paddle.nn.initializer.Constant(value=0.0),
|
|
trainable=False)
|
|
|
|
if 'weight_attr' in kwargs:
|
|
weight_attr = get_param_attr_dict(kwargs['weight_attr'])
|
|
|
|
bias_attr = None
|
|
if 'bias_attr' in kwargs:
|
|
bias_attr = get_param_attr_dict(kwargs['bias_attr'])
|
|
|
|
self.feat_bn = nn.BatchNorm1D(
|
|
num_features,
|
|
momentum=0.9,
|
|
epsilon=1e-05,
|
|
weight_attr=weight_attr,
|
|
bias_attr=bias_attr)
|
|
|
|
self.flatten = nn.Flatten()
|
|
|
|
def forward(self, x):
|
|
x = self.flatten(x)
|
|
x = self.feat_bn(x)
|
|
return x
|