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- # -*- coding: utf-8 -*-
- # @Time : 2019/12/6 11:19
- # @Author : zhoujun
- from paddle import nn
- class ConvBnRelu(nn.Layer):
- def __init__(
- self,
- in_channels,
- out_channels,
- kernel_size,
- stride=1,
- padding=0,
- dilation=1,
- groups=1,
- bias=True,
- padding_mode="zeros",
- inplace=True,
- ):
- super().__init__()
- self.conv = nn.Conv2D(
- in_channels=in_channels,
- out_channels=out_channels,
- kernel_size=kernel_size,
- stride=stride,
- padding=padding,
- dilation=dilation,
- groups=groups,
- bias_attr=bias,
- padding_mode=padding_mode,
- )
- self.bn = nn.BatchNorm2D(out_channels)
- self.relu = nn.ReLU()
- def forward(self, x):
- x = self.conv(x)
- x = self.bn(x)
- x = self.relu(x)
- return x
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