basic.py

# -*- 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