Source code for layers.conv_bn_relu

import torch.nn as nn
import torch.nn.functional as F


class ConvBNReLU(nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True):
        super(ConvBNReLU, self).__init__()
        self.kernel_size = kernel_size
        self.conv = nn.Conv1d(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, bias)
        self.bn = nn.BatchNorm1d(out_channels)
        self.relu = F.relu

    def forward(self, x):
        x = self.conv(x)
        x = self.bn(x)
        x = self.relu(x)

        return x