(self, in_channels, out_channels)
| 127 | |
| 128 | class TransitionLayer(nn.Module): |
| 129 | def __init__(self, in_channels, out_channels): |
| 130 | super().__init__() |
| 131 | self.bn = nn.BatchNorm2d(in_channels) |
| 132 | self.relu = nn.ReLU(inplace=True) |
| 133 | self.conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=False) |
| 134 | self.pool = nn.AvgPool2d(kernel_size=2, stride=2) |
| 135 | |
| 136 | def forward(self, x): |
| 137 | x = self.conv(self.relu(self.bn(x))) |