def __init__(self, in_channels, base_channels, out_channels, norm_cfg=dict(type='BN')):
    super().__init__()
    self.norm_cfg = norm_cfg
    self.net = nn.Sequential(nn.ReLU(), nn.AvgPool2d(5, stride=2, padding=0, count_include_pad=False), nn.Conv2d(in_channels, base_channels, kernel_size=1, bias=False), build_norm_layer(self.norm_cfg, base_channels)[1], nn.ReLU(inplace=True), nn.Conv2d(base_channels, out_channels, kernel_size=2, bias=False), build_norm_layer(self.norm_cfg, out_channels)[1], nn.ReLU(inplace=True))
def __init__(self, in_channels, base_channels, out_channels, norm_cfg=dict(type='BN')):
    super().__init__()
    self.norm_cfg = norm_cfg
    self.net = nn.Sequential(nn.ReLU(), nn.AvgPool2d(5, stride=2, padding=0, count_include_pad=False), nn.Conv2d(in_channels, base_channels, kernel_size=1, bias=False), build_norm_layer(self.norm_cfg, base_channels)[1], nn.ReLU(inplace=True), nn.Conv2d(base_channels, out_channels, kernel_size=2, bias=False), build_norm_layer(self.norm_cfg, out_channels)[1], nn.ReLU(inplace=True))