def __init__(self, in_channels, middle_channels, out_channels, upscale=Upscale.upsample_bilinear):
    super().__init__()
    self.layer = nn.Sequential(nn.Upsample(scale_factor=2), nn.Conv2d(in_channels, out_channels, 3, padding=1), nn.BatchNorm2d(out_channels), nn.ReLU(inplace=True))
def __init__(self, in_channels, middle_channels, out_channels, upscale=Upscale.upsample_bilinear):
    super().__init__()
    self.layer = nn.Sequential(nn.Upsample(scale_factor=2), nn.Conv2d(in_channels, out_channels, 3, padding=1), nn.BatchNorm2d(out_channels), nn.ReLU(inplace=True))