def __init__(self, in_channels, out_channels, skip_channels=0, use_batchnorm=True):
    super().__init__()
    self.conv1 = Conv3dReLU((in_channels + skip_channels), out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.conv2 = Conv3dReLU(out_channels, out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.up = nn.Upsample(scale_factor=2, mode='trilinear', align_corners=False)
def __init__(self, in_channels, out_channels, skip_channels=0, use_batchnorm=True):
    super().__init__()
    self.conv1 = Conv3dReLU((in_channels + skip_channels), out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.conv2 = Conv3dReLU(out_channels, out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.up = nn.Upsample(scale_factor=2, mode='trilinear', align_corners=False)