def __init__(self, in_channels, skip_channels, out_channels, use_batchnorm=True, attention_type=None):
    super().__init__()
    self.conv1 = md.Conv2dReLU((in_channels + skip_channels), out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.attention1 = md.Attention(attention_type, in_channels=(in_channels + skip_channels))
    self.conv2 = md.Conv2dReLU(out_channels, out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.attention2 = md.Attention(attention_type, in_channels=out_channels)
def __init__(self, in_channels, skip_channels, out_channels, use_batchnorm=True, attention_type=None):
    super().__init__()
    self.conv1 = md.Conv2dReLU((in_channels + skip_channels), out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.attention1 = md.Attention(attention_type, in_channels=(in_channels + skip_channels))
    self.conv2 = md.Conv2dReLU(out_channels, out_channels, kernel_size=3, padding=1, use_batchnorm=use_batchnorm)
    self.attention2 = md.Attention(attention_type, in_channels=out_channels)