x = cls.downsampling_block(dim, x, ifilters, "downsampling-"+str(i), **kwargs)
encoder_outputs.append(x)
x = conv_block(dim, x, filters[-1]//2, 2, "t", "middle", strides=2, **kwargs)
axis = -1 if kwargs["data_format"] == "channels_last" else 1
for i, ifilters in enumerate(filters[::-1][1:]):
x = tf.concat([encoder_outputs[-i-2], x], axis=axis)
After Change
encoder_outputs.append(x)
for i, ifilters in enumerate(filters[::-1]):
x = cls.upsampling_block((x, encoder_outputs[-i-2]), ifilters//2, name="upsampling-"+str(i), **kwargs)
return x
