Only the first channel converges

[alexberd]

I run your code with slightly different network parameters:

enc = Encoder(in_ch=1)
dec = Decoder(out_ch=37)
dis = Discriminator(in_ch=1, out_ch=37)

After many training iterations I found that only the first channel out of the 37 channels of "out_ch" converges. When checking the "gen_all" output at your out_image module the first channel converged fine but all other channels have values between -1 and -0.8.

Would it be anything else to have in mind when changing encoder's, decoder's and discriminator's channels?

Would it be possible the case that pix2pix cannot learn to produce more output channel than inputs channels?

**UPDATED
Few more notes:
-When tested all other parameters such as network configuration and image dimensions were kept the same
-Dataset had 35000 samples
-The first layer converges impresively well after 4.5 epochs

Any help/advice will be really appreciated.

Thanks,
Alex