I'm using PGGAN and I found out that
in the optimizeParameters function on base_GAN.py, the self.real_input shape changes right after it enters discriminator(before going through any layers).
the self.real_input had shape of [16, 3, 4, 4]
and I printed out the input x, in the discriminator forward function
It printed [4,3,4,4] .
why is that and where does it change the dimension?
I'm using PGGAN and I found out that in the optimizeParameters function on base_GAN.py, the self.real_input shape changes right after it enters discriminator(before going through any layers). the self.real_input had shape of [16, 3, 4, 4] and I printed out the input x, in the discriminator forward function It printed [4,3,4,4] . why is that and where does it change the dimension?