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DCGANS – Adding more convolutions [Project]

I’m training a DCGAN on a dataset of 10k images. I want to expirement with adding and taking away convolutions in attempt to balance out the generator and discriminator. Whats the rule to do this in practice?

Here is my generator:

self.main = nn.Sequential( nn.ConvTranspose2d(100, 512, 4, 1, 0, bias = False), nn.BatchNorm2d(512), # We normalize all the features along the dimension of the batch. nn.ReLU(True), # We apply a ReLU rectification to break the linearity. nn.ConvTranspose2d(512, 256, 4, 2, 1, bias = False), nn.BatchNorm2d(256), # We normalize again. nn.ReLU(True), # We apply another ReLU. nn.ConvTranspose2d(256, 128, 4, 2, 1, bias = False), nn.BatchNorm2d(128), # We normalize again. nn.ReLU(True), # We apply another ReLU. nn.ConvTranspose2d(128, 64, 4, 2, 1, bias = False),
nn.BatchNorm2d(64), # We normalize again. nn.ReLU(True), # We apply another ReLU. nn.ConvTranspose2d(64, 3, 4, 2, 1, bias = False), nn.Tanh() )

What input and output values should I have for the 6th layer?

submitted by /u/CasualTrip
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.