I am going through the tutorial below, but I am confused as to how the right image shape is created via the generator.
https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html 9
It seems the latent vector created is a one dimensional vector of size 100:
We are feeding that into ConvTranspose2D as getting back a  512, 8x8?
ConvTranspose2d(100, 512, kernel_size=(4, 4), stride=(1, 1), bias=False)
How exactly is this happening?
In the diagram shown within tutorial, 100z is being projected into a 1024, 4, 4 vector then converted to
512,8,8 via ConvTranspore.
Are we skipping this step?  I am assuming the projection would take place using a fc layer and then reshape?
So what exactly is happening here:
ConvTranspose2d(100, 512, kernel_size=(4, 4), stride=(1, 1), bias=False)