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

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)`