Figure1
Figure 1. Generator architecture. The input is 1 × 1024-dimensional Gaussian noise; that input is first transformed into a 1 × 18432 tensor with a 1024 × 18432 fully connected layer. Then the tensor is projected and reshaped into a 128 × 12 × 12 tensor. There are two convolution layers. The output is a generated 1 × 48 × 48-dimensional grey image.
