DCGANGenerator#
- class deepinv.models.DCGANGenerator(output_size=64, nz=100, ngf=64, nc=3)[source]#
Bases:
Module
DCGAN Generator.
The DCGAN generator model was originally proposed in Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (Radford et al.) and takes a latent sample as input.
Implementation taken from https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html
See Imaging inverse problems with adversarial networks for how to use this for adversarial training.
- Parameters:
- forward(z, *args, **kwargs)[source]#
Generate an image
- Parameters:
z (torch.Tensor) – latent vector
Examples using DCGANGenerator
:#

Imaging inverse problems with adversarial networks
Imaging inverse problems with adversarial networks