DCGANDiscriminator

class deepinv.models.DCGANDiscriminator(ndf=64, nc=3, dim=2)

Bases: Module

DCGAN Discriminator.

The DCGAN discriminator model was originally proposed by Radford et al.[1]. 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:

• ndf (int) – hidden layer size, defaults to 64

• nc (int) – number of input channels, defaults to 3

• dim (str, int) – Whether to build 2D or 3D network (if str, can be “2”, “2d”, “3D”, etc.)

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References:

[1]

Alec Radford, Luke Metz, and Soumith Chintala. Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434, 2015.

forward(x)

Forward pass of discriminator model.

Parameters:

x (torch.Tensor) – input image

Examples using DCGANDiscriminator:

Imaging inverse problems with adversarial networks

Imaging inverse problems with adversarial networks