Pytorch implementation of our paper accepted by NeurIPS 2021 -- Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme

Last update: Mar 31, 2022

Related tags

Deep Learning GCC

Overview

Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme (NeurIPS2021) (Link)

Overview

Prerequisites

Linux
Python 3
CPU or NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

Please type the command
```
pip install -r requirements.txt
```
to install dependencies.

Data preparation

cityscapes
horse2zebra
celeb
Coco, Set5, Set14, B100, Urban100

Pretrained Model

We provide a list of pre-trained models in link.

Pre-Training For Pruning

Run the following script to pretrain a pix2pix on cityscapes dataset for generator pruning, all scripts for sagan, cyclegan, pix2pix, srgan can be found in ./scripts
```
bash scripts/pix2pix/pretrain_for_pruning.sh
```

Training

train lightweight generator using GCC
```
bash scripts/pix2pix/train.sh
```

Testing

test resulted models, FID or mIoU will be calculated, take pix2pix generator on cityscapes dataset as an example
```
bash scripts/pix2pix/test.sh
```

Acknowledgements

Our code is developed based on DMAD, Self-Attention-GAN, pytorch-CycleGAN-and-pix2pix, a-PyTorch-Tutorial-to-Super-Resolution.

Owner

Shaojie Li

Shaojie Li

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