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

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Deep LearningGCC
Overview

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

Overview

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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