Online Multi-Granularity Distillation for GAN Compression (ICCV2021)

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Deep Learning OMGD
Overview

Online Multi-Granularity Distillation for GAN Compression (ICCV2021)

This repository contains the pytorch codes and trained models described in the ICCV2021 paper "Online Multi-Granularity Distillation for GAN Compression" By Yuxi Ren*, Jie Wu*, Xuefeng Xiao, Jianchao Yang.

Overview

overview

Performance

performance

Prerequisites

  • Linux
  • Python 3
  • CPU or NVIDIA GPU + CUDA CuDNN

Getting Started

Installation

  • Clone this repo:

    git clone https://github.com/bytedance/OMGD.git
cd OMGD

  • Install dependencies.

    conda create -n OMGD python=3.7
conda activate OMGD
pip install torch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 
pip install -r requirements.txt

Data preparation

  • edges2shoes
  • cityscapes
  • horse2zebra
  • summer2winter

Training

  • pretrained vgg16 we should prepare weights of a vgg16 to calculate the style loss

  • train student model using OMGD Run the following script to train a unet-style student on cityscapes dataset, all scripts for cyclegan and pix2pix on horse2zebra,summer2winter,edges2shoes and cityscapes can be found in ./scripts

    bash scripts/unet_pix2pix/cityscapes/distill.sh

Testing

  • test student models, FID or mIoU will be calculated, take unet-style generator on cityscapes dataset as an example

    bash scripts/unet_pix2pix/cityscapes/test.sh

Citation

If you use this code for your research, please cite our paper.

Acknowledgements

Our code is developed based on GAN Compression

Comments
  • get_real_stat.py

    get_real_stat.py

    @WuJie1010 Hi there, why don't you include the "get_real_stat.py" in the OMGD repository so that we can test on different images waiting for your reply

    opened by seekingdeep 2
  • About

    About "n_share" in netD

    Thanks for your work! I noticed that in distill.sh the n_shared parameter was setted to be 5 https://github.com/bytedance/OMGD/blob/e70a3cc4397808b933ed41fff2435a60b144b523/scripts/unet_pix2pix/cityscapes/distill.sh#L7

    And in discriminator forward code: https://github.com/bytedance/OMGD/blob/e70a3cc4397808b933ed41fff2435a60b144b523/models/modules/discriminators.py#L102-L111

    So actually those all 5 blocks are using self.blockXs[-1], which means we only use one discriminator in pix2pix training, correct me if I'm wrong :-D

    opened by mazzzystar 1
  • Why OMGD reduces latency time by 90%?

    Why OMGD reduces latency time by 90%?

    Hi, thanks for the solid work. I have a question about the latency time. In Table 5 (arxiv), I am surprised OMGD reduces latency time by 90% on mobile phones? As I know, depthwise operations could slow down the latency time. OMGD contains depthwise and pointwise. How does OMGD get 10x speed up? What are the differences between servers and mobile phones (tflite toolkits)? Thank you!

    opened by Wanggcong 1
  • No such file or directory: 'real_stat/cityscapes_A.npz'

    No such file or directory: 'real_stat/cityscapes_A.npz'

    在运行train和test的时候会出现No such file or directory: 'real_stat/cityscapes_A.npz' 这个文件在哪里可以获取？ ` Traceback (most recent call last): File "test.py", line 98, in npz = np.load(opt.real_stat_path) File "/opt/AN/envs/OMGD/lib/python3.7/site-packages/numpy/lib/npyio.py", line 417, in load fid = stack.enter_context(open(os_fspath(file), "rb")) FileNotFoundError: [Errno 2] No such file or directory: 'real_stat/cityscapes_A.npz'

    `

    opened by TomatoBoy90 1
  • No handlers found:

    No handlers found: "aten::leaky_relu_".

    I get this warning: "torchprofile/profile.py:23: UserWarning: No handlers found: "aten::leaky_relu_". Skipped.". Did you have any ideas to solve it?

    opened by kasim0226 0
  • Reproduce unet_pix2pix, low performance

    Reproduce unet_pix2pix, low performance

    Evaluate epoch: 750 mIoU_teacher_w: 41.340 mIoU-best_teacher_w: 42.220 mIoU_teacher_d: 40.310 mIoU-best_teacher_d: 42.230 mIoU_student: 45.640 mIoU-best_student: 46.490

    lower than 48.91 in the paper.

    How can I solve it?

    Are there any tricks in the training?

    opened by huxiaotaostasy 0
  • a little issue

    a little issue

    Maybe this line should be replaced by model.save_student_networks(epoch), otherwise, it always saves the teacher model checkpoint. https://github.com/bytedance/OMGD/blob/e70a3cc4397808b933ed41fff2435a60b144b523/trainer.py#L121

    opened by zhuzhu18 1
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Bytedance Inc.
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