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

Related tags

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
GitHub Repository
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.

collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do

ShopRunner 96 Dec 29, 2022
A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch

A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch

Korbinian Pöppel 47 Nov 28, 2022
ObjectDetNet is an easy, flexible, open-source object detection framework

Getting started with the ObjectDetNet ObjectDetNet is an easy, flexible, open-source object detection framework which allows you to easily train, resu

5 Aug 25, 2020
(NeurIPS 2020) Wasserstein Distances for Stereo Disparity Estimation

Wasserstein Distances for Stereo Disparity Estimation Accepted in NeurIPS 2020 as Spotlight. [Project Page] Wasserstein Distances for Stereo Disparity

Divyansh Garg 92 Dec 12, 2022
Original Implementation of Prompt Tuning from Lester, et al, 2021

Prompt Tuning This is the code to reproduce the experiments from the EMNLP 2021 paper "The Power of Scale for Parameter-Efficient Prompt Tuning" (Lest

Google Research 282 Dec 28, 2022
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis

Bilateral Denoising Diffusion Models (BDDMs) This is the official PyTorch implementation of the following paper: BDDM: BILATERAL DENOISING DIFFUSION M

172 Dec 23, 2022
A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21

MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen

Graph Analysis & Deep Learning Laboratory, GRAND 32 Jan 02, 2023
Stacked Generative Adversarial Networks

Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the

Xun Huang 241 May 07, 2022
Jupyter notebooks for using & learning Keras

deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好，或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例

ErhWen Kuo 2.1k Dec 27, 2022
Angular & Electron desktop UI framework. Angular components for native looking and behaving macOS desktop UI (Electron/Web)

Angular Desktop UI This is a collection for native desktop like user interface components in Angular, especially useful for Electron apps. It starts w

Marc J. Schmidt 49 Dec 22, 2022
这是一个yolox-pytorch的源码，可以用于训练自己的模型。

YOLOX：You Only Look Once目标检测模型在Pytorch当中的实现 目录 性能情况 Performance 实现的内容 Achievement 所需环境 Environment 小技巧的设置 TricksSet 文件下载 Download 训练步骤 How2train 预测步骤

Bubbliiiing 613 Jan 05, 2023
Non-Imaging Transient Reconstruction And TEmporal Search (NITRATES)

Non-Imaging Transient Reconstruction And TEmporal Search (NITRATES) This repo contains the full NITRATES pipeline for maximum likelihood-driven discov

13 Nov 08, 2022
Auto-Encoding Score Distribution Regression for Action Quality Assessment

DAE-AQA It is an open source program reference to paper Auto-Encoding Score Distribution Regression for Action Quality Assessment. 1.Introduction DAE

13 Nov 16, 2022
Official PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.

DD3D: "Is Pseudo-Lidar needed for Monocular 3D Object detection?" Install // Datasets // Experiments // Models // License // Reference Full video Offi

Toyota Research Institute - Machine Learning 364 Dec 27, 2022
Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, and finding their unique parameters (e.g. death rate).

DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a

19 Dec 10, 2022
TuckER: Tensor Factorization for Knowledge Graph Completion

TuckER: Tensor Factorization for Knowledge Graph Completion This codebase contains PyTorch implementation of the paper: TuckER: Tensor Factorization f

Ivana Balazevic 296 Dec 06, 2022
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?

Shen Lab at Texas A&M University 106 Nov 11, 2022
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

THUML: Machine Learning Group @ THSS 243 Dec 26, 2022
The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding"

AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:

AutoML Research 64 Dec 17, 2022
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Kalman and Bayesian Filters in Python Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written

Roger Labbe 13k Dec 29, 2022