[Preprint] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang

Overview

Chasing Sparsity in Vision Transformers: An End-to-End Exploration

License: MIT

Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Exploration.

Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang

Overall Results

Extensive results on ImageNet with diverse ViT backbones validate the effectiveness of our proposals which obtain significantly reduced computational cost and almost unimpaired generalization. Perhaps most surprisingly, we find that the proposed sparse (co-)training can even improve the ViT accuracy rather than compromising it, making sparsity a tantalizing “free lunch”. For example, our sparsified DeiT-Small at (5%, 50%) sparsity for (data, architecture), improves 0.28% top-1 accuracy, and meanwhile enjoys 49.32% FLOPs and 4.40% running time savings.

Proposed Framework of SViTE

Implementations of SViTE

Set Environment

conda create -n vit python=3.6

pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

pip install tqdm scipy timm

git clone https://github.com/NVIDIA/apex

cd apex

pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

pip install -v --disable-pip-version-check --no-cache-dir ./

Cmd

Command for unstructured sparsity, i.e., SViTE.

  • SViTE-Small
bash cmd/ vm/0426/vm1.sh 0,1,2,3,4,5,6,7

Details

CUDA_VISIBLE_DEVICES=$1 \
python -m torch.distributed.launch \
    --nproc_per_node=8 \
    --use_env main.py \
    --model deit_small_patch16_224 \
    --epochs 600 \
    --batch-size 64 \
    --data-path ../../imagenet \
    --output_dir ./small_dst_uns_0426_vm1 \
    --dist_url tcp://127.0.0.1:23305 \
    --sparse_init fixed_ERK \
    --density 0.4 \
    --update_frequency 15000 \
    --growth gradient \
    --death magnitude \
    --redistribution none
  • SViTE-Base
bash cmd/ vm/0426/vm3.sh 0,1,2,3,4,5,6,7

Details

CUDA_VISIBLE_DEVICES=$1 \
python -m torch.distributed.launch \
    --nproc_per_node=8 \
    --use_env main.py \
    --model deit_base_patch16_224 \
    --epochs 600 \
    --batch-size 128 \
    --data-path ../../imagenet \
    --output_dir ./base_dst_uns_0426_vm3 \
    --dist_url tcp://127.0.0.1:23305 \
    --sparse_init fixed_ERK \
    --density 0.4 \
    --update_frequency 7000 \
    --growth gradient \
    --death magnitude \
    --redistribution none

Remark. More commands can be found under the "cmd" folder.

Command for structured sparsity is comming soon!

Pre-traiend SViTE Models.

  1. SViTE-Base with 40% structural sparsity ACC=82.22

https://www.dropbox.com/s/ix7mmduvf0wlc4b/deit_base_structure_40_82.22.pth?dl=0

  1. SViTE-Base with 40% unstructured sparsity ACC=81.56

https://www.dropbox.com/s/vltm4piwn9cwsop/deit_base_unstructure_40_81.56.pth?dl=0

  1. SViTE-Small with 50% unstructued sparsity and 5% data sparisity ACC=80.18

https://www.dropbox.com/s/kofps21g857wlbt/deit_small_unstructure_50_sparseinput_0.95_80.18.pth?dl=0

  1. SViTE-Small with 50% unstructured sparsity and 10% data sparsity ACC=79.91

https://www.dropbox.com/s/bdhpc6nfrwahcuc/deit_small_unstructure_50_sparseinput_0.90_79.91.pth?dl=0

Citation

@misc{chen2021chasing,
      title={Chasing Sparsity in Vision Transformers:An End-to-End Exploration}, 
      author={Tianlong Chen and Yu Cheng and Zhe Gan and Lu Yuan and Lei Zhang and Zhangyang Wang},
      year={2021},
      eprint={2106.04533},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Acknowledge Related Repos

ViT : https://github.com/jeonsworld/ViT-pytorch

ViT : https://github.com/google-research/vision_transformer

Rig : https://github.com/google-research/rigl

DeiT: https://github.com/facebookresearch/deit

Owner
VITA
Visual Informatics Group @ University of Texas at Austin
VITA
PyTorch implementation of Rethinking Positional Encoding in Language Pre-training

TUPE PyTorch implementation of Rethinking Positional Encoding in Language Pre-training. Quickstart Clone this repository. git clone https://github.com

Jake Tae 5 Jan 27, 2022
[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

CC 4.4k Dec 27, 2022
PyTorch implementation of paper A Fast Knowledge Distillation Framework for Visual Recognition.

FKD: A Fast Knowledge Distillation Framework for Visual Recognition Official PyTorch implementation of paper A Fast Knowledge Distillation Framework f

Zhiqiang Shen 129 Dec 24, 2022
Annotate with anyone, anywhere.

h h is the web app that serves most of the https://hypothes.is/ website, including the web annotations API at https://hypothes.is/api/. The Hypothesis

Hypothesis 2.6k Jan 08, 2023
An Implementation of SiameseRPN with Feature Pyramid Networks

SiameseRPN with FPN This project is mainly based on HelloRicky123/Siamese-RPN. What I've done is just add a Feature Pyramid Network method to the orig

3 Apr 16, 2022
A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swar.

Omni-swarm A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swarm Introduction Omni-swarm is a decentralized omn

HKUST Aerial Robotics Group 99 Dec 23, 2022
Deeprl - Standard DQN and dueling network for simple games

DeepRL This code implements the standard deep Q-learning and dueling network with experience replay (memory buffer) for playing simple games. DQN algo

Yao Zhou 6 Apr 12, 2020
Multivariate Time Series Transformer, public version

Multivariate Time Series Transformer Framework This code corresponds to the paper: George Zerveas et al. A Transformer-based Framework for Multivariat

363 Jan 03, 2023
Bringing Computer Vision and Flutter together , to build an awesome app !!

Bringing Computer Vision and Flutter together , to build an awesome app !! Explore the Directories Flutter · Machine Learning Table of Contents About

Padmanabha Banerjee 14 Apr 07, 2022
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)

Graph Neural Networks with Learnable Structural and Positional Representations Source code for the paper "Graph Neural Networks with Learnable Structu

Vijay Prakash Dwivedi 180 Dec 22, 2022
CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes (AAAI2022)

CMUA-Watermark The official code for CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes (AAAI2022) arxiv. It is bas

50 Nov 26, 2022
A Dataset of Python Challenges for AI Research

Python Programming Puzzles (P3) This repo contains a dataset of python programming puzzles which can be used to teach and evaluate an AI's programming

Microsoft 850 Dec 24, 2022
[ICML 2021] A fast algorithm for fitting robust decision trees.

GROOT: Growing Robust Trees Growing Robust Trees (GROOT) is an algorithm that fits binary classification decision trees such that they are robust agai

Cyber Analytics Lab 17 Nov 21, 2022
Instance-level Image Retrieval using Reranking Transformers

Instance-level Image Retrieval using Reranking Transformers Fuwen Tan, Jiangbo Yuan, Vicente Ordonez, ICCV 2021. Abstract Instance-level image retriev

UVA Computer Vision 87 Jan 03, 2023
Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Ali Aliev 15.3k Jan 05, 2023
Simple-Image-Classification - Simple Image Classification Code (PyTorch)

Simple-Image-Classification Simple Image Classification Code (PyTorch) Yechan Kim This repository contains: Python3 / Pytorch code for multi-class ima

Yechan Kim 8 Oct 29, 2022
[ACMMM 2021 Oral] Enhanced Invertible Encoding for Learned Image Compression

InvCompress Official Pytorch Implementation for "Enhanced Invertible Encoding for Learned Image Compression", ACMMM 2021 (Oral) Figure: Our framework

96 Nov 30, 2022
SmallInitEmb - LayerNorm(SmallInit(Embedding)) in a Transformer to improve convergence

SmallInitEmb LayerNorm(SmallInit(Embedding)) in a Transformer I find that when t

PENG Bo 11 Dec 25, 2022
Sample and Computation Redistribution for Efficient Face Detection

Introduction SCRFD is an efficient high accuracy face detection approach which initially described in Arxiv. Performance Precision, flops and infer ti

Sajjad Aemmi 13 Mar 05, 2022
Multiview Dataset Toolkit

Multiview Dataset Toolkit Using multi-view cameras is a natural way to obtain a complete point cloud. However, there is to date only one multi-view 3D

11 Dec 22, 2022