IOT: Instance-wise Layer Reordering for Transformer Structures

Related tags

Deep LearningIOT
Overview

Introduction

This repository contains the code for Instance-wise Ordered Transformer (IOT), which is introduced in the ICLR2021 paper IOT: Instance-wise Layer Reordering for Transformer Structures.

If you find this work helpful in your research, please cite as:

@inproceedings{
zhu2021iot,
title={{\{}IOT{\}}: Instance-wise Layer Reordering for Transformer Structures},
author={Jinhua Zhu and Lijun Wu and Yingce Xia and Shufang Xie and Tao Qin and Wengang Zhou and Houqiang Li and Tie-Yan Liu},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=ipUPfYxWZvM}
}

Requirements and Installation

  • PyTorch version == 1.0.0
  • Python version >= 3.5

To install IOT:

git clone https://github.com/instance-wise-ordered-transformer/IOT
cd IOT
pip install --editable .

Getting Started

Take IWSLT14 De-En translation as an example.

Data Preprocessing

cd examples/translation/
bash prepare-iwslt14.sh
cd ../..

TEXT=examples/translation/iwslt14.tokenized.de-en
python preprocess.py --source-lang de --target-lang en \
    --trainpref $TEXT/train --validpref $TEXT/valid --testpref $TEXT/test \
    --destdir data-bin/iwslt14.tokenized.de-en --joined-dictionary

Training

Encoder order is set to be the default one without reordering (ENCODER_MAX_ORDER=1), since the paper finds that both reordering encoder and decoder is not good as reordering decoder only.

#!/bin/bash
export CUDA_VISIBLE_DEVICES=${1:-0}
nvidia-smi

ENCODER_MAX_ORDER=1
DECODER_MAX_ORDER=3
DECODER_ORDER="0 3 5"
DIVERSITY=0.1
GS_MAX=20
GS_MIN=2
GS_R=0
GS_UF=5000
KL=0.01
CLAMPVAL=0.05

DECODER_ORDER_NAME=`echo $DECODER_ORDER | sed 's/ //g'`
SAVE_DIR=checkpoints/dec_${DECODER_MAX_ORDER}_order_${DECODER_ORDER_NAME}_div_${DIVERSITY}_gsmax_${GS_MAX}_gsmin_${GS_MIN}_gsr_${GS_R}_gsuf_${GS_UF}_kl_${KL}_clampval_${CLAMPVAL}
mkdir -p ${SAVE_DIR}

python -u train.py data-bin/iwslt14.tokenized.de-en -a transformer_iwslt_de_en \
--optimizer adam --lr 0.0005 -s de -t en --label-smoothing 0.1 --dropout 0.3 --max-tokens 4000 \
--min-lr 1e-09 --lr-scheduler inverse_sqrt --weight-decay 0.0001 --criterion label_smoothed_cross_entropy \
--max-update 100000 --warmup-updates 4000 --warmup-init-lr 1e-07 --adam-betas '(0.9,0.98)' \
--save-dir $SAVE_DIR --share-all-embeddings  --gs-clamp --decoder-orders $DECODER_ORDER  \
--encoder-max-order $ENCODER_MAX_ORDER  --decoder-max-order $DECODER_MAX_ORDER  --diversity $DIVERSITY \
--gumbel-softmax-max $GS_MAX  --gumbel-softmax-min $GS_MIN --gumbel-softmax-tau-r $GS_R  --gumbel-softmax-update-freq $GS_UF \
--kl $KL --clamp-value $CLAMPVAL | tee -a ${SAVE_DIR}/train.log

Evaluation

#!/bin/bash
set -x
set -e

pip install -e . --user
export CUDA_VISIBLE_DEVICES=${1:-0}
nvidia-smi

ENCODER_MAX_ORDER=1
DECODER_MAX_ORDER=3
DECODER_ORDER="0 3 5"
DIVERSITY=0.1
GS_MAX=20
GS_MIN=2
GS_R=0
GS_UF=5000
KL=0.01
CLAMPVAL=0.05

DECODER_ORDER_NAME=`echo $DECODER_ORDER | sed 's/ //g'`
SAVE_DIR=checkpoints/dec_${DECODER_MAX_ORDER}_order_${DECODER_ORDER_NAME}_div_${DIVERSITY}_gsmax_${GS_MAX}_gsmin_${GS_MIN}_gsr_${GS_R}_gsuf_${GS_UF}_kl_${KL}_clampval_${CLAMPVAL}

python generate.py data-bin/iwslt14.tokenized.de-en \
  --path $SAVE_DIR/checkpint_best.pt \
  --batch-size 128 --beam 5 --remove-bpe --quiet --num-ckts $DECODER_MAX_ORDER 
pyspark🍒🥭 is delicious,just eat it!😋😋

如何用10天吃掉pyspark? 🔥 🔥 《10天吃掉那只pyspark》 🚀

lyhue1991 578 Dec 30, 2022
1st ranked 'driver careless behavior detection' for AI Online Competition 2021, hosted by MSIT Korea.

2021AICompetition-03 본 repo 는 mAy-I Inc. 팀으로 참가한 2021 인공지능 온라인 경진대회 중 [이미지] 운전 사고 예방을 위한 운전자 부주의 행동 검출 모델] 태스크 수행을 위한 레포지토리입니다. mAy-I 는 과학기술정보통신부가 주최하

Junhyuk Park 9 Dec 01, 2022
TC-GNN with Pytorch integration

TC-GNN (Running Sparse GNN on Dense Tensor Core on Ampere GPU) Cite this project and paper. @inproceedings{TC-GNN, title={TC-GNN: Accelerating Spars

YUKE WANG 19 Dec 01, 2022
PoseViz – Multi-person, multi-camera 3D human pose visualization tool built using Mayavi.

PoseViz – 3D Human Pose Visualizer Multi-person, multi-camera 3D human pose visualization tool built using Mayavi. As used in MeTRAbs visualizations.

István Sárándi 79 Dec 30, 2022
Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model

Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model. Designed sample dashboard with insights and recommendation for

Yash 2 Apr 07, 2022
DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene.

DirectVoxGO reconstructs a scene representation from a set of calibrated images capturing the scene. We achieve NeRF-comparable novel-view synthesis quality with super-fast convergence.

sunset 709 Dec 31, 2022
Dynamic Token Normalization Improves Vision Transformers

Dynamic Token Normalization Improves Vision Transformers This is the PyTorch implementation of the paper Dynamic Token Normalization Improves Vision T

Wenqi Shao 20 Oct 09, 2022
Pytorch implementation of "M-LSD: Towards Light-weight and Real-time Line Segment Detection"

M-LSD: Towards Light-weight and Real-time Line Segment Detection Pytorch implementation of "M-LSD: Towards Light-weight and Real-time Line Segment Det

123 Jan 04, 2023
The second project in Python course on FCC

Assignment Write a function named add_time that takes in two required parameters and one optional parameter: a start time in the 12-hour clock format

Denise T 1 Dec 13, 2021
A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.

OpenCDA OpenCDA is a SIMULATION tool integrated with a prototype cooperative driving automation (CDA; see SAE J3216) pipeline as well as regular autom

UCLA Mobility Lab 726 Dec 29, 2022
NAACL2021 - COIL Contextualized Lexical Retriever

COIL Repo for our NAACL paper, COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List. The code covers learning

Luyu Gao 108 Dec 31, 2022
Vision Deep-Learning using Tensorflow, Keras.

Welcome! I am a computer vision deep learning developer working in Korea. This is my blog, and you can see everything I've studied here. https://www.n

kimminjun 6 Dec 14, 2022
Making Structure-from-Motion (COLMAP) more robust to symmetries and duplicated structures

SfM disambiguation with COLMAP About Structure-from-Motion generally fails when the scene exhibits symmetries and duplicated structures. In this repos

Computer Vision and Geometry Lab 193 Dec 26, 2022
EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation (CVPR'21)

EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation (CVPR'21) Citation If y

addisonwang 18 Nov 11, 2022
Omnidirectional camera calibration in python

Omnidirectional Camera Calibration Key features pure python initial solution based on A Toolbox for Easily Calibrating Omnidirectional Cameras (Davide

Thomas Pönitz 12 Nov 22, 2022
Time Delayed NN implemented in pytorch

Pytorch Time Delayed NN Time Delayed NN implemented in PyTorch. Usage kernels = [(1, 25), (2, 50), (3, 75), (4, 100), (5, 125), (6, 150)] tdnn = TDNN

Daniil Gavrilov 79 Aug 04, 2022
LaBERT - A length-controllable and non-autoregressive image captioning model.

Length-Controllable Image Captioning (ECCV2020) This repo provides the implemetation of the paper Length-Controllable Image Captioning. Install conda

bearcatt 53 Nov 13, 2022
A foreign language learning aid using a neural network to predict probability of translating foreign words

Langy Langy is a reading-focused foreign language learning aid orientated towards young children. Reading is an activity that every child knows. It is

Shona Lowden 6 Nov 17, 2021
[Link]deep_portfolo - Use Reforcemet earg ad Supervsed learg to Optmze portfolo allocato []

rl_portfolio This Repository uses Reinforcement Learning and Supervised learning to Optimize portfolio allocation. The goal is to make profitable agen

Deepender Singla 165 Dec 02, 2022
A best practice for tensorflow project template architecture.

A best practice for tensorflow project template architecture.

Mahmoud Gamal Salem 3.6k Dec 22, 2022