Official code repository of the paper Linear Transformers Are Secretly Fast Weight Programmers.

Overview

Linear Transformers Are Secretly Fast Weight Programmers

This repository contains the code accompanying the paper Linear Transformers Are Secretly Fast Weight Programmers which is published at ICML'21. It also contains the logs of all synthetic experiments.

Synthetic Experiments

Requirements

$ cat req.txt 
jupyter==1.0.0
pandas==1.0.1
seaborn==0.10.0
torch==1.6.0
matplotlib==3.1.3
numpy==1.17.2
pip3 install -r req.txt

Rerun Experiments

Logs are provided in the synthetic/logs folder. The files in that folder are a result of running the following commands:

Setting 1 (capacity):

python3 main.py --begin=20 --end=600 --step=20 --attn_name=softmax --update_rule=sum
python3 main.py --begin=20 --end=600 --step=20 --attn_name=linear --update_rule=sum
python3 main.py --begin=20 --end=600 --step=20 --attn_name=dpfp --attn_arg=1 --update_rule=sum
python3 main.py --begin=20 --end=600 --step=20 --attn_name=dpfp --attn_arg=2 --update_rule=sum

python3 main.py --begin=20 --end=600 --step=20 --attn_name=dpfp --attn_arg=3 --update_rule=sum
python3 main.py --begin=20 --end=600 --step=20 --attn_name=favor --attn_arg=64 --update_rule=sum
python3 main.py --begin=20 --end=600 --step=20 --attn_name=favor --attn_arg=128 --update_rule=sum
python3 main.py --begin=20 --end=600 --step=20 --attn_name=favor --attn_arg=512 --update_rule=sum

Setting 2 (update rule):

python3 main.py --begin=20 --end=200 --step=20 --attn_name=dpfp --attn_arg=1 --update_rule=sum --replace
python3 main.py --begin=20 --end=200 --step=20 --attn_name=dpfp --attn_arg=1 --update_rule=ours --replace
python3 main.py --begin=20 --end=200 --step=20 --attn_name=tanh --update_rule=fwm --replace
python3 main.py --begin=20 --end=200 --step=20 --attn_name=dpfp --attn_arg=1 --update_rule=fwm --replace

python3 main.py --begin=20 --end=200 --step=20 --attn_name=dpfp --attn_arg=2 --update_rule=ours --replace
python3 main.py --begin=20 --end=200 --step=20 --attn_name=linear --update_rule=ours --replace
python3 main.py --begin=20 --end=200 --step=20 --attn_name=favor --attn_arg=64 --update_rule=ours --replace
python3 main.py --begin=20 --end=200 --step=20 --attn_name=favor --attn_arg=128 --update_rule=ours --replace

Generate figures from the logs using the following notebooks:

synthetic/setting1_generate_figure.ipynb
synthetic/setting2_generate_figure.ipynb

Language Modelling & Machine Translation

The toolkit and scripts for language modeling experiments can be found at IDSIA/lmtool-fwms.

For machine translation experiments, we ported the different attention functions implemented in the language modeling toolkit to the multi-head attention implementation in FAIRSEQ.

Citation

@inproceedings{schlag2021linear,
      title={Linear Transformers Are Secretly Fast Weight Programmers}, 
      author={Imanol Schlag and Kazuki Irie and J\"urgen Schmidhuber},
      booktitle={Proc. Int. Conf. on Machine Learning (ICML)},
      address = {Virtual only},
      month = jul,
      year={2021}
}
Owner
Imanol Schlag
Imanol Schlag
Speach Recognitions

easy_meeting Добро пожаловать в интерфейс сервиса автопротоколирования совещаний Easy Meeting. Website - http://cf5c-62-192-251-83.ngrok.io/ Принципиа

Maksim 3 Feb 18, 2022
TweebankNLP - Pre-trained Tweet NLP Pipeline (NER, tokenization, lemmatization, POS tagging, dependency parsing) + Models + Tweebank-NER

TweebankNLP This repo contains the new Tweebank-NER dataset and off-the-shelf Twitter-Stanza pipeline for state-of-the-art Tweet NLP, as described in

Laboratory for Social Machines 84 Dec 20, 2022
Deal or No Deal? End-to-End Learning for Negotiation Dialogues

Introduction This is a PyTorch implementation of the following research papers: (1) Hierarchical Text Generation and Planning for Strategic Dialogue (

Facebook Research 1.4k Dec 29, 2022
texlive expressions for documents

tex2nix Generate Texlive environment containing all dependencies for your document rather than downloading gigabytes of texlive packages. Installation

Jörg Thalheim 70 Dec 26, 2022
OpenAI CLIP text encoders for multiple languages!

Multilingual-CLIP OpenAI CLIP text encoders for any language Colab Notebook · Pre-trained Models · Report Bug Overview OpenAI recently released the pa

Fredrik Carlsson 481 Dec 30, 2022
PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

Ryan Spring 114 Nov 04, 2022
QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries

Moment-DETR QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries Jie Lei, Tamara L. Berg, Mohit Bansal For dataset de

Jie Lei 雷杰 133 Dec 22, 2022
HAIS_2GNN: 3D Visual Grounding with Graph and Attention

HAIS_2GNN: 3D Visual Grounding with Graph and Attention This repository is for the HAIS_2GNN research project. Tao Gu, Yue Chen Introduction The motiv

Yue Chen 1 Nov 26, 2022
Include MelGAN, HifiGAN and Multiband-HifiGAN, maybe NHV in the future.

Fast (GAN Based Neural) Vocoder Chinese README Todo Submit demo Support NHV Discription Include MelGAN, HifiGAN and Multiband-HifiGAN, maybe include N

Zhengxi Liu (刘正曦) 134 Dec 16, 2022
Codename generator using WordNet parts of speech database

codenames Codename generator using WordNet parts of speech database References: https://possiblywrong.wordpress.com/2021/09/13/code-name-generator/ ht

possiblywrong 27 Oct 30, 2022
초성 해석기 based on ko-BART

초성 해석기 개요 한국어 초성만으로 이루어진 문장을 입력하면, 완성된 문장을 예측하는 초성 해석기입니다. 초성: ㄴㄴ ㄴㄹ ㅈㅇㅎ 예측 문장: 나는 너를 좋아해 모델 모델은 SKT-AI에서 공개한 Ko-BART를 이용합니다. 데이터 문장 단위로 이루어진 아무 코퍼스나

Dawoon Jung 29 Oct 28, 2022
[Preprint] Escaping the Big Data Paradigm with Compact Transformers, 2021

Compact Transformers Preprint Link: Escaping the Big Data Paradigm with Compact Transformers By Ali Hassani[1]*, Steven Walton[1]*, Nikhil Shah[1], Ab

SHI Lab 367 Dec 31, 2022
The tool to make NLP datasets ready to use

chazutsu photo from Kaikado, traditional Japanese chazutsu maker chazutsu is the dataset downloader for NLP. import chazutsu r = chazutsu.data

chakki 243 Dec 29, 2022
A Python 3.6+ package to run .many files, where many programs written in many languages may exist in one file.

RunMany Intro | Installation | VSCode Extension | Usage | Syntax | Settings | About A tool to run many programs written in many languages from one fil

6 May 22, 2022
Toward Model Interpretability in Medical NLP

Toward Model Interpretability in Medical NLP LING380: Topics in Computational Linguistics Final Project James Cross ( 1 Mar 04, 2022

This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini!

About CappuccinoJs This converter will create the exact measure for your cappuccino recipe from the grandiose Rafaella Ballerini! Este conversor criar

Arthur Ottoni Ribeiro 48 Nov 15, 2022
UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language

UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language This repository contains UA-GEC data and an accompanying Python lib

Grammarly 227 Jan 02, 2023
Russian GPT3 models.

Russian GPT-3 models (ruGPT3XL, ruGPT3Large, ruGPT3Medium, ruGPT3Small) trained with 2048 sequence length with sparse and dense attention blocks. We also provide Russian GPT-2 large model (ruGPT2Larg

Sberbank AI 1.6k Jan 05, 2023
Augmenty is an augmentation library based on spaCy for augmenting texts.

Augmenty: The cherry on top of your NLP pipeline Augmenty is an augmentation library based on spaCy for augmenting texts. Besides a wide array of high

Kenneth Enevoldsen 124 Dec 29, 2022
Protein Language Model

ProteinLM We pretrain protein language model based on Megatron-LM framework, and then evaluate the pretrained model results on TAPE (Tasks Assessing P

THUDM 77 Dec 27, 2022