Code to reprudece NeurIPS paper: Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks

Overview

Accelerated Sparse Neural Training: A Provable and Efficient Method to FindN:M Transposable Masks

Recently, researchers proposed pruning deep neural network weights (DNNs) using an $N:M$ fine-grained block sparsity mask. In this mask, for each block of M weights, we have at least N zeros. In contrast to unstructured sparsity, N:M fine-grained block sparsity allows acceleration in actual modern hardware. Previously suggested solutions enabled DNN acceleration at the inference phase. To also allow such acceleration in the training phase, we suggest a novel transposable-fine-grained sparsity mask where the same mask can be used for both forward and backward passes. Our transposable mask ensures that both the weight matrix and its transpose follow the same sparsity pattern; thus the matrix multiplication required for passing the error backward can also be accelerated. We discuss the transposable constraint and devise a new measure for mask constraints, called mask-diversity (MD), which correlates with their expected accuracy. Lastly, we formulate the problem of finding the optimal transposable mask as a minimum-cost-flow problem and suggest a fast linear approximation that can be used when the masks dynamically change while training. Our experiments suggest 2x speed-up with no accuracy degradation over vision and language models. A reference implementation is available in the supplementary material.

Reproducing the results

This repository is partially based on convNet.pytorch repo. please ensure that you are using pytorch 1.7+. Reproducing AdaPrune results

cd AdaPrune
sh scripts/adaprune_dense_bnt.sh
sh scripts/adaprune_sparse.sh

Reproducing static NM-transposable starting from dense pre-trained model:

cd static_TNM
sh scripts/prune_pretrained_R50.sh

Reproducing dynamic NM-transposable from scratch:

cd dynamic_TNM
sh scripts/clone_and_copy.sh
sh scripts/run_R18.sh
sh scripts/run_R50.sh
Owner
itay hubara
itay hubara
Perform sentiment analysis on textual data that people generally post on websites like social networks and movie review sites.

Sentiment Analyzer The goal of this project is to perform sentiment analysis on textual data that people generally post on websites like social networ

Madhusudan.C.S 53 Mar 01, 2022
Flaxformer: transformer architectures in JAX/Flax

Flaxformer: transformer architectures in JAX/Flax Flaxformer is a transformer library for primarily NLP and multimodal research at Google. It is used

Google 114 Dec 29, 2022
🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.

pySBD: Python Sentence Boundary Disambiguation (SBD) pySBD - python Sentence Boundary Disambiguation (SBD) - is a rule-based sentence boundary detecti

Nipun Sadvilkar 549 Jan 06, 2023
A Lightweight NLP Data Loader for All Deep Learning Frameworks in Python

LineFlow: Framework-Agnostic NLP Data Loader in Python LineFlow is a simple text dataset loader for NLP deep learning tasks. LineFlow was designed to

TofuNLP 177 Jan 04, 2023
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
DLO8012: Natural Language Processing & CSL804: Computational Lab - II

NATURAL-LANGUAGE-PROCESSING-AND-COMPUTATIONAL-LAB-II DLO8012: NLP & CSL804: CL-II [SEMESTER VIII] Syllabus NLP - Reference Books THE WALL MEGA SATISH

AMEY THAKUR 7 Apr 28, 2022
PyTorch implementation of NATSpeech: A Non-Autoregressive Text-to-Speech Framework

A Non-Autoregressive Text-to-Speech (NAR-TTS) framework, including official PyTorch implementation of PortaSpeech (NeurIPS 2021) and DiffSpeech (AAAI 2022)

760 Jan 03, 2023
A fast hierarchical dimensionality reduction algorithm.

h-NNE: Hierarchical Nearest Neighbor Embedding A fast hierarchical dimensionality reduction algorithm. h-NNE is a general purpose dimensionality reduc

Marios Koulakis 35 Dec 12, 2022
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning

GenSen Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning Sandeep Subramanian, Adam Trischler, Yoshua B

Maluuba Inc. 309 Oct 19, 2022
Module for automatic summarization of text documents and HTML pages.

Automatic text summarizer Simple library and command line utility for extracting summary from HTML pages or plain texts. The package also contains sim

Mišo Belica 3k Jan 08, 2023
This project uses word frequency and Term Frequency-Inverse Document Frequency to summarize a text.

Text Summarizer This project uses word frequency and Term Frequency-Inverse Document Frequency to summarize a text. Team Members This mini-project was

1 Nov 16, 2021
Transcribing audio files using Hugging Face's implementation of Wav2Vec2 + "chain-linking" NLP tasks to combine speech-to-text with downstream tasks like translation and summarisation.

PART 2: CHAIN LINKING AUDIO-TO-TEXT NLP TASKS 2A: TRANSCRIBE-TRANSLATE-SENTIMENT-ANALYSIS In notebook3.0, I demo a simple workflow to: transcribe a lo

Chua Chin Hon 30 Jul 13, 2022
RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network trained to work with different pairs (images, texts).

RuCLIPtiny Zero-shot image classification model for Russian language RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network

Shahmatov Arseniy 26 Sep 20, 2022
Code for "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022.

README Code for Two-stage Identifier: "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022. For details of the model a

Yongliang Shen 45 Nov 29, 2022
This repository is home to the Optimus data transformation plugins for various data processing needs.

Transformers Optimus's transformation plugins are implementations of Task and Hook interfaces that allows execution of arbitrary jobs in optimus. To i

Open Data Platform 37 Dec 14, 2022
Uses Google's gTTS module to easily create robo text readin' on command.

Tool to convert text to speech, creating files for later use. TTRS uses Google's gTTS module to easily create robo text readin' on command.

0 Jun 20, 2021
Simple python code to fix your combo list by removing any text after a separator or removing duplicate combos

Combo List Fixer A simple python code to fix your combo list by removing any text after a separator or removing duplicate combos Removing any text aft

Hamidreza Dehghan 3 Dec 05, 2022
Code for text augmentation method leveraging large-scale language models

HyperMix Code for our paper GPT3Mix and conducting classification experiments using GPT-3 prompt-based data augmentation. Getting Started Installing P

NAVER AI 47 Dec 20, 2022
code for modular summarization work published in ACL2021 by Krishna et al

This repository contains the code for running modular summarization pipelines as described in the publication Krishna K, Khosla K, Bigham J, Lipton ZC

Approximately Correct Machine Intelligence (ACMI) Lab 21 Nov 24, 2022
自然言語で書かれた時間情報表現を抽出/規格化するルールベースの解析器

ja-timex 自然言語で書かれた時間情報表現を抽出/規格化するルールベースの解析器 概要 ja-timex は、現代日本語で書かれた自然文に含まれる時間情報表現を抽出しTIMEX3と呼ばれるアノテーション仕様に変換することで、プログラムが利用できるような形に規格化するルールベースの解析器です。

Yuki Okuda 116 Nov 09, 2022