FasterAI: A library to make smaller and faster models with FastAI.

Related tags

Deep Learningcompressionpytorchpruningfastaiknowledge-distillation
Overview

Fasterai

header

fasterai is a library created to make neural network smaller and faster. It essentially relies on common compression techniques for networks such as pruning, knowledge distillation, ...

Project Documentation

Visit Read The Docs Project Page or read following README to know more about using Fasterai

Available Methods

1. Pruning

Make your model sparse (i.e. prune it) according to a:

  • Sparsity: the amount of weights that will be replaced by 0
  • Granularity: the granularity at which you operate the pruning (removing weights, vectors, kernels, filters)
  • Method: prune either each layer independantly (local pruning) or the whole model (global pruning)
  • Criteria: the criteria used to select the weights to remove (magnitude, movement, ...)
  • Schedule: which schedule you want to use for pruning (one shot, iterative, gradual, ...)

2. Knowledge Distillation

Distill the knowledge acquired by a big model into a smaller one.

3. Lottery Ticket Hypothesis

Find the winning ticket in you network, i.e. the initial subnetwork able to attain at least similar performances than the network as a whole.

Quick Start

1. Create your model with fastai

learn = cnn_learner(dls, model)

2. Get you Fasterai Callback

sp_cb=SparsifyCallback(end_sparsity, granularity, method, criteria, sched_func)

3. Train you model to make it sparse !

learn.fit_one_cycle(n_epochs, cbs=sp_cb)

More about other methods in the tutorials section

Installation

pip install git+https://github.com/nathanhubens/fasterai.git

or

pip install fasterai

Citing

@misc{Hubens:2020,
  Author = {Nathan Hubens},
  Title = {Fasterai},
  Year = {2020},
  Publisher = {GitHub},
  Journal = {GitHub repository},
  Howpublished = {\url{https://github.com/nathanhubens/fasterai}}
}

footer

You might also like...
shufflev2-yolov5：lighter, faster and easier to deploy
shufflev2-yolov5：lighter, faster and easier to deploy

shufflev2-yolov5: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~

pogg 1.5k Jan 5, 2023
LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.
LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image.

This project is based on ultralytics/yolov3. LF-YOLO (Lighter and Faster YOLO) is used to detect defect of X-ray weld image. Download $ git clone http

null 26 Dec 13, 2022
A Python package for faster, safer, and simpler ML processes

Bender 🤖 A Python package for faster, safer, and simpler ML processes. Why use bender? Bender will make your machine learning processes, faster, safe

Otovo 6 Dec 13, 2022
Much faster than SORT(Simple Online and Realtime Tracking), a little worse than SORT

QSORT QSORT(Quick + Simple Online and Realtime Tracking) is a simple online and realtime tracking algorithm for 2D multiple object tracking in video s

Yonghye Kwon 8 Jul 27, 2022
This project is based on RIFE and aims to make RIFE more practical for users by adding various features and design new models
This project is based on RIFE and aims to make RIFE more practical for users by adding various features and design new models

This project is based on RIFE and aims to make RIFE more practical for users by adding various features and design new models. Because improving the PSNR index is not compatible with subjective effects, we hope this part of work and our academic research are independent of each other.

hzwer 190 Jan 8, 2023
LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference
LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference

LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference This repository contains PyTorch evaluation code, training code and pretrained

Facebook Research 504 Jan 2, 2023
Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression.

Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me

Google Research 27 Dec 12, 2022
PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM
PyTorch implementation of the Quasi-Recurrent Neural Network - up to 16 times faster than NVIDIA's cuDNN LSTM

Quasi-Recurrent Neural Network (QRNN) for PyTorch Updated to support multi-GPU environments via DataParallel - see the the multigpu_dataparallel.py ex

Salesforce 1.3k Dec 28, 2022
A pytorch implementation of faster RCNN detection framework (Use detectron2, it's a masterpiece)
A pytorch implementation of faster RCNN detection framework (Use detectron2, it's a masterpiece)

Notice(2019.11.2) This repo was built back two years ago when there were no pytorch detection implementation that can achieve reasonable performance.

Ruotian(RT) Luo 1.8k Jan 1, 2023
Releases(v0.1.9)
Owner
Nathan Hubens
Nathan Hubens
GitHub Repository https://nathanhubens.github.io/fasterai/
View model summaries in PyTorch!

torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor

Tyler Yep 1.5k Jan 05, 2023
GitHub repository for "Improving Video Generation for Multi-functional Applications"

Improving Video Generation for Multi-functional Applications GitHub repository for "Improving Video Generation for Multi-functional Applications" Pape

Bernhard Kratzwald 328 Dec 07, 2022
Decision Transformer: A brand new Offline RL Pattern

DecisionTransformer_StepbyStep Intro Decision Transformer: A brand new Offline RL Pattern. 这是关于NeurIPS 2021 热门论文Decision Transformer的复现。 👍 原文地址: Deci

Irving 14 Nov 22, 2022
Black box hyperparameter optimization made easy.

BBopt BBopt aims to provide the easiest hyperparameter optimization you'll ever do. Think of BBopt like Keras (back when Theano was still a thing) for

Evan Hubinger 70 Nov 03, 2022
DvD-TD3: Diversity via Determinants for TD3 version

DvD-TD3: Diversity via Determinants for TD3 version The implementation of paper Effective Diversity in Population Based Reinforcement Learning. Instal

3 Feb 11, 2022
TensorFlow ROCm port

Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a

ROCm Software Platform 622 Jan 09, 2023
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style [NeurIPS 2021] Official code to reproduce the results and data p

Yash Sharma 27 Sep 19, 2022
Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal"

Patch-wise Adversarial Removal Implementation of paper "Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal

4 Oct 12, 2022
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

Imbalanced Dataset Sampler Introduction In many machine learning applications, we often come across datasets where some types of data may be seen more

Ming 2k Jan 08, 2023
Source codes for "Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs"

Structure-Aware-BART This repo contains codes for the following paper: Jiaao Chen, Diyi Yang:Structure-Aware Abstractive Conversation Summarization vi

GT-SALT 56 Dec 08, 2022
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking We revisit and address issues with Oxford 5k and Paris 6k image retrieval benchm

Filip Radenovic 188 Dec 17, 2022
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework

OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework Introduction OpenFed is a foundational library for federated learning

25 Dec 12, 2022
DAN: Unfolding the Alternating Optimization for Blind Super Resolution

DAN-Basd-on-Openmmlab DAN: Unfolding the Alternating Optimization for Blind Super Resolution We reproduce DAN via mmediting based on open-sourced code

AlexZou 72 Dec 13, 2022
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

TorchCAM: class activation explorer Simple way to leverage the class-specific activation of convolutional layers in PyTorch. Quick Tour Setting your C

F-G Fernandez 1.2k Dec 29, 2022
Official Pytorch Implementation of Unsupervised Image Denoising with Frequency Domain Knowledge

Unsupervised Image Denoising with Frequency Domain Knowledge (BMVC 2021 Oral) : Official Project Page This repository provides the official PyTorch im

Donggon Jang 12 Sep 26, 2022
Code accompanying "Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity," accepted to IEEE SSCI ICES 2021

Evolving-spiking-neuron-cellular-automata-and-networks-to-emulate-in-vitro-neuronal-activity Code accompanying "Evolving spiking neuron cellular autom

SOCRATES: Self-Organizing Computational substRATES 2 Dec 02, 2022
Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators..

ARAPReg Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators.. Installation The cod

Bo Sun 132 Nov 28, 2022
mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms.

mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms. It provides easily interchangeable modeling and planning components, and a set of utility function

Facebook Research 724 Jan 04, 2023
This repo contains research materials released by members of the Google Brain team in Tokyo.

Brain Tokyo Workshop 🧠 🗼 This repo contains research materials released by members of the Google Brain team in Tokyo. Past Projects Weight Agnostic

Google 1.2k Jan 02, 2023
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu

Asaf 3 Dec 27, 2022