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/
Deep learning algorithms for muon momentum estimation in the CMS Trigger System

Deep learning algorithms for muon momentum estimation in the CMS Trigger System The Compact Muon Solenoid (CMS) is a general-purpose detector at the L

anuragB 2 Oct 06, 2021
Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.

Hera Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser. Setting up Step 1. Plant the spy Install the package pip

Keplr 495 Dec 10, 2022
This program was designed to detect whether someone is wearing a facemask through a live video stream.

This program was designed to detect whether someone is wearing a facemask through a live video stream. A custom lightweight CNN trained with TensorFlow on a public dataset provided by Kaggle is used

0 Apr 02, 2022
History Aware Multimodal Transformer for Vision-and-Language Navigation

History Aware Multimodal Transformer for Vision-and-Language Navigation This repository is the official implementation of History Aware Multimodal Tra

Shizhe Chen 46 Nov 23, 2022
Parsing, analyzing, and comparing source code across many languages

Semantic semantic is a Haskell library and command line tool for parsing, analyzing, and comparing source code. In a hurry? Check out our documentatio

GitHub 8.6k Dec 28, 2022
Reinforcement learning models in ViZDoom environment

DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p

Andrey Kolishchak 126 Dec 09, 2022
Weakly Supervised Segmentation by Tensorflow.

Weakly Supervised Segmentation by Tensorflow. Implements semantic segmentation in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

CHENG-YOU LU 52 Dec 27, 2022
REGTR: End-to-end Point Cloud Correspondences with Transformers

REGTR: End-to-end Point Cloud Correspondences with Transformers This repository contains the source code for REGTR. REGTR utilizes multiple transforme

Zi Jian Yew 108 Dec 17, 2022
This repo implements a 3D segmentation task for an airport baggage dataset.

3D CT Scan Segmentation With Occupancy Network This repo implements a 3D superresolution segmentation task for an airport baggage dataset. Our final p

Christoph Reich 2 Mar 28, 2022
A large-image collection explorer and fast classification tool

IMAX: Interactive Multi-image Analysis eXplorer This is an interactive tool for visualize and classify multiple images at a time. It written in Python

Matias Carrasco Kind 23 Dec 16, 2022
Cross-modal Deep Face Normals with Deactivable Skip Connections

Cross-modal Deep Face Normals with Deactivable Skip Connections Victoria Fernández Abrevaya*, Adnane Boukhayma*, Philip H. S. Torr, Edmond Boyer (*Equ

72 Nov 27, 2022
AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data

AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data [WIP] Unofficial Pytorch implementation of AdaSpeech 2. Requirements : All code written i

Rishikesh (ऋषिकेश) 63 Dec 28, 2022
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

Yuki M. Asano 249 Dec 22, 2022
Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks

MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks This is the code for the paper: MentorNet: Learning Data-Driven Curriculum fo

Google 302 Dec 23, 2022
sssegmentation is a general framework for our research on strongly supervised semantic segmentation.

sssegmentation is a general framework for our research on strongly supervised semantic segmentation.

445 Jan 02, 2023
Potato Disease Classification - Training, Rest APIs, and Frontend to test.

Potato Disease Classification Setup for Python: Install Python (Setup instructions) Install Python packages pip3 install -r training/requirements.txt

codebasics 95 Dec 21, 2022
ICON: Implicit Clothed humans Obtained from Normals (CVPR 2022)

ICON: Implicit Clothed humans Obtained from Normals Yuliang Xiu · Jinlong Yang · Dimitrios Tzionas · Michael J. Black CVPR 2022 News 🚩 [2022/04/26] H

Yuliang Xiu 1.1k Jan 04, 2023
Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech

Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech This repository is the official implementation of "Meta-TTS: Meta-Learning for Few

Sung-Feng Huang 128 Dec 25, 2022
code for Grapadora research paper experimentation

Road feature embedding selection method Code for research paper experimentation Abstract Traffic forecasting models rely on data that needs to be sens

Eric López Manibardo 0 May 26, 2022
PyJokes - Joking around with Python library pyjokes

Hi, it's Muhaimin again 👋 This is something unorthodox but cool. Don't forget t

Muhaimin A. Salay Kanton 1 Feb 02, 2022