BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构

Overview

BaseCls

Documentation Status CI codecov

BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构。

文档地址:https://basecls.readthedocs.io

安装

安装环境

BaseCls 需要 Python >= 3.6。

BaseCls 依赖 MegEngine >= 1.6.0。

通过包管理器安装

通过 pip 包管理器安装 BaseCls 的命令如下:

pip3 install basecls --user

默认不会安装包括 MegEngine 在内的部分依赖,可以通过以下命令进行完整安装:

pip3 install basecls[all] --user

对于 conda 用户, 可以选择通过在环境中先安装 pip,再按照上述方式进行 BaseCls 的安装。

通过源代码安装

为保证模型性能的可追溯性,避免实验碎片化,建议通过包管理器安装。如果包管理器安装的方式无法满足你的需求,则可以尝试自行通过源码安装。

安装依赖

pip3 install -r requirements.txt --user

安装 BaseCls

python3 setup.py develop --user

验证安装

在 Python 中导入 BaseCls 验证安装成功并查看安装版本:

import basecls
print(basecls.__version__)

开发者须知

开发环境

# 安装依赖
pip3 install -r requirements-dev.txt --user

# 配置 pre-commit
pre-commit install

开发流程

提交者需补充相应修改的单元测试。

# (外部开发者)fork repo,或(内部开发者)建立 new-feature 分支
git checkout -b new-feature

# 进行修改

# 代码风格检查与格式化
make lint
make format

# 单元测试与覆盖率检查
make unittest

# 提交修改
git commit

# 提交MR/PR
Owner
MEGVII Research
Power Human with AI. 持续创新拓展认知边界 非凡科技成就产品价值
MEGVII Research
PyTorch implementation of 'Gen-LaneNet: a generalized and scalable approach for 3D lane detection'

(pytorch) Gen-LaneNet: a generalized and scalable approach for 3D lane detection Introduction This is a pytorch implementation of Gen-LaneNet, which p

Yuliang Guo 233 Jan 06, 2023
Le dataset des images du projet d'IA de 2021

face-mask-dataset-ilc-2021 Le dataset des images du projet d'IA de 2021, Indiquez vos id git dans la issue pour les droits TL;DR: Choisir 200 images J

7 Nov 15, 2021
This project provides the proof of the uniqueness of the equilibrium and the global asymptotic stability.

Delayed-cellular-neural-network This project provides the proof of the uniqueness of the equilibrium and the global asymptotic stability. There is als

4 Apr 28, 2022
Galaxy images labelled by morphology (shape). Aimed at ML development and teaching

Galaxy images labelled by morphology (shape). Aimed at ML debugging and teaching.

Mike Walmsley 14 Nov 28, 2022
Implementation for our AAAI2021 paper (Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction).

SSAN Introduction This is the pytorch implementation of the SSAN model (see our AAAI2021 paper: Entity Structure Within and Throughout: Modeling Menti

benfeng 69 Nov 15, 2022
Source code for the Paper: CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints}

CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints Installation Run pipenv install (at your own risk with --skip-lo

Autonomous Learning Group 65 Dec 27, 2022
Official code repository for the publication "Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons"

Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons This repository contains the code to repr

Computational Neuroscience, University of Bern 3 Aug 04, 2022
K Closest Points and Maximum Clique Pruning for Efficient and Effective 3D Laser Scan Matching (To appear in RA-L 2022)

KCP The official implementation of KCP: k Closest Points and Maximum Clique Pruning for Efficient and Effective 3D Laser Scan Matching, accepted for p

Yu-Kai Lin 109 Dec 14, 2022
Implementing Vision Transformer (ViT) in PyTorch

Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re

2 Dec 24, 2021
Proposed n-stage Latent Dirichlet Allocation method - A Novel Approach for LDA

n-stage Latent Dirichlet Allocation (n-LDA) Proposed n-LDA & A Novel Approach for classical LDA Latent Dirichlet Allocation (LDA) is a generative prob

Anıl Güven 4 Mar 07, 2022
IPATool-py: download ipa easily

IPATool-py Python version of IPATool! Installation pip3 install -r requirements.txt Usage Quickstart: download app with specific bundleId into DIR: p

159 Dec 30, 2022
ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)

This is the project page for the paper: ISTR: End-to-End Instance Segmentation via Transformers, Jie Hu, Liujuan Cao, Yao Lu, ShengChuan Zhang, Yan Wa

Jie Hu 182 Dec 19, 2022
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.

Semantic Meshes A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model. Paper If you find this framework usefu

Florian 40 Dec 09, 2022
On the Analysis of French Phonetic Idiosyncrasies for Accent Recognition

On the Analysis of French Phonetic Idiosyncrasies for Accent Recognition With the spirit of reproducible research, this repository contains codes requ

0 Feb 24, 2022
Explanatory Learning: Beyond Empiricism in Neural Networks

Explanatory Learning This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks". Datasets Download the datasets

GLADIA Research Group 10 Dec 06, 2022
pybaum provides tools to work with pytrees which is a concept burrowed from JAX.

pybaum provides tools to work with pytrees which is a concept burrowed from JAX.

Open Source Economics 9 May 11, 2022
Novel and high-performance medical image classification pipelines are heavily utilizing ensemble learning strategies

An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks Novel and high-performance medical ima

14 Dec 18, 2022
transfer attack; adversarial examples; black-box attack; unrestricted Adversarial Attacks on ImageNet; CVPR2021 天池黑盒竞赛

transfer_adv CVPR-2021 AIC-VI: unrestricted Adversarial Attacks on ImageNet CVPR2021 安全AI挑战者计划第六期赛道2:ImageNet无限制对抗攻击 介绍 : 深度神经网络已经在各种视觉识别问题上取得了最先进的性能。

25 Dec 08, 2022
💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena

💃 VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena.

Heidelberg-NLP 17 Nov 07, 2022
Code for paper "Vocabulary Learning via Optimal Transport for Neural Machine Translation"

**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge

416 Jan 09, 2023