Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022

Overview

PyCRE

Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022

Dependencies

This project is developed using Python 3.6.9 on Ubuntu 18.04 LTS.

Name Version
Docker 20.10.8
Docker Compose 1.23.2

Python Package Knowledge Graph

We have opened our knowledge graphs in releases. If you need to create a new knowledge graph, follow the instructions below:

First, you need to install Neo4j 4.1.1 and its required Java version (Java SE 11).

Install extra Python dependencies:

pip install -r build_KG/requirements.txt

Automatically acquire knowledge and build KG for specific Python packages:

python build_KG/run.py <packages_file> <neo4j_HOME> <Python_version>

Load data from CSV files into an unused Neo4j database and dump the database into a single-file archive:

./build_KG/data/Pythonxxx/csv-data/run.sh

NEO4J_HOME/bin/neo4j-admin dump --database=neo4j --to=neo4j.dump

Inference

Move the dump files to the specific folder:

mv py2.dump py3.dump docker_env/neo4j

Build the docker images and start the deamon service:

cd docker_env

./build_images.sh

docker-compose up --detach

Install extra Python dependencies:

pip install -r bin/requirements.txt

Compile CryptoMiniSat SAT solver.

Then you can use PyCRE to infer a compatible runtime environment to a Python code:

python bin/run.py <snippet_path> <dependencies_dir>
You might also like...
A PoC Corporation Relationship Knowledge Graph System on top of Nebula Graph.
A PoC Corporation Relationship Knowledge Graph System on top of Nebula Graph.

Corp-Rel is a PoC of Corpartion Relationship Knowledge Graph System. It's built on top of the Open Source Graph Database: Nebula Graph with a dataset

Data-depth-inference - Data depth inference with python
Data-depth-inference - Data depth inference with python

Welcome! This readme will guide you through the use of the code in this reposito

Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.
Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.

Yolov5 running on TorchServe (GPU compatible) ! This is a dockerfile to run TorchServe for Yolo v5 object detection model. (TorchServe (PyTorch librar

Monocular 3D pose estimation. OpenVINO. CPU inference or iGPU (OpenCL) inference.
Monocular 3D pose estimation. OpenVINO. CPU inference or iGPU (OpenCL) inference.

human-pose-estimation-3d-python-cpp RealSenseD435 (RGB) 480x640 + CPU Corei9 45 FPS (Depth is not used) 1. Run 1-1. RealSenseD435 (RGB) 480x640 + CPU

PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices.

PyTorch-LIT PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices. With

[IJCAI-2021] A benchmark of data-free knowledge distillation from paper
[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"

DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa

TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A good teacher is patient and consistent by Beyer et al.

FunMatch-Distillation TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A g

Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)

SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language

This is the source code for: Context-aware Entity Typing in Knowledge Graphs.

This is the source code for: Context-aware Entity Typing in Knowledge Graphs.

Comments
  • Docker kill and restarting issue

    Docker kill and restarting issue

    When I try to run docker-compose I found that py2-neo4j and py3-neo4j can't be started at the same time. When the first starts, the second show this error (and vice versa): /build-files/load-and-start.sh: line 12: 76 Killed /docker-entrypoint.sh neo4j

    No problem when i run docker-compose including only once py2-neo4j or py3-neo4j.

    photo_2022-09-14_18-17-09

    Any ideas on how to resolve this issue?

    opened by vittoriapac94 1
Releases(v1.0.0)
Owner
[email protected]
The Websoft Research Group, Nanjing University
<a href=[email protected]">
Details about the wide minima density hypothesis and metrics to compute width of a minima

wide-minima-density-hypothesis Details about the wide minima density hypothesis and metrics to compute width of a minima This repo presents the wide m

Nikhil Iyer 9 Dec 27, 2022
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.

HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex

Waleed 1.7k Dec 31, 2022
High-Resolution 3D Human Digitization from A Single Image.

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization (CVPR 2020) News: [2020/06/15] Demo with Google Colab (i

Meta Research 8.4k Dec 29, 2022
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing

DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing Figure: Joint multi-attribute edits using DyStyle model. Great diversity

74 Dec 03, 2022
Sequence lineage information extracted from RKI sequence data repo

Pango lineage information for German SARS-CoV-2 sequences This repository contains a join of the metadata and pango lineage tables of all German SARS-

Cornelius Roemer 24 Oct 26, 2022
Pytorch implementation of "Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech"

GradTTS Unofficial Pytorch implementation of "Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech" (arxiv) About this repo This is an unoffic

HeyangXue1997 103 Dec 23, 2022
A collection of educational notebooks on multi-view geometry and computer vision.

Multiview notebooks This is a collection of educational notebooks on multi-view geometry and computer vision. Subjects covered in these notebooks incl

Max 65 Dec 09, 2022
Implements MLP-Mixer: An all-MLP Architecture for Vision.

MLP-Mixer-CIFAR10 This repository implements MLP-Mixer as proposed in MLP-Mixer: An all-MLP Architecture for Vision. The paper introduces an all MLP (

Sayak Paul 51 Jan 04, 2023
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Pytorch Lightning 21.1k Jan 01, 2023
StyleGAN2-ADA - Official PyTorch implementation

Need Help? If you’re new to StyleGAN2-ADA and looking to get started, please check out this video series from a course Lia Coleman and I taught in Oct

Derrick Schultz 217 Jan 04, 2023
An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results

EasyDatas An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results Installation pip install git+https

Ximing Yang 4 Dec 14, 2021
Most popular metrics used to evaluate object detection algorithms.

Most popular metrics used to evaluate object detection algorithms.

Rafael Padilla 4.4k Dec 25, 2022
Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

An official implementation of paper Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

11 Nov 23, 2022
This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Motion .

ROSEFusion 🌹 This project is based on our SIGGRAPH 2021 paper, ROSEFusion: Random Optimization for Online DenSE Reconstruction under Fast Camera Moti

219 Dec 27, 2022
一个多模态内容理解算法框架,其中包含数据处理、预训练模型、常见模型以及模型加速等模块。

Overview 架构设计 插件介绍 安装使用 框架简介 方便使用,支持多模态,多任务的统一训练框架 能力列表: bert + 分类任务 自定义任务训练(插件注册) 框架设计 框架采用分层的思想组织模型训练流程。 DATA 层负责读取用户数据,根据 field 管理数据。 Parser 层负责转换原

Tencent 265 Dec 22, 2022
A Kernel fuzzer focusing on race bugs

Razzer: Finding kernel race bugs through fuzzing Environment setup $ source scripts/envsetup.sh scripts/envsetup.sh sets up necessary environment var

Systems and Software Security Lab at Seoul National University (SNU) 328 Dec 26, 2022
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes

Sungyong Baik 44 Dec 29, 2022
This repository is for our EMNLP 2021 paper "Automated Generation of Accurate & Fluent Medical X-ray Reports"

Introduction: X-Ray Report Generation This repository is for our EMNLP 2021 paper "Automated Generation of Accurate & Fluent Medical X-ray Reports". O

no name 36 Dec 16, 2022
Efficient Training of Audio Transformers with Patchout

PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa

165 Dec 26, 2022
Employs neural networks to classify images into four categories: ship, automobile, dog or frog

Neural Net Image Classifier Employs neural networks to classify images into four categories: ship, automobile, dog or frog Viterbi_1.py uses a classic

Riley Baker 1 Jan 18, 2022