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]">
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021)

MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021) Overview We release the code of the MVFNet (Multi-View Fusion Network).

2 Jan 29, 2022
ConvMAE: Masked Convolution Meets Masked Autoencoders

ConvMAE ConvMAE: Masked Convolution Meets Masked Autoencoders Peng Gao1, Teli Ma1, Hongsheng Li2, Jifeng Dai3, Yu Qiao1, 1 Shanghai AI Laboratory, 2 M

Alpha VL Team of Shanghai AI Lab 345 Jan 08, 2023
LeetCode Solutions https://t.me/tenvlad

leetcode LeetCode Solutions groupped by common patterns YouTube: https://www.youtube.com/c/vladten Telegram: https://t.me/nilinterface Problems source

Vlad Ten 158 Dec 29, 2022
Collections for the lasted paper about multi-view clustering methods (papers, codes)

Multi-View Clustering Papers Collections for the lasted paper about multi-view clustering methods (papers, codes). There also exists some repositories

Andrew Guan 10 Sep 20, 2022
Vision-Language Pre-training for Image Captioning and Question Answering

VLP This repo hosts the source code for our AAAI2020 work Vision-Language Pre-training (VLP). We have released the pre-trained model on Conceptual Cap

Luowei Zhou 373 Jan 03, 2023
Prior-Guided Multi-View 3D Head Reconstruction

Prior-Guided Head MVS This repository includes some reconstruction results of our IEEE TMM 2021 paper, Prior-Guided Multi-View 3D Head Reconstruction.

11 Aug 17, 2022
Perception-aware multi-sensor fusion for 3D LiDAR semantic segmentation (ICCV 2021)

Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation (ICCV 2021) [中文|EN] 概述 本工作主要探索一种高效的多传感器(激光雷达和摄像头)融合点云语义分割方法。现有的多传感器融合方法主要将点云投影

ICE 126 Dec 30, 2022
Official repository for the paper, MidiBERT-Piano: Large-scale Pre-training for Symbolic Music Understanding.

MidiBERT-Piano Authors: Yi-Hui (Sophia) Chou, I-Chun (Bronwin) Chen Introduction This is the official repository for the paper, MidiBERT-Piano: Large-

137 Dec 15, 2022
Consensus score for tripadvisor

ContripScore ContripScore is essentially a score that combines an Internet platform rating and a consensus rating from sentiment analysis (For instanc

Pepe 1 Jan 13, 2022
Fully Convolutional DenseNets for semantic segmentation.

Introduction This repo contains the code to train and evaluate FC-DenseNets as described in The One Hundred Layers Tiramisu: Fully Convolutional Dense

485 Nov 26, 2022
A PyTorch implementation of Learning to learn by gradient descent by gradient descent

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

Ilya Kostrikov 300 Dec 11, 2022
Neural Scene Flow Prior (NeurIPS 2021 spotlight)

Neural Scene Flow Prior Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey Will appear on Thirty-fifth Conference on Neural Information Processing Syste

Lilac Lee 85 Jan 03, 2023
QuALITY: Question Answering with Long Input Texts, Yes!

QuALITY: Question Answering with Long Input Texts, Yes! Authors: Richard Yuanzhe Pang,* Alicia Parrish,* Nitish Joshi,* Nikita Nangia, Jason Phang, An

ML² AT CILVR 61 Jan 02, 2023
Music source separation is a task to separate audio recordings into individual sources

Music Source Separation Music source separation is a task to separate audio recordings into individual sources. This repository is an PyTorch implmeme

Bytedance Inc. 958 Jan 03, 2023
Sibur challange 2021 competition - 6 place

sibur challange 2021 Решение на 6 место: https://sibur.ai-community.com/competitions/5/tasks/13 Скор 1.4066/1.4159 public/private. Архитектура - однос

Ivan 5 Jan 11, 2022
Modifications of the official PyTorch implementation of StyleGAN3. Let's easily generate images and videos with StyleGAN2/2-ADA/3!

Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation of the NeurIPS 2021 paper Alias-Free Generative Adversarial Net

Diego Porres 185 Dec 24, 2022
Learnable Motion Coherence for Correspondence Pruning

Learnable Motion Coherence for Correspondence Pruning Yuan Liu, Lingjie Liu, Cheng Lin, Zhen Dong, Wenping Wang Project Page Any questions or discussi

liuyuan 41 Nov 30, 2022
Local Multi-Head Channel Self-Attention for FER2013

LHC-Net Local Multi-Head Channel Self-Attention This repository is intended to provide a quick implementation of the LHC-Net and to replicate the resu

12 Jan 04, 2023
Pytorch implementation of Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization https://arxiv.org/abs/2008.11646

[TCSVT] Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization LPN [Paper] NEWs Prerequisites Python 3.6 GPU Memory = 8G Numpy 1.

46 Dec 14, 2022
A python3 tool to take a 360 degree survey of the RF spectrum (hamlib + rotctld + RTL-SDR/HackRF)

RF Light House (rflh) A python script to use a rotor and a SDR device (RTL-SDR or HackRF One) to measure the RF level around and get a data set and be

Pavel Milanes (CO7WT) 11 Dec 13, 2022