Python Performance Resources

Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag

Website • Docs • Community Slack 💡 What is NannyML? NannyML is an open-source python library that allows you to estimate post-deployment model perfor

简体中文 | English 项目介绍 FastAPI-Amis-Admin fastapi-amis-admin是一个拥有高性能,高效率,易拓展的fastapi管理后台框架. 启发自Django-Admin,并且拥有不逊色于Django-Admin的强大功能. 源码 · 在线演示 · 文档 · 文

Easy Data Augmentation Implementation This repository contains my Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Per

Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of given options.

CLI tool to measure the build time of different, free configurable Sphinx-Projec

Collie is for uncovering RDMA NIC performance anomalies. Overview Prerequ

[ICLR'21] DARTS-: Robustly Stepping out of Performance Collapse Without Indicators [openreview] Authors: Xiangxiang Chu, Xiaoxing Wang, Bo Zhang, Shun

FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.

A simple stopwatch for measuring code performance. This is a fork from python-stopwatch, which adds static typing and a few other things.

Official code release for 3DV 2021 paper Human Performance Capture from Monocular Video in the Wild.

Pruner for nested cross-validation - Sphinx-Doc Nested cross-validation is necessary to avoid biased model performance in embedded feature selection i

This speeds up PyCharm's package index processes and avoids CPU & memory overloading

Lark-Cython Cython plugin for Lark, reimplementing the LALR parser & lexer for better performance on CPython. Install: pip install lark-cython Usage:

Running Performance Calculator 👉 Have you ever wondered if you ran 10km at 2000

defichain_maxi This script is made to optimize your defichain vault rewards by m

Hatchet Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing

Unicorn can be used for performance analyses of highly configurable systems with causal reasoning. Users or developers can query Unicorn for a performance task.

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

aCe - Data-Centric Parallel Programming Decoupling domain science from performance optimization. DaCe is a parallel programming framework that takes c

Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act

TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I

Look into Palanteer and get an omniscient view of your program Palanteer is a set of lean and efficient tools to improve the quality of software, for

Benchmark for Tuning Accuracy and Efficiency Overview The benchmark includes our

Data App Performance Tests My hypothesis is that The different architectures of

PEPit: Performance Estimation in Python This open source Python library provides a generic way to use PEP framework in Python. Performance estimation

Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach Thanh Luan Nguyen, Tri Nhu Do, Georges Kaddoum

Clothes Parsing Overview This code provides an implementation of the research paper: A High Performance CRF Model for Clothes Parsing Edgar Simo-S

BPF Performance Tools This is the official repository of BPF (eBPF) tools from the book BPF Performance Tools: Linux and Application Observability. Th

Generate FastAPI projects for high performance applications. Based on MVC architectural pattern, WSGI + ASGI. Includes tests, pipeline, base utilities, Helm chart, and script for bootstrapping local Minikube with high available Redis cluster.

D-Analyst : High Performance Visualization Tool D-Analyst is a high performance data visualization built with python and based on OpenGL. It allows to

Solathon is an high performance, easy to use and feature-rich Solana SDK for Python. Easy for beginners, powerful for real world applications.

IKPy Demo Live demos of what IKPy can do (click on the image below to see the video): Also, a presentation of IKPy: Presentation. Features With IKPy,

TODOs Reference to published paper or online version of it loadtest_plotter.py: Cleanup and reading data from files ARS_simulation.py: Cleanup, docume

Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems.

The Diff Match and Patch libraries offer robust algorithms to perform the operations required for synchronizing plain text. Diff: Compare two blocks o

Scalene: a high-performance CPU, GPU and memory profiler for Python by Emery Berger, Sam Stern, and Juan Altmayer Pizzorno. Scalene community Slack Ab

Stock History Display Available on Heroku: https://stock-history-display.herokua

Introduction 关键点版本：已完成 全景分割版本：已完成 实例分割版本：已完成 YOLOX is an anchor-free version of

ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme

Scout Python APM Agent Monitor the performance of Python Django apps, Flask apps, and Celery workers with Scout's Python APM Agent. Detailed performan

Raster processing benchmarks This repository contains a collection of raster processing benchmarks for Python and R packages. The tests cover the most

Profile and test to gain insights into the performance of your beautiful Python code View Demo - Report Bug - Request Feature QuickPotato in a nutshel

Isaac ROS Visual Odometry This repository provides a ROS2 package that estimates stereo visual inertial odometry using the Isaac Elbrus GPU-accelerate

Browbeat Browbeat is a performance tuning and analysis tool for OpenStack. Browbeat is free, Open Source software. Analyze and tune your Cloud for opt

MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling Demos | Blog Post | Colab Notebook | Paper | MIDI-DDSP is a hierarchical

BioThings SDK Quick Summary BioThings SDK provides a Python-based toolkit to build high-performance data APIs (or web services) from a single data sou

Flyable - A python compiler for highly performant code Flyable is a Python compiler that generates efficient native code. It uses different techniques

Python PG Extras Python port of Heroku PG Extras with several additions and improvements. The goal of this project is to provide powerful insights int

ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an

High-Performance MLS-MPM Solver with Cutting and Coupling (CPIC) (MIT License) A Moving Least Squares Material Point Method with Displacement Disconti

Overview This repository is an implementation of the Auxiliary Raw Net (ARawNet), which is ASVSpoof detection system taking both raw waveform and hand

Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering Modular Primitives for High-Performance Differentiable Rendering Samuli

Blockchain-enabled Server-less Federated Learning Repository containing the files used to reproduce the results of the publication "Blockchain-enabled

Pyinstrument🚴 Call stack profiler for Python. Shows you why your code is slow!

Dust-model-dichotomous-performance-analysis Using a collated dataset of 90,000 dust point source observations from 9 drylands studies from around the

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

An ipywidgets wrapper of regular-table for Jupyter. Examples Two Billion Rows Notebook Click Events Notebook Edit Events Notebook Styling Notebook Pan

소켓을 이용한 RDT protocols (RDT3.0,GBN,SR) 구현 및 성능 평가 코드 입니다. 코드를 실행할때 리시버를 먼저 실행하세요. 성능 평가 코드는 패킷 전송 과정을 제외하고 시간당 전송률을 출력합니다. RDT3.0 GBN SR(버그 발견으로 구현중 입니

HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop

Saleor Commerce Customer-centric e-commerce on a modern stack A headless, GraphQL commerce platform delivering ultra-fast, dynamic, personalized shopp

immutables An immutable mapping type for Python. The underlying datastructure is a Hash Array Mapped Trie (HAMT) used in Clojure, Scala, Haskell, and

bubblewrap a wrapper around pytest for assessing flakiness and runtime regressions a cs implementations practice project How to Run: First, install de

System Monitoring Center GTK3 and Python 3 based, system performance and usage monitoring tool. Features: Detailed system performance and usage usage

PixMix Introduction In real-world applications of machine learning, reliable and safe systems must consider measures of performance beyond standard te

This Python library was evolved at IronPort Systems and has been provided as open source by Cisco Systems under an MIT license. Intro Shrapnel is a li

WebDataset WebDataset is a PyTorch Dataset (IterableDataset) implementation providing efficient access to datasets stored in POSIX tar archives and us

Fuzz introspector Fuzz introspector is a tool to help fuzzer developers to get an understanding of their fuzzer’s performance and identify any potenti

MegBA: A High-Performance and Distributed Library for Large-Scale Bundle Adjustment This repo contains an official implementation of MegBA. MegBA is a

Senator Stock Trading Tester Program to compare stock performance of Senator's transactions vs when the sale is disclosed. Using to find if tracking S

Racing Dreamer: Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars In this work, we propose to learn a racing contro

Introduction This repository contains research code for the ACL 2021 paper "How Good is Your Tokenizer? On the Monolingual Performance of Multilingual

ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t

Optimized Einsum Optimized Einsum: A tensor contraction order optimizer Optimized einsum can significantly reduce the overall execution time of einsum

Anakin2.0 Welcome to the Anakin GitHub. Anakin is a cross-platform, high-performance inference engine, which is originally developed by Baidu engineer

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

PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI platform@Kuaishou Technology, collaborating with ETH. It

An encryption format offering better security, performance and ease of use than PGP. File a bug if you found anything where we are worse than our competition, and we will fix it.

Jittor: a Just-in-time(JIT) deep learning framework Quickstart | Install | Tutorial | Chinese Jittor is a high-performance deep learning framework bas

Auto locust load test config and worker distribution with Docker and GitHub Action Install Fork the repo and change the visibility option to private S

giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G

About Sometimes you just want to compute simple 1D or 2D histograms with regular bins. Fast. No nonsense. Numpy's histogram functions are versatile, a

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

Fcpy: A Python package for high performance, fast convergence and high precision numerical fractional calculus computing.

SudokuSolver Terrible sudoku solver with spaghetti code and performance issues - if it's unable to figure out next step it will stop working, it never

Taichi is a parallel programming language for high-performance numerical computations.

Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees Implementation of the paper titled "Using Sampling to

HDBSCAN HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates

High performance distributed framework for training deep learning recommendation models based on PyTorch.

An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing

RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment

Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?

gc_log This package consists of two separate utilities useful for : gc_log_visualizer.py regionsize.py GC Log Visualizer This was updated to run under

Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi

Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support

A Higher Performance Pytorch Implementation of DeepLab V3 Plus Introduction This repo is an (re-)implementation of Encoder-Decoder with Atrous Separab

MassDNS A high-performance DNS stub resolver MassDNS is a simple high-performance DNS stub resolver targeting those who seek to resolve a massive amou

futuresboard A python based scraper and dashboard to monitor the performance of your Binance Futures account. Note: A local sqlite3 database config/fu

Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks. Generally, we intergrete different kind of functional

Deep Neural Network Prediction Step 1. Genernate random parameters and Run them sequentially : $ python3 collect_data.py -gp -ep -pp -pl pooling -num