262 Repositories
Python performance-characterization Libraries
A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.
Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag
Detecting silent model failure. NannyML estimates performance with an algorithm called Confidence-based Performance estimation (CBPE), developed by core contributors. It is the only open-source algorithm capable of fully capturing the impact of data drift on performance.
Website • Docs • Community Slack 💡 What is NannyML? NannyML is an open-source python library that allows you to estimate post-deployment model perfor
FastAPI-Amis-Admin is a high-performance, efficient and easily extensible FastAPI admin framework. Inspired by django-admin, and has as many powerful functions as django-admin.
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
My Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks using Tensorflow
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
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.
Sphinx-performance - CLI tool to measure the build time of different, free configurable Sphinx-Projects
CLI tool to measure the build time of different, free configurable Sphinx-Projec
Collie is for uncovering RDMA NIC performance anomalies
Collie is for uncovering RDMA NIC performance anomalies. Overview Prerequ
Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification
Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification Usage The required packages are lis
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
[ICLR'21] DARTS-: Robustly Stepping out of Performance Collapse Without Indicators [openreview] Authors: Xiangxiang Chu, Xiaoxing Wang, Bo Zhang, Shun
A framework for GPU based high-performance medical image processing and visualization
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 with static typing.
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.
Official code release for 3DV 2021 paper Human Performance Capture from Monocular Video in the Wild.
Nested cross-validation is necessary to avoid biased model performance in embedded feature selection in high-dimensional data with tiny sample sizes
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
This speeds up PyCharm's package index processes and avoids CPU & memory overloading
Cython plugin for Lark, reimplementing the LALR parser & lexer for better performance
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
Running Performance Calculator 👉 Have you ever wondered if you ran 10km at 2000
Defichain maxi - Scripts to optimize performance on defichain rewards
defichain_maxi This script is made to optimize your defichain vault rewards by m
Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data.
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
Unicorn can be used for performance analyses of highly configurable systems with causal reasoning. Users or developers can query Unicorn for a performance task.
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
DaCe is a parallel programming framework that takes code in Python/NumPy and other programming languages
aCe - Data-Centric Parallel Programming Decoupling domain science from performance optimization. DaCe is a parallel programming framework that takes c
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions
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
TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I
Visual Python and C++ nanosecond profiler, logger, tests enabler
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
ColossalAI-Benchmark - Performance benchmarking with ColossalAI
Benchmark for Tuning Accuracy and Efficiency Overview The benchmark includes our
Data App Performance Tests
Data App Performance Tests My hypothesis is that The different architectures of
PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.
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
Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach Thanh Luan Nguyen, Tri Nhu Do, Georges Kaddoum
Code for the paper 'A High Performance CRF Model for Clothes Parsing'.
Clothes Parsing Overview This code provides an implementation of the research paper: A High Performance CRF Model for Clothes Parsing Edgar Simo-S
Official repository for the BPF Performance Tools book
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
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 : High Performance Visualization Tool D-Analyst is a high performance data visualization built with python and based on OpenGL. It allows to
☄️ High performance, easy to use and feature-rich Solana SDK for Python.
Solathon is an high performance, easy to use and feature-rich Solana SDK for Python. Easy for beginners, powerful for real world applications.
An Inverse Kinematics library aiming performance and modularity
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,
Python scripts for a generic performance testing infrastructure using Locust.
TODOs Reference to published paper or online version of it loadtest_plotter.py: Cleanup and reading data from files ARS_simulation.py: Cleanup, docume
BigDL - Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems
Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems.
Diff Match Patch is a high-performance library in multiple languages that manipulates plain text.
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, high-precision CPU, GPU, and memory profiler for Python
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 - something like a easy yearly review for your stock performance
Stock History Display Available on Heroku: https://stock-history-display.herokua
Yoloxkeypointsegment - An anchor-free version of YOLO, with a simpler design but better performance
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 is a high-performance neural network inference framework optimized for the mobile platform
ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme
ScoutAPM Python Agent. Supports Django, Flask, and many other frameworks.
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 for Python and R packages
Raster processing benchmarks This repository contains a collection of raster processing benchmarks for Python and R packages. The tests cover the most
Analysis and plotting for motor/prop/ESC characterization, thrust vs RPM and torque vs thrust
esc_test This is a Python package used to plot and analyze data collected for the purpose of characterizing a particular propeller, motor, and ESC con
Profile and test to gain insights into the performance of your beautiful Python code
Profile and test to gain insights into the performance of your beautiful Python code View Demo - Report Bug - Request Feature QuickPotato in a nutshel
Visual odometry package based on hardware-accelerated NVIDIA Elbrus library with world class quality and performance.
Isaac ROS Visual Odometry This repository provides a ROS2 package that estimates stereo visual inertial odometry using the Isaac Elbrus GPU-accelerate
Performance monitoring and testing of OpenStack
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
MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling Demos | Blog Post | Colab Notebook | Paper | MIDI-DDSP is a hierarchical
BioThings API framework - Making high-performance API for biological annotation data
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
Python compiler that massively increases Python's code performance without code changes.
Flyable - A python compiler for highly performant code Flyable is a Python compiler that generates efficient native code. It uses different techniques
Python PostgreSQL database performance insights. Locks, index usage, buffer cache hit ratios, vacuum stats and more.
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: cross-platform, high performance ML inferencing and training accelerator
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an
High-performance moving least squares material point method (MLS-MPM) solver.
High-Performance MLS-MPM Solver with Cutting and Coupling (CPIC) (MIT License) A Moving Least Squares Material Point Method with Displacement Disconti
Auxiliary Raw Net (ARawNet) is a ASVSpoof detection model taking both raw waveform and handcrafted features as inputs, to balance the trade-off between performance and model complexity.
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
Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering Modular Primitives for High-Performance Differentiable Rendering Samuli
Simulation-based performance analysis of server-less Blockchain-enabled Federated Learning
Blockchain-enabled Server-less Federated Learning Repository containing the files used to reproduce the results of the publication "Blockchain-enabled
Pyinstrument - a Python profiler. A profiler is a tool to help you optimize your code - make it faster.
Pyinstrument🚴 Call stack profiler for Python. Shows you why your code is slow!
Dust model dichotomous performance analysis
Dust-model-dichotomous-performance-analysis Using a collated dataset of 90,000 dust point source observations from 9 drylands studies from around the
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition
SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec
High performance, editable, stylable datagrids in jupyter and jupyterlab
An ipywidgets wrapper of regular-table for Jupyter. Examples Two Billion Rows Notebook Click Events Notebook Edit Events Notebook Styling Notebook Pan
The RDT protocol (RDT3.0,GBN,SR) implementation and performance evaluation code using socket
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
A high-performance distributed deep learning system targeting large-scale and automated distributed training.
HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop
A modular, high performance, headless e-commerce platform built with Python, GraphQL, Django, and React.
Saleor Commerce Customer-centric e-commerce on a modern stack A headless, GraphQL commerce platform delivering ultra-fast, dynamic, personalized shopp
A high-performance immutable mapping type for Python.
immutables An immutable mapping type for Python. The underlying datastructure is a Hash Array Mapped Trie (HAMT) used in Clojure, Scala, Haskell, and
a wrapper around pytest for executing tests to look for test flakiness and runtime regression
bubblewrap a wrapper around pytest for assessing flakiness and runtime regressions a cs implementations practice project How to Run: First, install de
GTK and Python based, system performance and usage monitoring tool
System Monitoring Center GTK3 and Python 3 based, system performance and usage monitoring tool. Features: Detailed system performance and usage usage
In real-world applications of machine learning, reliable and safe systems must consider measures of performance beyond standard test set accuracy
PixMix Introduction In real-world applications of machine learning, reliable and safe systems must consider measures of performance beyond standard te
Shrapnel is a scalable, high-performance cooperative threading library for Python.
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
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
WebDataset WebDataset is a PyTorch Dataset (IterableDataset) implementation providing efficient access to datasets stored in POSIX tar archives and us
Fuzz introspector is a tool to help fuzzer developers to get an understanding of their fuzzer’s performance and identify any potential blockers.
Fuzz introspector Fuzz introspector is a tool to help fuzzer developers to get an understanding of their fuzzer’s performance and identify any potenti
A High-Performance Distributed Library for Large-Scale Bundle Adjustment
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
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
Model-based Reinforcement Learning Improves Autonomous Racing Performance
Racing Dreamer: Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars In this work, we propose to learn a racing contro
Research code for the paper "How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models"
Introduction This repository contains research code for the ACL 2021 paper "How Good is Your Tokenizer? On the Monolingual Performance of Multilingual
Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from time series data.
ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t
⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.
Optimized Einsum Optimized Einsum: A tensor contraction order optimizer Optimized einsum can significantly reduce the overall execution time of einsum
High performance Cross-platform Inference-engine, you could run Anakin on x86-cpu,arm, nv-gpu, amd-gpu,bitmain and cambricon devices.
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.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
High performance distributed framework for training deep learning recommendation models based on PyTorch.
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.
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 is a high-performance deep learning framework based on JIT compiling and meta-operators.
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
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
A high-performance topological machine learning toolbox in Python
giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G
Fast 1D and 2D histogram functions in Python
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.
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.
Fcpy: A Python package for high performance, fast convergence and high precision numerical fractional calculus computing.
Terrible sudoku solver with spaghetti code and performance issues
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.
Taichi is a parallel programming language for high-performance numerical computations.
Implementation of the paper titled "Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees"
Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees Implementation of the paper titled "Using Sampling to
A high performance implementation of HDBSCAN clustering.
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.
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
An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing
Improving the robustness and performance of biomedical NLP models through adversarial training
RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment
Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.
Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?
Tools for analyzing Java JVM gc log files
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
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.
Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi
Training PSPNet in Tensorflow. Reproduce the performance from the paper.
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(DeepLab v3+)
A Higher Performance Pytorch Implementation of DeepLab V3 Plus Introduction This repo is an (re-)implementation of Encoder-Decoder with Atrous Separab
A high-performance DNS stub resolver for bulk lookups and reconnaissance (subdomain enumeration)
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
Dashboard to monitor the performance of your Binance Futures account
futuresboard A python based scraper and dashboard to monitor the performance of your Binance Futures account. Note: A local sqlite3 database config/fu