Search Results for "convert python to c" - Page 12

Showing 4924 open source projects for "convert python to c"

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  • 1
    libCEED

    libCEED

    CEED Library: Code for Efficient Extensible Discretizations

    libCEED provides fast algebra for element-based discretizations, designed for performance portability, run-time flexibility, and clean embedding in higher-level libraries and applications. It offers a C99 interface as well as bindings for Fortran, Python, Julia, and Rust. While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the user manual and API implementation portion
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  • 2
    PaddleSpeech

    PaddleSpeech

    Easy-to-use Speech Toolkit including Self-Supervised Learning model

    PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks in speech and audio, with state-of-art and influential models. Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing modules, and deployment process. Low barriers to install, CLI, Server, and Streaming Server is available to quick-start your journey. We provide...
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  • 3
    PyTorch/XLA

    PyTorch/XLA

    Enabling PyTorch on Google TPU

    PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs. You can try it right now, for free, on a single Cloud TPU with Google Colab, and use it in production and on Cloud TPU Pods with Google Cloud. Take a look at one of our Colab notebooks to quickly try different PyTorch networks running on Cloud TPUs and learn how to use Cloud TPUs as PyTorch devices. We are also introducing new TPU VMs for more transparent...
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  • 4
    jsii

    jsii

    jsii allows code in any language to naturally interact with JavaScript

    jsii allows code in any language to naturally interact with JavaScript classes. It is the technology that enables the AWS Cloud Development Kit to deliver polyglot libraries from a single codebase! A class library written in TypeScript can be used in projects authored in TypeScript or Javascript (as usual), but also in C# (and other languages from the .NET family), Go, Java, Python, etc. More languages will be added in the future! Due to JSON marshaling costs and the absence of a distributed...
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    AI4U

    AI4U

    Multi-engine plugin to specify agents with reinforcement learning

    AI4U is a multi-engine plugin (Godot and Unity) that allows you to design Non-Player Characters (NPCs) of games using an agent abstraction. In addition, AI4U has a low-level API that allows you to connect the agent to any algorithm made available in Python by the reinforcement learning community specifically and by the Artificial Intelligence community in general. Reinforcement learning promises to overcome traditional navigation mesh mechanisms in games and to provide more autonomous...
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  • 6
    Perspective

    Perspective

    A data visualization and analytics component

    Perspective is a high-performance data visualization library for building real-time, interactive analytics dashboards. Developed by FINOS, it supports WebAssembly-powered pivot tables and can handle large streaming datasets with speed and flexibility. Perspective is ideal for fintech, trading, and IoT applications where insights from live data need to be visualized, sliced, and explored quickly in a browser.
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  • 7
    audioFlux

    audioFlux

    A library for audio and music analysis, feature extraction

    A library for audio and music analysis, and feature extraction. Can be used for deep learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. audioflux is a deep learning tool library for audio and music analysis, feature extraction. It supports dozens of time-frequency analysis transformation methods and hundreds of corresponding time-domain and frequency-domain feature combinations. It can be provided to deep learning networks for training and is used to...
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  • 8
    DataFrame

    DataFrame

    C++ DataFrame for statistical, Financial, and ML analysis

    This is a C++ analytical library designed for data analysis similar to libraries in Python and R. For example, you would compare this to Pandas, R data.frame, or Polars. You can slice the data in many different ways. You can join, merge, and group-by the data. You can run various statistical, summarization, financial, and ML algorithms on the data. You can add your custom algorithms easily. You can multi-column sort, custom pick, and delete the data. DataFrame also includes a large collection...
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  • 9
    cuML

    cuML

    RAPIDS Machine Learning Library

    cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU...
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  • 10
    DifferentialEquations.jl

    DifferentialEquations.jl

    Multi-language suite for high-performance solvers of equations

    This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations, using classic algorithms and ones from recent research which routinely outperform the “standard” C/Fortran methods, and include algorithms optimized...
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  • 11
    staq

    staq

    Full-stack quantum processing toolkit

    staq is a modern C++ library for the synthesis, transformation, optimization and compilation of quantum circuits. staq is written in standard C++17 and has very low external dependencies. It is usable either through the provided binary tools, or as a header-only library that can be included to provide direct support for parsing & manipulating circuits written in the OpenQASM circuit description language. Inspired by Clang, staq is designed to manipulate OpenQASM syntax trees directly, rather...
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  • 12
    jCasbin

    jCasbin

    An authorization library that supports access control models

    An authorization library that supports access control models like ACL, RBAC, ABAC for Golang, Java, C/C++, Node.js, Javascript, PHP, Laravel, Python, .NET (C#), Delphi, Rust, Ruby, Swift (Objective-C), Lua (OpenResty), Dart (Flutter) and Elixir. In Casbin, an access control model is abstracted into a CONF file based on the PERM metamodel (Policy, Effect, Request, Matchers). So switching or upgrading the authorization mechanism for a project is just as simple as modifying a configuration...
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  • 13
    Casbin

    Casbin

    An authorization library that supports access control models

    An authorization library that supports access control models like ACL, RBAC, ABAC for Golang, Java, C/C++, Node.js, Javascript, PHP, Laravel, Python, .NET (C#), Delphi, Rust, Ruby, Swift (Objective-C), Lua (OpenResty), Dart (Flutter) and Elixir. In Casbin, an access control model is abstracted into a CONF file based on the PERM metamodel (Policy, Effect, Request, Matchers). So switching or upgrading the authorization mechanism for a project is just as simple as modifying a configuration...
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  • 14
    dap-mode

    dap-mode

    Emacs Debug Adapter Protocol

    Emacs client/library for Debug Adapter Protocol is a wire protocol for communication between client and Debug Server. It's similar to the LSP but provides integration with debug server. The API considered unstable until 1.0 release is out. It is tested against Java, Python, Ruby, Elixir and LLDB (C/C++/Objective-C/Swift). The main entry points are dap-debug and dap-debug-edit-template. The first one asks for a registered debug template and starts the configuration using the default values...
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  • 15
    re2

    re2

    Alternative to backtracking regular expression engines

    RE2 is a fast, safe, thread-friendly alternative to backtracking regular expression engines like those used in PCRE, Perl, and Python. It is a C++ library. This is the source code repository for RE2, a regular expression library. There is a fair amount of documentation (including code snippets) in the re2.h header file. Unless otherwise noted, the RE2 source files are distributed under the BSD-style license found in the LICENSE file. In POSIX mode, RE2 accepts standard POSIX (egrep) syntax...
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  • 16
    Transformer Engine

    Transformer Engine

    A library for accelerating Transformer models on NVIDIA GPUs

    Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference. TE provides a collection of highly optimized building blocks for popular Transformer architectures and an automatic mixed precision-like API that can be used seamlessly with your framework-specific code. TE also includes a framework-agnostic C++ API...
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  • 17
    IVY

    IVY

    The Unified Machine Learning Framework

    ... an awesome model on GitHub, written in JAX. We'll use PerceiverIO as an example. Implement the model in PyTorch yourself, spending time and energy ensuring every detail is correct. Otherwise, wait for a PyTorch version to appear on GitHub, among the many re-implementation attempts that appear (a, b, c, d, e, f). Instantly transpile the JAX model to PyTorch. This creates an identical PyTorch equivalent of the original model.
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  • 18
    SHAP

    SHAP

    A game theoretic approach to explain the output of ml models

    SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark...
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  • 19
    Google Open Source Project Style Guide

    Google Open Source Project Style Guide

    Chinese version of Google open source project style guide

    Each larger open source project has its own style guide, a series of conventions on how to write code for the project (sometimes more arbitrary). When all the code maintains a consistent style, it is more important when understanding large code bases. easy. The meaning of "style" covers a wide range, from "variables use camelCase" to "never use global variables" to "never use exceptions". The English version of the project maintains the programming style guidelines used in Google. If the...
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  • 20
    Build your own X

    Build your own X

    Master programming by recreating your favorite technologies

    Build Your Own X is a curated collection of tutorials and guides that walk you through re-implementing core technologies from scratch. The idea is that by building things yourself—emulators, OS kernels, databases, web servers, etc.—you gain deeper understanding of how they work. It’s not a single software project but a knowledge repository with external links, organized by categories of technologies.
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  • 21
    Julia VS Code

    Julia VS Code

    Julia extension for Visual Studio Code

    This VS Code extension provides support for the Julia programming language. We build on Julia’s unique combination of ease-of-use and performance. Beginners and experts can build better software more quickly, and get to a result faster. With a completely live environment, Julia for VS Code aims to take the frustration and guesswork out of programming and put the fun back in. A hybrid “canvas programming” style combines the exploratory power of a notebook with the productivity and static...
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  • 22
    Eris

    Eris

    A NodeJS Discord library

    A Node.js wrapper for interfacing with Discord. You will need NodeJS 10.4+. If you need voice support you will also need Python 2.7 and a C++ compiler. Create a directory for your bot, and change to that directory in your command line. If you want to be more updated (at the expense of stability), you can install the beta builds instead. Eris supports a few optional libraries that could potentially improve bot performance but may require additional dependencies. If you want Eris to use any...
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  • 23
    ViZDoom

    ViZDoom

    Doom-based AI research platform for reinforcement learning

    ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research in machine visual learning, and deep reinforcement learning, in particular. ViZDoom is based on ZDOOM, the most popular modern source-port of DOOM. This means compatibility with a huge range of tools and resources that can be used to create custom scenarios, availability of detailed documentation of the engine and tools and support of Doom community....
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  • 24
    libgit2

    libgit2

    A cross-platform, portable, linkable Git implementation library

    libgit2 is a portable, pure C implementation of the Git core methods provided as a re-entrant linkable library with a solid API, allowing you to write native speed custom Git applications in any language which supports C bindings. Libgit2 is developed with CMake, and this is be the easiest way to build a binary from the source. The CMake build system provides lots of options to configure the libgit2 build for your particular needs. It’s highly recommended that you build libgit2 as a static...
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  • 25
    OpenMLDB

    OpenMLDB

    OpenMLDB is an open-source machine learning database

    ... and inference. Real-time features are essential for many machine learning applications, such as real-time personalized recommendations and risk analytics. However, a feature engineering script developed by data scientists (Python scripts in most cases) cannot be directly deployed into production for online inference because it usually cannot meet the engineering requirements, such as low latency, high throughput and high availability.
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