Search Results for "c++ to python converter"
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Showing 143 open source projects for "c++ to python converter"
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Confluent's .NET Client for Apache Kafka
Confluent's Apache Kafka .NET client
confluent-kafka-dotnet is Confluent's .NET client for Apache Kafka and the Confluent Platform. Confluent-kafka-dotnet is a lightweight wrapper around librdkafka, a finely tuned C client. There are a lot of details to get right when writing an Apache Kafka client. We get them right in one place (librdkafka) and leverage this work across all of our clients (also confluent-kafka-python and confluent-kafka-go). Confluent, founded by the creators of Kafka, is building a streaming platform... -
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Unicorn Engine
Unicorn CPU emulator framework (ARM, AArch64, M68K, Mips, Sparc
Unicorn is a lightweight multi-platform, multi-architecture CPU emulator framework. Highlight features. Multi-architectures: ARM, ARM64 (ARMv8), m68k, MIPS, PowerPC, RISC-V, S390x (SystemZ), SPARC, TriCore & x86 (include x86_64). Clean/simple/lightweight/intuitive architecture-neutral API. Implemented in pure C language, with bindings for Pharo, Crystal, Clojure, Visual Basic, Perl, Rust, Haskell, Ruby, Python, Java, Go, D, Lua, JavaScript, .NET, Delphi/Pascal & MSVC available. Native support... -
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Serverless Framework
The easy and open way to build serverless applications
Serverless Framework gives you everything you need to build serverless applications on any cloud. It provides structure, workflow automation and best practices out-of-the-box so you can deploy sophisticated serverless architectures. It uses new, event-driven compute services, such as AWS Lambda, Azure Functions, Google CloudFunctions and more. Serverless Framework lets you build apps made up of microservices that run in response to events. These auto-scale and will only charge you when... -
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waifu2x ncnn Vulkan
waifu2x converter ncnn version, run fast GPU with vulkan
ncnn implementation of waifu2x converter. Runs fast on Intel/AMD/Nvidia/Apple-Silicon with Vulkan API. waifu2x-ncnn-vulkan uses ncnn project as the universal neural network inference framework. -
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tvm
Open deep learning compiler stack for cpu, gpu, etc.
... machine learning models for any hardware platform. Compilation of deep learning models in Keras, MXNet, PyTorch, Tensorflow, CoreML, DarkNet and more. Start using TVM with Python today, build out production stacks using C++, Rust, or Java the next day. -
6
Capstone
Capstone disassembly/disassembler framework
... architecture-neutral API. Provide details on disassembled instruction (called “decomposer” by others). Provide semantics of the disassembled instruction, such as list of implicit registers read & written. Implemented in pure C language, with lightweight bindings for D, Clojure, F#, Common Lisp, Visual Basic, PHP, PowerShell, Emacs, Haskell, Perl, Python, Ruby, C#, NodeJS, Java, GO, C++, OCaml, Lua, Rust, Delphi, Free Pascal & Vala (ready either in main code, or provided externally by the community). -
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PHP-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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MegEngine
Easy-to-use deep learning framework with 3 key features
.... Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference. -
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Jittor
Jittor is a high-performance deep learning framework
... learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. Printing those variables shows they have the same shape and dtype. -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
... memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding. -
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F´
A flight software and embedded systems framework
... of the user’s system must be met, Linux or Mac OS X operating system (or Windows Subsystem for Linux on Windows), CMake, Bash or Bash compatible shell, Clang or GCC compiler, Python 3 and PIP. F´ can be quickly installed and ready to use by cloning the GitHub repository, installing Python code (typically in a virtual environment), and building one of our reference applications. -
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Fury
A blazing fast multi-language serialization framework
Fury is a blazing-fast multi-language serialization framework powered by jit(just-in-time compilation) and zero-copy, providing up to 170x performance and ultimate ease of use. Based on efficient JIT, struct deserialization can get 170x speed up compared to other serialization frameworks. In serialization scenarios, Fury can achieve a 100x speed up compared to traditional serialization frameworks. If you use Java clusters on a large scale, this will save a lot of computing resources. -
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PyObjC
The Python <-> Objective-C Bridge with bindings for macOS frameworks
PyObjC is a Python-Objective-C bridge that allows Python scripts to interact with macOS Cocoa libraries. It enables developers to write native macOS apps entirely in Python by accessing Objective-C APIs. -
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F·W·K
3D game engine/framework in C, with Luajit and Python bindings now
3D game framework in C, with Luajit and Python bindings now. -
15
gopy
gopy generates a CPython extension module from a go package
This is an improved version that works with current versions of Go (e.g., 1.15 -- should work with any future version going forward), and uses unique int64 handles to interface with python, so that no pointers are interchanged, making everything safe for the more recent moving garbage collector. It also supports python modules having any number of Go packages, and generates a separate .py module file for each package, which link into a single common binding library. It has been tested... -
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wxPython Project Phoenix
wxPython's Project Phoenix. A new implementation of wxPython
... like "Classic" wxPython, Phoenix wraps the wxWidgets C++ toolkit and provides access to the user interface portions of the wxWidgets API, enabling Python applications to have a native GUI on Windows, Macs or Unix systems, with a native look and feel and requiring very little (if any) platform-specific code. -
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OnlineJudge 2.0
Open source online judge based on Vue, Django and Docker
An open-source online judge system based on Python and Vue. Based on Docker; One-click deployment. Separated backend and frontend; Modular programming; Micro service. ACM/OI rule support; realtime/non-realtime rank support. Amazing charting and visualization. Template-problem support. More reasonable permission control. Multi-language support: C, C++, Java, Python2, Python3. Markdown & MathJax support. Contest participants IP limit(CIDR). You can control the menu and chart status in rankings. -
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QPanda 2
QPanda 2 is an open source quantum computing framework
QPanda2 is an open source quantum computing framework developed by Origin Quantum, which can be used to build, run and optimize quantum algorithms. QPanda2 is the basic library of a series of software developed by Origin Quantum, which provides core components for QRunes, Qurator and quantum computing services. -
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Bot Framework SDK for .NET
Welcome to the Bot Framework SDK for .NET repository
This repository contains code for the .NET version of the Microsoft Bot Framework SDK, which is part of the Microsoft Bot Framework - a comprehensive framework for building enterprise-grade conversational AI experiences. This SDK enables developers to model conversation and build sophisticated bot applications using .NET. SDKs for JavaScript, Python and Java (preview) are also available. To get started building bots using the SDK, see the Azure Bot Service Documentation. -
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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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Framework Benchmarks
Source for the TechEmpower Framework Benchmarks project
If you're new to the project, welcome! Please feel free to ask questions here. We encourage new frameworks and contributors to ask questions. We're here to help! This project provides representative performance measures across a wide field of web application frameworks. With much help from the community, coverage is quite broad and we are happy to broaden it further with contributions. The project presently includes frameworks on many languages including Go, Python, Java, Ruby, PHP, C#, F... -
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
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Distributed Transactions Manager
A distributed transaction framework that supports multiple languages
Support HTTP and GRPC, provide easy-to-use interfaces, lower substantially the barrier of getting started with distributed transactions, and newcomers can adapt quickly. Developers no longer worry about suspension, null compensation, idempotent transaction, and other tricky problems, the framework layer handles them all. Suitable for companies with the multi-language stack. Easy for go, python, php, nodejs, ruby and so forth. The only external dependence is the database server, easy to deploy... -
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C# ECG Toolkit
ECG Toolkit support for: SCP-ECG, DICOM, HL7 aECG, ISHNE & MUSE-XML
C# ECG Toolkit is an open source software toolkit to convert, view and print electrocardiograms. The toolkit is developed using C# .NET Framework 2.0 and later (code also supports netstandard2.0). Support for ECG formats: SCP-ECG, DICOM, HL7 aECG, ISHNE, MUSE-XML and OmronECG. -
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wxWidgets
A cross-platform GUI library
wxWidgets is a C++ library that lets developers create applications for Windows, Mac OS X, Linux and other platforms with a single code base. It has popular language bindings for Python, Perl, Ruby and many other languages, and unlike other cross-platform toolkits, wxWidgets gives applications a truly native look and feel because it uses the platform's native API rather than emulating the GUI. It's also extensive, free, open-source and mature.
