Search Results for "python framework"
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Showing 193 open source projects for "python framework"
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Codon
A high-performance, zero-overhead, extensible Python compiler
Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 100x or more, on a single thread. Codon supports native multithreading which can lead to speedups many times higher still. The Codon framework is fully modular and extensible, allowing for the seamless integration of new modules, compiler optimizations, domain-specific languages and so on. ... -
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CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. ... -
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SQLiteStudio
A free, open source, multi-platform SQLite database manager
...You can execute SQL statements that refer to multiple databases within a single query, thanks to a transparent database attaching mechanism built into the SQL Editor of SQLiteStudio. You can implement your own SQL functions (scalar & aggregate) using JavaScript, Python, or Tcl. There is a repository of ready-to-use scripts on the wiki page. -
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F´
A flight software and embedded systems framework
...To develop applications with F´, the following requirements 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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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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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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Panda3D
Powerful, mature open-source cross-platform game engine for Python
Powerful, mature open-source cross-platform game engine for Python and C++, developed by Disney and CMU. Panda3D is a game engine, a framework for 3D rendering and game development for Python and C++ programs. Panda3D is open-source and free for any purpose, including commercial ventures, thanks to its liberal license. To learn more about Panda3D's capabilities, visit the gallery and the feature list. -
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FAY
Framework for building AI-powered interactive digital humans and agent
Fay is an open source framework designed to build and deploy interactive digital humans powered by large language models. It acts as a middleware layer that connects digital character technologies with conversational AI systems and business applications. Fay supports various types of digital humans, including 2.5D and 3D avatars, and can be integrated with applications running on mobile devices, PCs, web platforms, and embedded systems. Its architecture allows developers to combine different... -
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fairseq2
FAIR Sequence Modeling Toolkit 2
fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a... -
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TensorFlow
TensorFlow is an open source library for machine learning
...Nodes take tensors—multidimensional arrays—as input and produce tensors as output. The framework allows for these algorithms to be run in C++ for better performance, while the multiple levels of APIs let the user determine how high or low they wish the level of abstraction to be in the models produced. Tensorflow can also be used for research and production with TensorFlow Extended. -
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S2 Geometry
Computational geometry and spatial indexing on the sphere
...This makes it particularly suited for applications involving geospatial data, such as mapping, spatial indexing, and geographic information systems (GIS). The library provides a robust mathematical framework for spherical geometry, allowing developers to work with polygons, points, and regions on the Earth’s surface using consistent and precise algorithms. Unlike traditional 2D geometry libraries, S2 ensures accuracy over large scales by modeling the globe directly, avoiding distortions caused by map projections. The project includes core C++ support, optional Python bindings, and integrations with Bazel and CMake for flexible builds. ... -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
...The fully fused MLP component of this framework requires a very large amount of shared 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. -
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CGraph
A general, three-party dependency-free, cross-platform
CGraph is a high-performance, cross-platform Directed Acyclic Graph (DAG) framework implemented in pure C++ with no third-party dependencies, designed for building complex task pipelines and parallel execution workflows. It allows developers to model computational processes as graph structures, where nodes represent tasks and edges define dependencies, enabling efficient scheduling and execution. The framework includes a pipeline system that supports sequential and parallel execution,... -
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wxWidgets
Cross-Platform C++ GUI Library
wxWidgets is a C++ library that lets developers create applications for Windows, macOS, Linux, and other platforms with a single code base. It has popular language bindings for Python, Ruby, Lua, Perl, and several 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. -
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Cactus
Low-latency AI inference engine optimized for mobile devices
Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing... -
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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to... -
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The Arcade Learning Environment
The Arcade Learning Environment (ALE) -- a platform for AI research
Arcade Learning Environment (ALE) is a widely used open-source framework that wraps hundreds of Atari 2600 games via an emulator and presents them as RL environments for AI agents. It decouples the game/emulation aspects from the agent interface, providing a clean API (C++, Python, Gymnasium) so researchers can focus on agent design rather than game plumbing. This environment suite has been central to many RL breakthroughs, including value-based agents, deep Q-nets, and general-agent benchmarking, because the Atari games span many genres and present diverse learning challenges (pixels, actions, delayed rewards). ... -
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XGBoost
Scalable and Flexible Gradient Boosting
...It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples. -
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Cutter
Free and Open Source Reverse Engineering Platform
Cutter is a free and open-source graphical reverse-engineering platform powered by the Rizin framework. It provides a visual interface for inspecting binaries, functions, strings, references, control flow, and low-level program structure. The application is designed to make advanced binary analysis more approachable without sacrificing access to Rizin’s underlying capabilities. Its interface can be extended with Python and native C++ plugins. -
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OpenSpiel
Environments and algorithms for research in general reinforcement
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and sequential, strictly turn-taking and simultaneous-move, perfect and imperfect information games, as well as traditional multiagent environments such as (partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel also includes tools to... -
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DearPyGui
Graphical User Interface Toolkit for Python with minimal dependencies
...DPG offers a solid framework for developing scientific, engineering, gaming, data science and other applications that require fast and interactive interfaces. The Tutorials will provide a great overview and links to each topic in the API Reference for more detailed reading. Complete theme and style control. GPU-based rendering and efficient C/C++ code. -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
...It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. ... -
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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. -
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OGRE
scene-oriented, flexible 3D engine (C++, Python, C#, Java)
OGRE (Object-Oriented Graphics Rendering Engine) is a scene-oriented, flexible 3D engine written in C++ designed to make it easier and more intuitive for developers to produce games and demos utilizing 3D hardware. The class library abstracts all the details of using the underlying system libraries like Direct3D and OpenGL and provides an interface based on world objects and other intuitive classes. We consider the results of our GL3Plus RenderSystem as the gold standard. The respective... -
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SimpleITK
A layer built on top of the Insight Toolkit (ITK)
SimpleITK is an image analysis toolkit with a large number of components supporting general filtering operations, image segmentation and registration. It is built on top of the Insight Segmentation and Registration Toolkit ITK with the intent of providing a simplified interface to ITK. SimpleITK itself is written in C++ but is available for a large number of programming languages. Wrapping of the C++ code is accomplished through SWIG, in principle, any language wrapped by SWIG should be...
