Search Results for "python" - Page 2
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Showing 561 open source projects for "python"
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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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Faiss
Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes... -
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NumCpp
C++ implementation of the Python Numpy library
A Templatized Header Only C++ Implementation of the Python NumPy Library. The main data structure in NumCpp is the NdArray. It is inherently a 2D array class, with 1D arrays being implemented as 1xN arrays. There is also a DataCube class that is provided as a convenience container for storing an array of 2D NdArrays, but it has limited usefulness past a simple container. -
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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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OpenSpiel
Environments and algorithms for research in general reinforcement
... to analyze learning dynamics and other common evaluation metrics. Games are represented as procedural extensive-form games, with some natural extensions. The core API and games are implemented in C++ and exposed to Python. Algorithms and tools are written both in C++ and Python. To try OpenSpiel in Google Colaboratory, please refer to open_spiel/colabs subdirectory. -
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ccapi
A header-only C++ library for interacting with crypto exchanges
A header-only C++ library for streaming market data and executing trades directly from cryptocurrency exchanges (i.e. the connections are between your server and the exchange server without anything in-between). -
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nghttp2
HTTP/2 C Library and tools
... and nghttp2 is now one of the most mature HTTP/2 implementations. HTTP/2 utilizes header compression method called HPACK. We offer HPACK encoder and decoder are available as public API. nghttp2 library itself is a bit low-level. The experimental high-level C++ API is also available. We have Python binding of this library, but we have not covered everything yet. -
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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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cuDF
GPU DataFrame Library
... with conda (miniconda, or the full Anaconda distribution) from the rapidsai channel. cuDF is supported only on Linux, and with Python versions 3.7 and later. The RAPIDS suite of open-source software libraries aims to enable the execution of end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization but exposing that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. -
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pybind11
Seamless operability between C++11 and Python
Pybind11 is a lightweight, header‑only C++ library that simplifies and streamlines creating Python bindings for C++11+ code. It uses template meta-programming to automatically infer types, minimizing boilerplate compared to Boost.Python, and works seamlessly with major build systems -
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Fast Binary Encoding (FBE)
Fast Binary Encoding is fast and universal serialization solution
Fast Binary Encoding is ultra fast and universal serialization solution for C++, C#, Go, Java, JavaScript, Kotlin, Python, Ruby, and Swift. Fast Binary Encoding allows to description of any domain models, business objects, complex data structures, client/server requests & responses and generate native code for different programming languages and platforms. -
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SageMaker TensorFlow
SageMaker specific extensions to TensorFlow
This package contains SageMaker-specific extensions to TensorFlow, including the PipeModeDataset class, that allows SageMaker Pipe Mode channels to be read using TensorFlow Datasets. This package supports Python 3.7-3.9 and TensorFlow versions 1.7 and higher, including 2.0-2.9.1. For TensorFlow 1.x support, see the master branch. sagemaker-tensorflow releases for all supported versions are available on PyPI. SageMaker TensorFlow extensions builds on Python 3.4-3.9 in Linux with a TensorFlow... -
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Double Conversion
Efficient binary-decimal & decimal-binary conversion routines for IEEE
Double Conversion is a high-performance C++ library that provides precise and efficient binary-decimal and decimal-binary conversion routines for IEEE 754 double-precision floating-point numbers. Originally extracted from the V8 JavaScript engine, it was refactored into a standalone library to make its robust number conversion algorithms easily reusable in other projects. The library ensures consistent and accurate results for converting between double values and their string... -
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TensorStore
Library for reading and writing large multi-dimensional arrays
.... Transactional semantics allow atomic updates and consistent snapshots, which is essential for large, shared datasets used by ML and scientific workflows. The library is engineered for scalability—background caching, chunk sharding, and retryable operations keep throughput high even over unreliable networks. With language bindings, it fits into Python-heavy analysis pipelines while retaining a fast C++ core. -
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X's Recommendation Algorithm
Source code for the X Recommendation Algorithm
The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. Written primarily in... -
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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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XLS
XLS: Accelerated HW Synthesis
XLS is an open-source toolkit for building high-level hardware with a modern compiler stack that spans from a functional DSL to optimized IR and hardware generation. At the front end, DSLX lets you describe algorithms with strong typing and familiar control flow while remaining synthesis-friendly. The compiler lowers DSLX into a rich intermediate representation, applies aggressive optimization and scheduling passes, and can either JIT the design for software simulation or emit Verilog for... -
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CPU Features
A cross platform C99 library to get cpu features at runtime
cpu_features is a cross-platform C library developed by Google that provides a simple and efficient way to detect available CPU features at runtime across a wide range of architectures and operating systems. It enables applications to determine which instruction sets (such as SSE, AVX, or NEON) are supported on the host machine, allowing developers to optimize performance dynamically. The library supports numerous architectures—including x86, ARM, AArch64, MIPS, POWER, RISCV, LoongArch, and... -
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FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to... -
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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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DALI
A GPU-accelerated library containing highly optimized building blocks
The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding,... -
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mlpack
mlpack: a scalable C++ machine learning library
mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. Written in C++ and built on the Armadillo linear... -
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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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glslViewer
Console-based GLSL Sandbox for 2D/3D shaders shaders
GlslViewer is a flexible console-based OpenGL Sandbox to display 2D/3D GLSL shaders without the need of a UI. You can definitely make your own UI or wrapper using the Python Module (include) or any other tool that communicates back/forth with the GPS viewer through the standard POSIX console In/Out or OSC. Default vert/frag shaders for 2D shader and 3D material shaders with PBR lighting model. Hot reload of files on changes. One default light and one default camera. Interactive commands thought... -
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PyCXX is a set of classes to help create extensions of Python in the C++ language. The first part encapsulates the Python C API taking care of exceptions and ref counting. The second part supports the building of Python extension modules in C++.
