Search Results for "compilation"
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Showing 28 open source projects for "compilation"
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1
PyTorch
Open source machine learning framework
...This project allows for fast, flexible experimentation and efficient production. PyTorch consists of torch (Tensor library), torch.autograd (tape-based automatic differentiation library), torch.jit (a compilation stack [TorchScript]), torch.nn (neural networks library), torch.multiprocessing (Python multiprocessing), and torch.utils (DataLoader and other utility functions). PyTorch can be used as a replacement for Numpy, or as a deep learning research platform that provides optimum flexibility and speed. -
2
tvm
Open deep learning compiler stack for cpu, gpu, etc.
...The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging 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. -
3
AutoClip
AI-powered video clipping and highlight generation
...YouTube, Bilibili), or accepting local uploads, and then applies AI analysis to identify segments worth clipping based on content (e.g. high energy moments, speech, or other heuristics). Once highlights are identified, AutoClip can automatically cut those segments and optionally assemble them into a compilation, thus greatly reducing manual video editing effort. It uses a modern web application stack with a front end (React + TypeScript) for user interaction and a back end that handles downloading, processing, clipping, and queue management, allowing real-time progress feedback and easy deployment, e.g. via Docker. -
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Image Fusion
Deep Learning-based Image Fusion: A Survey
...It is not a single monolithic tool, but rather a curated reference and aggregation of methods, code and performance comparisons in the domain of image fusion. Survey style description of method taxonomy, architectures, loss types. Compilation of many state-of-the-art image fusion methods (infrared + visible, multi-focus, multi-exposure). Survey style description of method taxonomy, architectures, loss types. -
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5
DeepGEMM
Clean and efficient FP8 GEMM kernels with fine-grained scaling
DeepGEMM is a specialized CUDA library for efficient, high-performance general matrix multiplication (GEMM) operations, with particular focus on low-precision formats such as FP8 (and experimental support for BF16). The library is designed to work cleanly and simply, avoiding overly templated or heavily abstracted code, while still delivering performance that rivals expert-tuned libraries. It supports both standard and “grouped” GEMMs, which is useful for architectures like Mixture of... -
6
ml.js
Machine learning tools in JavaScript
This library is a compilation of the tools developed in the mljs organization. It is mainly maintained for use in the browser. If you are working with Node.js, you might prefer to add to your dependencies only the libraries that you need, as they are usually published to npm more often. We prefix all our npm package names with ml- (eg. ml-matrix) so they are easy to find. -
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Torch-TensorRT
PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT
...Unlike PyTorch’s Just-In-Time (JIT) compiler, Torch-TensorRT is an Ahead-of-Time (AOT) compiler, meaning that before you deploy your TorchScript code, you go through an explicit compile step to convert a standard TorchScript program into a module targeting a TensorRT engine. Torch-TensorRT operates as a PyTorch extension and compiles modules that integrate into the JIT runtime seamlessly. After compilation using the optimized graph should feel no different than running a TorchScript module. You also have access to TensorRT’s suite of configurations at compile time, so you are able to specify operating precision (FP32/FP16/INT8) and other settings for your module. -
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PyTensor
Python library for defining and optimizing mathematical expressions
...Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that currently provides compilation via C, JAX, and Numba. Based on one of the most widely-used Python tensor libraries: Theano. -
9
IREE
A retargetable MLIR-based machine learning compiler runtime toolkit
IREE (Intermediate Representation Execution Environment, pronounced as "eerie") is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the data center and down to satisfy the constraints and special considerations of mobile and edge deployments. -
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10
OneFlow
OneFlow is a deep learning framework designed to be user-friendly
...Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous distributed expansion. It adheres to the core concept and architecture of static compilation and streaming parallelism and solves the memory wall challenge at the cluster level. world-leading level. Provides a variety of services from primary AI talent training to enterprise-level machine learning lifecycle integrated management (MLOps), including AI training and AI development, and supports three deployment modes of public cloud, private cloud and hybrid cloud. -
11
torchvision
Datasets, transforms and models specific to Computer Vision
...Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. It supports libjpeg-turbo as well. libpng and libjpeg must be available at compilation time in order to be available. TorchVision also offers a C++ API that contains C++ equivalent of python models. -
12
StatsForecast
Fast forecasting with statistical and econometric models
StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery... -
13
festival3os
mods to the Festival sokoban solver to run on OSX + Win + linux
Mods to the Festival sokoban solver that allow building on OSX, Linux, & Windows -
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Gorgonia
Gorgonia is a library that helps facilitate machine learning in Go
...The primary goal for Gorgonia is to be a highly performant machine learning/graph computation-based library that can scale across multiple machines. It should bring the appeal of Go (simple compilation and deployment process) to the ML world. It's a long way from there currently, however, the baby steps are already there. The main reason to use Gorgonia is developer comfort. If you're using a Go stack extensively, now you have access to the ability to create production-ready machine learning systems in an environment that you are already familiar and comfortable with. -
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SNOBOL4, while known primarily as a string language excels at any task involving symbolic manipulations. It provides run time typing, garbage collection, user data types, on the fly compilation.
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ManimML
ManimML is a project focused on providing animations
ManimML is a project focused on providing animations and visualizations of common machine-learning concepts with the Manim Community Library. Please check out our paper. We want this project to be a compilation of primitive visualizations that can be easily combined to create videos about complex machine-learning concepts. Additionally, we want to provide a set of abstractions that allow users to focus on explanations instead of software engineering. -
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Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across... -
18
TensorRT Pro
C++ library based on tensorrt integration
High-level interface for C++/Python. Simplify the implementation of the custom plugin. And serialization and deserialization have been encapsulated for easier usage. Simplify the compilation of fp32, fp16 and int8 for facilitating the deployment with C++/Python in server or embedded device. Models ready for use also with examples are RetinaFace, Scrfd, YoloV5, YoloX, Arcface, AlphaPose, CenterNet and DeepSORT(C++). -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to... -
20
raspicam
C++ library for controlling Raspberry Pi Camera (with/without OpenCV)
...Main features: - Provides class RaspiCam for easy and full control of the camera - Provides class RaspiCam_Cv for easy control of the camera with OpenCV. - Easy compilation/installation using cmake. - No need to install development file of userland. Implementation is hidden. - Many examples -
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Easy-TensorFlow
Simple and comprehensive tutorials in TensorFlow
The goal of this repository is to provide comprehensive tutorials for TensorFlow while maintaining the simplicity of the code. Each tutorial includes a detailed explanation (written in .ipynb) format, as well as the source code (in .py format). There is a necessity to address the motivations for this project. TensorFlow is one of the deep learning frameworks available with the largest community. This repository is dedicated to suggesting a simple path to learn TensorFlow. In addition to the... -
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Toolbox
Piotr's Image & Video Matlab Toolbox
...It augments MATLAB’s native capabilities (not replacing the Image Processing Toolbox) by providing efficient, reusable wrappers and optimized routines. Example and demo scripts for usage (e.g. acfReadme, detector readmes). Support for compilation / mex (for speed) and cross-platform compatibility. -
23
NNVM
Open deep learning compiler stack for cpu, gpu
The vision of the Apache NNVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. Compilation of deep learning models into minimum deployable modules. Infrastructure to automatically generates and optimize models on more backend with better performance. Compilation and minimal runtimes commonly unlock ML workloads on existing hardware. Automatically generate and optimize tensor operators on more backends. Need support for block sparsity, quantization (1,2,4,8 bit integers, posit), random forests/classical ML, memory planning, MISRA-C compatibility, Python prototyping or all of the above? ... -
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Intelligent Tools
NLP and Machine Learning ideas and applications
This project is a compilation of many tools that use deep learning architectures. -
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ConvNetJS
Deep learning in Javascript to train convolutional neural networks
...The library allows you to formulate and solve Neural Networks in Javascript. If you would like to add features to the library, you will have to change the code in src/ and then compile the library into the build/ directory. The compilation script simply concatenates files in src/ and then minifies the result.
