#Tensor
Showing 57 of 57 repositories tagged #tensor, ranked by stars
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
Open Machine Learning Compiler Framework
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
NumPy & SciPy for GPU
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
The AI search platform
MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
On-device AI across mobile, embedded and edge for PyTorch
C++ DataFrame for statistical, financial, and ML analysis in modern C++
A list of awesome compiler projects and papers for tensor computation and deep learning.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Deep learning in Rust, with shape checked tensors and neural networks
SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐
TensorLy: Tensor Learning in Python.
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
common in-memory tensor structure
Introduction to PyTorch, covering tensor initialization, operations, indexing, and reshaping.
⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.
Library for specialized dense and sparse matrix operations, and deep learning primitives.
Deep learning with spiking neural networks (SNNs) in PyTorch.
AutoKernel 是一个简单易用，低门槛的自动算子优化工具，提高深度学习算法部署效率。
Visualize PyTorch tensors with a single line of code.
DiffSharp: Differentiable Functional Programming
Tensors and differentiable operations (like TensorFlow) in Rust
Minimalist ML framework for Go.
OCaml bindings for PyTorch
A Machine Learning framework from scratch in Pure Mojo 🔥
Experimental tensor-typed deep learning
Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, MacOS), multimodal model for text and images and so on.
A deep learning framework built on an autograd engine with high level abstractions and low level control.
The V Tensor Library
My personal reference for Tensorflow
GPU accelerated deep learning and numeric computing for Scala 3.
A machine learning library built with user convenience at its core
An experimental deep learning framework for Nim based on a differentiable array programming language
Born is a modern ML framework for Go — train and deploy models as single binaries. Pure Go, zero CGO, GPU accelerated.
High-performance C++ tensor library with NumPy/PyTorch-like API
Provides a systematic and extensible way to build, train, evaluate, and tune deep learning models using PyTorch.
Colourful tensor operation visuals for NumPy style arrays, built for notebooks, docs, and teaching shape transformations.
A Python module for compiling PyTorch graphs to C
TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch
A learning-focused, high-performance tensor computation library built from scratch in Rust, featuring automatic differentiation and CPU/CUDA backends.
🐍 A Collection of Notes for Learning & Understanding Deep Learning / Machine Learning / Artificial Intelligence (AI) with TensorFlow 🐍
A next-generation dynamic and high-performance language for AI and IOT with natural born distributed computing ability.
A very small PyTorch container in Alpine Linux
Deep Learning framework with NVIDIA & AMD support
TensorLogic compiles logical rules (predicates, quantifiers, implications) into tensor equations (einsum graphs) with a minimal DSL + IR, enabling neural/symbolic/probabilistic models within a unified tensor computation framework.
Deep Learning framework in Go with Tensors, AutoGrad, and GPU acceleration
Python Module for PyTorch Tensor Visualisation in CUDA Eliminating CPU Transfer
European Distributed Deep Learning (EDDL) library. A general-purpose library initially developed to cover deep learning needs in healthcare use cases within the DeepHealth project.
RusTorch is a production-grade deep learning framework re-imagined in Rust. It combines the usability you love from PyTorch with the performance, safety, and concurrency guarantees of Rust. Say goodbye to GIL locks, GC pauses, and runtime errors. Say hello to RusTorch.
Toy autograd engine in OCaml with Apple Accelerate backend
To ease the driver to identify the Traffic Signs and also for the efficient working of Self-Driving Cars.
Datastore for Tensors based on Xarray and Zarr
Format matrices and tensors to HTML, string, and LaTeX, with Jupyter integration.