Tensor Python Packages

torch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

einops

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

simsimd

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 📐

cupy-cuda12x

NumPy & SciPy for GPU

pytorch-tokenizers

On-device AI across mobile, embedded and edge for PyTorch

cupy-cuda13x

NumPy & SciPy for GPU

autoray

Abstract your array operations.

numkong

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 📐

cotengra

Hyper optimized contraction trees for large tensor networks and einsums

executorch

On-device AI across mobile, embedded and edge for PyTorch

tensorly

TensorLy: Tensor Learning in Python.

cupy

NumPy & SciPy for GPU

tenseal

A library for doing homomorphic encryption operations on tensors

cupy-cuda11x

NumPy & SciPy for GPU

cloud-volume

Read and write Neuroglancer datasets programmatically.

multidim-indexing

Batch multidimensional indexing for pytorch

tensorly-torch

TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch

pymars

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

apache-tvm

Open Machine Learning Compiler Framework

cupy-rocm-7-0

NumPy & SciPy for GPU

pytat

Tensor Network State Packages

tensorpac

Phase-Amplitude Coupling under Python

tensortrax

Differentiable Tensors based on NumPy Arrays

cupy-cuda102

NumPy & SciPy for GPU