Tensors and Dynamic neural networks in Python with strong GPU acceleration

Open deep learning compiler stack for cpu, gpu and specialized accelerators

NumPy & SciPy for GPU

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

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

TensorLy: Tensor Learning in Python.

common in-memory tensor structure

⚡️Optimizing einsum functions in NumPy, Tensorflow, Dask, and more with contraction order optimization.

Deep learning with spiking neural networks (SNNs) in PyTorch.

Visualize PyTorch tensors with a single line of code.

Let DI-treetensor help you simplify the structure processing!（树形运算一不小心就逻辑混乱？DI-treetensor快速帮你搞定）

Hyper optimized contraction trees for large tensor networks and einsums

Framework agnostic python runtime for RWKV models

Abstract your array operations.

Read and write Neuroglancer datasets programmatically.

Tensor Train Toolbox

Provides a systematic and extensible way to build, train, evaluate, and tune deep learning models using PyTorch.

Phase-Amplitude Coupling under Python

Python client for RedisAI

A Python module for compiling PyTorch graphs to C