Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Updated
Apr 17, 2025 - Python
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
On-device AI across mobile, embedded and edge for PyTorch
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.
⚡️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.
Machine Learning with Symbolic Tensors
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
Abstract your array operations.
Read and write Neuroglancer datasets programmatically.
Framework agnostic python runtime for RWKV models
Tensor Train Toolbox
Phase-Amplitude Coupling under Python
Provides a systematic and extensible way to build, train, evaluate, and tune deep learning models using PyTorch.
A Python module for compiling PyTorch graphs to C
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