Tensors and Dynamic neural networks in Python with strong GPU acceleration

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

⚡ A Fast, Extensible Progress Bar for Python and CLI

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

Image-to-Image Translation in PyTorch

Datasets, Transforms and Models specific to Computer Vision

Image augmentation for machine learning experiments.

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

Declarative statistical visualization library for Python

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

Structured Text Generation

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…

Matplotlib styles for scientific plotting

Python Data. Leaflet.js Maps.

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, …

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

Astronomy and astrophysics core library

Command line driven CI frontend and development task automation tool.

A highly efficient implementation of Gaussian Processes in PyTorch

min(DALL·E) is a fast, minimal port of DALL·E Mini to PyTorch

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)

On the Variance of the Adaptive Learning Rate and Beyond

Codebase for Image Classification Research, written in PyTorch.

PySAL: Python Spatial Analysis Library Meta-Package

Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

A toolbox to iNNvestigate neural networks' predictions!

Deep learning models trained to correct input errors in short, message-like text