Datasets is a lightweight library providing access to major public datasets (image, audio, text, etc.), as well as enabling efficient data preparation for inspection and ML model evaluation and training.

keopscore is the KeOps meta programming engine. This python module should be used through a binder (e.g. pykeops or rkeops).

Equinox is a comprehensive JAX library that provides a wide range of tools and features not found in core JAX, including neural networks with PyTorch-like syntax, filtered APIs for transformations, PyTree manipulation routines, and advanced features like runtime errors.

imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance.

This package provides a Python library for outlier and anomaly detection, integrating classical and deep learning techniques .

PyDMD is a Python package designed for Dynamic Mode Decomposition (DMD), a data-driven method used for analyzing and extracting spatiotemporal coherent structures from time-varying datasets. It provides a comprehensive and user-friendly interface for performing DMD analysis, making it a valuable tool for researchers, engineers, and data scientists working in various fields.

PyTorch extension for handling deeply nested sequences of variable length.

Melissa is a file-avoiding, adaptive, fault-tolerant and elastic framework, to run large-scale sensitivity analysis or deep-surrogate training on supercomputers. This package builds the API used when instrumenting the clients.

ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. ruptures focuses on ease of use by providing a well-documented and consistent interface. In addition, thanks to its modular structure, different algorithms and models can be connected and extended within this package.

Orbax is a namespace providing common utility libraries for JAX users. Orbax also includes a serialization library for JAX users, enabling the exporting of JAX models to the TensorFlow SavedModel format.

TensorStore is a C++ and Python software library designed for storage and manipulation of large multi-dimensional arrays that:

• Provides advanced, fully composable indexing operations and virtual views.

• Provides a uniform API for reading and writing multiple array formats, including zarr and N5.

• Natively supports multiple storage systems, such as local and network filesystems, Google Cloud Storage, Amazon S3-compatible object stores, HTTP servers, and in-memory storage.

• Offers an asynchronous API to enable high-throughput access even to high-latency remote storage.

• Supports read caching and transactions, with strong atomicity, isolation, consistency, and durability (ACID) guarantees.

• Supports safe, efficient access from multiple processes and machines via optimistic concurrency.

Python bindings for KeOps, on CPUs and GPUs, with autodiff and without memory overflows.

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute. These are the provided Ray AI libraries:

• Data: Scalable datasets for ML;

• Train: Distributed training;

• Tune: Scalable hyperparameter tuning;

• RLlib: Scalable reinforcement learning;

• Serve: Scalable and programmable serving.

EZyRB is a python library for the Model Order Reduction based on baricentric triangulation for the selection of the parameter points and on Proper Orthogonal Decomposition for the selection of the modes.

This package provides a library for sending commands and receiving replies to and from a Redis server. It comes with a synchronous API, asynchronous API and reply parsing API. Only the binary-safe Redis protocol is supported.

Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16. It abstracts exactly and only the boilerplate code related to multi-GPUs/TPU/fp16 and leaves the rest of your code unchanged.

Flax is a neural network library for JAX that is designed for flexibility.

Haiku is a simple neural network library for JAX. It is developed by some of the authors of Sonnet, a neural network library for TensorFlow.

Geomstats is an open-source Python package for computations, statistics, and machine learning on nonlinear manifolds. Data from many application fields are elements of manifolds. For instance, the manifold of 3D rotations SO(3) naturally appears when performing statistical learning on articulated objects like the human spine or robotics arms. Likewise, shape spaces modeling biological shapes or other natural shapes are manifolds.

This package provides a set of custom transformers, metrics and models complementing scikit-learn, which results from a collaboration between multiple companies in the Netherlands.

AlphaFold is an AI system developed by DeepMind that predicts a protein’s 3D structure from its amino acid sequence. It regularly achieves accuracy competitive with experiment.

Python front-end in charge of orchestrating the execution a Melissa based study. It automatically handles large-scale scheduler interactions in OpenMPI and with common cluster schedulers (e.g. slurm or OAR).

This package provides a set of scikit-learn-style transformers for encoding categorical variables into numeric by means of different techniques.

This is a minimum version for checking the input argument dict. It would examine argument's type, as well as keys and types of its sub-arguments. A special case called variant is also handled, where you can determine the items of a dict based the value of on one of its flag_name key.