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.

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.

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.

This package is an integration module of Optuna, an automatic Hyperparameter optimization software framework. The modules in this package provide users with extended functionalities for Optuna in combination with third-party libraries such as PyTorch, sklearn, and TensorFlow.

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 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.

PyThresh is a comprehensive and scalable Python toolkit for thresholding outlier detection likelihood scores in univariate/multivariate data. It has been written to work in tandem with PyOD and has similar syntax and data structures. However, it is not limited to this single library.

PyThresh is meant to threshold likelihood scores generated by an outlier detector. It thresholds these likelihood scores and replaces the need to set a contamination level or have the user guess the amount of outliers that may exist in the dataset beforehand. These non-parametric methods were written to reduce the user's input/guess work and rather rely on statistics instead to threshold outlier likelihood scores. For thresholding to be applied correctly, the outlier detection likelihood scores must follow this rule: the higher the score, the higher the probability that it is an outlier in the dataset. All threshold functions return a binary array where inliers and outliers are represented by a 0 and 1 respectively.

PyThresh includes more than 30 thresholding algorithms. These algorithms range from using simple statistical analysis like the Z-score to more complex mathematical methods that involve graph theory and topology.

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.

This package provides a neural network library for PyTorch compatible with the scikit-learn API.

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.

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.

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation and providing a delightful developer experience.

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.

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.

DOLFINx is the computational environment of FEniCSx and implements the FEniCS Problem Solving Environment in C++ and Python.

This package provides the C++ interface.

Grace is a 2D plotting tool for the X Window System. It has a Motif-based GUI and a scripting language that includes curve fitting, analysis, and export capabilities.

FFCx is a compiler for finite element variational forms.

From a high-level description of the form in the UFL, it generates efficient low-level C code that can be used to assemble the corresponding discrete operator (tensor). In particular, a bilinear form may be assembled into a matrix and a linear form may be assembled into a vector.

This package provides the CLI and Python library.

DBCSR is a library designed to efficiently perform sparse matrix-matrix multiplication, among other operations. It is MPI and OpenMP parallel and can exploit Nvidia and AMD GPUs via CUDA and HIP.

DOLFINx is the computational environment of FEniCSx and implements the FEniCS Problem Solving Environment in C++ and Python.

This package provides the Python interface.

The Unified Form Language (UFL) is a domain specific language for declaration of finite element discretizations of variational forms. More precisely, it defines a flexible interface for choosing finite element spaces and defining expressions for weak forms in a notation close to mathematical notation.

Basix is a finite element definition and tabulation runtime library.

Basix allows users to:

• evaluate finite element basis functions and their derivatives at a set of points;

• access geometric and topological information about reference cells;

• apply push forward and pull back operations to map data between a reference cell and a physical cell;

• permute and transform DOFs to allow higher-order elements to be use on arbitrary meshes;

• interpolate into and between finite element spaces.

Basix includes a range of built-in elements, and also allows the user to define their own custom elements.

This package provides the Python wrapper for Basix.

FFCx is a compiler for finite element variational forms.

From a high-level description of the form in the UFL, it generates efficient low-level C code that can be used to assemble the corresponding discrete operator (tensor). In particular, a bilinear form may be assembled into a matrix and a linear form may be assembled into a vector.

This package provides the UFCx interface header.

The Linear Algebra PACKage (LAPACK) is a standard software library for numerical linear algebra. The objective of LAPACK++ is to provide a convenient, performance oriented API for development in the C++ language, that, for the most part, preserves established conventions, while, at the same time, takes advantages of modern C++ features, such as: namespaces, templates, exceptions, etc.