Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.
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GET /api/packages?search=hello&page=1&limit=20
where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned
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This package provides tools for automated download of UMLS data.
This package provides a Python module for finding installed BLAS library in a system, along with its headers. It is intended to be used for easily linking Cython-wrapped C/C++ code that calls BLAS functions to the corresponding system's library.
This package provides utilities for downloading several URL as one, as well as supporting multi-part URLs.
Click is a package for creating powerful and beautiful command line interfaces (CLI) in Python, but it has no the functionality for creating option groups. The aim of this package is to provide group options with extensible functionality using canonical and clean API (Click-like API as far as possible).
ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.
ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.
This library implements support for mixed precision training in JAX. It provides two key abstractions. These abstractions are mixed precision policies and loss scaling.
JAXopt provides hardware accelerated, batchable and differentiable optimizers in JAX.
Hardware accelerated: the implementations run on GPU and TPU, in addition to CPU.
Batchable: multiple instances of the same optimization problem can be automatically vectorized using JAX’s
vmap.Differentiable: optimization problem solutions can be differentiated with respect to their inputs either implicitly or via autodiff of unrolled algorithm iterations.
TensorFlow is a flexible platform for building and training machine learning models. It provides a library for high performance numerical computation and includes high level Python APIs, including both a sequential API for beginners that allows users to build models quickly by plugging together building blocks and a subclassing API with an imperative style for advanced research.
TensorFlow is a flexible platform for building and training machine learning models. It provides a library for high performance numerical computation and includes high level Python APIs, including both a sequential API for beginners that allows users to build models quickly by plugging together building blocks and a subclassing API with an imperative style for advanced research.
ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.
This module contains classes for the object model defined by the Static Analysis Results Interchange Format (SARIF) file format.
Optax is a gradient processing and optimization library for JAX.
NumPyro is a lightweight probabilistic programming library that provides a NumPy backend for Pyro. It relies on JAX for automatic differentiation and JIT compilation to GPU / CPU.
This is a collection of independent Python modules providing utilities for various projects.
Chex is a library of utilities for helping to write reliable JAX code. This includes utils to help:
Instrument your code (e.g. assertions)
Debug (e.g. transforming
pmapsinvmapswithin a context manager).Test JAX code across many
variants(e.g. jitted vs non-jitted).
This package provides tools for Makefile execution powered by pure Python.
Protocol buffers are a language-neutral, platform-neutral extensible mechanism for serializing structured data.
TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of probabilistic methods with deep networks, gradient-based inference via automatic differentiation, and scalability to large datasets and models via hardware acceleration (e.g., GPUs) and distributed computation.
The h5py package provides both a high- and low-level interface to the HDF5 library from Python. The low-level interface is intended to be a complete wrapping of the HDF5 API, while the high-level component supports access to HDF5 files, datasets and groups using established Python and NumPy concepts.
JAX is Autograd and XLA, brought together for high-performance numerical computing, including large-scale machine learning research. With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order.
JAX is Autograd and XLA, brought together for high-performance numerical computing, including large-scale machine learning research. With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order.
ScotchPy is a python module to interface the Scotch/PT-Scotch graph partitioner library.
This package is part of the [React Native CLI](../../README.md). It contains commands for diagnosing and fixing common Node.js, iOS, Android & React Native issues.