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Some package managers, including pip, use PyPI as the default source for packages and their dependencies. [6] [7] As of 6 May 2024, more than 530,000 Python packages are available. PyPI primarily hosts Python packages in the form of source archives, called "sdists", or of "wheels" [8] that may contain binary modules from a compiled language.
An output of pip install virtualenv. Pip's command-line interface allows the install of Python software packages by issuing a command: pip install some-package-name. Users can also remove the package by issuing a command: pip uninstall some-package-name. pip has a feature to manage full lists of packages and corresponding version numbers ...
revoscalepy is a machine learning package in Python created by Microsoft.It is available as part of Machine Learning Services in Microsoft SQL Server 2017 and Machine Learning Server 9.2.0 and later.
py2exe is a Python extension which converts Python scripts (.py) into Microsoft Windows executables (.exe). These executables can run on a system without Python installed. [3] ...
Beautiful Soup was started in 2004 by Leonard Richardson. [citation needed] It takes its name from the poem Beautiful Soup from Alice's Adventures in Wonderland [5] and is a reference to the term "tag soup" meaning poorly-structured HTML code. [6]
PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.
The Open Neural Network Exchange project was created by Meta and Microsoft in September 2017 for converting models between frameworks. Caffe2 was merged into PyTorch at the end of March 2018. [ 23 ] In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux ...
The library is designed to reduce computing power and memory use and to train large distributed models with better parallelism on existing computer hardware. [2] [3] DeepSpeed is optimized for low latency, high throughput training.