Paketti: python3-torch-geometric (2.4.0-2)

[ Source: pytorch-geometric  ]

Graph Neural Network Library for PyTorch

PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.

It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support, distributed graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds.

Muut pakettiin python3-torch-geometric liittyvät paketit

• dep: python3

  interactive high-level object-oriented language (default python3 version)

• dep: python3-jinja2

  small but fast and easy to use stand-alone template engine

• dep: python3-numpy

  Fast array facility to the Python language (Python 3)

• dep: python3-psutil

  module providing convenience functions for managing processes (Python3)

• dep: python3-pyparsing

  alternative to creating and executing simple grammars - Python 3.x

• dep: python3-requests

  elegant and simple HTTP library for Python3, built for human beings

• dep: python3-scipy

  scientific tools for Python 3

• dep: python3-sklearn

  Python modules for machine learning and data mining - Python 3

• dep: python3-tqdm

  fast, extensible progress bar for Python 3 and CLI tool

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Arkkitehtuuri	Paketin koko	Koko asennettuna	Tiedostot
all	495.3 kt	3,600.0 kt	[tiedostoluettelo]