PyTorch is an open-source machine learning framework developed by Facebook's AI Research lab (FAIR). It provides a flexible and dynamic computational graph that enables developers to build and train deep learning models efficiently.

Features of PyTorch:

• PyTorch uses a dynamic computational graph, allowing for more flexible model architectures and easier debugging compared to static graph frameworks.
• It offers extensive support for tensor operations, making it suitable for various machine learning tasks, including neural networks, natural language processing, and computer vision.
• PyTorch provides seamless GPU acceleration, enabling faster training and inference of deep learning models on supported hardware.
• PyTorch enables the creation of dynamic neural networks, where the structure of the network can change during runtime, allowing for more adaptive and complex models.

Disclaimer: PyTorch is distributed under the BSD-style license and is provided free of charge. It is not affiliated with, endorsed by, or sponsored by any company. PyTorch is provided "as is," without any warranty, express or implied. Users utilize this software at their own risk. The developers and contributors to PyTorch hold no responsibility for any damages, losses, or consequences resulting from the use of this software. Users are advised to carefully review and comply with licensing terms and any applicable regulations while using PyTorch.