What is pytorch used for?

PyTorch is an open-source machine learning library that is primarily used for developing deep learning models. It was developed by Facebook's artificial intelligence research group and is widely used in both academia and industry.

PyTorch provides a flexible and dynamic computational graph that allows developers to easily build and train neural networks. It also includes a variety of tools and utilities to assist with tasks such as data loading, model visualization, and deployment.

Some key features of PyTorch include:

1. Dynamic computation graph: PyTorch uses a dynamic computation graph, which allows for more flexibility and easier debugging compared to static computation graphs used by other libraries like TensorFlow.

2. Support for GPU acceleration: PyTorch provides support for NVIDIA GPUs, allowing for faster training of deep learning models.

3. Extensive library of pre-trained models: PyTorch includes a wide range of pre-trained models for tasks such as image classification, object detection, and natural language processing.

4. Active community and ecosystem: PyTorch has a large and active community of developers and researchers who contribute to its development, as well as a growing ecosystem of libraries and tools to extend its functionality.

Overall, PyTorch is a powerful and versatile library for building deep learning models, and is widely used for a variety of applications such as image recognition, natural language processing, and reinforcement learning.