# PyTorch

- Category: AI platforms
- Official site: https://pytorch.org/
- HTML: https://www.88z.ai/en/tools/pytorch
- Markdown: https://www.88z.ai/en/tools/pytorch.md

An open-source deep learning framework backed by the PyTorch Foundation, enablin

## What is PyTorch?

PyTorch is an open-source deep learning framework hosted by the PyTorch Foundation, designed to provide developers with flexible and powerful tools for building AI applications.It supports the entire workflow from experimental research to large-scale production deployment, backed by an active community and a rich ecosystem.

The framework features production-ready capabilities, allowing users to switch seamlessly between eager and graph modes via TorchScript and accelerate model deployment with TorchServe.Its robust ecosystem covers domains such as computer vision and NLP, with strong support across major cloud platforms.

## Key features

- **Production Ready**：Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe.
- **Distributed Trai**：Scalable distributed training and performance optimization in research and production enabled by the torch.distributed backend.
- **Robust Ecosystem**：A rich ecosystem of tools and libraries extends PyTorch, supporting development in computer vision, NLP, and more, including projects like Captum and PyTorch Geometric.
- **Cloud Support**：Well supported on major cloud platforms like AWS, Google Cloud, Microsoft Azure, and Alibaba Cloud, providing frictionless development and easy scaling.
- **Flexible Install**：Supports Linux, Mac, and Windows, offering various packages like Pip and LibTorch, compatible with compute platforms such as CUDA and ROCm.

## How to use it

1. Visit the official website to use the installation command generator, selecting your OS, package manager, language, and compute platform.
2. Install PyTorch in your local environment using the generated command (e.g., pip3 install torch...).
3. Explore the 'Get Started' guide or 'PyTorch Recipes' in the official documentation to learn the basics.
4. Deploy trained models to production using TorchServe or scale them using supported cloud platforms.
5. Join the PyTorch community forums or working groups to access developer resources and support.

## Where it fits

- **Academic Researc**：Leverage PyTorch's flexibility to efficiently research new algorithmic approaches, as demonstrated by Stanford University.
- **Large-Scale Pret**：Supports training trillion-parameter Mixture-of-Experts (MoE) models on public infrastructure.
- **Enterprise Infer**：Helps enterprises reduce inference costs and scale services, as seen in the Amazon Advertising case study.

## Pricing and free quota

PyTorch is an open-source framework and is free to use.Specific cloud service costs depend on the chosen cloud provider.

## Who it is for

- Deep Learning Researchers
- AI Application Developers
- Data Scientists
- Machine Learning Engineers

## FAQ

### What Python version does PyTorch require?

The latest stable version of PyTorch requires Python 3.10 or later.

### Which cloud platforms support PyTorch?

PyTorch is well supported on major cloud platforms including AWS, Google Cloud Platform, Microsoft Azure, and Alibaba Cloud.

### How can I accelerate production deployment of PyTorch models?

You can use TorchServe to accelerate model deployment and switch between eager and graph modes using TorchScript for performance optimization.

## Tags

Deep Learning · Open Source Framework · Distributed Training

Features, pricing and availability follow the official site. Except for 88z.ai’s own API pages, this is a third-party product; 88z.ai only provides a directory introduction.