PyTorch
Open SourceOpen-source end-to-end machine learning framework for flexible experimentation and efficient production deployment.
Tool Information
What is PyTorch?
PyTorch is an open-source deep learning framework that enables fast, flexible experimentation and efficient production through a user-friendly front-end, distributed training, and an ecosystem of tools and libraries.
Core Features
Production Ready with TorchScript
Provides ease-of-use and flexibility in eager mode while seamlessly transitioning to graph mode for speed, optimization, and functionality in C++ runtime environments.
TorchServe
Easy-to-use tool for deploying PyTorch models at scale that is cloud and environment agnostic and supports multi-model serving, logging, metrics, and RESTful endpoints for application integration.
Distributed Training
Native support for asynchronous execution of collective operations and peer-to-peer communication accessible from Python and C++ to optimize performance in research and production.
Mobile Support
End-to-end workflow from Python to deployment on iOS and Android that extends the PyTorch API for common preprocessing and integration tasks needed for mobile applications (experimental).
Robust Ecosystem
Rich ecosystem of tools and libraries built by researchers and developers that extends PyTorch and supports development in areas from computer vision to reinforcement learning.
Native ONNX Support
Export models in the standard ONNX (Open Neural Network Exchange) format for direct access to ONNX-compatible platforms, runtimes, visualizers, and more.
Cloud Support
Well supported on major cloud platforms, providing frictionless development and easy scaling.
Use Cases
- #1
Flexible Machine Learning Experimentation
Rapid model prototyping and research using a user-friendly front-end with seamless transition from eager to graph mode.
- #2
Production Model Deployment
Deploy and serve PyTorch models at scale with TorchServe including multi-model serving and RESTful endpoints.
- #3
Large-Scale Distributed Training
Optimize training performance across multiple devices using native distributed backends for research and production workloads.
- #4
Mobile Machine Learning Applications
Incorporate ML models into iOS and Android applications with end-to-end Python-to-mobile workflow support.
- #5
Domain-Specific Development
Extend and apply models in computer vision, NLP, reinforcement learning, and related areas via the ecosystem of tools and libraries.
Pricing Plans
Free and open-source deep learning framework and ecosystem hosted by the PyTorch Foundation.
Alternatives
Frequently Asked Questions
What is PyTorch?
Is PyTorch free?
What platforms does PyTorch support?
How can I deploy PyTorch models in production?
Does PyTorch support distributed training?
Is mobile deployment supported?
What ecosystems and integrations does PyTorch offer?
PyTorch Contact & Social Media
- CompanyPyTorch Foundation
- Support
- Website:
- Twitter
- Facebook
- YouTube
- LinkedIn
- GitHub
- Discord
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