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PyTorch

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Open-source end-to-end machine learning framework for flexible experimentation and efficient production deployment.

Sitio web:https://pytorch.org/
Añadido en:13 jul 2026
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open sourcedeep learningmachine learningAI frameworkTorchScriptTorchServe
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Información de la herramienta

¿Qué es 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.

Características principales

  • 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.

Casos de uso

  • #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.

Lo mejor para:Machine learning researchersAI and deep learning developersProduction ML engineersData scientists working on computer vision, NLP, or reinforcement learning

Planes de precios

Free and open-source deep learning framework and ecosystem hosted by the PyTorch Foundation.

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Preguntas frecuentes

What is PyTorch?
PyTorch is an open-source end-to-end machine learning framework for flexible experimentation and efficient production deployment, featuring a user-friendly front-end, distributed training, and a rich ecosystem of tools and libraries.
Is PyTorch free?
Yes. PyTorch is free and open-source, hosted by the PyTorch Foundation.
What platforms does PyTorch support?
PyTorch supports Linux, macOS, Windows, iOS, and Android, along with CPU, CUDA, and ROCm compute platforms.
How can I deploy PyTorch models in production?
Use TorchServe for cloud- and environment-agnostic deployment at scale with multi-model serving, logging, metrics, and RESTful endpoints, or TorchScript to transition from eager mode to optimized graph mode for C++ runtimes.
Does PyTorch support distributed training?
Yes. It includes native support for asynchronous collective operations and peer-to-peer communication accessible from Python and C++ to optimize research and production workloads.
Is mobile deployment supported?
PyTorch offers an end-to-end workflow from Python to iOS and Android, extending the API for common preprocessing and integration tasks. Mobile support is experimental.
What ecosystems and integrations does PyTorch offer?
It provides a robust ecosystem of tools and libraries for computer vision, NLP, and reinforcement learning, native ONNX export, and well-supported integrations with major cloud platforms including Amazon Web Services, Google Cloud Platform, Microsoft Azure, and Lightning Studios.

PyTorch Contacto y redes sociales

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Información de la herramienta

Modelo de preciosOpen Source
CategoríaHerramientas para desarrolladores
Etiquetas
open sourcedeep learningmachine learningAI frameworkTorchScriptTorchServe
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Última actualización16 jul 2026
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