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《PyTorch documentation》(PyTorch 文档)

2025/5/1 15:46:10 来源:https://blog.csdn.net/zheng_ruiguo/article/details/147637175  浏览:    关键词:《PyTorch documentation》(PyTorch 文档)

PyTorch documentation(PyTorch 文档

PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.

(PyTorch是一个优化的张量库,用于使用GPU和CPU进行深度学习。)

Features described in this documentation are classified by release status:

(此留档中描述的功能按发布状态分类:)

Stable: These features will be maintained long-term and there should generally be no major performance limitations or gaps in documentation. We also expect to maintain backwards compatibility (although breaking changes can happen and notice will be given one release ahead of time).

稳定:这些特性将长期保持,通常不应该有主要的性能限制或留档差距。我们还希望保持向后兼容性(尽管可能会发生重大更改,并且会提前通知一个版本)。

Beta: These features are tagged as Beta because the API may change based on user feedback, because the performance needs to improve, or because coverage across operators is not yet complete. For Beta features, we are committing to seeing the feature through to the Stable classification. We are not, however, committing to backwards compatibility.

测试版:这些功能被标记为测试版,因为应用编程接口可能会根据用户反馈而改变,因为性能需要提高,或者因为跨运营商的覆盖尚未完成。对于测试版功能,我们承诺将该功能纳入稳定分类。但是,我们不承诺向后兼容。

Prototype: These features are typically not available as part of binary distributions like PyPI or Conda, except sometimes behind run-time flags, and are at an early stage for feedback and testing.

原型:这些功能通常不能作为PyPI或Conda等二进制发行版的一部分提供,除非有时在运行时标志之后,并且处于反馈和测试的早期阶段。

Community(社区)

  • PyTorch Governance | Build + CI
  • PyTorch Contribution Guide
  • PyTorch Design Philosophy
  • PyTorch Governance | Mechanics
  • PyTorch Governance | Maintainers

Developer Notes(开发者笔记

  • Automatic Mixed Precision examples
  • Autograd mechanics
  • Broadcasting semantics
  • CPU threading and TorchScript inference
  • CUDA semantics
  • PyTorch Custom Operators Landing Page
  • Distributed Data Parallel
  • Extending PyTorch

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