论文标题
热切：编写与Pytorch，Tensorflow，Jax和Numpy本地合作的代码
EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy
论文作者
论文摘要
热切是一个Python框架，可让您编写与Pytorch，Tensorflow，Jax和Numpy自动使用的代码。图书馆开发人员不再需要在仅支持这些框架之一或为每个框架重新实现库和处理代码复制之间进行选择。此类库的用户可以更轻松地切换框架，而不会被特定的第三方库锁定。除了多框架的支持之外，急切还为任何框架带来了全面的类型注释和对方法链的一致支持。最新的文档可在https://eagerpy.jonasrauber.de上在线获得，并且代码可以在https://github.com/jonasrauber/eagerpy上找到。
EagerPy is a Python framework that lets you write code that automatically works natively with PyTorch, TensorFlow, JAX, and NumPy. Library developers no longer need to choose between supporting just one of these frameworks or reimplementing the library for each framework and dealing with code duplication. Users of such libraries can more easily switch frameworks without being locked in by a specific 3rd party library. Beyond multi-framework support, EagerPy also brings comprehensive type annotations and consistent support for method chaining to any framework. The latest documentation is available online at https://eagerpy.jonasrauber.de and the code can be found on GitHub at https://github.com/jonasrauber/eagerpy.
