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improved the readme
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Jonas Rauber committed Feb 14, 2020
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<a href="https://jonasrauber.github.io/eagerpy/"><img src="https://raw.githubusercontent.com/jonasrauber/eagerpy/master/docs/.vuepress/public/logo_small.png" align="right" /></a>

======================================================================================
EagerPy: PyTorch, TensorFlow, JAX and NumPy — all of them natively using the same code
======================================================================================

`EagerPy <https://jonasrauber.github.io/eagerpy/>`_ is a **Python framework** that let's you write code that automatically works natively with `PyTorch <https://pytorch.org>`_, `TensorFlow <https://www.tensorflow.org>`_, `JAX <https://github.com/google/jax>`_, and `NumPy <https://numpy.org>`_.

EagerPy is **also great when you work with just one framework** but prefer a clean and consistent NumPy-inspired API that is fully chainable, provides extensive type annotions and let's you write beautiful code. It often combines the best of PyTorch's API and NumPy's API.

.. image:: https://badge.fury.io/py/eagerpy.svg
:target: https://badge.fury.io/py/eagerpy

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.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
:target: https://github.com/ambv/black

.. image:: https://raw.githubusercontent.com/jonasrauber/eagerpy/master/docs/.vuepress/public/logo_small.png
:target: https://jonasrauber.github.io/eagerpy/
:align: right

=======
EagerPy
=======

`EagerPy <https://jonasrauber.github.io/eagerpy/>`_ is a **Python framework** that let's you write code that automatically works natively with `PyTorch <https://pytorch.org>`_, `TensorFlow <https://www.tensorflow.org>`_, `JAX <https://github.com/google/jax>`_, and `NumPy <https://numpy.org>`_.

EagerPy is **also great when you work with just one framework** but prefer a clean and consistent NumPy-inspired API that is fully chainable, provides extensive type annotions and let's you write beautiful code. It often combines the best of PyTorch's API and NumPy's API.

🔥 Design goals
--------------
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- **Fully Chainable**: All functionality is available as methods on the tensor objects and as EagerPy functions.
- **Type Checking**: Catch bugs before running your code thanks to EagerPy's extensive type annotations.


📖 Documentation
---------------

Learn more about in the `documentation <https://jonasrauber.github.io/eagerpy/>`_.


🚀 Quickstart
------------

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# and return a native tensor
return result.raw
🗺 Use cases
-----------

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using EagerPy instead of NumPy to achieve native performance on models
developed in PyTorch, TensorFlow and JAX, all with one code base.


🐍 Compatibility
---------------

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