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Update README.md and CHANGELOG.md.

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Peter Hawkins 2020-01-28 09:57:15 -05:00
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These are the release notes for JAX.
## jax 0.1.58 (unreleased)
## jax 0.1.59 (unreleased)
## jax 0.1.58
### Breaking changes
* JAX has dropped Python 2 support, because Python 2 reached its end of life on
January 1, 2020. Please update to Python 3.5 or newer.
### New features
- Forward AD of while loop (https://github.com/google/jax/pull/1980)
* Forward-mode automatic differentiation (`jvp`) of while loop
(https://github.com/google/jax/pull/1980)
* New NumPy and SciPy functions:
* `jax.numpy.fft.fft2`
* `jax.numpy.fft.ifft2`
* `jax.numpy.fft.rfft`
* `jax.numpy.fft.irfft`
* `jax.numpy.fft.rfft2`
* `jax.numpy.fft.irfft2`
* `jax.numpy.fft.rfftn`
* `jax.numpy.fft.irfftn`
* `jax.numpy.fft.fftfreq`
* `jax.numpy.fft.rfftfreq`
* `jax.numpy.linalg.matrix_rank`
* `jax.numpy.linalg.matrix_power`
* `jax.scipy.special.betainc`
* Batched Cholesky decomposition on GPU now uses a more efficient batched
kernel.
### Notable bug fixes
* With the Python 3 upgrade, JAX no longer depends on `fastcache`, which should
help with installation.

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| [**Install guide**](#installation)
| [**Reference docs**](https://jax.readthedocs.io/en/latest/)
## Announcements
* `jax` 0.1.58 has been released. As of `jax` 0.1.58, JAX has dropped Python 2
support. Please update to Python 3.5 or newer.
## What is JAX?
JAX is [Autograd](https://github.com/hips/autograd) and
[XLA](https://www.tensorflow.org/xla),
brought together for high-performance machine learning research.