Jax

Latest version: v0.4.35

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0.1.76

* [GitHub commits](https://github.com/jax-ml/jax/compare/jax-v0.1.75...jax-v0.1.76).

0.1.75

* [GitHub commits](https://github.com/jax-ml/jax/compare/jax-v0.1.74...jax-v0.1.75).
* Bug Fixes:
* make jnp.abs() work for unsigned inputs (3914)
* Improvements:
* "Omnistaging" behavior added behind a flag, disabled by default (3370)

0.1.74

* [GitHub commits](https://github.com/jax-ml/jax/compare/jax-v0.1.73...jax-v0.1.74).
* New Features:
* BFGS (3101)
* TPU support for half-precision arithmetic (3878)
* Bug Fixes:
* Prevent some accidental dtype warnings (3874)
* Fix a multi-threading bug in custom derivatives (3845, 3869)
* Improvements:
* Faster searchsorted implementation (3873)
* Better test coverage for jax.numpy sorting algorithms (3836)

jaxlib 0.1.52 (July 22, 2020)

* Update XLA.

0.1.73

* [GitHub commits](https://github.com/jax-ml/jax/compare/jax-v0.1.72...jax-v0.1.73).
* The minimum jaxlib version is now 0.1.51.
* New Features:
* jax.image.resize. (3703)
* hfft and ihfft (3664)
* jax.numpy.intersect1d (3726)
* jax.numpy.lexsort (3812)
* `lax.scan` and the `scan` primitive support an `unroll`
parameter for loop unrolling when lowering to XLA
({jax-issue}`3738`).
* Bug Fixes:
* Fix reduction repeated axis error (3618)
* Fix shape rule for lax.pad for input dimensions of size 0. (3608)
* make psum transpose handle zero cotangents (3653)
* Fix shape error when taking JVP of reduce-prod over size 0 axis. (3729)
* Support differentiation through jax.lax.all_to_all (3733)
* address nan issue in jax.scipy.special.zeta (3777)
* Improvements:
* Many improvements to jax2tf
* Reimplement argmin/argmax using a single pass variadic reduction. (3611)
* Enable XLA SPMD partitioning by default. (3151)
* Add support for 0d transpose convolution (3643)
* Make LU gradient work for low-rank matrices (3610)
* support multiple_results and custom JVPs in jet (3657)
* Generalize reduce-window padding to support (lo, hi) pairs. (3728)
* Implement complex convolutions on CPU and GPU. (3735)
* Make jnp.take work for empty slices of empty arrays. (3751)
* Relax dimension ordering rules for dot_general. (3778)
* Enable buffer donation for GPU. (3800)
* Add support for base dilation and window dilation to reduce window op… (3803)

jaxlib 0.1.51 (July 2, 2020)

* Update XLA.
* Add new runtime support for host_callback.

0.1.72

* [GitHub commits](https://github.com/jax-ml/jax/compare/jax-v0.1.71...jax-v0.1.72).
* Bug fixes:
* Fix an odeint bug introduced in the previous release, see
{jax-issue}`3587`.

0.1.71

* [GitHub commits](https://github.com/jax-ml/jax/compare/jax-v0.1.70...jax-v0.1.71).
* The minimum jaxlib version is now 0.1.48.
* Bug fixes:
* Allow `jax.experimental.ode.odeint` dynamics functions to close over
values with respect to which we're differentiating
{jax-issue}`3562`.

jaxlib 0.1.50 (June 25, 2020)

* Add support for CUDA 11.0.
* Drop support for CUDA 9.2 (we only maintain support for the last four CUDA
versions.)
* Update XLA.

jaxlib 0.1.49 (June 19, 2020)

* Bug fixes:
* Fix build issue that could result in slow compiles
(<https://github.com/tensorflow/tensorflow/commit/f805153a25b00d12072bd728e91bb1621bfcf1b1>)

jaxlib 0.1.48 (June 12, 2020)

* New features:
* Adds support for fast traceback collection.
* Adds preliminary support for on-device heap profiling.
* Implements `np.nextafter` for `bfloat16` types.
* Complex128 support for FFTs on CPU and GPU.
* Bug fixes:
* Improved float64 `tanh` accuracy on GPU.
* float64 scatters on GPU are much faster.
* Complex matrix multiplication on CPU should be much faster.
* Stable sorts on CPU should actually be stable now.
* Concurrency bug fix in CPU backend.

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