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asmith26 / jax_toolkit

A collection of jax functions to help with common machine/deep learning related functionality.
https://asmith26.github.io/jax_toolkit/
Apache License 2.0
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Bump jax from 0.2.8 to 0.2.14 #197

Closed dependabot[bot] closed 3 years ago

dependabot[bot] commented 3 years ago

Bumps jax from 0.2.8 to 0.2.14.

Changelog

Sourced from jax's changelog.

jax 0.2.14 (unreleased)

jax 0.2.14 (June 10 2021)

  • GitHub commits.

  • New features:

    • The {func}jax2tf.convert now has support for pjit and sharded_jit.

    • A new configuration option JAX_TRACEBACK_FILTERING controls how JAX filters tracebacks.

    • A new traceback filtering mode using __tracebackhide__ is now enabled by default in sufficiently recent versions of IPython.

    • The {func}jax2tf.convert supports shape polymorphism even when the unknown dimensions are used in arithmetic operations, e.g., jnp.reshape(-1) ({jax-issue}[#6827](https://github.com/google/jax/issues/6827)).

    • The {func}jax2tf.convert generates custom attributes with location information in TF ops. The code that XLA generates after jax2tf has the same location information as JAX/XLA.

  • Breaking changes:

  • Bug fixes:

    • The {func}jax2tf.convert now ensures that it uses the same typing rules for Python scalars and for choosing 32-bit vs. 64-bit computations as JAX ({jax-issue}[#6883](https://github.com/google/jax/issues/6883)).
    • The {func}jax2tf.convert now scopes the enable_xla conversion parameter properly to apply only during the just-in-time conversion ({jax-issue}[#6720](https://github.com/google/jax/issues/6720)).
    • The {func}jax2tf.convert now converts lax.dot_general using the XlaDot TensorFlow op, for better fidelity w.r.t. JAX numerical precision ({jax-issue}[#6717](https://github.com/google/jax/issues/6717)).
    • The {func}jax2tf.convert now has support for inequality comparisons and min/max for complex numbers ({jax-issue}[#6892](https://github.com/google/jax/issues/6892)).

jaxlib 0.1.67 (unreleased)

jaxlib 0.1.66 (May 11 2021)

  • New features:

    • CUDA 11.1 wheels are now supported on all CUDA 11 versions 11.1 or higher.

      NVidia now promises compatibility between CUDA minor releases starting with CUDA 11.1. This means that JAX can release a single CUDA 11.1 wheel that is compatible with CUDA 11.2 and 11.3.

      There is no longer a separate jaxlib release for CUDA 11.2 (or higher); use the CUDA 11.1 wheel for those versions (cuda111).

    • Jaxlib now bundles libdevice.10.bc in CUDA wheels. There should be no need to point JAX to a CUDA installation to find this file.

... (truncated)

Commits
  • 3d1a6a3 Merge pull request #6945 from skye:version
  • e8068c0 Merge pull request #6943 from jakevdp:bcoo-todense-fix
  • 063401f Update jax version to 0.2.14
  • 42b540c Merge pull request #6942 from skye:tpu_driver_version
  • 72fe3ba bcoo_todense: fix corner case
  • 4abac4f Pin the tpu_driver version used for Cloud TPU Colabs, instead of using nightly.
  • d622d5c Merge pull request #6939 from 8bitmp3:patch-1
  • 888db31 [jax2tf] Fix passing of indices_are_sorted to the TF XlaGather op
  • 8568aee Add missing back ticks to fix jax2tf README Markdown rendering in Different 6...
  • f67acb9 Merge pull request #6937 from mariosasko:specify-zip-safe
  • Additional commits viewable in compare view


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dependabot[bot] commented 3 years ago

Superseded by #206.