chore(deps-dev): update jaxlib requirement from <=0.1.65 to <=0.4.30

[dependabot]

Updates the requirements on jaxlib to permit the latest version.

Changelog

Sourced from jaxlib's changelog.

jax 0.4.30 (June 18, 2024)

• Changes

  • JAX supports ml_dtypes >= 0.2. In 0.4.29 release, the ml_dtypes version was bumped to 0.4.0 but this has been rolled back in this release to give users of both TensorFlow and JAX more time to migrate to a newer TensorFlow release.
  • jax.experimental.mesh_utils can now create an efficient mesh for TPU v5e.
  • jax now depends on jaxlib directly. This change was enabled by the CUDA plugin switch: there are no longer multiple jaxlib variants. You can install a CPU-only jax with pip install jax, no extras required.
  • Added an API for exporting and serializing JAX functions. This used to exist in jax.experimental.export (which is being deprecated), and will now live in jax.export. See the documentation.

• Deprecations

  • Internal pretty-printing tools jax.core.pp_* are deprecated, and will be removed in a future release.
  • Hashing of tracers is deprecated, and will lead to a TypeError in a future JAX release. This previously was the case, but there was an inadvertent regression in the last several JAX releases.
  • jax.experimental.export is deprecated. Use {mod}jax.export instead. See the migration guide.
  • Passing an array in place of a dtype is now deprecated in most cases; e.g. for arrays x and y, x.astype(y) will raise a warning. To silence it use x.astype(y.dtype).
  • jax.xla_computation is deprecated and will be removed in a future release. Please use the AOT APIs to get the same functionality as jax.xla_computation.
    • jax.xla_computation(fn)(*args, **kwargs) can be replaced with jax.jit(fn).lower(*args, **kwargs).compiler_ir('hlo').
    • You can also use .out_info property of jax.stages.Lowered to get the output information (like tree structure, shape and dtype).
    • For cross-backend lowering, you can replace jax.xla_computation(fn, backend='tpu')(*args, **kwargs) with jax.jit(fn).trace(*args, **kwargs).lower(lowering_platforms=('tpu',)).compiler_ir('hlo').

jaxlib 0.4.30 (June 18, 2024)

• Support for monolithic CUDA jaxlibs has been dropped. You must use the plugin-based installation (pip install jax[cuda12] or pip install jax[cuda12_local]).

jax 0.4.29 (June 10, 2024)

• Changes
  • We anticipate that this will be the last release of JAX and jaxlib supporting a monolithic CUDA jaxlib. Future releases will use the CUDA plugin jaxlib (e.g. pip install jax[cuda12]).
  • JAX now requires ml_dtypes version 0.4.0 or newer.

... (truncated)

Commits

• f4158ac Merge pull request #21949 from hawkinsp:winwheel
• b0b0268 Add --allow-downgrade to Windows wheel builds.
• 5d35c99 Merge pull request #21945 from hawkinsp:release
• d7bc6b4 Update XLA dependency to use revision
• 3f4f79c Prepare for 0.4.30 release.
• dfcfb36 Pallas GPU no longer falls back to lax.pow for integer powers
• 5bfd6af Removed unnecessary skip in pallas_test.py::SoftmaxTest
• 3fd9326 [jax] Enable api_test with XLA:CPU thunks
• ed4958c [XLA:Mosaic] Add internal scratch VMEM
• 701c63e [Pallas/TPU] Add API for megacore partitioning of pipelines
• Additional commits viewable in compare view

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Summary by Sourcery

Chores:

• Update jaxlib requirement from <=0.1.65 to <=0.4.30

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request updates the jaxlib dependency version for the neural_tangents and all extra requirements in setup.cfg. The upper bound of the allowed version is increased from 0.1.65 to 0.4.30.

No diagrams generated as the changes look simple and do not need a visual representation.

File-Level Changes

Change	Details	Files
Update the maximum allowed version of the jaxlib dependency for neural_tangents and all extra requirements.	Increased the upper bound of the jaxlib dependency from 0.1.65 to 0.4.30 for the neural_tangents extra requirement. Increased the upper bound of the jaxlib dependency from 0.1.65 to 0.4.30 for the all extra requirement.	setup.cfg

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