kjappelbaum / pyepal

Multiobjective active learning with tunable accuracy/efficiency tradeoff and clear stopping criterion.
Apache License 2.0
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chore(deps-dev): update jaxlib requirement from <=0.1.65 to <0.4.4 #279

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Updates the requirements on jaxlib to permit the latest version.

Changelog

Sourced from jaxlib's changelog.

jax 0.4.3 (Feb 8, 2023)

  • Breaking changes

    • Deleted {func}jax.scipy.linalg.polar_unitary, which was a deprecated JAX extension to the scipy API. Use {func}jax.scipy.linalg.polar instead.
  • Changes

    • Added {func}jax.scipy.stats.rankdata.

jaxlib 0.4.3 (Feb 8, 2023)

jax 0.4.2 (Jan 24, 2023)

  • Breaking changes

    • Deleted jax.experimental.callback
    • Operations with dimensions in presence of jax2tf shape polymorphism have been generalized to work in more scenarios, by converting the symbolic dimension to JAX arrays. Operations involving symbolic dimensions and np.ndarray now can raise errors when the result is used as a shape value ({jax-issue}[#14106](https://github.com/google/jax/issues/14106)).
    • jaxpr objects now raise an error on attribute setting in order to avoid problematic mutations ({jax-issue}14102)
  • Changes

    • {func}jax2tf.call_tf has a new parameter has_side_effects (default True) that can be used to declare whether an instance can be removed or replicated by JAX optimizations such as dead-code elimination ({jax-issue}[#13980](https://github.com/google/jax/issues/13980)).
    • Added more support for floordiv and mod for jax2tf shape polymorphism. Previously, certain division operations resulted in errors in presence of symbolic dimensions ({jax-issue}[#14108](https://github.com/google/jax/issues/14108)).

jaxlib 0.4.2 (Jan 24, 2023)

  • Changes
    • Set JAX_USE_PJRT_C_API_ON_TPU=1 to enable new Cloud TPU runtime, featuring automatic device memory defragmentation.

jax 0.4.1 (Dec 13, 2022)

  • Changes
    • Support for Python 3.7 has been dropped, in accordance with JAX's {ref}version-support-policy.
    • We introduce jax.Array which is a unified array type that subsumes DeviceArray, ShardedDeviceArray, and GlobalDeviceArray types in JAX. The jax.Array type helps make parallelism a core feature of JAX, simplifies and unifies JAX internals, and allows us to unify jit and pjit. jax.Array has been enabled by default in JAX 0.4 and makes some breaking change to the pjit API. The jax.Array migration guide can help you migrate your codebase to jax.Array. You can also look at the Distributed arrays and automatic parallelization

... (truncated)

Commits
  • 7783a5e Merge pull request #14343 from skye:cache_options_check
  • 1228cbd Change the executable_build_options check in compilation_cache.py to be more ...
  • a46f31b Merge pull request #14342 from skye:version
  • 8ab1585 Update WORKSPACE and setup.py for jax/jaxlib 0.4.3 release
  • eb13c05 Add option to run tests with persistent compilation cache enabled.
  • 6860cb8 Move jax.interpreters.xla to jax._src.interpreters.xla.
  • 9c827fb Merge pull request #14340 from ROCmSoftwarePlatform:rocm_reenable_linalg_spar...
  • 01a10a1 [ROCm] Re-enable some linalg and sparse tests
  • 8eb00c5 Merge pull request #14335 from jakevdp:doc-transformations
  • a022a4e DOC: remove transformations.md
  • Additional commits viewable in compare view


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dependabot[bot] commented 1 year ago

Superseded by #281.