Bump jax from 0.3.17 to 0.4.5

[dependabot]

Bumps jax from 0.3.17 to 0.4.5.

Release notes

Sourced from jax's releases.

Jax release v0.4.4

No release notes provided.

Jaxlib release v0.4.4

No release notes provided.

JAX release v0.4.3

No release notes provided.

jaxlib release v0.4.3

No release notes provided.

JAX release v0.4.2

No release notes provided.

jaxlib release v0.4.2

No release notes provided.

Jax release v0.4.1

• 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 tutorial to understand the new concepts.
  • PartitionSpec and Mesh are now out of experimental. The new API endpoints are jax.sharding.PartitionSpec and jax.sharding.Mesh. jax.experimental.maps.Mesh and jax.experimental.PartitionSpec are deprecated and will be removed in 3 months.
  • with_sharding_constraints new public endpoint is jax.lax.with_sharding_constraint.
  • If using ABSL flags together with jax.config, the ABSL flag values are no longer read or written after the JAX configuration options are initially populated from the ABSL flags. This change improves performance of reading jax.config options, which are used pervasively in JAX.
  • The jax2tf.call_tf function now uses for TF lowering the first TF device of the same platform as used by the embedding JAX computation. Before, it was using the 0th device for the JAX-default backend.
  • A number of jax.numpy functions now have their arguments marked as positional-only, matching NumPy.
  • jnp.msort is now deprecated, following the deprecation of np.msort in numpy 1.24. It will be removed in a future release, in accordance with the {ref}api-compatibility policy. It can be replaced with jnp.sort(a, axis=0).

... (truncated)

Changelog

Sourced from jax's changelog.

jax 0.4.5 (Mar 2, 2023)

• Deprecations
  • jax.sharding.OpShardingSharding has been renamed to jax.sharding.GSPMDSharding. jax.sharding.OpShardingSharding will be removed in 3 months from Feb 17, 2023.
  • The following jax.Array methods are deprecated and will be removed 3 months from Feb 23 2023:
    • jax.Array.broadcast: use {func}jax.lax.broadcast instead.
    • jax.Array.broadcast_in_dim: use {func}jax.lax.broadcast_in_dim instead.
    • jax.Array.split: use {func}jax.numpy.split instead.

jax 0.4.4 (Feb 16, 2023)

• Changes
  • The implementation of jit and pjit has been merged. Merging jit and pjit changes the internals of JAX without affecting the public API of JAX. Before, jit was a final style primitive. Final style means that the creation of jaxpr was delayed as much as possible and transformations were stacked on top of each other. With the jit-pjit implementation merge, jit becomes an initial style primitive which means that we trace to jaxpr as early as possible. For more information see this section in autodidax. Moving to initial style should simplify JAX's internals and make development of features like dynamic shapes, etc easier. You can disable it only via the environment variable i.e. os.environ['JAX_JIT_PJIT_API_MERGE'] = '0'. The merge must be disabled via an environment variable since it affects JAX at import time so it needs to be disabled before jax is imported.
  • axis_resources argument of with_sharding_constraint is deprecated. Please use shardings instead. There is no change needed if you were using axis_resources as an arg. If you were using it as a kwarg, then please use shardings instead. axis_resources will be removed after 3 months from Feb 13, 2023.
  • added the {mod}jax.typing module, with tools for type annotations of JAX functions.
  • The following names have been deprecated:
    • jax.xla.Device and jax.interpreters.xla.Device: use jax.Device.
    • jax.experimental.maps.Mesh. Use jax.sharding.Mesh instead.
    • jax.experimental.pjit.NamedSharding: use jax.sharding.NamedSharding.
    • jax.experimental.pjit.PartitionSpec: use jax.sharding.PartitionSpec.
    • jax.interpreters.pxla.Mesh: use jax.sharding.Mesh.
    • jax.interpreters.pxla.PartitionSpec: use jax.sharding.PartitionSpec.
• Breaking Changes
  • the initial argument to reduction functions like :func:jax.numpy.sum is now required to be a scalar, consistent with the corresponding NumPy API. The previous behavior of broadcating the output against non-scalar initial values was an unintentional implementation detail ({jax-issue}[#14446](https://github.com/google/jax/issues/14446)).

jaxlib 0.4.4 (Feb 16, 2023)

... (truncated)

Commits

• a002643 Fix stale reference to util.prod.
• a9421a8 Merge pull request #14728 from mattjj:custom-vjp-bwd-wrapped-fun
• bf07395 [custom_vjp] bwd function should not be WrappedFun, may run multiple times
• abc6c9b [sparse] adjust tolerance on bcoo_dot_general_sampled
• 3abae68 Rollforward of Add a fastpath to pmap_lib for sharding np.ndarray directly in...
• c73cc49 Use in_shardings and out_shardings since those are the new arguments that pji...
• a21bdad Merge pull request #14738 from jakevdp:update-sphinx
• 55d9c06 DOC: update sphinx & sphinx-autodoc-typehints
• b348fce Merge pull request #14736 from jakevdp:fix-rtd
• e8a4e64 Merge pull request #14737 from hawkinsp:kaggle
• Additional commits viewable in compare view

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[dependabot]

Superseded by #80.