Bump jax[cpu] from 0.3.25 to 0.4.1

[dependabot]

Bumps jax[cpu] from 0.3.25 to 0.4.1.

Release notes

Sourced from jax[cpu]'s releases.

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).

Jaxlib release v0.4.1

• Changes
  • Support for Python 3.7 has been dropped, in accordance with JAX's {ref}version-support-policy.
  • The behavior of XLA_PYTHON_CLIENT_MEM_FRACTION=.XX has been changed to allocate XX% of the total GPU memory instead of the previous behavior of using currently available GPU memory to calculate preallocation. Please refer to GPU memory allocation for more details.
  • The deprecated method .block_host_until_ready() has been removed. Use .block_until_ready() instead.

Changelog

Sourced from jax[cpu]'s changelog.

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 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).

jaxlib 0.4.1 (Dec 13, 2022)

• Changes
  • Support for Python 3.7 has been dropped, in accordance with JAX's {ref}version-support-policy.
  • The behavior of XLA_PYTHON_CLIENT_MEM_FRACTION=.XX has been changed to allocate XX% of the total GPU memory instead of the previous behavior of using currently available GPU memory to calculate preallocation. Please refer to GPU memory allocation for more details.
  • The deprecated method .block_host_until_ready() has been removed. Use .block_until_ready() instead.

jax 0.4.0 (Dec 12, 2022)

• The release was yanked.

... (truncated)

Commits

• c4d590b Update values for release 0.4.1
• 17c6796 Merge pull request #13619 from jakevdp:sparse-validate
• dc8ead0 Update CHANGELOG to indicate that 0.4.0 was yanked.
• 71569e1 Remove the specialized sm versions for testing. It caused release wheels to s...
• 0bdb7ec Finish jax and jaxlib release 0.4.0
• d491d9f Remove the cached check in aot compiled call in MeshExecutable because a fast...
• e9cc523 [sparse] validate BCOO on instantiation
• 23001ae Merge pull request #13603 from gnecula:native_unused
• 5e8c0ec Merge pull request #13614 from hawkinsp:cuda
• b868cf7 Merge pull request #13616 from jakevdp:fix-sparse-error
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[codecov-commenter]

Codecov Report

Merging #1971 (6dd4ffc) into main (5ddd8ef) will decrease coverage by 0.01%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##             main    #1971      +/-   ##
==========================================
- Coverage   85.41%   85.40%   -0.02%     
==========================================
  Files         290      290              
  Lines       25437    25437              
  Branches     4573     4573              
==========================================
- Hits        21728    21725       -3     
- Misses       2541     2543       +2     
- Partials     1168     1169       +1     

Impacted Files	Coverage Δ
art/estimators/certification/abstain.py	90.90% <0.00%> (-9.10%)	⬇️
art/estimators/poison_mitigation/strip/strip.py	94.44% <0.00%> (-5.56%)	⬇️