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)).
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Updates the requirements on jax[cpu] to permit the latest version.
Changelog
Sourced from jax[cpu]'s changelog.
... (truncated)
Commits
a002643Fix stale reference to util.prod.a9421a8Merge pull request #14728 from mattjj:custom-vjp-bwd-wrapped-funbf07395[custom_vjp] bwd function should not be WrappedFun, may run multiple timesabc6c9b[sparse] adjust tolerance on bcoo_dot_general_sampled3abae68Rollforward of Add a fastpath to pmap_lib for sharding np.ndarray directly in...c73cc49Use in_shardings and out_shardings since those are the new arguments that pji...a21bdadMerge pull request #14738 from jakevdp:update-sphinx55d9c06DOC: update sphinx & sphinx-autodoc-typehintsb348fceMerge pull request #14736 from jakevdp:fix-rtde8a4e64Merge pull request #14737 from hawkinsp:kaggleDependabot 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
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