Update jax requirement from <0.4,>=0.3.16 to >=0.3.16,<0.5
Created by: dependabot[bot]
Updates the requirements on jax to permit the latest version.
Release notes
Sourced from jax'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 subsumesDeviceArray
,ShardedDeviceArray
, andGlobalDeviceArray
types in JAX. Thejax.Array
type helps make parallelism a core feature of JAX, simplifies and unifies JAX internals, and allows us to unifyjit
andpjit
.jax.Array
has been enabled by default in JAX 0.4 and makes some breaking change to thepjit
API. The jax.Array migration guide can help you migrate your codebase tojax.Array
. You can also look at the Distributed arrays and automatic parallelization tutorial to understand the new concepts.PartitionSpec
andMesh
are now out of experimental. The new API endpoints arejax.sharding.PartitionSpec
andjax.sharding.Mesh
.jax.experimental.maps.Mesh
andjax.experimental.PartitionSpec
are deprecated and will be removed in 3 months.with_sharding_constraint
s new public endpoint isjax.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 readingjax.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 ofnp.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 withjnp.sort(a, axis=0)
.
Changelog
Sourced from jax'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 subsumesDeviceArray
,ShardedDeviceArray
, andGlobalDeviceArray
types in JAX. Thejax.Array
type helps make parallelism a core feature of JAX, simplifies and unifies JAX internals, and allows us to unifyjit
andpjit
.jax.Array
has been enabled by default in JAX 0.4 and makes some breaking change to thepjit
API. The jax.Array migration guide can help you migrate your codebase tojax.Array
. You can also look at the Distributed arrays and automatic parallelization tutorial to understand the new concepts.PartitionSpec
andMesh
are now out of experimental. The new API endpoints arejax.sharding.PartitionSpec
andjax.sharding.Mesh
.jax.experimental.maps.Mesh
andjax.experimental.PartitionSpec
are deprecated and will be removed in 3 months.with_sharding_constraint
s new public endpoint isjax.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 readingjax.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 ofnp.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 withjnp.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
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