chore(deps): update all non-major dependencies

[renovate]

ℹ️ Note

This PR body was truncated due to platform limits.

Motivation

Automated dependency update by Renovate bot.

Description

This PR contains the following updates:

Package	Change	Age	Confidence
armonik	>=3.25.0 → >=3.29.3
jax	>=0.6.1 → >=0.11.1
maven (source)	3.9.6 → 3.9.16
maven-wrapper (source)	3.2.0 → 3.3.4
myst_parser	==4.0.0 → ==4.0.1
pymonik	>=0.2.2 → >=0.2.5
sphinx (changelog)	==8.1.3 → ==8.2.3
sphinx-rtd-theme	==3.0.2 → ==3.1.0
sphinxcontrib-mermaid (changelog)	==1.0.0 → ==1.2.3
com.google.cloud.tools:jib-maven-plugin	3.5.1 → 3.5.2
org.apache.maven.plugins:maven-assembly-plugin (source)	3.7.1 → 3.8.0
org.codehaus.mojo:exec-maven-plugin (source)	3.1.0 → 3.6.4
org.apache.maven.plugins:maven-shade-plugin (source)	3.6.1 → 3.6.2
org.apache.maven.plugins:maven-compiler-plugin (source)	3.12.1 → 3.16.0
org.apache.maven.plugins:maven-wrapper-plugin (source)	3.2.0 → 3.3.4
fr.aneo:armonik-client	0.1.2 → 0.1.4
fr.aneo:armonik-worker	0.1.2 → 0.1.4
fr.aneo:armonik-worker-domain	0.1.2 → 0.1.4
ch.qos.logback:logback-classic (source, changelog)	1.5.20 → 1.6.3

Testing

This is an automated dependency update. No functional changes are expected.

Impact

---

Release Notes

aneoconsulting/ArmoniK.Api (armonik)

v3.29.3

Compare Source

   🐞 Bug Fixes

• ci:
  • Pin pnpm/ni versions in ci.yml to match publish.yml  -  by @​jfonseca-aneo (bc8bf)
  • Pin pnpm/ni versions in ci.yml to match publish.yml  -  by @​aneojgurhem in #​755 (8691c)
• cpp:
  • Pin libarmonik-dev deps to exact built package version  -  by @​jfonseca-aneo (66e18)
  • Pin libarmonik-dev deps to exact built package version  -  by @​aneojgurhem in #​722 (f8996)
  • Send the communication token with CreateResultsMetaData  -  by @​aneojgurhem (f4778)
  • Send the communication token with CreateResultsMetaData  -  by @​lemaitre-aneo in #​749 (1ea09)
• python:
  • Declare the ruff rule selection instead of inheriting it  -  by @​wkirschenmann (393de)
  • Keep ruff format off the Markdown it never formatted  -  by @​wkirschenmann (f77b0)
  • Declare the ruff rule selection instead of inheriting it  -  by @​wkirschenmann in #​687 (8199e)
• rust:
  • Put the test dependencies where they belong, and make the serde feature compile  -  by @​wkirschenmann (1a143)
  • Correct the build script comment that stated a measured falsehood  -  by @​wkirschenmann (45d35)
  • Apply the request timeout and rate limit that were being parsed and dropped  -  by @​wkirschenmann (8fcd2)
  • Reject a zero rate limit instead of leaving it to panic  -  by @​wkirschenmann (2910b)
  • Apply the request timeout and rate limit that were being parsed and dropped  -  by @​wkirschenmann in #​690 (0f562)
  • Read a bracketed IPv6 override target instead of panicking on it  -  by @​wkirschenmann (b63f4)
  • Read a bracketed IPv6 override target instead of panicking on it  -  by @​wkirschenmann in #​742 (20751)
  • Synchronize Cargo.lock with 3.29.3 version bump  -  by @​jfonseca-aneo (f6710)

   🏎 Performance

• rust: Declare the build script's dependencies so an unrelated edit stops running protoc  -  by @​wkirschenmann (5cdeb)

    View changes on GitHub

v3.29.2

Compare Source

   🚀 Features

(14a6b52)

• Self contained implementation of string view  -  by @​jfonseca-aneo in #​680 (4c19e)
• packaging:
  • Split deb/rpm into runtime and devel packages  -  by @​jfonseca-aneo in #​678 (e34b2)

   🐞 Bug Fixes

• Unpin grpcio version in Python API  -  by @​AncientPatata in #​681 (d3c11)
• cpp:
  • Move fmt-dependent util.h out of public install headers  -  by @​jfonseca-aneo in #​682 (65b89)
  • Link abseil log libs on RHEL regardless of BUILD_SHARED_LIBS  -  by @​jfonseca-aneo in #​684 (06da5)

    View changes on GitHub

v3.29.1

Compare Source

   🐞 Bug Fixes

• TCP no delay  -  by @​lemaitre-aneo in #​674 (ace62)
• python:
  • Replace removed setuptools_scm private import with packaging.version  -  by @​aneojgurhem (f7bdb)
  • Replace removed setuptools_scm private import with packaging.version  -  by @​aneojgurhem in #​673 (9241d)

    View changes on GitHub

v3.29.0

Compare Source

   🚀 Features

• Added get_resource_data to TaskHandler  -  by @​AncientPatata in #​661 (90270)

   🐞 Bug Fixes

• Bad handling of cancellation in WaitForResultsAsync  -  by @​PierrePicard20 (45614)
• Angular package builds incorrect TaskOptionEnum  -  by @​fdewas-aneo in #​667 (ef5af)
• Bad handling of cancellation in WaitForResultsAsync  -  by @​PierrePicard20 in #​668 (15e38)
• grpc channel: Fix unix and tcp socket connection issues  -  by @​jfonseca-aneo in #​669 (cb7ed)

    View changes on GitHub

v3.28.3

Compare Source

   🏎 Performance

• Avoid sharing TCP connections accross channels  -  by @​lemaitre-aneo in #​659 (58eda)

    View changes on GitHub

v3.28.2

Compare Source

   🐞 Bug Fixes

• Session status in rust bindings  -  by @​aneojgurhem in #​654 (43993)
• Propagate right log level to formatter and writer  -  by @​lemaitre-aneo in #​653 (14870)
• Public ILogger for LocalLogger  -  by @​lemaitre-aneo in #​655 (f4130)

    View changes on GitHub

v3.28.1

Compare Source

   🐞 Bug Fixes

• Use System.Linq.AsyncEnumerable instead of System.Linq.Async to be compatible with dotnet 10  -  by @​aneojgurhem (21eb4)
• Use System.Linq.AsyncEnumerable instead of System.Linq.Async to be compatible with dotnet 10  -  by @​aneojgurhem in #​649 (b2dcb)

    View changes on GitHub

v3.28.0

Compare Source

   🚀 Features

• java:
  • Add gRPC channel builder with SSL/TLS configuration  -  by @​camory-aneo in #​629 (8d3a9)
  • Add retry policy for GrpcChannelBuilder  -  by @​camory (3573b)
  • Add retry policy for GrpcChannelBuilder  -  by @​camory in #​645 (c492d)

   🐞 Bug Fixes

• Remove grpc-proto from image used for cpp compilation  -  by @​jfonseca-aneo (690c0)
• Remove grpc-proto from image used for cpp compilation  -  by @​lemaitre-aneo in #​642 (fdfd3)
• Stream clear bug  -  by @​lemaitre-aneo in #​635 (abbbf)
• buffer: Utiliser .str() au lieu de .clear()  -  by Hugo Vuacheux (7291a)

    View changes on GitHub

v3.27.0

Compare Source

What's Changed

• refactor(java,proto)!: standardize Java gRPC package structure and add java_package options by @​camory-aneo in #​628
• chore: update dependencies by @​aneojgurhem in #​630
• chore: prepare release 3.27.0 by @​aneojgurhem in #​632

New Contributors

• @​camory-aneo made their first contribution in #​628

Full Changelog: aneoconsulting/ArmoniK.Api@3.26.1...3.27.0

v3.26.1

Compare Source

   🚀 Features

• Rust API server  -  by @​lemaitre-aneo in #​569 (12d2a)

   🐞 Bug Fixes

• Pod configuration gets used raw  -  by @​AncientPatata in #​622 (1fa91)
• Remove HashMap for names  -  by @​lemaitre-aneo in #​624 (8e3f5)
• Properly passing in task options in the worker's task handler  -  by @​AncientPatata in #​625 (424a7)

    View changes on GitHub

v3.26.0

Compare Source

   🚀 Features

• Option to turn off data deletion by armonik  -  by @​aneojgurhem (c6655)
• Option to turn off data deletion by armonik  -  by @​aneojgurhem in #​608 (560c9)

   🐞 Bug Fixes

• Fix TaskHandler  -  by @​dbrasseur-aneo (d061f)
• Add missing fields  -  by @​aneojgurhem (65996)
• Add-eslint-config  -  by @​fdewas-aneo (c2010)

    View changes on GitHub

jax-ml/jax (jax)

v0.11.1

Compare Source

• New features

  • Added an error check for trying to deserialize JAX exports that are older
    than the backwards compatibility window. Without this check the
    deserialization of expired artifacts may succeed and then result in
    obscure downstream errors.
    Added a configuration flag --jax_export_deserialize_expired_versions to
    temporarily bypass the error check.
    See https://docs.jax.dev/en/latest/export/export.html#compatibility-guarantees.
  • Added {func}jax.numpy.top_k, which implements {func}numpy.top_k, added in
    in NumPy v2.6.0 ({jax-issue}#39729).

• Breaking changes

  • The exec_time_optimization_effort and memory_fitting_effort flags have been
    removed in favor of the EffortLevel enum.
  • JAX does not support anymore deserialization of Exported modules from
    before January 15th, 2026 because they are beyond the backwards compatibility
    window. On that date we added support to serialize shardings as NamedSharding,
    and now that is the only sharding serialization that is supported.
  • jnp.take_along_axis now always defaults wrap_negative_indices to True.
    It used to default to False for mode=promise_in_bounds and True otherwise.
    (This also means None is no longer a valid value for wrap_negative_indices.)

• Deprecations

  • The fields in_shardings_hlo and out_shardings_hlo of
    jax.export.Exported have been deprecated for a while. Now accessing them
    raises a warning. Use in_shardings_jax and out_shardings_jax instead.

• Changes

  • The cuDNN fused attention backward pass (used by
    {func}jax.nn.dot_product_attention with implementation='cudnn') no
    longer computes a bias gradient when the only attention bias comes from
    a boolean mask, whose gradient no caller can request. Bias gradients
    for an explicit bias or a non-boolean mask are unchanged
    ({jax-issue}#34685).
  • {func}jax.numpy.meshgrid, {obj}jax.numpy.ogrid, and
    {func}jax.numpy.broadcast_arrays now return tuples rather than lists
    in order to align with NumPy>2.0 and the Array API specification.
    ({jax-issue}#39783, {jax-issue}#39789, {jax-issue}#39802)
  • When {func}jax.grad or {func}jax.value_and_grad rejects a function with
    a non-scalar output, the error message now suggests reducing the output
    to a scalar (e.g. with output.sum()), using {func}jax.jacobian, or
    reshaping size-1 outputs ({jax-issue}#2303).
  • When indexing with non-static or traced slice indices, the error message
    now suggests using {func}jax.lax.dynamic_slice,
    {func}jax.lax.dynamic_update_slice, or jax.ds, and shows tracer
    provenance ({jax-issue}#7222).
  • PyTree metadata equality comparison failures now report the specific
    registered pytree type that caused the error ({jax-issue}#13027).

• Bug fixes

  • {func}jax.numpy.linalg.det and {func}jax.numpy.linalg.slogdet now use a
    closed-form LU decomposition with row pivoting for 2x2 and 3x3 matrices
    instead of closed-form polynomial expansions to avoid numerical instability
    and catastrophic cancellation ({jax-issue}#39905).
  • Fixed a crash when jax_explain_cache_misses is enabled and a
    jax.custom_batching.custom_vmap-decorated function (or
    custom_partitioning, custom_gradient, closure_convert,
    linear_call, or run_state) is retraced with different-shaped
    arguments ({jax-issue}#40110).
  • The batching rules of the cuDNN fused attention primitives (used by
    {func}jax.nn.dot_product_attention with implementation='cudnn') now
    support operands that do not carry the vmap axis, including a shared
    bias or mask. Previously jax.jacobian, jax.vmap with partial
    in_axes, and jax.vmap of a VJP or of jax.grad failed with a
    reshape TypeError ({jax-issue}#38495).
  • jax.vmap of fp8 cuDNN fused attention now works: its batching rules
    additionally mislabeled or dropped the amax outputs and restored output
    shapes incorrectly, so previously no vmap of the fp8 path succeeded at
    all. The amax outputs are whole-batch statistics and do not carry the
    vmap axis; vmap over the scale/descale operands raises a clear
    NotImplementedError.
  • Setting jax_compiler_enable_remat_pass to False now adds
    rematerialization to the set of disabled XLA passes instead of
    overwriting it, so HLO passes disabled via
    XLA_FLAGS=--xla_disable_hlo_passes=... stay disabled
    ({jax-issue}#37391).
  • {func}jax.numpy.split, {func}jax.numpy.array_split, and the
    hsplit/vsplit/dsplit variants once again accept negative entries in
    indices_or_sections, resolving them against the axis size as NumPy does
    ({jax-issue}#6599). Out-of-bound indices are now clipped to the axis
    bounds and produce empty sections, also matching NumPy, instead of raising
    ValueError: Sizes passed to split must be nonnegative.
  • Fixed abstract evaluation in {func}jax.lax.scan to only check .mat
    equivalency when the abstract value is a ShapedArray
    ({jax-issue}#39700).
  • Fixed propagation of singleton sharded dimensions in {func}jax.lax.reshape
    when reshaping arrays with sharding constraints ({jax-issue}#39309).
  • Fixed {func}jax.tree_util.flatten_one_level_with_keys for namedtuple
    instances ({jax-issue}#39297).
  • Fixed _get_prime_factors in jax.experimental.mesh_utils
    ({jax-issue}#38286).
  • PyTreeDef.deserialize_using_proto now raises ValueError for a
    malformed PyTreeDefProto instead of crashing the interpreter. A node
    whose arity exceeds the subtrees preceding it is rejected, as is a dict
    node whose arity disagrees with its key list, which previously segfaulted
    later, when the structure was used to unflatten.
    PyTreeDef.compose likewise raises ValueError rather than crashing when
    an operand carries such an inconsistent arity, which is reachable from
    pickle.loads ({jax-issue}#37410).

v0.11.0

Compare Source

• New features

  • Added a doc on defining custom derivative rules with the experimental
    hijax API ({ref}hijax-custom-derivatives), along with
    jax.experimental.hijax helpers for deriving HiPrim autodiff
    rules from a jvp or lin rule: linearize_from_jvp with
    apply_derived_linearization, vjp_fwd_from_jvp with transpose_jvp,
    vjp_fwd_from_lin with transpose_linearized, and jvp_from_lin.
  • Added {func}jax.custom_remat to the top-level jax namespace, for
    per-function control of rematerialization under the new jax_remat3
    implementation.
  • jax.checkpoint_policies is now a submodule rather than a namespace
    object (so from jax.checkpoint_policies import ... now works; attribute
    access is unchanged), and it additionally exposes the name-based policy
    classes SaveOnlyTheseNames, SaveAnyNamesButThese, and
    SaveAndOffloadOnlyTheseNames.
  • Added {class}jax.Inline enum for specify inlining policies to
    {func}jax.jit.

• Breaking changes

  • The deprecated module jax.cloud_tpu_init was removed. This did nothing and
    references to it can be safely removed.
  • Support for Python 3.11, NumPy 2.0, and SciPy 1.14 has been dropped, per the
    deprecation policy.
  • Support for Python 3.13 free-threaded (3.13t) has been dropped. Python
    3.13 free-threaded was an experimental build needed to bootstrap free
    threading support. Now that Python 3.14t is stable, it is time to drop the
    experimental build. Other parts of the Python ecosystem (e.g.
    cibuildwheel, scipy) are making similar moves.
  • {func}jax.numpy.empty and {func}jax.numpy.empty_like now produce
    uninitialized arrays, similar to their NumPy counterparts. Prior to v0.11.0,
    they produced arrays initialized to zeros. To recover the previous behavior,
    use {func}jax.numpy.zeros or {func}jax.numpy.zeros_like instead.

• Deprecations

  • Passing 2-dimensional arrays (or mixed 2D and 3D arrays) to {func}jax.numpy.cross is deprecated and will be removed in JAX 0.12.0, aligning with NumPy 2.5 behavior.
  • Several previously-deprecated APIs from {mod}jax.core have been removed, including
    CallPrimitive, DebugInfo, DropVar, Effect, Effects, InconclusiveDimensionOperation,
    JaxprTypeError, abstract_token, check_jaxpr, concrete_or_error, find_top_trace, gensym,
    get_opaque_trace_state, is_concrete, is_constant_dim, is_constant_shape, jaxprs_in_params,
    new_jaxpr_eqn, no_effects, nonempty_axis_env_DO_NOT_USE, primal_dtype_to_tangent_dtype,
    unsafe_am_i_under_a_jit_DO_NOT_USE, unsafe_am_i_under_a_vmap_DO_NOT_USE,
    unsafe_get_axis_names_DO_NOT_USE, valid_jaxtype, JaxprPpContext, JaxprPpSettings, OutputType,
    aval_mapping_handlers, call, concretization_function_error, custom_typechecks,
    literalable_types, no_axis_name, and trace_ctx.
  • Several previously-deprecated APIs from {mod}jax.interpreters.pxla have been removed, including
    Index, MeshAxisName, MeshExecutable, global_aval_to_result_handler, global_result_handlers,
    are_hlo_shardings_equal, is_hlo_sharding_replicated, ArrayMapping, _UNSPECIFIED,
    array_mapping_to_axis_resources, and op_sharding_to_indices.

v0.10.2

Compare Source

• New features
  • Added {func}jax.scipy.linalg.invhilbert for the closed-form inverse
    of the Hilbert matrix ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.invpascal for the inverse of the Pascal
    matrix ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.fiedler_companion for constructing the
    pentadiagonal Fiedler companion matrix of a polynomial
    ({jax-issue}#10144).
  • Added {func}jax.ShapeDtypeStruct.like -- a shortcut for constructing a
    {class}jax.ShapeDtypeStruct from an object with shape and dtype
    attributes.

v0.10.1

Compare Source

• New features

  • Added ResizeMethod.AREA to {func}jax.image.resize, which matches
    TensorFlow's AREA resizing ({jax-issue}#20098).
  • Added {func}jax.scipy.linalg.hadamard for constructing Hadamard
    matrices ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.circulant for constructing circulant
    matrices ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.dft for constructing discrete Fourier
    transform matrices ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.leslie for constructing Leslie matrices
    ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.companion for constructing companion
    matrices from polynomial coefficients ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.fiedler for constructing symmetric Fiedler
    matrices ({jax-issue}#10144).
  • Added {func}jax.scipy.linalg.helmert for constructing Helmert matrices
    ({jax-issue}#10144).
  • Added {func}jax.scipy.special.boxcox and
    {func}jax.scipy.special.boxcox1p for the Box-Cox power transformation.
  • Moved RNG APIs from "implementations" to dtypes ({jax-issue}#27854):
    • Added jax.random.key_dtype to get the dtype corresponding to a PRNG
      implementation name.
    • jax.random.key and wrap_key_data now accept a dtype argument.

• Breaking changes

  • with mesh: context manager has been deprecated. Please use
    with jax.set_mesh(mesh): instead.

• Deprecations

  • Passing the copy, order, and ndmin arguments to
    {func}jax.numpy.array positionally is deprecated. Use keyword arguments
    instead. This matches the signature of numpy.array.
  • Python dict_values, generators, zip return type and iterators generally
    are deprecated by default when used as leaves in pytrees. In a future
    version of JAX, this will become an error, if you depend on using them as
    leaves, pass is_leaf to jax.tree.* methods.

v0.10.0

Compare Source

• New features:

  • Added ResizeMethod.CUBIC_PYTORCH to {func}jax.image.resize to match
    PyTorch's bicubic resize ({jax-issue}#15768).
  • We now support differentiation of {func}jax.lax.linalg.qr for wide
    matrices and when full_matrices is True.
  • LAPACK operations are now parallelized along the batch dimension on CPU.
  • Added perturb_singular argument to
    {func}jax.lax.linalg.tridiagonal_solve to handle singular matrices by
    perturbing near-zero pivots in the LU decomposition. This is useful for
    solving numerically singular systems when computing eigenvectors by inverse
    iteration.
  • {func}jax.scipy.linalg.eigh_tridiagonal now supports computing
    eigenvectors on CPU and GPU.
  • Added the {meth}jax.numpy.ndarray.byteswap method.

• Breaking changes:

  • PartitionSpec objects no longer report themselves to be equal to tuples.
    Convert tuples to PartitionSpec objects before testing equality.
  • The .vma property has been removed from jax.core.ShapedArray. Use
    .manual_axis_type.varying instead.
  • JAX CPU devices now report their names as cpu:0, cpu:1, etc. instead of
    TFRT_CPU_0, TFRT_CPU_1.
  • The config state jax_pmap_shmap_merge has been removed. jax.pmap
    will now always use the new implementation that wraps
    jax.jit(jax.shard_map). Please see
    https://docs.jax.dev/en/latest/migrate_pmap.html for more information.
  • jax.device_put_sharded and jax.device_put_replicated have been removed
    from the public API and now raise an AttributeError when accessed.
    Please see
    https://docs.jax.dev/en/latest/migrate_pmap.html#drop-in-replacements for
    drop-in replacements.
  • The C++ pmap infrastructure has been removed. The following public APIs
    are no longer available:
    • jax.sharding.PmapSharding
    • From jaxlib.xla_extension: PmapFunction, pmap,
      NoSharding, Chunked, Unstacked, ShardedAxis, Replicated,
      ShardingSpec.
    • From jax.interpreters.pxla: MapTracer, PmapExecutable,
      parallel_callable, shard_args, xla_pmap_p, Chunked,
      NoSharding, Replicated, ShardedAxis, ShardingSpec,
      Unstacked, spec_to_indices.
  • The deprecated keyword arguments a, a_min, and a_max to
    jax.numpy.clip have been removed.
  • Functions jax.numpy.hstack, jax.numpy.vstack, jax.numpy.dstack,
    jax.numpy.column_stack, jax.numpy.atleast_1d, jax.numpy.atleast_2d,
    and jax.numpy.atleast_3d no longer accept non-ArrayLike inputs.
    Doing so previously issued a DeprecationWarning.
  • {func}jax.scipy.stats.rankdata now returns floating point values in
    all cases, following a similar change in the SciPy 1.18 release.

• Deprecations:

  • A number of internal APIs in jax.core have been newly deprecated and
    some have been moved to jax.extend.core. These include CallPrimitive,
    DebugInfo, DropVar, Effect, Effects, InconclusiveDimensionOperation,
    JaxprTypeError, check_jaxpr, concrete_or_error, find_top_trace,
    gensym, get_opaque_trace_state, jaxprs_in_params, new_jaxpr_eqn,
    no_effects, nonempty_axis_env_DO_NOT_USE, primal_dtype_to_tangent_dtype,
    unsafe_am_i_under_a_jit_DO_NOT_USE, unsafe_am_i_under_a_vmap_DO_NOT_USE,
    unsafe_get_axis_names_DO_NOT_USE, valid_jaxtype, JaxprPpContext,
    JaxprPpSettings, OutputType, abstract_token, aval_mapping_handlers,
    call, concretization_function_error, custom_typechecks, is_concrete,
    is_constant_dim, is_constant_shape, literalable_types, no_axis_name,
    pytype_aval_mappings, and trace_ctx.

• Changes:

  • The minimum supported SciPy version is now 1.14.
  • vma parameter of jax.ShapeDtypeStruct has been replaced with
    manual_axis_type: jax.sharding.ManualAxisType. The .vma property has
    been replaced with .manual_axis_type.varying.
  • Removed experimental {func}jax.experimental.custom_dce.custom_dce
  • {func}jax.scipy.linalg.cho_solve, {func}jax.scipy.linalg.lu_solve, and
    {func}jax.scipy.linalg.solve_triangular now show a deprecation warning for
    batched 1D solves with b.ndim > 1. In the future these will be treated as
    batched 2D solves.
  • Added a new version 10 for the jax.export serialization format. This is
    an optimization for when there are multiple occurrences of the same
    abstract value, abstract mesh, or sharding.

• Bug fixes:

  • Fixed a bug that led to differing output between CPU and GPU for
    non-symmetric multidimensional IRFFTs ({jax-issue}#29325).
  • Fixed an error when tiny matrices were passed to
    jax.lax.linalg.tridiagonal_solve on GPU ({jax-issue}#32487).
  • Fixed a bug in jax.scipy.fft.dctn and idctn where axes=None
    incorrectly defaulted to all axes when s was specified, instead of the
    last len(s) axes to match SciPy behavior ({jax-issue}#29426).
  • Fixed a bug where calling jax.distributed.initialize() on a GCE TPU
    Managed Instance Group raised an IndexError ({jax-issue}#36593). When
    jax.distributed.initialize() is called on a GCE VM, it uses the GCE
    metadata
    server to
    learn the addresses of all participating tasks. The format of this metadata
    on Managed Instance Groups was not a format JAX expected, leading to the
    exception. We now parse this format correctly.

v0.9.2

Compare Source

• Changes:
  • The semi-private type jax._src.literals.TypedNdArray is now a subclass of
    np.ndarray, rather than a duck type of it.
  • {func}jax.numpy.arange with step specified no longer generates the array
    on host. The benefit is more efficient code, though this can lead to less
    precise outputs for narrow-width floats (e.g. bfloat16). To recover the
    previous behavior in this case, use jnp.array(np.arange(...)).

v0.9.1

Compare Source

• Changes:

  • JAX tracers that are not of Array type (e.g., of Ref type) will no
    longer report themselves to be instances of Array.
  • Using jax.shard_map in Explicit mode will raise an error
    if the PartitionSpec of input does not match the PartitionSpec specified in
    in_specs. In other words, it will act like an assert instead of an
    implicit reshard.
    in_specs is an optional argument so you can omit specifying it
    and shard_map will infer the PartitionSpec from the argument. If you
    want to reshard your inputs, you can use jax.reshard on the arguments and
    then pass those args to shard_map.

• New features:

  • Added a debug config jax_compilation_cache_check_contents. If set, we miss
    when get() is called on a value that has not been put() by the current
    process, even if the value is actually in the disk cache. When a value is
    put(), we verify that its contents match.

v0.9.0.1: JAX v0.9.0.1

Compare Source

JAX v0.9.0.1 is identical to v0.9.0 with the commits from the following four PRs patched in:

• openxla/xla#36579
• openxla/xla#36345
• openxla/xla#36755
• openxla/xla#36696

v0.9.0

Compare Source

• New features:

  • Added {func}jax.thread_guard, a context manager that detects when devices
    are used by multiple threads in multi-controller JAX.

• Bug fixes:

  • Fixed a workspace size calculation error for pivoted QR (magma_zgeqp3_gpu)
    in MAGMA 2.9.0 when using use_magma=True and pivoting=True.
    ({jax-issue}#34145).

• Deprecations:

  • The flag jax_collectives_common_channel_id was removed.
  • The jax_pmap_no_rank_reduction config state has been removed. The
    no-rank-reduction behavior is now the only supported behavior: a
    jax.pmapped function f sees inputs of the same rank as the input to
    jax.pmap(f). For example, if jax.pmap(f) receives shape (8, 128) on
    8 devices, then f receives shape (1, 128).
  • Setting the jax_pmap_shmap_merge config state is deprecated in JAX v0.9.0
    and will be removed in JAX v0.10.0.
  • {func}jax.numpy.fix is deprecated, anticipating the deprecation of
    {func}numpy.fix in NumPy v2.5.0. {func}jax.numpy.trunc is a drop-in
    replacement.

• Changes:

  • {func}jax.export now supports explicit sharding. This required a new
    export serialization format version that includes the NamedSharding,
    including the abstract mesh, and the partition spec. As part of this
    change we have added a restriction in the use of exported modules: when
    calling them the abstract mesh must match the one used at export time,
    including the axis names. Previously, only the number of the devices
    mattered.

v0.8.3: JAX v0.8.3

Compare Source

JAX v0.8.3 is identical to v0.8.2 with the following two bug fixes patched in:

• openxla/xla@4bc723d
• openxla/xla@21552fd

v0.8.2

Compare Source

• Deprecations

  • jax.lax.pvary has been deprecated.
    Please use jax.lax.pcast(..., to='varying') as the replacement.
  • Complex arguments passed to {func}jax.numpy.arange now result in a
    deprecation warning, because the output is poorly-defined.
  • From {mod}jax.core a number of symbols are newly deprecated including:
    call_impl, get_aval, mapped_aval, subjaxprs, set_current_trace,
    take_current_trace, traverse_jaxpr_params, unmapped_aval,
    AbstractToken, and TraceTag.
  • All symbols in {mod}jax.interpreters.pxla are deprecated. These are
    primarily JAX internal APIs, and users should not rely on them.

• Changes:

  • jax's Tracer no longer inherits from jax.Array at runtime. However,
    jax.Array now uses a custom metaclass such isinstance(x, Array) is true
    if an object x represents a traced Array. Only some Tracers represent
    Arrays, so it is not correct for Tracer to inherit from Array.

    For the moment, during Python type checking, we continue to declare Tracer
    as a subclass of Array, however we expect to remove this in a future
    release.

  • jax.experimental.si_vjp has been deleted.
    jax.vjp subsumes it's functionality.

v0.8.1

Compare Source

• New features:

  • {func}jax.jit now supports the decorator factory pattern; i.e instead of
    writing

    @functools.partial(jax.jit, static_argnames=['n'])
    def f(x, n):
      ...
    

    you may write

    @jax.jit(static_argnames=['n'])
    def f(x, n):
      ...
    

• Changes:

  • {func}jax.lax.linalg.eigh now accepts an implementation argument to
    select between QR (CPU/GPU), Jacobi (GPU/TPU), and QDWH (TPU)
    implementations. The EighImplementation enum is publicly exported from
    {mod}jax.lax.linalg.

  • {func}jax.lax.linalg.svd now implements an algorithm that uses the polar
    decomposition on CUDA GPUs. This is also an alias for the existing algorithm
    on TPUs.

• Bug fixes:

  • Fixed a bug introduced in JAX 0.7.2 where eigh failed for large matrices on
    GPU (({jax-issue}#33062).

• Deprecations:

  • jax.sharding.PmapSharding is now deprecated. Please use
    jax.NamedSharding instead.
  • jx.device_put_replicated is now deprecated. Please use jax.device_put
    with the appropriate sharding instead.
  • jax.device_put_sharded is now deprecated. Please use jax.device_put with
    the appropriate sharding instead.
  • Default axis_types of jax.make_mesh will change in JAX v0.9.0 to return
    jax.sharding.AxisType.Explicit. Leaving axis_types unspecified will raise a
    DeprecationWarning.
  • {mod}jax.cloud_tpu_init and its contents were deprecated. There is no reason for a user to import or use the contents of this module; JAX handles this for you automatically if needed.

v0.8.0

Compare Source

• Breaking changes:

  • JAX is changing the default jax.pmap implementation to one implemented in
    terms of jax.jit and jax.shard_map. jax.pmap is in maintenance mode
    and we encourage all new code to use jax.shard_map directly. See the
    migration guide for
    more information.
  • The auto= parameter of jax.experimental.shard_map.shard_map has been
    removed. This means that jax.experimental.shard_map.shard_map no longer
    supports nesting. If you want to nest shard_map calls, please use
    jax.shard_map.
  • JAX no longer allows passing objects that support __jax_array__ directly
    to, e.g. jit-ed functions. Call jax.numpy.asarray on them first.
  • {func}jax.numpy.cov is now returns NaN for empty arrays ({jax-issue}#32305),
    and matches NumPy 2.2 behavior for single-row design matrices ({jax-issue}#32308).
  • JAX no longer accepts Array values where a dtype value is expected. Call
    .dtype on these values first.
  • The deprecated function {func}jax.interpreters.mlir.custom_call was
    removed.
  • The jax.util, jax.extend.ffi, and jax.experimental.host_callback
    modules have been removed. All public APIs within these modules were
    deprecated and removed in v0.7.0 or earlier.
  • The deprecated symbol {obj}jax.custom_derivatives.custom_jvp_call_jaxpr_p
    was removed.
  • jax.experimental.multihost_utils.process_allgather raises an error when
    the input is a jax.Array and not fully-addressable and tiled=False. To fix
    this, pass tiled=True to your process_allgather invocation.
  • from {mod}jax.experimental.compilation_cache, the deprecated symbols
    is_initialized and initialize_cache were removed.
  • The deprecated function {func}jax.interpreters.xla.canonicalize_dtype
    was removed.
  • {mod}jaxlib.hlo_helpers has been removed. Use {mod}jax.ffi instead.
  • The option jax_cpu_enable_gloo_collectives has been removed. Use
    jax_cpu_collectives_implementation instead.
  • The previously-deprecated interpolation argument to
    {func}jax.numpy.percentile and {func}jax.numpy.quantile has been
    removed; use method instead.
  • The JAX-internal for_loop primitive was removed. Its functionality,
    reading from and writing to refs in the loop body, is now directly
    supported by {func}jax.lax.fori_loop. If you need help updating your
    code, please file a bug.
  • {func}jax.numpy.trimzeros now errors for non-1D input.
  • The where argument to {func}jax.numpy.sum and other reductions is now
    required to be boolean. Non-boolean values have resulted in a
    DeprecationWarning since JAX v0.5.0.
  • The deprecated functions in {mod} jax.dlpack, {mod} jax.errors, {mod}
    jax.lib.xla_bridge, {mod} jax.lib.xla_client, and {mod}
    jax.lib.xla_extension were removed.
  • jax.interpreters.mlir.dense_bool_array was removed. Use MLIR APIs to
    construct attributes instead.

• Changes

  • {func}jax.numpy.linalg.eig now returns a namedtuple (with attributes
    eigenvalues and eigenvectors) instead of a plain tuple.
  • {func}jax.grad and {func}jax.vjp will now round always primals to
    float32 if float64 mode is not enabled.
  • {func}jax.dlpack.from_dlpack now accepts arrays with non-default layouts,
    for example, transposed.
  • The default nonsymmetric eigendecomposition on NVIDIA GPUs now uses
    cusolver. The magma and LAPACK implementations are still available via the
    new implementation argument to {func}jax.lax.linalg.eig
    ({jax-issue}#27265). The use_magma argument is now deprecated in favor
    of implementation.
  • {func}jax.numpy.trim_zeros now follows NumPy 2.2 in supporting
    multi-dimensional inputs.

• Deprecations

  • {func}jax.experimental.enable_x64 and {func}jax.experimental.disable_x64
    are deprecated in favor of the new non-experimental context manager
    {func}jax.enable_x64.
  • {func}jax.experimental.shard_map.shard_map is deprecated; going forward use
    {func}jax.shard_map.
  • {func}jax.experimental.pjit.pjit is deprecated; going forward use
    {func}jax.jit.

v0.7.2

Compare Source

• Breaking changes:

  • {func}jax.dlpack.from_dlpack no longer accepts a DLPack capsule. This
    behavior was deprecated and is now removed. The function must be called
    with an array implementing __dlpack__ and __dlpack_device__.

• Changes

  • The minimum supported NumPy version is now 2.0. Since SciPy 1.13 is required
    for NumPy 2.0 support, the minimum supported SciPy version is now 1.13.

  • JAX now represents constants in its internal jaxpr representation as a
    TypedNdArray, which is a private JAX type that duck types as a
    numpy.ndarray. This type may be exposed to users via custom_jvp rules,
    for example, and may break code that uses `

❗ Important

✂ PR body was truncated to here.