chore(deps): update dependency jaxlib to v0.4.35

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
jaxlib	0.4.23 -> 0.4.35

---

Release Notes

jax-ml/jax (jaxlib)

v0.4.35

• Breaking Changes

  • {func}jax.numpy.isscalar now returns True for any array-like object with
    zero dimensions. Previously it only returned True for zero-dimensional
    array-like objects with a weak dtype.
  • jax.experimental.host_callback has been deprecated since March 2024, with
    JAX version 0.4.26. Now we removed it.
    See {jax-issue}#20385 for a discussion of alternatives.

• Changes:

  • jax.lax.FftType was introduced as a public name for the enum of FFT
    operations. The semi-public API jax.lib.xla_client.FftType has been
    deprecated.
  • TPU: JAX now installs TPU support from the libtpu package rather than
    libtpu-nightly. For the next few releases JAX will pin an empty version of
    libtpu-nightly as well as libtpu to ease the transition; that dependency
    will be removed in Q1 2025.

• Deprecations:

  • The semi-public API jax.lib.xla_client.PaddingType has been deprecated.
    No JAX APIs consume this type, so there is no replacement.
  • The default behavior of {func}jax.pure_callback and
    {func}jax.extend.ffi.ffi_call under vmap has been deprecated and so has
    the vectorized parameter to those functions. The vmap_method parameter
    should be used instead for better defined behavior. See the discussion in
    {jax-issue}#23881 for more details.
  • The semi-public API jax.lib.xla_client.register_custom_call_target has
    been deprecated. Use the JAX FFI instead.
  • The semi-public APIs jax.lib.xla_client.dtype_to_etype,
    jax.lib.xla_client.ops,
    jax.lib.xla_client.shape_from_pyval, jax.lib.xla_client.PrimitiveType,
    jax.lib.xla_client.Shape, jax.lib.xla_client.XlaBuilder, and
    jax.lib.xla_client.XlaComputation have been deprecated. Use StableHLO
    instead.

v0.4.34

• New Functionality

  • This release includes wheels for Python 3.13. Free-threading mode is not yet
    supported.
  • jax.errors.JaxRuntimeError has been added as a public alias for the
    formerly private XlaRuntimeError type.

• Breaking changes

  • jax_pmap_no_rank_reduction flag is set to True by default.
    • array[0] on a pmap result now introduces a reshape (use array[0:1]
      instead).
    • The per-shard shape (accessable via jax_array.addressable_shards or
      jax_array.addressable_data(0)) now has a leading (1, ...). Update code
      that directly accesses shards accordingly. The rank of the per-shard-shape
      now matches that of the global shape which is the same behavior as jit.
      This avoids costly reshapes when passing results from pmap into jit.
  • jax.experimental.host_callback has been deprecated since March 2024, with
    JAX version 0.4.26. Now we set the default value of the
    --jax_host_callback_legacy configuration value to True, which means that
    if your code uses jax.experimental.host_callback APIs, those API calls
    will be implemented in terms of the new jax.experimental.io_callback API.
    If this breaks your code, for a very limited time, you can set the
    --jax_host_callback_legacy to True. Soon we will remove that
    configuration option, so you should instead transition to using the
    new JAX callback APIs. See {jax-issue}#20385 for a discussion.

• Deprecations

  • In {func}jax.numpy.trim_zeros, non-arraylike arguments or arraylike
    arguments with ndim != 1 are now deprecated, and in the future will result
    in an error.
  • Internal pretty-printing tools jax.core.pp_* have been removed, after
    being deprecated in JAX v0.4.30.
  • jax.lib.xla_client.Device is deprecated; use jax.Device instead.
  • jax.lib.xla_client.XlaRuntimeError has been deprecated. Use
    jax.errors.JaxRuntimeError instead.

• Deletion:

  • jax.xla_computation is deleted. It's been 3 months since it's deprecation
    in 0.4.30 JAX release.
    Please use the AOT APIs to get the same functionality as jax.xla_computation.
    • jax.xla_computation(fn)(*args, **kwargs) can be replaced with
      jax.jit(fn).lower(*args, **kwargs).compiler_ir('hlo').
    • You can also use .out_info property of jax.stages.Lowered to get the
      output information (like tree structure, shape and dtype).
    • For cross-backend lowering, you can replace
      jax.xla_computation(fn, backend='tpu')(*args, **kwargs) with
      jax.jit(fn).trace(*args, **kwargs).lower(lowering_platforms=('tpu',)).compiler_ir('hlo').
  • {class}jax.ShapeDtypeStruct no longer accepts the named_shape argument.
    The argument was only used by xmap which was removed in 0.4.31.
  • jax.tree.map(f, None, non-None), which previously emitted a
    DeprecationWarning, now raises an error in a future version of jax. None
    is only a tree-prefix of itself. To preserve the current behavior, you can
    ask jax.tree.map to treat None as a leaf value by writing:
    jax.tree.map(lambda x, y: None if x is None else f(x, y), a, b, is_leaf=lambda x: x is None).
  • jax.sharding.XLACompatibleSharding has been removed. Please use
    jax.sharding.Sharding.

• Bug fixes

  • Fixed a bug where {func}jax.numpy.cumsum would produce incorrect outputs
    if a non-boolean input was provided and dtype=bool was specified.
  • Edit implementation of {func}jax.numpy.ldexp to get correct gradient.

v0.4.33

This is a patch release on top of jax 0.4.32, that fixes two bugs found in that
release.

A TPU-only data corruption bug was found in the version of libtpu pinned by
JAX 0.4.32, which manifested only if multiple TPU slices were present in the
same job, for example, if training on multiple v5e slices.
This release fixes that issue by pinning a fixed version of libtpu.

This release fixes an inaccurate result for F64 tanh on CPU (#​23590).

v0.4.32

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Note: This release was yanked from PyPi because of a data corruption bug on TPU.
See the 0.4.33 release notes for more details.

• New Functionality

  • Added {func}jax.extend.ffi.ffi_call and {func}jax.extend.ffi.ffi_lowering
    to support the use of the new {ref}ffi-tutorial to interface with custom
    C++ and CUDA code from JAX.

• Changes

  • jax_enable_memories flag is set to True by default.
  • {mod}jax.numpy now supports v2023.12 of the Python Array API Standard.
    See {ref}python-array-api for more information.
  • Computations on the CPU backend may now be dispatched asynchronously in
    more cases. Previously non-parallel computations were always dispatched
    synchronously. You can recover the old behavior by setting
    jax.config.update('jax_cpu_enable_async_dispatch', False).
  • Added new {func}jax.process_indices function to replace the
    jax.host_ids() function that was deprecated in JAX v0.2.13.
  • To align with the behavior of numpy.fabs, jax.numpy.fabs has been
    modified to no longer support complex dtypes.
  • jax.tree_util.register_dataclass now checks that data_fields
    and meta_fields includes all dataclass fields with init=True
    and only them, if nodetype is a dataclass.
  • Several {mod}jax.numpy functions now have full {class}~jax.numpy.ufunc
    interfaces, including {obj}~jax.numpy.add, {obj}~jax.numpy.multiply,
    {obj}~jax.numpy.bitwise_and, {obj}~jax.numpy.bitwise_or,
    {obj}~jax.numpy.bitwise_xor, {obj}~jax.numpy.logical_and,
    {obj}~jax.numpy.logical_and, and {obj}~jax.numpy.logical_and.
    In future releases we plan to expand these to other ufuncs.
  • Added {func}jax.lax.optimization_barrier, which allows users to prevent
    compiler optimizations such as common-subexpression elimination and to
    control scheduling.

• Breaking changes

  • The MHLO MLIR dialect (jax.extend.mlir.mhlo) has been removed. Use the
    stablehlo dialect instead.

• Deprecations

  • Complex inputs to {func}jax.numpy.clip and {func}jax.numpy.hypot are
    no longer allowed, after being deprecated since JAX v0.4.27.
  • Deprecated the following APIs:
    • jax.lib.xla_bridge.xla_client: use {mod}jax.lib.xla_client directly.
    • jax.lib.xla_bridge.get_backend: use {func}jax.extend.backend.get_backend.
    • jax.lib.xla_bridge.default_backend: use {func}jax.extend.backend.default_backend.
  • The jax.experimental.array_api module is deprecated, and importing it is no
    longer required to use the Array API. jax.numpy supports the array API
    directly; see {ref}python-array-api for more information.
  • The internal utilities jax.core.check_eqn, jax.core.check_type, and
    jax.core.check_valid_jaxtype are now deprecated, and will be removed in
    the future.
  • jax.numpy.round_ has been deprecated, following removal of the corresponding
    API in NumPy 2.0. Use {func}jax.numpy.round instead.
  • Passing a DLPack capsule to {func}jax.dlpack.from_dlpack is deprecated.
    The argument to {func}jax.dlpack.from_dlpack should be an array from
    another framework that implements the __dlpack__ protocol.

v0.4.31

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• Deletion

  • xmap has been deleted. Please use {func}shard_map as the replacement.

• Changes

  • The minimum CuDNN version is v9.1. This was true in previous releases also,
    but we now declare this version constraint formally.
  • The minimum Python version is now 3.10. 3.10 will remain the minimum
    supported version until July 2025.
  • The minimum NumPy version is now 1.24. NumPy 1.24 will remain the minimum
    supported version until December 2024.
  • The minimum SciPy version is now 1.10. SciPy 1.10 will remain the minimum
    supported version until January 2025.
  • {func}jax.numpy.ceil, {func}jax.numpy.floor and {func}jax.numpy.trunc now return the output
    of the same dtype as the input, i.e. no longer upcast integer or boolean inputs to floating point.
  • libdevice.10.bc is no longer bundled with CUDA wheels. It must be
    installed either as a part of local CUDA installation, or via NVIDIA's CUDA
    pip wheels.
  • {class}jax.experimental.pallas.BlockSpec now expects block_shape to
    be passed before index_map. The old argument order is deprecated and
    will be removed in a future release.
  • Updated the repr of gpu devices to be more consistent
    with TPUs/CPUs. For example, cuda(id=0) will now be CudaDevice(id=0).
  • Added the device property and to_device method to {class}jax.Array, as
    part of JAX's Array API support.

• Deprecations

  • Removed a number of previously-deprecated internal APIs related to
    polymorphic shapes. From {mod}jax.core: removed canonicalize_shape,
    dimension_as_value, definitely_equal, and symbolic_equal_dim.
  • HLO lowering rules should no longer wrap singleton ir.Values in tuples.
    Instead, return singleton ir.Values unwrapped. Support for wrapped values
    will be removed in a future version of JAX.
  • {func}jax.experimental.jax2tf.convert with native_serialization=False
    or enable_xla=False is now deprecated and this support will be removed in
    a future version.
    Native serialization has been the default since JAX 0.4.16 (September 2023).
  • The previously-deprecated function jax.random.shuffle has been removed;
    instead use jax.random.permutation with independent=True.

v0.4.30

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• Changes

  • JAX supports ml_dtypes >= 0.2. In 0.4.29 release, the ml_dtypes version was
    bumped to 0.4.0 but this has been rolled back in this release to give users
    of both TensorFlow and JAX more time to migrate to a newer TensorFlow
    release.
  • jax.experimental.mesh_utils can now create an efficient mesh for TPU v5e.
  • jax now depends on jaxlib directly. This change was enabled by the CUDA
    plugin switch: there are no longer multiple jaxlib variants. You can install
    a CPU-only jax with pip install jax, no extras required.
  • Added an API for exporting and serializing JAX functions. This used
    to exist in jax.experimental.export (which is being deprecated),
    and will now live in jax.export.
    See the documentation.

• Deprecations

  • Internal pretty-printing tools jax.core.pp_* are deprecated, and will be removed
    in a future release.
  • Hashing of tracers is deprecated, and will lead to a TypeError in a future JAX
    release. This previously was the case, but there was an inadvertent regression in
    the last several JAX releases.
  • jax.experimental.export is deprecated. Use {mod}jax.export instead.
    See the migration guide.
  • Passing an array in place of a dtype is now deprecated in most cases; e.g. for arrays
    x and y, x.astype(y) will raise a warning. To silence it use x.astype(y.dtype).
  • jax.xla_computation is deprecated and will be removed in a future release.
    Please use the AOT APIs to get the same functionality as jax.xla_computation.
    • jax.xla_computation(fn)(*args, **kwargs) can be replaced with
      jax.jit(fn).lower(*args, **kwargs).compiler_ir('hlo').
    • You can also use .out_info property of jax.stages.Lowered to get the
      output information (like tree structure, shape and dtype).
    • For cross-backend lowering, you can replace
      jax.xla_computation(fn, backend='tpu')(*args, **kwargs) with
      jax.jit(fn).trace(*args, **kwargs).lower(lowering_platforms=('tpu',)).compiler_ir('hlo').

v0.4.29

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• Changes

  • We anticipate that this will be the last release of JAX and jaxlib
    supporting a monolithic CUDA jaxlib. Future releases will use the CUDA
    plugin jaxlib (e.g. pip install jax[cuda12]).
  • JAX now requires ml_dtypes version 0.4.0 or newer.
  • Removed backwards-compatibility support for old usage of the
    jax.experimental.export API. It is not possible anymore to use
    from jax.experimental.export import export, and instead you should use
    from jax.experimental import export.
    The removed functionality has been deprecated since 0.4.24.
  • Added is_leaf argument to {func}jax.tree.all & {func}jax.tree_util.tree_all.

• Deprecations

  • jax.sharding.XLACompatibleSharding is deprecated. Please use
    jax.sharding.Sharding.
  • jax.experimental.Exported.in_shardings has been renamed as
    jax.experimental.Exported.in_shardings_hlo. Same for out_shardings.
    The old names will be removed after 3 months.
  • Removed a number of previously-deprecated APIs:
    • from {mod}jax.core: non_negative_dim, DimSize, Shape
    • from {mod}jax.lax: tie_in
    • from {mod}jax.nn: normalize
    • from {mod}jax.interpreters.xla: backend_specific_translations,
      translations, register_translation, xla_destructure,
      TranslationRule, TranslationContext, XlaOp.
  • The tol argument of {func}jax.numpy.linalg.matrix_rank is being
    deprecated and will soon be removed. Use rtol instead.
  • The rcond argument of {func}jax.numpy.linalg.pinv is being
    deprecated and will soon be removed. Use rtol instead.
  • The deprecated jax.config submodule has been removed. To configure JAX
    use import jax and then reference the config object via jax.config.
  • {mod}jax.random APIs no longer accept batched keys, where previously
    some did unintentionally. Going forward, we recommend explicit use of
    {func}jax.vmap in such cases.
  • In {func}jax.scipy.special.beta, the x and y parameters have been
    renamed to a and b for consistency with other beta APIs.

• New Functionality

  • Added {func}jax.experimental.Exported.in_shardings_jax to construct
    shardings that can be used with the JAX APIs from the HloShardings
    that are stored in the Exported objects.

v0.4.28

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• Bug fixes

  • Reverted a change to make_jaxpr that was breaking Equinox (#​21116).

• Deprecations & removals

  • The kind argument to {func}jax.numpy.sort and {func}jax.numpy.argsort
    is now removed. Use stable=True or stable=False instead.
  • Removed get_compute_capability from the jax.experimental.pallas.gpu
    module. Use the compute_capability attribute of a GPU device, returned
    by {func}jax.devices or {func}jax.local_devices, instead.
  • The newshape argument to {func}jax.numpy.reshapeis being deprecated
    and will soon be removed. Use shape instead.

• Changes

  • The minimum jaxlib version of this release is 0.4.27.

v0.4.27

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• New Functionality

  • Added {func}jax.numpy.unstack and {func}jax.numpy.cumulative_sum,
    following their addition in the array API 2023 standard, soon to be
    adopted by NumPy.
  • Added a new config option jax_cpu_collectives_implementation to select the
    implementation of cross-process collective operations used by the CPU backend.
    Choices available are 'none'(default), 'gloo' and 'mpi' (requires jaxlib 0.4.26).
    If set to 'none', cross-process collective operations are disabled.

• Changes

  • {func}jax.pure_callback, {func}jax.experimental.io_callback
    and {func}jax.debug.callback now use {class}jax.Array instead
    of {class}np.ndarray. You can recover the old behavior by transforming
    the arguments via jax.tree.map(np.asarray, args) before passing them
    to the callback.
  • complex_arr.astype(bool) now follows the same semantics as NumPy, returning
    False where complex_arr is equal to 0 + 0j, and True otherwise.
  • core.Token now is a non-trivial class which wraps a jax.Array. It could
    be created and threaded in and out of computations to build up dependency.
    The singleton object core.token has been removed, users now should create
    and use fresh core.Token objects instead.
  • On GPU, the Threefry PRNG implementation no longer lowers to a kernel call
    by default. This choice can improve runtime memory usage at a compile-time
    cost. Prior behavior, which produces a kernel call, can be recovered with
    jax.config.update('jax_threefry_gpu_kernel_lowering', True). If the new
    default causes issues, please file a bug. Otherwise, we intend to remove
    this flag in a future release.

• Deprecations & Removals

  • Pallas now exclusively uses XLA for compiling kernels on GPU. The old
    lowering pass via Triton Python APIs has been removed and the
    JAX_TRITON_COMPILE_VIA_XLA environment variable no longer has any effect.
  • {func}jax.numpy.clip has a new argument signature: a, a_min, and
    a_max are deprecated in favor of x (positional only), min, and
    max ({jax-issue}20550).
  • The device() method of JAX arrays has been removed, after being deprecated
    since JAX v0.4.21. Use arr.devices() instead.
  • The initial argument to {func}jax.nn.softmax and {func}jax.nn.log_softmax
    is deprecated; empty inputs to softmax are now supported without setting this.
  • In {func}jax.jit, passing invalid static_argnums or static_argnames
    now leads to an error rather than a warning.
  • The minimum jaxlib version is now 0.4.23.
  • The {func}jax.numpy.hypot function now issues a deprecation warning when
    passing complex-valued inputs to it. This will raise an error when the
    deprecation is completed.
  • Scalar arguments to {func}jax.numpy.nonzero, {func}jax.numpy.where, and
    related functions now raise an error, following a similar change in NumPy.
  • The config option jax_cpu_enable_gloo_collectives is deprecated.
    Use jax.config.update('jax_cpu_collectives_implementation', 'gloo') instead.
  • The jax.Array.device_buffer and jax.Array.device_buffers methods have
    been removed after being deprecated in JAX v0.4.22. Instead use
    {attr}jax.Array.addressable_shards and {meth}jax.Array.addressable_data.
  • The condition, x, and y parameters of jax.numpy.where are now
    positional-only, following deprecation of the keywords in JAX v0.4.21.
  • Non-array arguments to functions in {mod}jax.lax.linalg now must be
    specified by keyword. Previously, this raised a DeprecationWarning.
  • Array-like arguments are now required in several :func:jax.numpy APIs,
    including {func}~jax.numpy.apply_along_axis,
    {func}~jax.numpy.apply_over_axes, {func}~jax.numpy.inner,
    {func}~jax.numpy.outer, {func}~jax.numpy.cross,
    {func}~jax.numpy.kron, and {func}~jax.numpy.lexsort.

• Bug fixes

  • {func}jax.numpy.astype will now always return a copy when copy=True.
    Previously, no copy would be made when the output array would have the same
    dtype as the input array. This may result in some increased memory usage.
    The default value is set to copy=False to preserve backwards compatibility.

v0.4.26

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• New Functionality

  • Added {func}jax.numpy.trapezoid, following the addition of this function in
    NumPy 2.0.

• Changes

  • Complex-valued {func}jax.numpy.geomspace now chooses the logarithmic spiral
    branch consistent with that of NumPy 2.0.
  • The behavior of lax.rng_bit_generator, and in turn the 'rbg'
    and 'unsafe_rbg' PRNG implementations, under jax.vmap has
    changed so that
    mapping over keys results in random generation only from the first
    key in the batch.
  • Docs now use jax.random.key for construction of PRNG key arrays
    rather than jax.random.PRNGKey.

• Deprecations & Removals

  • {func}jax.tree_map is deprecated; use jax.tree.map instead, or for backward
    compatibility with older JAX versions, use {func}jax.tree_util.tree_map.
  • {func}jax.clear_backends is deprecated as it does not necessarily do what
    its name suggests and can lead to unexpected consequences, e.g., it will not
    destroy existing backends and release corresponding owned resources. Use
    {func}jax.clear_caches if you only want to clean up compilation caches.
    For backward compatibility or you really need to switch/reinitialize the
    default backend, use {func}jax.extend.backend.clear_backends.
  • The jax.experimental.maps module and jax.experimental.maps.xmap are
    deprecated. Use jax.experimental.shard_map or jax.vmap with the
    spmd_axis_name argument for expressing SPMD device-parallel computations.
  • The jax.experimental.host_callback module is deprecated.
    Use instead the new JAX external callbacks.
    Added JAX_HOST_CALLBACK_LEGACY flag to assist in the transition to the
    new callbacks. See {jax-issue}#20385 for a discussion.
  • Passing arguments to {func}jax.numpy.array_equal and {func}jax.numpy.array_equiv
    that cannot be converted to a JAX array now results in an exception.
  • The deprecated flag jax_parallel_functions_output_gda has been removed.
    This flag was long deprecated and did nothing; its use was a no-op.
  • The previously-deprecated imports jax.interpreters.ad.config and
    jax.interpreters.ad.source_info_util have now been removed. Use jax.config
    and jax.extend.source_info_util instead.
  • JAX export does not support older serialization versions anymore. Version 9
    has been supported since October 27th, 2023 and has become the default
    since February 1, 2024.
    See a description of the versions.
    This change could break clients that set a specific
    JAX serialization version lower than 9.

v0.4.25

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• New Features

  • Added CUDA Array
    Interface
    import support (requires jaxlib 0.4.24).
  • JAX arrays now support NumPy-style scalar boolean indexing, e.g. x[True] or x[False].
  • Added {mod}jax.tree module, with a more convenient interface for referencing functions
    in {mod}jax.tree_util.
  • {func}jax.tree.transpose (i.e. {func}jax.tree_util.tree_transpose) now accepts
    inner_treedef=None, in which case the inner treedef will be automatically inferred.

• Changes

  • Pallas now uses XLA instead of the Triton Python APIs to compile Triton
    kernels. You can revert to the old behavior by setting the
    JAX_TRITON_COMPILE_VIA_XLA environment variable to "0".
  • Several deprecated APIs in {mod}jax.interpreters.xla that were removed in v0.4.24
    have been re-added in v0.4.25, including backend_specific_translations,
    translations, register_translation, xla_destructure, TranslationRule,
    TranslationContext, and XLAOp. These are still considered deprecated, and
    will be removed again in the future when better replacements are available.
    Refer to {jax-issue}#19816 for discussion.

• Deprecations & Removals

  • {func}jax.numpy.linalg.solve now shows a deprecation warning for batched 1D
    solves with b.ndim > 1. In the future these will be treated as batched 2D
    solves.
  • Conversion of a non-scalar array to a Python scalar now raises an error, regardless
    of the size of the array. Previously a deprecation warning was raised in the case of
    non-scalar arrays of size 1. This follows a similar deprecation in NumPy.
  • The previously deprecated configuration APIs have been removed
    following a standard 3 months deprecation cycle (see {ref}api-compatibility).
    These include
    • the jax.config.config object and
    • the define_*_state and DEFINE_* methods of {data}jax.config.
  • Importing the jax.config submodule via import jax.config is deprecated.
    To configure JAX use import jax and then reference the config object
    via jax.config.
  • The minimum jaxlib version is now 0.4.20.

v0.4.24

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• Changes

  • JAX lowering to StableHLO does not depend on physical devices anymore.
    If your primitive wraps custom_partitioning or JAX callbacks in the lowering
    rule i.e. function passed to rule parameter of mlir.register_lowering then add your
    primitive to jax._src.dispatch.prim_requires_devices_during_lowering set.
    This is needed because custom_partitioning and JAX callbacks need physical
    devices to create Shardings during lowering.
    This is a temporary state until we can create Shardings without physical
    devices.
  • {func}jax.numpy.argsort and {func}jax.numpy.sort now support the stable
    and descending arguments.
  • Several changes to the handling of shape polymorphism (used in
    {mod}jax.experimental.jax2tf and {mod}jax.experimental.export):
    • cleaner pretty-printing of symbolic expressions ({jax-issue}#19227)
    • added the ability to specify symbolic constraints on the dimension variables.
      This makes shape polymorphism more expressive, and gives a way to workaround
      limitations in the reasoning about inequalities.
      See https://github.com/jax-ml/jax/blob/main/jax/experimental/jax2tf/README.md#user-specified-symbolic-constraints.
    • with the addition of symbolic constraints ({jax-issue}#19235) we now
      consider dimension variables from different scopes to be different, even
      if they have the same name. Symbolic expressions from different scopes
      cannot interact, e.g., in arithmetic operations.
      Scopes are introduced by {func}jax.experimental.jax2tf.convert,
      {func}jax.experimental.export.symbolic_shape, {func}jax.experimental.export.symbolic_args_specs.
      The scope of a symbolic expression e can be read with e.scope and passed
      into the above functions to direct them to construct symbolic expressions in
      a given scope.
      See https://github.com/jax-ml/jax/blob/main/jax/experimental/jax2tf/README.md#user-specified-symbolic-constraints.
    • simplified and faster equality comparisons, where we consider two symbolic dimensions
      to be equal if the normalized form of their difference reduces to 0
      ({jax-issue}#19231; note that this may result in user-visible behavior
      changes)
    • improved the error messages for inconclusive inequality comparisons
      ({jax-issue}#19235).
    • the core.non_negative_dim API (introduced recently)
      was deprecated and core.max_dim and core.min_dim were introduced
      ({jax-issue}#18953) to express max and min for symbolic dimensions.
      You can use core.max_dim(d, 0) instead of core.non_negative_dim(d).
    • the shape_poly.is_poly_dim is deprecated in favor of export.is_symbolic_dim
      ({jax-issue}#19282).
    • the export.args_specs is deprecated in favor of export.symbolic_args_specs ({jax-issue}#​19283`).
    • the shape_poly.PolyShape and jax2tf.PolyShape are deprecated, use
      strings for polymorphic shapes specifications ({jax-issue}#19284).
    • JAX default native serialization version is now 9. This is relevant
      for {mod}jax.experimental.jax2tf and {mod}jax.experimental.export.
      See description of version numbers.
  • Refactored the API for jax.experimental.export. Instead of
    from jax.experimental.export import export you should use now
    from jax.experimental import export. The old way of importing will
    continue to work for a deprecation period of 3 months.
  • Added {func}jax.scipy.stats.sem.
  • {func}jax.numpy.unique with return_inverse = True returns inverse indices
    reshaped to the dimension of the input, following a similar change to
    {func}numpy.unique in NumPy 2.0.
  • {func}jax.numpy.sign now returns x / abs(x) for nonzero complex inputs. This is
    consistent with the behavior of {func}numpy.sign in NumPy version 2.0.
  • {func}jax.scipy.special.logsumexp with return_sign=True now uses the NumPy 2.0
    convention for the complex sign, x / abs(x). This is consistent with the behavior
    of {func}scipy.special.logsumexp in SciPy v1.13.
  • JAX now supports the bool DLPack type for both import and export.
    Previously bool values could not be imported and were exported as integers.

• Deprecations & Removals

  • A number of previously deprecated functions have been removed, following a
    standard 3+ month deprecation cycle (see {ref}api-compatibility).
    This includes:
    • From {mod}jax.core: TracerArrayConversionError,
      TracerIntegerConversionError, UnexpectedTracerError,
      as_hashable_function, collections, dtypes, lu, map,
      namedtuple, partial, pp, ref, safe_zip, safe_map,
      source_info_util, total_ordering, traceback_util, tuple_delete,
      tuple_insert, and zip.
    • From {mod}jax.lax: dtypes, itertools, naryop, naryop_dtype_rule,
      standard_abstract_eval, standard_naryop, standard_primitive,
      standard_unop, unop, and unop_dtype_rule.
    • The jax.linear_util submodule and all its contents.
    • The jax.prng submodule and all its contents.
    • From {mod}jax.random: PRNGKeyArray, KeyArray, default_prng_impl,
      threefry_2x32, threefry2x32_key, threefry2x32_p, rbg_key, and
      unsafe_rbg_key.
    • From {mod}jax.tree_util: register_keypaths, AttributeKeyPathEntry, and
      GetItemKeyPathEntry.
    • from {mod}jax.interpreters.xla: backend_specific_translations, translations,
      register_translation, xla_destructure, TranslationRule, TranslationContext,
      axis_groups, ShapedArray, ConcreteArray, AxisEnv, backend_compile,
      and XLAOp.
    • from {mod}jax.numpy: NINF, NZERO, PZERO, row_stack, issubsctype,
      trapz, and in1d.
    • from {mod}jax.scipy.linalg: tril and triu.
  • The previously-deprecated method PRNGKeyArray.unsafe_raw_array has been
    removed. Use {func}jax.random.key_data instead.
  • bool(empty_array) now raises an error rather than returning False. This
    previously raised a deprecation warning, and follows a similar change in NumPy.
  • Support for the mhlo MLIR dialect has been deprecated. JAX no longer uses
    the mhlo dialect, in favor of stablehlo. APIs that refer to "mhlo" will be
    removed in the future. Use the "stablehlo" dialect instead.
  • {mod}jax.random: passing batched keys directly to random number generation functions,
    such as {func}~jax.random.bits, {func}~jax.random.gamma, and others, is deprecated
    and will emit a FutureWarning. Use jax.vmap for explicit batching.
  • {func}jax.lax.tie_in is deprecated: it has been a no-op since JAX v0.2.0.

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