JAX v0.7.2
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Breaking changes:
jax.dlpack.from_dlpackno 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__.
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Changes
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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.
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JAX now represents constants in its internal jaxpr representation as a
LiteralArray, which is a private JAX type that duck types as anumpy.ndarray. This type may be exposed to users viacustom_jvprules, for example, and may break code that usesisinstance(x, np.ndarray). If this breaks your code, you may convert these arrays to classic NumPy arrays usingnp.asarray(x).
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Bug fixes
arr.view(dtype=None)now returns the array unchanged, matching NumPy's semantics. Previously it returned the array with a float dtype.jax.random.randintnow produces a less-biased distribution for 8-bit and 16-bit integer types ({jax-issue}#27742). To restore the previous biased behavior, you may temporarily set thejax_safer_randintconfiguration toFalse, but note this is a temporary config that will be removed in a future release.
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Deprecations:
- The parameters
enable_xlaandnative_serializationforjax2tf.convertare deprecated and will be removed in a future version of JAX. These were used for jax2tf with non-native serialization, which has been now removed. - Setting the config state
jax_pmap_no_rank_reductiontoFalseis deprecated. By default,jax_pmap_no_rank_reductionwill be set toTrueandjax.pmapshards will not have their rank reduced, keeping the same rank as their enclosing array.
- The parameters