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Fix Typos in CHANGELOG.md
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This PR fixes the typos in Change log documentation
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rajasekharporeddy authored Mar 12, 2024
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24 changes: 12 additions & 12 deletions CHANGELOG.md
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Expand Up @@ -89,7 +89,7 @@ Remember to align the itemized text with the first line of an item within a list
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 in
to the above functions to direct them to construct sybolic expressions in
to the above functions to direct them to construct symbolic expressions in
a given scope.
See https://github.com/google/jax/blob/main/jax/experimental/jax2tf/README.md#user-specified-symbolic-constraints.
* simplified and faster equality comparisons, where we consider two symbolic dimensions
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that cannot be converted to a JAX array is deprecated and now raises a
{obj}`DeprecationWaning`. Currently the functions return False, in the future this
will raise an exception.
* The `device()` method of JAX arrays deprecated. Depending on the context, it may
* The `device()` method of JAX arrays is deprecated. Depending on the context, it may
be replaced with one of the following:
- {meth}`jax.Array.devices` returns the set of all devices used by the array.
- {attr}`jax.Array.sharding` gives the sharding configuration used by the array.
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## jax 0.4.17 (Oct 3, 2023)

* New features
* Added new {func}`jax.numpy.bitwise_count` function, matching the API of the simlar
* Added new {func}`jax.numpy.bitwise_count` function, matching the API of the similar
function recently added to NumPy.
* Deprecations
* Removed the deprecated module `jax.abstract_arrays` and all its contents.
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custom pytree node. This includes:
* `tree_flatten_with_path` that flattens a tree and return not only each leaf but
also their key paths.
* `tree_map_with_paths` that can map a function that takes the key path as argument.
* `register_pytree_with_keys`` to register how the key path and leaves should looks
* `tree_map_with_path` that can map a function that takes the key path as an argument.
* `register_pytree_with_keys` to register how the key path and leaves should looks
like in a custom pytree node.
* `keystr` that pretty-prints a key path.

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* 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`
The previous behavior of broadcasting the output against non-scalar `initial`
values was an unintentional implementation detail ({jax-issue}`#14446`).

## jaxlib 0.4.4 (Feb 16, 2023)
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changes to how `isinstance` works for {class}`jax.numpy.ndarray` for jax-internal
objects, as {class}`jax.numpy.ndarray` is now a simple alias of {class}`jax.Array`.
* Breaking changes
* `jax._src` is no longer imported into the from the public `jax` namespace.
* `jax._src` is no longer imported into the public `jax` namespace.
This may break users that were using JAX internals.
* `jax.soft_pmap` has been deleted. Please use `pjit` or `xmap` instead.
`jax.soft_pmap` is undocumented. If it were documented, a deprecation period
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`format_shape_dtype_string`, `rand_uniform`, `skip_on_devices`, `with_config`, `xla_bridge`, and
`_default_tolerance` ({jax-issue}`#10389`). These, along with previously-deprecated `JaxTestCase`,
`JaxTestLoader`, and `BufferDonationTestCase`, will be removed in a future JAX release.
Most of these utilites can be replaced by calls to standard python & numpy testing utilities found
Most of these utilities can be replaced by calls to standard python & numpy testing utilities found
in e.g. {mod}`unittest`, {mod}`absl.testing`, {mod}`numpy.testing`, etc. JAX-specific functionality
such as device checking can be replaced through the use of public APIs such as {func}`jax.devices`.
Many of the deprecated utilities will still exist in {mod}`jax._src.test_util`, but these are not
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* Bug fixes:
* Out-of-bounds indices to `jax.ops.segment_sum` will now be handled with
`FILL_OR_DROP` semantics, as documented. This primarily afects the
`FILL_OR_DROP` semantics, as documented. This primarily affects the
reverse-mode derivative, where gradients corresponding to out-of-bounds
indices will now be returned as 0. (#8634).
* jax2tf will force the converted code to use XLA for the code fragments
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## jaxlib 0.1.61 (February 12 2021)

## jaxlib 0.1.60 (Febuary 3 2021)
## jaxlib 0.1.60 (February 3 2021)

* Bug fixes:
* Fixed a memory leak when converting CPU DeviceArrays to NumPy arrays. The
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* `host_callback.outfeed_receiver` has been removed (it is not necessary,
and was deprecated a few months ago).
* New features:
* New flag for debugging `inf`, analagous to that for `NaN` ({jax-issue}`#5224`).
* New flag for debugging `inf`, analogous to that for `NaN` ({jax-issue}`#5224`).

## jax 0.2.7 (Dec 4 2020)

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* Adds preliminary support for on-device heap profiling.
* Implements `np.nextafter` for `bfloat16` types.
* Complex128 support for FFTs on CPU and GPU.
* Bugfixes:
* Bug fixes:
* Improved float64 `tanh` accuracy on GPU.
* float64 scatters on GPU are much faster.
* Complex matrix multiplication on CPU should be much faster.
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