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	docs fixes (#1263)
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		@@ -2559,7 +2559,7 @@ void init_ops(nb::module_& m) {
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              If unspecified, it defaults to ``-1``.
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        Returns:
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            array: The `uint32`` array containing indices that partition the input.
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            array: The ``uint32`` array containing indices that partition the input.
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      )pbdoc");
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  m.def(
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      "topk",
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@@ -4388,20 +4388,21 @@ void init_ops(nb::module_& m) {
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        Perform the Walsh-Hadamard transform along the final axis.
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        Equivalent to:
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        ```python
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        from scipy.linalg import hadamard
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        y = hadamard(len(x)) @ x
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        ```
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        .. code-block:: python
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        Supports sizes `n = m*2^k` where m in (1, 12, 20, 28)
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          and 2^k <= 8192 for FP32 and 2^k <= 16384 for FP16/BF16.
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           from scipy.linalg import hadamard
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           y = hadamard(len(x)) @ x
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        Supports sizes ``n = m*2^k`` for ``m`` in ``(1, 12, 20, 28)`` and ``2^k
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        <= 8192`` for float32 and ``2^k <= 16384`` for float16/bfloat16.
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        Args:
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            a (array): Input array or scalar.
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            scale (float): Scale the output by this factor.
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        Returns:
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            array: The array with the new type.
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            array: The transformed array.
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      )pbdoc");
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}
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@@ -934,9 +934,9 @@ void init_transforms(nb::module_& m) {
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      This class is meant to be used as a function decorator. Instances are
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      callables that behave identically to the wrapped function. However, when
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      a function transformation is used (e.g. computing gradients using
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      :func:`value_and_grad`) then the functions defined via :method:`vjp`,
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      :method:`jvp` and :method:`vmap` are used instead of the default
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      transformation.
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      :func:`value_and_grad`) then the functions defined via
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      :meth:`custom_function.vjp`, :meth:`custom_function.jvp` and
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      :meth:`custom_function.vmap` are used instead of the default transformation.
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      Note, all custom transformations are optional. Undefined transformations
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      fall back to the default behaviour.
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