ak.to_backend
-------------

.. py:module: ak.to_backend

Defined in `awkward.operations.ak_to_backend <https://github.com/scikit-hep/awkward/blob/76cb66b946cbf2ae355bddf2530b323465395bae/src/awkward/operations/ak_to_backend.py>`__ on `line 16 <https://github.com/scikit-hep/awkward/blob/76cb66b946cbf2ae355bddf2530b323465395bae/src/awkward/operations/ak_to_backend.py#L16>`__.

.. py:function:: ak.to_backend(array, backend, *, highlevel=True, behavior=None, attrs=None)


    :param array: Array-like data (anything :py:obj:`ak.to_layout` recognizes).
    :param backend: If ``"cpu"``, the array structure is
                recursively copied (if need be) to main memory for use with
                the default Numpy backend; if ``"cuda"``, the structure is copied
                to the GPU(s) for use with CuPy. If ``"jax"``, the structure is
                copied to the CPU for use with JAX.
    :type backend: ``"cpu"``, ``"cuda"``, or ``"jax"``
    :param highlevel: If True, return an :py:obj:`ak.Array`; otherwise, return
                  a low-level :py:obj:`ak.contents.Content` subclass.
    :type highlevel: bool
    :param behavior: Custom :py:obj:`ak.behavior` for the output array, if
                 high-level.
    :type behavior: None or dict
    :param attrs: Custom attributes for the output array, if
              high-level.
    :type attrs: None or dict

Converts an array from ``"cpu"``, ``"cuda"``, ``"jax"`` kernels to ``"cpu"``,
``"cuda"``, ``"jax"``, or ``"typetracer"`` .

Any components that are already in the desired backend are viewed,
rather than copied, so this operation can be an inexpensive way to ensure
that an array is ready for a particular library.

To use ``"cuda"``, the ``cupy`` package must be installed, either with

.. code-block:: python


    pip install cupy

or

.. code-block:: python


    conda install -c conda-forge cupy

To use ``"jax"``, the ``jax`` package must be installed, either with

.. code-block:: python


    pip install jax

or

.. code-block:: python


    conda install -c conda-forge jax

See :py:obj:`ak.kernels`.