ak.to_backend ============= Defined in `awkward.operations.ak_to_backend `__ on `line 16 `__. .. py:function:: ak.to_backend(array, backend, *, highlevel=True, behavior=None, attrs=None) Returns an array on a different backend (kernel set). 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:: pip install cupy or:: conda install -c conda-forge cupy To use ``"jax"``, the ``jax`` package must be installed, either with:: pip install jax or:: conda install -c conda-forge jax See :py:obj:`ak.kernels`. :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"``, ``"jax"``, or ``"typetracer"`` :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 :returns: An array with the same data as the input, moved to the requested backend (kernel set).