def chunk(
        self,
        chunks: T_ChunksFreq = {},  # noqa: B006  # {} even though it's technically unsafe, is being used intentionally here (#4667)
        name_prefix: str = "xarray-",
        token: str | None = None,
        lock: bool = False,
        inline_array: bool = False,
        chunked_array_type: str | ChunkManagerEntrypoint | None = None,
        from_array_kwargs=None,
        **chunks_kwargs: T_ChunkDimFreq,
    ) -> Self:
        """Coerce all arrays in all groups in this tree into dask arrays with the given
        chunks.

        Non-dask arrays in this tree will be converted to dask arrays. Dask
        arrays will be rechunked to the given chunk sizes.

        If neither chunks is not provided for one or more dimensions, chunk
        sizes along that dimension will not be updated; non-dask arrays will be
        converted into dask arrays with a single block.

        Along datetime-like dimensions, a :py:class:`groupers.TimeResampler` object is also accepted.

        Parameters
        ----------
        chunks : int, tuple of int, "auto" or mapping of hashable to int or a TimeResampler, optional
            Chunk sizes along each dimension, e.g., ``5``, ``"auto"``, or
            ``{"x": 5, "y": 5}`` or ``{"x": 5, "time": TimeResampler(freq="YE")}``.
        name_prefix : str, default: "xarray-"
            Prefix for the name of any new dask arrays.
        token : str, optional
            Token uniquely identifying this datatree.
        lock : bool, default: False
            Passed on to :py:func:`dask.array.from_array`, if the array is not
            already as dask array.
        inline_array: bool, default: False
            Passed on to :py:func:`dask.array.from_array`, if the array is not
            already as dask array.
        chunked_array_type: str, optional
            Which chunked array type to coerce this datatree's arrays to.
            Defaults to 'dask' if installed, else whatever is registered via the `ChunkManagerEntryPoint` system.
            Experimental API that should not be relied upon.
        from_array_kwargs: dict, optional
            Additional keyword arguments passed on to the `ChunkManagerEntrypoint.from_array` method used to create
            chunked arrays, via whichever chunk manager is specified through the `chunked_array_type` kwarg.
            For example, with dask as the default chunked array type, this method would pass additional kwargs
            to :py:func:`dask.array.from_array`. Experimental API that should not be relied upon.
        **chunks_kwargs : {dim: chunks, ...}, optional
            The keyword arguments form of ``chunks``.
            One of chunks or chunks_kwargs must be provided

        Returns
        -------
        chunked : xarray.DataTree

        See Also
        --------
        Dataset.chunk
        Dataset.chunksizes
        xarray.unify_chunks
        dask.array.from_array
        """
        # don't support deprecated ways of passing chunks
        if not isinstance(chunks, Mapping):
            raise TypeError(
                f"invalid type for chunks: {type(chunks)}. Only mappings are supported."
            )
        combined_chunks = either_dict_or_kwargs(chunks, chunks_kwargs, "chunk")

        all_dims = self._get_all_dims()

        bad_dims = combined_chunks.keys() - all_dims
        if bad_dims:
            raise ValueError(
                f"chunks keys {tuple(bad_dims)} not found in data dimensions {tuple(all_dims)}"
            )

        rechunked_groups = {
            path: node.dataset.chunk(
                {
                    dim: size
                    for dim, size in combined_chunks.items()
                    if dim in node._node_dims
                },
                name_prefix=name_prefix,
                token=token,
                lock=lock,
                inline_array=inline_array,
                chunked_array_type=chunked_array_type,
                from_array_kwargs=from_array_kwargs,
            )
            for path, node in self.subtree_with_keys
        }

        return self.from_dict(rechunked_groups, name=self.name)
Coerce all arrays in all groups in this tree into dask arrays with the given
        chunks.

        Non-dask arrays in this tree will be converted to dask arrays. Dask
        arrays will be rechunked to the given chunk sizes.

        If neither chunks is not provided for one or more dimensions, chunk
        sizes along that dimension will not be updated; non-dask arrays will be
        converted into dask arrays with a single block.

        Along datetime-like dimensions, a :py:class:`groupers.TimeResampler` object is also accepted.

        Parameters
        ----------
        chunks : int, tuple of int, "auto" or mapping of hashable to int or a TimeResampler, optional
            Chunk sizes along each dimension, e.g., ``5``, ``"auto"``, or
            ``{"x": 5, "y": 5}`` or ``{"x": 5, "time": TimeResampler(freq="YE")}``.
        name_prefix : str, default: "xarray-"
            Prefix for the name of any new dask arrays.
        token : str, optional
            Token uniquely identifying this datatree.
        lock : bool, default: False
            Passed on to :py:func:`dask.array.from_array`, if the array is not
            already as dask array.
        inline_array: bool, default: False
            Passed on to :py:func:`dask.array.from_array`, if the array is not
            already as dask array.
        chunked_array_type: str, optional
            Which chunked array type to coerce this datatree's arrays to.
            Defaults to 'dask' if installed, else whatever is registered via the `ChunkManagerEntryPoint` system.
            Experimental API that should not be relied upon.
        from_array_kwargs: dict, optional
            Additional keyword arguments passed on to the `ChunkManagerEntrypoint.from_array` method used to create
            chunked arrays, via whichever chunk manager is specified through the `chunked_array_type` kwarg.
            For example, with dask as the default chunked array type, this method would pass additional kwargs
            to :py:func:`dask.array.from_array`. Experimental API that should not be relied upon.
        **chunks_kwargs : {dim: chunks, ...}, optional
            The keyword arguments form of ``chunks``.
            One of chunks or chunks_kwargs must be provided

        Returns
        -------
        chunked : xarray.DataTree

        See Also
        --------
        Dataset.chunk
        Dataset.chunksizes
        xarray.unify_chunks
        dask.array.from_array
        
xarray/core/datatree.py