How to use the rioxarray.crs.crs_to_wkt function in rioxarray

Set the CRS value for the Dataset/DataArray without modifying
        the dataset/data array.

        Parameters
        ----------
        input_crs: object
            Anything accepted by `rasterio.crs.CRS.from_user_input`.
        inplace: bool, optional
            If True, it will write to the existing dataset. Default is False.

        Returns
        -------
        :obj:`xarray.Dataset` | :obj:`xarray.DataArray`:
            Dataset with crs attribute.
        """
        crs = CRS.from_wkt(crs_to_wkt(input_crs))
        obj = self._get_obj(inplace=inplace)
        obj.rio._crs = crs
        return obj

self.grid_mapping if grid_mapping_name is None else grid_mapping_name
        )
        try:
            del data_obj.coords[grid_mapping_name]
        except KeyError:
            pass

        if data_obj.rio.crs is None:
            raise MissingCRS(
                "CRS not found. Please set the CRS with 'set_crs()' or 'write_crs()'."
            )
        # add grid mapping coordinate
        data_obj.coords[grid_mapping_name] = xarray.Variable((), 0)
        grid_map_attrs = pyproj.CRS.from_user_input(data_obj.rio.crs).to_cf()
        # spatial_ref is for compatibility with GDAL
        crs_wkt = crs_to_wkt(data_obj.rio.crs)
        grid_map_attrs["spatial_ref"] = crs_wkt
        grid_map_attrs["crs_wkt"] = crs_wkt
        if transform is not None:
            grid_map_attrs["GeoTransform"] = " ".join(
                [str(item) for item in transform.to_gdal()]
            )
        data_obj.coords[grid_mapping_name].rio.set_attrs(grid_map_attrs, inplace=True)

        return data_obj.rio.write_grid_mapping(
            grid_mapping_name=grid_mapping_name, inplace=True
        )

invert: boolean, optional
            If False, pixels that do not overlap shapes will be set as nodata.
            Otherwise, pixels that overlap the shapes will be set as nodata.
            False by default.

        Returns
        -------
        :obj:`xarray.DataArray`:
            The clipped object.
        """
        if self.crs is None:
            raise MissingCRS(
                "CRS not found. Please set the CRS with 'set_crs()' or 'write_crs()'."
                f"{_get_data_var_message(self._obj)}"
            )
        crs = CRS.from_wkt(crs_to_wkt(crs)) if crs is not None else self.crs
        if self.crs != crs:
            geometries = [
                rasterio.warp.transform_geom(crs, self.crs, geometry)
                for geometry in geometries
            ]

        clip_mask_arr = geometry_mask(
            geometries=geometries,
            out_shape=(int(self.height), int(self.width)),
            transform=self.transform(recalc=True),
            invert=not invert,
            all_touched=all_touched,
        )
        clip_mask_xray = xarray.DataArray(
            clip_mask_arr,
            coords={

Parameters
        ----------
        match_data_array:  :obj:`xarray.DataArray` | :obj:`xarray.Dataset`
            DataArray of the target resolution and projection.
        resampling: Resampling method, optional
            See rasterio.warp.reproject for more details.


        Returns
        --------
        :obj:`xarray.DataArray`:
            Contains the data from the src_data_array, reprojected to match
            match_data_array.
        """
        dst_crs = crs_to_wkt(match_data_array.rio.crs)
        return self.reproject(
            dst_crs,
            transform=match_data_array.rio.transform(recalc=True),
            shape=match_data_array.rio.shape,
            resampling=resampling,
        )