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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def chunk(*argnames, concatfunc=None):
 """Make a function compatible with multicore chunk processing. This function is intended to be used as a decorator like:: or you can set a global chunk parameter outside the function:: """

    def _chunk(func):
        depth = [s.function for s in stack()].index('<module>')
        f_globals = getframe(depth).f_globals

        # original (unwrapped) function
        orgname = '_original_' + func.__name__
        orgfunc = dc.utils.copy_function(func, orgname)
        f_globals[orgname] = orgfunc

        @wraps(func)
        def wrapper(*args, **kwargs):
            depth = [s.function for s in stack()].index('<module>')
            f_globals = getframe(depth).f_globals

            # parse args and kwargs
            params = signature(func).parameters
            for i, (key, val) in enumerate(params.items()):
                if not val.kind == Parameter.POSITIONAL_OR_KEYWORD:
                    break

                try:
                    kwargs.update({key: args[i]})
                except IndexError:
                    kwargs.setdefault(key, val.default)

            # n_chunks and n_processes
            n_chunks = DEFAULT_N_CHUNKS
            n_processes = MAX_WORKERS

            if argnames:
                length = len(kwargs[argnames[0]])

                if 'numchunk' in kwargs:
                    n_chunks = kwargs.pop('numchunk')
                elif 'timechunk' in kwargs:
                    n_chunks = round(length / kwargs.pop('timechunk'))
                elif 'numchunk' in f_globals:
                    n_chunks = f_globals['numchunk']
                elif 'timechunk' in f_globals:
                    n_chunks = round(length / f_globals['timechunk'])

                if 'n_processes' in kwargs:
                    n_processes = kwargs.pop('n_processes')
                elif 'n_processes' in f_globals:
                    n_processes = f_globals['n_processes']

            # make chunked args
            chunks = {}
            for name in argnames:
                arg = kwargs.pop(name)
                try:
                    chunks.update({name: np.array_split(arg, n_chunks)})
                except TypeError:
                    chunks.update({name: np.tile(arg, n_chunks)})

            # run the function
            futures = []
            results = []
            with dc.utils.one_thread_per_process(), Pool(n_processes) as p:
                for i in range(n_chunks):
                    chunk = {key: val[i] for key, val in chunks.items()}
                    futures.append(p.submit(orgfunc, **{**chunk, **kwargs}))

                for future in futures:
                    results.append(future.result())

            # make an output
            if concatfunc is not None:
                return concatfunc(results)

            try:
                return xr.concat(results, 't')
            except TypeError:
                return np.concatenate(results, 0)

        return wrapper

    return _chunk