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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 _load_data_from_disk(file_set, preprocess_func=lambda ds: ds, data_vars='minimal', coords='minimal', grid_attrs=None, **kwargs):
 """Load a Dataset from a list or glob-string of files. Datasets from files are concatenated along time, and all grid attributes are renamed to their aospy internal names. Parameters file_set : list or str List of paths to files or glob-string preprocess_func : function (optional) Custom function to call before applying any aospy logic to the loaded dataset data_vars : str (default 'minimal') Mode for concatenating data variables in call to ``xr.open_mfdataset`` coords : str (default 'minimal') Mode for concatenating coordinate variables in call to ``xr.open_mfdataset``. grid_attrs : dict Overriding dictionary of grid attributes mapping aospy internal names to names of grid attributes used in a particular model. Returns ------- Dataset """

    apply_preload_user_commands(file_set)
    func = _preprocess_and_rename_grid_attrs(preprocess_func, grid_attrs,
                                             **kwargs)
    return xr.open_mfdataset(file_set, preprocess=func, concat_dim=TIME_STR,
                             decode_times=False, decode_coords=False,
                             mask_and_scale=True, data_vars=data_vars,
                             coords=coords)