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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 _add_grid_attributes(self, ds):
 """Add model grid attributes to a dataset"""

        for name_int, names_ext in self._grid_attrs.items():
            ds_coord_name = set(names_ext).intersection(set(ds.coords) |
                                                        set(ds.data_vars))
            model_attr = getattr(self.model, name_int, None)
            if ds_coord_name and (model_attr is not None):
                # Force coords to have desired name.
                ds = ds.rename({list(ds_coord_name)[0]: name_int})
                ds = ds.set_coords(name_int)
                if not np.array_equal(ds[name_int], model_attr):
                    if np.allclose(ds[name_int], model_attr):
                        msg = ("Values for '{0}' are nearly (but not exactly) "
                               "the same in the Run {1} and the Model {2}.  "
                               "Therefore replacing Run's values with the "
                               "model's.".format(name_int, self.run,
                                                 self.model))
                        logging.info(msg)
                        ds[name_int].values = model_attr.values
                    else:
                        msg = ("Model coordinates for '{0}' do not match those"
                               " in Run: {1} vs. {2}"
                               "".format(name_int, ds[name_int], model_attr))
                        logging.info(msg)

            else:
                # Bring in coord from model object if it exists.
                ds = ds.load()
                if model_attr is not None:
                    ds[name_int] = model_attr
                    ds = ds.set_coords(name_int)
            if (self.dtype_in_vert == 'pressure' and
                    internal_names.PLEVEL_STR in ds.coords):
                self.pressure = ds.level
        return ds