How to use the h5netcdf.core._LazyObjectLookup function in h5netcdf

def __init__(self, parent, name):
        self._parent = parent
        self._root = parent._root
        self._h5path = _join_h5paths(parent.name, name)

        if parent is not self:
            self._dim_sizes = parent._dim_sizes.new_child()
            self._current_dim_sizes = parent._current_dim_sizes.new_child()
            self._dim_order = parent._dim_order.new_child()
            self._all_h5groups = parent._all_h5groups.new_child(self._h5group)

        self._variables = _LazyObjectLookup(self, self._variable_cls)
        self._groups = _LazyObjectLookup(self, self._group_cls)

        # # initialize phony dimension counter
        if self._root._phony_dims_mode is not None:
            self._phony_dims = {}
            phony_dims = defaultdict(int)
            labeled_dims = defaultdict(int)

        for k, v in self._h5group.items():
            if isinstance(v, h5_group_types):
                # add to the groups collection if this is a h5py(d) Group
                # instance
                self._groups.add(k)
            else:
                if v.attrs.get('CLASS') == b'DIMENSION_SCALE':
                    dim_id = v.attrs.get('_Netcdf4Dimid')
                    if '_Netcdf4Coordinates' in v.attrs:

def __init__(self, parent, name):
        self._parent = parent
        self._root = parent._root
        self._h5path = _join_h5paths(parent.name, name)

        if parent is not self:
            self._dim_sizes = parent._dim_sizes.new_child()
            self._current_dim_sizes = parent._current_dim_sizes.new_child()
            self._dim_order = parent._dim_order.new_child()
            self._all_h5groups = parent._all_h5groups.new_child(self._h5group)

        self._variables = _LazyObjectLookup(self, self._variable_cls)
        self._groups = _LazyObjectLookup(self, self._group_cls)

        # # initialize phony dimension counter
        if self._root._phony_dims_mode is not None:
            self._phony_dims = {}
            phony_dims = defaultdict(int)
            labeled_dims = defaultdict(int)

        for k, v in self._h5group.items():
            if isinstance(v, h5_group_types):
                # add to the groups collection if this is a h5py(d) Group
                # instance
                self._groups.add(k)
            else:
                if v.attrs.get('CLASS') == b'DIMENSION_SCALE':
                    dim_id = v.attrs.get('_Netcdf4Dimid')