def METHOD_NAME(
    cls,
    edge_id_dict: Dict[EdgeType, Tensor],
    edge_index_dict: Dict[EdgeType, Tensor],
    num_nodes_dict: Dict[NodeType, int],
) -> 'LocalGraphStore':
    r"""Creates a local graph store from a heterogeneous :pyg:`PyG` graph.
    Args:
        edge_id_dict (Dict[EdgeType, torch.Tensor]): The global identifier
            for every local edge of every edge type.
        edge_index_dict (Dict[EdgeType, torch.Tensor]): The local edge
            indices of every edge type.
        num_nodes_dict (Dict[NodeType, int]): The number of nodes in the
            local graph of every node type.
    """
    attr_dict = {}
    for edge_type in edge_index_dict.keys():
        src, _, dst = edge_type
        attr_dict[edge_type] = dict(
            edge_type=edge_type,
            layout='coo',
            size=(num_nodes_dict[src], num_nodes_dict[dst]),
        )
    graph_store = cls()
    for edge_type, edge_index in edge_index_dict.items():
        attr = attr_dict[edge_type]
        edge_id = edge_id_dict[edge_type]
        graph_store.put_edge_index(edge_index, **attr)
        graph_store.put_edge_id(edge_id, **attr)
    return graph_store