class_docstr: An abstract base class to access edges from a remote graph store.
  
  Args:
      edge_attr_cls (EdgeAttr, optional): A user-defined
          :class:`EdgeAttr` class to customize the required attributes and
          their ordering to uniquely identify edges. (default: :obj:`None`)
class_docstr_tok: ["An","abstract","base","class","to","access","edges","from","a","remote","graph","store",".","Args",":","edge_attr_cls","(","EdgeAttr",",","optional",")",":","A","user-defined",":","class",":","`","EdgeAttr","`","class","to","customize","the","required","attributes","and","their","ordering","to","uniquely","identify","edges",".","(","default",":",":","obj",":","`","None","`",")"]
code: def __init__(self, edge_attr_cls: Optional[Any] = None):
      super().__init__()
      self.__dict__["_edge_attr_cls"] = edge_attr_cls or EdgeAttr
  
imports: import copy
  from abc import abstractmethod
  from collections import defaultdict
  from dataclasses import dataclass
  from enum import Enum
  from typing import Any, Dict, List, Optional, Tuple
  from torch import Tensor
  from torch_geometric.typing import EdgeTensorType, EdgeType, OptTensor
  from torch_geometric.utils import index_sort
  from torch_geometric.utils.mixin import CastMixin
  from torch_geometric.utils.sparse import index2ptr, ptr2index
label_desc: Use image node_id 1 to create a new GraphStore object  with example: obj = GraphStore(edge_attr_cls)