class_docstr: The superedge structure in GripNet. Each superedge is a bipartite subgraph containing nodes from two categories
  forming two node sets, connected by edges between them. A superedge can be regarded as a heterogeneous graph
  connecting two supervertices.
  
  Args:
      source_supervertex (str): the name of the source supervertex.
      target_supervertex (str): the name of the target supervertex.
      edge_index (torch.Tensor): edge indices in COO format with shape [2, #edges]. The first row is the index of
          source nodes, and the second row is the index of target nodes.
      edge_weight (torch.Tensor, optional): one-dimensional weight for each edge. Defaults to None.
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code: def __repr__(self) -> str:
      return (
          f"SuperEdges(\n    edge_direction={self.source_supervertex}->{self.target_supervertex}, "
          f"\n    edge_index={self.edge_index.shape})"
      )
  
imports: import logging
  from typing import Dict, List, Optional
  import networkx
  import torch
label_desc: Use image node_id 2 for calling the SuperEdge obj's underlying member method code with example usage: obj.__repr__() and returns: str, self, str, self, str, self, str