class_docstr: Removes duplicated edges from a given homogeneous or heterogeneous
  graph. Useful to clean-up known repeated edges/self-loops in common
  benchmark datasets, *e.g.*, in :obj:`ogbn-products`.
  (functional name: :obj:`remove_duplicated_edges`).
  
  Args:
      key (str or [str], optional): The name of edge attribute(s) to merge in
          case of duplication. (default: :obj:`["edge_weight", "edge_attr"]`)
      reduce (str, optional): The reduce operation to use for merging edge
          attributes (:obj:`"add"`, :obj:`"mean"`, :obj:`"min"`,
          :obj:`"max"`, :obj:`"mul"`). (default: :obj:`"add"`)
code: def __init__(
      self,
      key: Union[str, List[str]] = ["edge_attr", "edge_weight"],
      reduce: str = "add",
  ) -> None:
      if isinstance(key, str):
          key = [key]
  
      self.keys = key
      self.reduce = reduce
  
file_path: pytorch_geometric/torch_geometric/transforms/remove_duplicated_edges.py
imports: from typing import List, Union
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
  from torch_geometric.utils import coalesce
label_desc: Use image node_id 1 to create a new RemoveDuplicatedEdges object from inherited base classes: BaseTransform with example: obj = RemoveDuplicatedEdges(key, reduce)