class_docstr: Really simple unweighted directed graph data structure to track dependencies.
  
  The API is pretty much the same as networkx so if you add something just
  copy their API.
class_docstr_tok: ["Really","simple","unweighted","directed","graph","data","structure","to","track","dependencies",".","The","API","is","pretty","much","the","same","as","networkx","so","if","you","add","something","just","copy","their","API","."]
docstr: Returns an iterator over all edges (u, v) in the graph
docstr_tok: ["Returns","an","iterator","over","all","edges","(","u",",","v",")","in","the","graph"]
code: def edges(self):
      """Returns an iterator over all edges (u, v) in the graph"""
      for n, successors in self._succ.items():
          for succ in successors:
              yield n, succ
  
file_path: pytorch/torch/package/_digraph.py
imports: from collections import deque
  from typing import List, Set
label_desc: Use image node_id 6 for calling the DiGraph obj's underlying member method code with example usage: obj.edges() without return types