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 the dot representation of the graph.
  
  Returns:
      A dot representation of the graph.
docstr_tok: ["Returns","the","dot","representation","of","the","graph",".","Returns",":","A","dot","representation","of","the","graph","."]
code: def to_dot(self) -> str:
      """Returns the dot representation of the graph.
  
      Returns:
          A dot representation of the graph.
      """
      edges = "\n".join(f'"{f}" -> "{t}";' for f, t in self.edges)
      return f"""\
  digraph G {{
  rankdir = LR;
  node [shape=box];
  {edges}
  }}
  """
  
file_path: pytorch/torch/package/_digraph.py
imports: from collections import deque
  from typing import List, Set
label_desc: Use image node_id 14 for calling the DiGraph obj's underlying member method code with example usage: obj.to_dot() and returns: str, edges, str