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 True if ``n`` is a node in the graph, False otherwise.
docstr_tok: ["Returns","True","if","``","n","``","is","a","node","in","the","graph",",","False","otherwise","."]
code: def __contains__(self, n):
      """Returns True if ``n`` is a node in the graph, False otherwise."""
      try:
          return n in self._node
      except TypeError:
          return False
  
file_path: pytorch/torch/package/_digraph.py
imports: from collections import deque
  from typing import List, Set
label_desc: Use image node_id 9 for calling the DiGraph obj's underlying member method code with example usage: obj.__contains__(n) and returns: unknown, False