docstr: A generator that is an ensemble of many generators.
  
  Args:
      generators (List[:class:`Generator`]): A list of Generators.
      gen_prob (Array like): An array like (list) probabilities with 
          the same length as generators. It specifies the probability 
          of sampling from each generator. If it is `None`, the 
          :class:`EnsembleGenerator` will uniformly sample a generator.
docstr_tok: ["A","generator","that","is","an","ensemble","of","many","generators",".","Args",":","generators","(","List","[",":","class",":","`","Generator","`","]",")",":","A","list","of","Generators",".","gen_prob","(","Array","like",")",":","An","array","like","(","list",")","probabilities","with","the","same","length","as","generators",".","It","specifies","the","probability","of","sampling","from","each","generator",".","If","it","is","`","None","`",",","the",":","class",":","`","EnsembleGenerator","`","will","uniformly","sample","a","generator","."]
code: def __init__(self, generators, gen_prob=None, dataset_len=0):
      r"""
      A generator that is an ensemble of many generators.
  
      Args:
          generators (List[:class:`Generator`]): A list of Generators.
          gen_prob (Array like): An array like (list) probabilities with
              the same length as generators. It specifies the probability
              of sampling from each generator. If it is `None`, the
              :class:`EnsembleGenerator` will uniformly sample a generator.
      """
      super(EnsembleGenerator, self).__init__(
          None, dataset_len=dataset_len
      )
      if gen_prob is None:
          self.gen_prob = np.ones(len(generators)) / len(generators)
      else:
          self.gen_prob = gen_prob
      self.generators = generators
  
imports: import copy
  import math
  import types
  import random
  import networkx
  import numpy
  import torch
  import deepsnap
  from deepsnap.graph import Graph
  from deepsnap.hetero_graph import HeteroGraph
  import pdb
  from typing import Dict, List, Union
  import warnings
label_desc: Use image node_id 1 to create a new EnsembleGenerator object from inherited base classes: Generator with example: obj = EnsembleGenerator(generators, gen_prob, dataset_len)