class_docstr: Dictionary probability distribution.
  
  The respective functions either return
      - the per key distribution properties or
      - aggregate the properties across the sub-distributions using a reduce_fun such as mean or sum.
  
  :param distribution_dict: dictionary holding sub-probability distributions.
class_docstr_tok: ["Dictionary","probability","distribution",".","The","respective","functions","either","return","-","the","per","key","distribution","properties","or","-","aggregate","the","properties","across","the","sub-distributions","using","a","reduce_fun","such","as","mean","or","sum",".",":","param","distribution_dict",":","dictionary","holding","sub-probability","distributions","."]
code: def __init__(
      self, distribution_dict: Dict[str, ProbabilityDistribution]
  ):
      super().__init__()
      self.distribution_dict = distribution_dict
  
file_path: maze/maze/distributions/dict.py
imports: from typing import Dict
  import torch
  from maze.core.annotations import override
  from maze.distributions.distribution import ProbabilityDistribution
label_desc: Use image node_id 1 to create a new DictProbabilityDistribution object from inherited base classes: ProbabilityDistribution with example: obj = DictProbabilityDistribution(distribution_dict)