class_docstr: Models a perception module inference graph.
          Conditions on using the InferenceGraph object:
              1. All keys of the perception_blocks dictionary have to be unique
              2. All out_keys used when creating the blocks have to be unique
              3. All out_keys of a given block have to be sub-strings of the blocks key in the perception_blocks dict
  
  :param inference_block: An inference perception block to build the graph for.
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docstr: Construct the graph and show it.
  
  :param name: The name of the network to be drawn (used in the tile only).
  :param block_execution: Specify whether the execution should be blocked.
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code: def show(self, name: str, block_execution: bool) -> None:
      """Construct the graph and show it.
  
      :param name: The name of the network to be drawn (used in the tile only).
      :param block_execution: Specify whether the execution should be blocked.
      """
      self._draw(name=name, figure_size=None)
      plt.show(block=block_execution)
  
imports: import os
  import pickle
  from typing import Union, List, Dict, Optional, Sequence, Tuple
  import networkx
  import torch
  from matplotlib import pyplot
  from torch import nn
  from maze.core.annotations import override
  from maze.perception.blocks.base import PerceptionBlock
label_desc: Use image node_id 3 for calling the InferenceGraph obj's underlying member method code with example usage: obj.show(name, block_execution) without return types