code: def __init__(
      self,
      dict_size,
      key_width,
      num_actions,
      new_value_shift_coefficient=0.1,
      key_error_threshold=0.01,
      learning_rate=0.01,
      num_neighbors=50,
      return_additional_data=False,
      override_existing_keys=False,
      rebuild_on_every_update=False,
  ):
      self.dict_size = dict_size
      self.key_width = key_width
      self.num_actions = num_actions
      self.new_value_shift_coefficient = new_value_shift_coefficient
      self.key_error_threshold = key_error_threshold
      self.learning_rate = learning_rate
      self.num_neighbors = num_neighbors
      self.return_additional_data = return_additional_data
      self.override_existing_keys = override_existing_keys
      self.dicts = []
  
      # create a dict for each action
      for a in range(num_actions):
          new_dict = AnnoyDictionary(
              dict_size,
              key_width,
              new_value_shift_coefficient,
              key_error_threshold=key_error_threshold,
              num_neighbors=num_neighbors,
              override_existing_keys=override_existing_keys,
              rebuild_on_every_update=rebuild_on_every_update,
          )
          self.dicts.append(new_dict)
  
imports: import os
  import pickle
  import numpy
label_desc: Use image node_id 1 to create a new QDND object from inherited base classes: object with example: obj = QDND(dict_size, key_width, num_actions, new_value_shift_coefficient, key_error_threshold, learning_rate, num_neighbors, return_additional_data, override_existing_keys, rebuild_on_every_update)