class_docstr: In memory storage for testing-only.
  
  Uses a priority queue under the hood to sort the models according to their
  score.
  
  Currently the only supported score is 'loss'.
docstr: Returns all stored models.
code: def get_models(self) -> List[tf.keras.Model]:
      """Returns all stored models."""
      return [c.model for c in self._model_containers]
  
file_path: adanet/adanet/experimental/storages/in_memory_storage.py
imports: import heapq
  from typing import List
  from adanet.experimental.storages.storage import ModelContainer
  from adanet.experimental.storages.storage import Storage
  import tensorflow.compat.v2
label_desc: Use image node_id 3 for calling the InMemoryStorage obj's underlying member method code with example usage: obj.get_models() and returns: unknown