class_docstr: An ensemble strategy that adds one candidate to the ensemble at a time.
code: def __call__(
      self, candidates: List[tf.keras.Model]
  ) -> Iterable[List[tf.keras.Model]]:
      return [[candidate] for candidate in candidates]
  
imports: import abc
  import random
  from typing import Iterable, Iterator, List
  from adanet.experimental.keras.ensemble_model import EnsembleModel
  from adanet.experimental.keras.ensemble_model import MeanEnsemble
  from adanet.experimental.phases.phase import DatasetProvider
  from adanet.experimental.phases.phase import ModelProvider
  from adanet.experimental.storages.in_memory_storage import InMemoryStorage
  from adanet.experimental.storages.storage import Storage
  from adanet.experimental.work_units.keras_trainer_work_unit import KerasTrainerWorkUnit
  from adanet.experimental.work_units.work_unit import WorkUnit
  import tensorflow.compat.v2
label_desc: Use image node_id 1 for calling the GrowStrategy obj's underlying member method code with example usage: obj.__call__(candidates) and returns: unknown