class_docstr: An ensemble strategy that adds k random candidates (with replacement).
docstr: Initializes a RandomKStrategy ensemble strategy.
  
  Args:
    k: Number of candidates to sample.
    seed: Random seed.
docstr_tok: ["Initializes","a","RandomKStrategy","ensemble","strategy",".","Args",":","k",":","Number","of","candidates","to","sample",".","seed",":","Random","seed","."]
code: def __init__(self, k, seed=None):
      """Initializes a RandomKStrategy ensemble strategy.
  
      Args:
        k: Number of candidates to sample.
        seed: Random seed.
      """
      self._k = k
      self._seed = seed
  
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 to create a new RandomKStrategy object from inherited base classes: EnsembleStrategy with example: obj = RandomKStrategy(k, seed)