class_docstr: A set of tests for the Learner.
class_docstr_tok: ["A","set","of","tests","for","the","Learner","."]
code: def _build_learner_with_strategy(
      self,
      create_agent_and_dataset_fn,
      strategy,
      sample_batch_size=2,
      root_dir=None,
  ):
      if strategy is None:
          # Get default strategy if None provided.
          strategy = tf.distribute.get_strategy()
  
      with strategy.scope():
          tf_env = tf_py_environment.TFPyEnvironment(
              suite_gym.load("CartPole-v0")
          )
  
          train_step = train_utils.create_train_step()
          agent, dataset, dataset_fn, _ = create_agent_and_dataset_fn(
              tf_env.action_spec(),
              tf_env.time_step_spec(),
              train_step,
              sample_batch_size,
          )
  
          if root_dir is None:
              root_dir = os.path.join(
                  self.create_tempdir().full_path, "learner"
              )
  
          test_learner = learner.Learner(
              root_dir=root_dir,
              train_step=train_step,
              agent=agent,
              experience_dataset_fn=dataset_fn,
              checkpoint_interval=1,
          )
          variables = agent.collect_policy.variables()
      return test_learner, dataset, variables, train_step, dataset_fn
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import os
  from absl import logging
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  import tensorflow
  from tf_agents.agents.behavioral_cloning import behavioral_cloning_agent
  from tf_agents.environments import suite_gym
  from tf_agents.environments import tf_py_environment
  from tf_agents.keras_layers import inner_reshape
  from tf_agents.networks import sequential
  from tf_agents.specs import tensor_spec
  from tf_agents.system import system_multiprocessing
  from tf_agents.train import learner
  from tf_agents.train.utils import test_utils
  from tf_agents.train.utils import train_utils
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 2 for calling the LearnerTest obj's underlying member method code with example usage: obj._build_learner_with_strategy(create_agent_and_dataset_fn, strategy, sample_batch_size, root_dir) and returns: test_learner,  dataset,  variables,  train_step,  dataset_fn