docstr: Tests whether the algorithm is reproducible within 3 iterations
  on discrete env cartpole.
code: def test_reproducibility_dqn_cartpole(self):
      """Tests whether the algorithm is reproducible within 3 iterations
      on discrete env cartpole."""
  
      register_env(
          "DeterministicCartPole-v1", create_cartpole_deterministic
      )
      config = dqn.DQNConfig().environment(
          env="DeterministicCartPole-v1", env_config={"seed": 42}
      )
      # tf-gpu is excluded for determinism
      # reason: https://github.com/tensorflow/tensorflow/issues/2732
      # https://github.com/tensorflow/tensorflow/issues/2652
      frameworks = ["torch"]
      if int(os.environ.get("RLLIB_NUM_GPUS", 0)) == 0:
          frameworks.append("tf")
  
      check_reproducibilty(
          algo_class=dqn.DQN,
          algo_config=config,
          fw_kwargs={"frameworks": frameworks},
          training_iteration=3,
      )
  
file_path: ray/python/ray/rllib/algorithms/dqn/tests/test_repro_dqn.py
imports: import unittest
  import os
  import ray
  from ray.tune import register_env
  import ray.rllib.algorithms.dqn
  from ray.rllib.examples.env.deterministic_envs import create_cartpole_deterministic
  from ray.rllib.utils.test_utils import check_reproducibilty
label_desc: Use image node_id 3 for calling the TestReproDQN obj's underlying member method code with example usage: obj.test_reproducibility_dqn_cartpole() without return types