class_docstr: Short benchmarks (~110 steps) for DQN CartPole environment.
class_docstr_tok: ["Short","benchmarks","(","~110","steps",")","for","DQN","CartPole","environment","."]
code: def benchmark_dqn_mirrored_1_gpu(self):
      strategy = distribution_strategy_utils.get_distribution_strategy(
          distribution_strategy="mirrored", num_gpus=1
      )
      self._run(strategy)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import unittest
  import numpy
  from six.moves import range
  import tensorflow
  from tf_agents.agents.dqn import dqn_agent
  from tf_agents.benchmark import distribution_strategy_utils
  from tf_agents.benchmark import utils
  from tf_agents.drivers import dynamic_step_driver
  from tf_agents.environments import random_py_environment
  from tf_agents.environments import tf_py_environment
  from tf_agents.networks import q_network
  from tf_agents.policies import random_tf_policy
  from tf_agents.replay_buffers import tf_uniform_replay_buffer
  from tf_agents.specs import array_spec
  from tf_agents.utils import common
  from tensorflow.python import tf2
label_desc: Use image node_id 14 for calling the DqnCartPoleAgentBenchmark obj's underlying member method code with example usage: obj.benchmark_dqn_mirrored_1_gpu() without return types