class_docstr: A Qtopt Agent.
  
  Implements the Qt-Opt algorithm from
  
  "QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic "
    "Manipulation"
  
   Dmitry Kalashnikov et al., 2018
   https://arxiv.org/abs/1806.10293
code: def _check_network_output(self, net, label):
      network_utils.check_single_floating_network_output(
          net.create_variables(), expected_output_shape=(), label=label
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import typing
  import gin
  import tensorflow
  from tf_agents.agents import data_converter
  from tf_agents.agents import tf_agent
  from tf_agents.networks import utils
  from tf_agents.policies import epsilon_greedy_policy
  from tf_agents.policies import qtopt_cem_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.typing import types
  from tf_agents.utils import common
  from tf_agents.utils import eager_utils
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 6 for calling the QtOptAgent obj's underlying member method code with example usage: obj._check_network_output(net, label) without return types