code: def test_cases():
      return parameterized.named_parameters(
          {
              "testcase_name": "_batch1_contextdim10_numagents2",
              "batch_size": 1,
              "context_dim": 10,
              "num_agents": 2,
          },
          {
              "testcase_name": "_batch4_contextdim5_numagents10",
              "batch_size": 4,
              "context_dim": 5,
              "num_agents": 10,
          },
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.agents import lin_ucb_agent
  from tf_agents.bandits.agents import mixture_agent
  from tf_agents.bandits.agents import neural_epsilon_greedy_agent
  from tf_agents.bandits.drivers import driver_utils
  from tf_agents.bandits.policies import mixture_policy
  from tf_agents.networks import q_network
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_cases() and returns: parameterized