code: def testInitializeAgent(self, batch_size, context_dim, num_agents):
      num_actions = 7
      observation_spec = tensor_spec.TensorSpec(
          [context_dim], tf.float32
      )
      time_step_spec = time_step.time_step_spec(observation_spec)
      action_spec = tensor_spec.BoundedTensorSpec(
          dtype=tf.int32, shape=(), minimum=0, maximum=num_actions - 1
      )
      agents = [
          lin_ucb_agent.LinearUCBAgent(time_step_spec, action_spec)
          for _ in range(num_agents)
      ]
      dist = tfd.Categorical(
          probs=tf.Variable(tf.range(num_agents, dtype=tf.float32))
      )
      mixed_agent = WeightRotatingMixtureAgent(dist, agents)
      self.evaluate(mixed_agent.initialize())
  
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 2 for calling the MixtureAgentTest obj's underlying member method code with example usage: obj.testInitializeAgent(batch_size, context_dim, num_agents) without return types