code: def testInitializeAgentEmptyObservationSpec(self):
      dtype = tf.float32
      num_actions = 5
      observation_spec = tensor_spec.TensorSpec((), 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
      )
      agent = linear_agent.LinearBanditAgent(
          exploration_policy=linear_agent.ExplorationPolicy.linear_ucb_policy,
          time_step_spec=time_step_spec,
          action_spec=action_spec,
          dtype=dtype,
      )
      self.evaluate(agent.initialize())
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from typing import Optional, Tuple
  from absl import flags
  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 linear_bandit_agent
  from tf_agents.bandits.agents import linear_thompson_sampling_agent
  from tf_agents.bandits.agents import utils
  from tf_agents.bandits.drivers import driver_utils
  from tf_agents.bandits.specs import utils
  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.typing import types
  from tf_agents.utils import common
label_desc: Use image node_id 3 for calling the LinearBanditAgentTest obj's underlying member method code with example usage: obj.testInitializeAgentEmptyObservationSpec() without return types