code: def test_explicit_bias_environment(
      self, batch_size, global_dim, item_dim, num_items, num_slots
  ):
      def _global_sampling_fn():
          return np.random.randint(-10, 10, [global_dim])
  
      def _item_sampling_fn():
          return np.random.randint(-2, 3, [item_dim])
  
      def _relevance_fn(global_obs, item_obs):
          min_dim = min(global_dim, item_dim)
          dot_prod = np.dot(
              global_obs[:min_dim], item_obs[:min_dim]
          ).astype(np.float32)
          return 1 / (1 + np.exp(-dot_prod))
  
      positional_biases = list(
          0.75 - np.arange(num_slots) / (2 * num_slots)
      )
      env = (
          ranking_environment.ExplicitPositionalBiasRankingEnvironment(
              _global_sampling_fn,
              _item_sampling_fn,
              _relevance_fn,
              num_items,
              positional_biases,
              batch_size,
          )
      )
  
      time_step_spec = env.time_step_spec()
      action_spec = env.action_spec()
  
      random_policy = random_py_policy.RandomPyPolicy(
          time_step_spec=time_step_spec, action_spec=action_spec
      )
  
      for _ in range(5):
          time_step = env.reset()
          self.assertTrue(
              check_unbatched_time_step_spec(
                  time_step=time_step,
                  time_step_spec=time_step_spec,
                  batch_size=env.batch_size,
              )
          )
  
          action = random_policy.action(time_step).action
          self.assertAllEqual(action.shape, [batch_size, num_slots])
          self.assertAllGreaterEqual(action, 0)
          time_step = env.step(action)
          reward = time_step.reward
          self.assertAllEqual(reward.shape, [batch_size, num_slots])
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.environments import ranking_environment
  from tf_agents.policies import random_py_policy
  from tf_agents.specs import array_spec
label_desc: Use image node_id 1 for calling the ExplicitBiasEnvironmentTest obj's underlying member method code with example usage: obj.test_explicit_bias_environment(batch_size, global_dim, item_dim, num_items, num_slots) and returns: np, np, unknown