code: def test_catch(self, policy_type: Text):
      env = catch.Catch(rows=2, seed=1)
      num_actions = env.action_spec().num_values
      model = simulator.Simulator(env)
      eval_fn = lambda _: (np.ones(num_actions) / num_actions, 0.0)
  
      timestep = env.reset()
      model.reset()
  
      search_policy = (
          search.bfs if policy_type == "bfs" else search.puct
      )
  
      root = search.mcts(
          observation=timestep.observation,
          model=model,
          search_policy=search_policy,
          evaluation=eval_fn,
          num_simulations=100,
          num_actions=num_actions,
      )
  
      values = np.array([c.value for c in root.children.values()])
      best_action = search.argmax(values)
  
      if env._paddle_x > env._ball_x:
          self.assertEqual(best_action, 0)
      if env._paddle_x == env._ball_x:
          self.assertEqual(best_action, 1)
      if env._paddle_x < env._ball_x:
          self.assertEqual(best_action, 2)
  
file_path: acme/acme/agents/tf/mcts/search_test.py
imports: from typing import Text
  from acme.agents.tf.mcts import search
  from acme.agents.tf.mcts.models import simulator
  from bsuite.environments import catch
  import numpy
  from absl.testing import absltest
  from absl.testing import parameterized
label_desc: Use image node_id 1 for calling the TestSearch obj's underlying member method code with example usage: obj.test_catch(policy_type) without return types