code: def testGeneratesBatchedActionsImplicitBatchSize(self, dtype):
      action_spec = [
          tensor_spec.BoundedTensorSpec((2, 3), dtype, -10, 10),
          tensor_spec.BoundedTensorSpec((1, 2), dtype, -10, 10),
      ]
      time_step_spec, time_step = self.create_time_step()
      time_step = self.create_batch(time_step, 2)
      policy = random_tf_policy.RandomTFPolicy(
          time_step_spec=time_step_spec, action_spec=action_spec
      )
  
      action_step = policy.action(time_step)
      tf.nest.assert_same_structure(action_spec, action_step.action)
  
      action_ = self.evaluate(action_step.action)
      self.assertTrue(np.all(action_[0] >= -10))
      self.assertTrue(np.all(action_[0] <= 10))
      self.assertTrue(np.all(action_[1] >= -10))
      self.assertTrue(np.all(action_[1] <= 10))
  
      self.assertEqual((2, 2, 3), action_[0].shape)
      self.assertEqual((2, 1, 2), action_[1].shape)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.specs import utils
  from tf_agents.policies import random_tf_policy
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import nest_utils
  from tf_agents.utils import test_utils
label_desc: Use image node_id 5 for calling the RandomTFPolicyTest obj's underlying member method code with example usage: obj.testGeneratesBatchedActionsImplicitBatchSize(dtype) without return types