docstr: Test the lockstep mode by adding batches from multiple policies.
docstr_tok: ["Test","the","lockstep","mode","by","adding","batches","from","multiple","policies","."]
code: def test_independent_mode_multiple_policies(self):
      """Test the lockstep mode by adding batches from multiple policies."""
  
      num_batches = 3
      buffer_size = 15
      num_policies = 2
      # Test lockstep mode with different policy ids using MultiAgentBatches
  
      self.batch_id = 0
  
      buffer = MultiAgentReplayBuffer(
          capacity=buffer_size,
          replay_mode="independent",
          num_steps_sampled_before_learning_starts=0,
          num_shards=1,
      )
  
      self._add_multi_agent_batch_to_buffer(
          buffer, num_policies=num_policies, num_batches=num_batches
      )
  
      # Sample 4 SampleBatches from only one policy
      for _id in range(num_policies):
          for __id in buffer.sample(4, policy_id=_id).policy_batches[
              _id
          ]["policy_id"]:
              assert __id == _id
  
      # Sample without specifying the policy should yield the same number
      # of batches from each policy
      num_sampled_dict = {_id: 0 for _id in range(num_policies)}
      num_samples = 200
      for i in range(num_samples):
          num_items = np.random.randint(0, 5)
          for _id, batch in buffer.sample(
              num_items=num_items
          ).policy_batches.items():
              num_sampled_dict[_id] += 1
              assert len(batch) == num_items
      assert np.allclose(
          np.array(list(num_sampled_dict.values())),
          len(num_sampled_dict) * [200],
          atol=0.1,
      )
  
file_path: ray/python/ray/rllib/utils/replay_buffers/tests/test_multi_agent_replay_buffer.py
imports: import unittest
  import numpy
  from ray.rllib.policy.sample_batch import SampleBatch, MultiAgentBatch, concat_samples
  from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID
  from ray.rllib.utils.replay_buffers.multi_agent_replay_buffer import MultiAgentReplayBuffer
  from ray.rllib.utils.replay_buffers.prioritized_replay_buffer import PrioritizedReplayBuffer
  from ray.rllib.utils.replay_buffers.replay_buffer import ReplayBuffer
label_desc: Use image node_id 6 for calling the TestMultiAgentReplayBuffer obj's underlying member method code with example usage: obj.test_independent_mode_multiple_policies() without return types