code: def test_multi_agent(self):
      max_seq_len = 5
      max_ep_len = 20
      capacity = 10
      obs_dim = 3
      act_dim = 5
  
      ma_buffer = MultiAgentSegmentationBuffer(
          capacity, max_seq_len, max_ep_len
      )
  
      policy_id1 = "1"
      policy_id2 = "2"
      policy_id3 = "3"
      policy_ids = {policy_id1, policy_id2, policy_id3}
  
      policy1_batches = []
      for i in range(0, 10):
          policy1_batches.append(
              _generate_episode_batch(max_ep_len, i, obs_dim, act_dim)
          )
      policy2_batches = []
      for i in range(10, 20):
          policy2_batches.append(
              _generate_episode_batch(max_ep_len, i, obs_dim, act_dim)
          )
      policy3_batches = []
      for i in range(20, 30):
          policy3_batches.append(
              _generate_episode_batch(max_ep_len, i, obs_dim, act_dim)
          )
  
      batches_mapping = {
          policy_id1: policy1_batches,
          policy_id2: policy2_batches,
          policy_id3: policy3_batches,
      }
  
      ma_batch = MultiAgentBatch(
          {
              policy_id1: concat_samples(policy1_batches),
              policy_id2: concat_samples(policy2_batches),
              policy_id3: concat_samples(policy3_batches),
          },
          max_ep_len * 10,
      )
  
      ma_buffer.add(ma_batch)
  
      # check all are added properly
      for policy_id in policy_ids:
          assert policy_id in ma_buffer.buffers.keys()
  
      for policy_id, buffer in ma_buffer.buffers.items():
          assert policy_id in policy_ids
          for i in range(10):
              test_utils.check(
                  batches_mapping[policy_id][i],
                  _get_internal_buffer(buffer)[i],
              )
  
      # check that sampling are proper
      for _ in range(50):
          ma_sample = ma_buffer.sample(100)
          for policy_id in policy_ids:
              assert policy_id in ma_sample.policy_batches.keys()
  
          for policy_id, batch in ma_sample.policy_batches.items():
              eps_id_start = (int(policy_id) - 1) * 10
              eps_id_end = eps_id_start + 10
  
              _assert_sample_batch_keys(batch)
  
              for i in range(100):
                  # Obs generated by _generate_episode_batch contains eps_id.
                  # Use -1 index because there might be front padding
                  eps_id = int(batch[SampleBatch.OBS][i, -1, 0])
                  assert (
                      eps_id_start <= eps_id < eps_id_end
                  ), "batch within multi agent batch has the wrong agent's episode."
  
      # sample twice and make sure they are not equal (probability equal almost zero)
      ma_sample1 = ma_buffer.sample(200)
      ma_sample2 = ma_buffer.sample(200)
      for policy_id in policy_ids:
          _assert_sample_batch_not_equal(
              ma_sample1.policy_batches[policy_id],
              ma_sample2.policy_batches[policy_id],
          )
  
imports: import unittest
  from typing import List, Union
  import numpy
  from rllib_dt.dt.segmentation_buffer import MultiAgentSegmentationBuffer, SegmentationBuffer
  import ray
  from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID, MultiAgentBatch, SampleBatch, concat_samples
  from ray.rllib.utils import test_utils
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
  from ray.rllib.utils.typing import PolicyID
label_desc: Use image node_id 8 for calling the TestSegmentationBuffer obj's underlying member method code with example usage: obj.test_multi_agent() without return types