code: def _add_sample_batch_to_buffer(
      self, buffer, batch_size, num_batches=5, **kwargs
  ):
      self.eps_id = 0
  
      def _generate_data():
          self.eps_id += 1
          return SampleBatch(
              {
                  SampleBatch.T: [0, 1],
                  SampleBatch.ACTIONS: 2 * [np.random.choice([0, 1])],
                  SampleBatch.REWARDS: 2 * [np.random.rand()],
                  SampleBatch.OBS: 2 * [np.random.random((4,))],
                  SampleBatch.NEXT_OBS: 2 * [np.random.random((4,))],
                  SampleBatch.TERMINATEDS: 2
                  * [np.random.choice([False, True])],
                  SampleBatch.TRUNCATEDS: 2
                  * [np.random.choice([False, True])],
                  SampleBatch.EPS_ID: 2 * [self.eps_id],
                  SampleBatch.AGENT_INDEX: 2 * [0],
                  "batch_id": 2 * [self.batch_id],
              }
          )
  
      for i in range(num_batches):
          data = [_generate_data() for _ in range(batch_size)]
          self.batch_id += 1
          batch = concat_samples(data)
          buffer.add(batch, **kwargs)
  
file_path: 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 1 for calling the TestMultiAgentReplayBuffer obj's underlying member method code with example usage: obj._add_sample_batch_to_buffer(buffer, batch_size, num_batches) and returns: SampleBatch