docstr: Merge new mini batch into running batch.
docstr_tok: ["Merge","new","mini","batch","into","running","batch","."]
code: def _merge_batch(self, batch1, batch2):
      """
      Merge new mini batch into running batch.
      """
      batch1 = self.engine.cache.pop(batch1.batch_id)
      batch2 = self.engine.cache.pop(batch2.batch_id)
  
      m_batch = InferBatch.merge(batch1, batch2)
      self.engine.cache[batch1.batch_id] = m_batch
      del batch1
      del batch2
  
imports: import time
  from typing import List
  from .dynamic_batching.get_tokenizer import get_tokenizer
  from .dynamic_batching.infer_batch import InferBatch
  from .dynamic_batching.io_struct import Batch, Req
  from .dynamic_batching.req_queue import ReqQueue
  from .dynamic_batching.sampling_params import SamplingParams
  from .dynamic_batching.stats import Stats
  from .tensor_parallel import TPInferEngine
label_desc: Use image node_id 11 for calling the DynamicBatchManager obj's underlying member method code with example usage: obj._merge_batch(batch1, batch2) without return types