code: def deploy_replicas(num_replicas, max_batch_size) -> List[str]:
      name = "echo"
  
      @serve.deployment(name=name, num_replicas=num_replicas)
      class Echo:
          @serve.batch(max_batch_size=max_batch_size)
          async def handle_batch(self, requests):
              return ["hi" for _ in range(len(requests))]
  
          async def __call__(self, request):
              return await self.handle_batch(request)
  
      serve.run(Echo.bind(), route_prefix=f"/{name}")
      return [name]
  
file_path: ray/release/serve_tests/workloads/single_deployment_1k_noop_replica.py
imports: import click
  import json
  import logging
  import math
  import os
  from ray import serve
  from serve_test_utils import aggregate_all_metrics, run_wrk_on_all_nodes, save_test_results, is_smoke_test
  from serve_test_cluster_utils import setup_local_single_node_cluster, setup_anyscale_cluster, NUM_CPU_PER_NODE, NUM_CONNECTIONS
  from typing import List, Optional
label_desc: Use image node_id 1 for calling a global function with example usage: deploy_replicas(num_replicas, max_batch_size) and returns: list, unknown, unknown