code: def parse_args():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--model_name",
          type=str,
          default="meta-llama/Llama-2-7b-hf",
          help="Name of the model in the model_files to benchmark",
      )
      parser.add_argument(
          "-d",
          "--deployment_name",
          type=str,
          default="benchmark_deployment",
      )
      parser.add_argument(
          "-t",
          "--task",
          type=str,
          help="Task type. Currently only text-generation is supported",
          default="text-generation",
      )
      parser.add_argument(
          "-m",
          "--tensor_parallel",
          type=int,
          help="Degree of tensor (model) parallelism",
          default=1,
      )
      parser.add_argument(
          "-b",
          "--ragged_batch_size",
          type=int,
          help="Max batch size for ragged batching",
          default=768,
      )
      parser.add_argument(
          "-r",
          "--replica_num",
          type=int,
          help="Number of replicas for load balancing",
          default=1,
      )
      parser.add_argument("cmd", help="start, stop, or restart")
      return parser.parse_args()
  
file_path: deepspeedexamples/benchmarks/inference/mii/server.py
imports: import mii
  import argparse
  from mii.constants import DeploymentType
  from deepspeed.inference import RaggedInferenceEngineConfig, DeepSpeedTPConfig
  from deepspeed.inference.v2.ragged import DSStateManagerConfig
label_desc: Use image node_id 3 for calling a global function with example usage: parse_args() and returns: parser