code: def test_huggingface_bert_batch_inference():
      batch_size = 2
      batch_delay = 10000  # 10 seconds
      params = (
          ("model_name", "BERTSeqClassification"),
          (
              "url",
              "https://torchserve.pytorch.org/mar_files/BERTSeqClassification.mar",
          ),
          ("initial_workers", "1"),
          ("batch_size", str(batch_size)),
          ("max_batch_delay", str(batch_delay)),
      )
      test_utils.start_torchserve(no_config_snapshots=True)
      test_utils.register_model_with_params(params)
      input_text = os.path.join(
          REPO_ROOT,
          "examples",
          "Huggingface_Transformers",
          "Seq_classification_artifacts",
          "sample_text.txt",
      )
  
      # Make 2 curl requests in parallel with &
      # curl --header \"X-Forwarded-For: 1.2.3.4\" won't work since you can't access local host anymore
      response = os.popen(
          f"curl http://127.0.0.1:8080/predictions/BERTSeqClassification -T {input_text} & curl http://127.0.0.1:8080/predictions/BERTSeqClassification -T {input_text}"
      )
      response = response.read()
  
      ## Assert that 2 responses are returned from the same batch
      assert response == "Not AcceptedNot Accepted"
      test_utils.unregister_model("BERTSeqClassification")
  
imports: import ast
  import json
  import logging
  import os
  import numpy
  import pytest
  import requests
  import test_utils
  import torch
label_desc: Use image node_id 16 for calling a global function with example usage: test_huggingface_bert_batch_inference() without return types