code: def test_automatic_speech_recognition(benchmark, setup_pytorch_tests):
      udf_name = "SpeechRecognizer"
      create_udf = (
          f"CREATE UDF {udf_name} TYPE HuggingFace "
          "TASK 'automatic-speech-recognition' MODEL 'openai/whisper-base';"
      )
      execute_query_fetch_all(setup_pytorch_tests, create_udf)
  
      # TODO: use with SAMPLE AUDIORATE 16000
      select_query = f"SELECT {udf_name}(audio) FROM VIDEOS;"
      output = benchmark(
          execute_query_fetch_all, setup_pytorch_tests, select_query
      )
  
      # verify that output has one row and one column only
      assert output.frames.shape == (1, 1)
      # verify that speech was converted to text correctly
      assert output.frames.iloc[0][0].count("touchdown") == 2
  
      drop_udf_query = f"DROP UDF {udf_name};"
      execute_query_fetch_all(setup_pytorch_tests, drop_udf_query)
  
file_path: evadb/test/benchmark_tests/test_benchmark_pytorch.py
imports: import os
  from test.util import create_large_scale_image_dataset
  import pytest
  from evadb.server.command_handler import execute_query_fetch_all
label_desc: Use image node_id 5 for calling a global function with example usage: test_automatic_speech_recognition(benchmark, setup_pytorch_tests) without return types