code: def test_should_run_benchmark_pytorch_and_facenet(
      benchmark, setup_pytorch_tests
  ):
      create_udf_query = """CREATE UDF IF NOT EXISTS FaceDetector
                  INPUT  (frame NDARRAY UINT8(3, ANYDIM, ANYDIM))
                  OUTPUT (bboxes NDARRAY FLOAT32(ANYDIM, 4),
                          scores NDARRAY FLOAT32(ANYDIM))
                  TYPE  FaceDetection
                  IMPL  'evadb/udfs/face_detector.py';
      """
      execute_query_fetch_all(setup_pytorch_tests, create_udf_query)
  
      select_query = """SELECT FaceDetector(data) FROM MyVideo
                      WHERE id < 5;"""
  
      actual_batch = benchmark(
          execute_query_fetch_all, setup_pytorch_tests, select_query
      )
      assert len(actual_batch) == 5
  
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 2 for calling a global function with example usage: test_should_run_benchmark_pytorch_and_facenet(benchmark, setup_pytorch_tests) without return types