code: def test_load_large_scale_image_dataset(
      benchmark, setup_pytorch_tests
  ):
      # Test load 1M images.
      tmp_dir = setup_pytorch_tests.config.get_value(
          "storage", "tmp_dir"
      )
  
      # Check directory's mounted disk available space.
      statvfs = os.statvfs(tmp_dir)
      available_gb = statvfs.f_frsize * statvfs.f_bavail / (1024**3)
  
      img_dir = os.path.join(
          tmp_dir, "large_scale_image_dataset_1000000"
      )
  
      # Check if dataset already exists.
      if not os.path.exists(img_dir):
          # Only run this large-scale test when the system
          # has more than 5GB disk space.
          if available_gb < 10:
              return
          create_large_scale_image_dataset()
  
      def _execute_query_list(query_list):
          for query in query_list:
              execute_query_fetch_all(setup_pytorch_tests, query)
  
      drop_query = "DROP TABLE IF EXISTS benchmarkImageDataset;"
      load_query = (
          f"LOAD IMAGE '{img_dir}/*.jpg' INTO benchmarkImageDataset;"
      )
      benchmark(_execute_query_list, [drop_query, load_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 7 for calling a global function with example usage: test_load_large_scale_image_dataset(benchmark, setup_pytorch_tests) without return types