code: def test_recognize_image_format(
      numpy_image, torch_image, files_image
  ):
      # correct image formats
      assert recognize_image_format(numpy_image) == "numpy"
      assert recognize_image_format(files_image) == "files"
  
      # incorrect image formats
      with pytest.raises(ValueError):
          recognize_image_format(None)
      with pytest.raises(ValueError):
          recognize_image_format([1, 2, 3])
      with pytest.raises(FileNotFoundError):
          recognize_image_format("non/existent/file/123")
  
file_path: traintool/tests/image_classification/test_preprocessing.py
imports: import comet_ml
  import pytest
  import numpy
  import torch
  from conftest import create_dataset, create_image
  from traintool.image_classification.preprocessing import recognize_data_format, torch_to_numpy, numpy_to_torch, files_to_numpy, files_to_torch, load_image, recognize_image_format, get_num_classes
label_desc: Use image node_id 8 for calling a global function with example usage: test_recognize_image_format(numpy_image, torch_image, files_image) without return types