code: def test_recognize_data_format(numpy_data, torch_data, files_data):
      # correct data formats
      assert recognize_data_format(numpy_data) == "numpy"
      assert recognize_data_format(torch_data) == "pytorch-dataset"
      assert recognize_data_format(files_data) == "files"
  
      # incorrect data formats
      with pytest.raises(ValueError):
          recognize_data_format(None)
      with pytest.raises(ValueError):
          recognize_data_format([1, 2, 3])
      with pytest.raises(FileNotFoundError):
          recognize_data_format("non/existent/dir/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 7 for calling a global function with example usage: test_recognize_data_format(numpy_data, torch_data, files_data) without return types