[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:"""\nDON\'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE\n"""\nfrom urllib.request import urlretrieve\nfrom os.path import isfile, isdir\nfrom tqdm import tqdm\nimport problem_unittests as tests\nimport tarfile\ncifar10_dataset_folder_path = \'cifar-10-batches-py\'\nclass DLProgress(tqdm):\nlast_block = 0\ndef hook(self, block_num=1, block_size=1, total_size=None):\nself.total = total_size\nself.update((block_num - self.last_block) * block_size)\nself.last_block = block_num\nif not isfile(\'cifar-10-python.tar.gz\'):\nwith DLProgress(unit=\'B\', unit_scale=True, miniters=1, desc=\'CIFAR-10 Dataset\') as pbar:\nurlretrieve(\n\'https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz\',\n\'cifar-10-python.tar.gz\',\npbar.hook)\nif not isdir(cifar10_dataset_folder_path):\nwith tarfile.open(\'cifar-10-python.tar.gz\') as tar:\ntar.extractall()\ntar.close()\ntests.test_folder_path(cifar10_dataset_folder_path)'}, {'role': 'assistant', 'content': "['helper_functions', 'load_data']"}]