<jupyter_start><jupyter_text>Almost like holdout.py in the script folder.<jupyter_code>import data
import network
tabulation = data.tabulation(path="./celebfaces-attribute-sample/csv/index.csv")
tabulation.read()
tabulation.data
tabulation.data['link'] = ["./celebfaces-attribute-sample/jpg/" + i for i in tabulation.data['image']]
tabulation.data
tabulation.distinct(what='data')
tabulation.train  ##  tabulation.exam, tabulation.test<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.13978494623655913, 'fraction_numerical': 0.0, 'mean_word_length': 7.175438596491228, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '113059', 'license': 'Apache-2.0', 'n_tokens_mistral': 160, 'n_tokens_neox': 156, 'n_words': 26, 'path': 'demo.ipynb', 'repo_name': 'houzeyu2683/VariationalAutoEncoder', 'size': '465'}