<jupyter_start><jupyter_text>How to use CycleGAN with notebook  Download a dataset, install in datasets folder<jupyter_code>dataset = 'summer2winter_yosemite'
!ls datasets
!sh ./download_dataset.sh $dataset # download a dataset
!ls datasets/<jupyter_output>camelyon16_2labels  camelyon16normal2tumor  horse2zebra  monet2photo<jupyter_text>Import config and change desired arguments * `--identity_loss_weight 5.0` would be `config.args.identity_loss_weight = 5`<jupyter_code>import config
config.args.dataset = dataset
config.args.load_size = 256
# ...use tab to see other options in config.args...<jupyter_output><empty_output><jupyter_text>Train a cyclegan<jupyter_code>import train as CycGAN
# loads in the previous model if it exists.
# set --new-run or config.args.new_run to True
# to initialize a new run in a new folder
CycGAN.train_CycleGAN()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08409090909090909, 'fraction_numerical': 0.017045454545454544, 'mean_word_length': 6.2809917355371905, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 12, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 3, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '654133', 'license': 'MIT', 'n_tokens_mistral': 309, 'n_tokens_neox': 291, 'n_words': 80, 'path': 'Example-Notebook.ipynb', 'repo_name': 'CharlesSS07/CycleGAN-Tensorflow-2', 'size': '880'}