<jupyter_start><jupyter_text>DeepFashion Training Script<jupyter_code>import detectron2.utils.comm as comm
from detectron2.config import get_cfg
from detectron2.engine import default_argument_parser, default_setup, hooks, launch
from detectron2.evaluation import verify_results
from detectron2.utils.file_io import PathManager
from detectron2.utils.logger import setup_logger
def setup(args):
    cfg = get_cfg()
    add_densepose_config(cfg)
    cfg.merge_from_file(args.config_file)
    cfg.merge_from_list(args.opts)
    cfg.freeze()
    default_setup(cfg, args)
    # Setup logger for "densepose" module
    setup_logger(output=cfg.OUTPUT_DIR, distributed_rank=comm.get_rank(), name="densepose")
    return cfg<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08064516129032258, 'fraction_numerical': 0.008064516129032258, 'mean_word_length': 6.233009708737864, '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': '236980', 'license': 'MIT', 'n_tokens_mistral': 241, 'n_tokens_neox': 237, 'n_words': 49, 'path': 'fashion_segmentation/scripts/train_net.ipynb', 'repo_name': 'TayaPenskaya/Diploma', 'size': '744'}