




"""simple docstring"""




from datetime import datetime as dt
import os

from github import Github


UpperCamelCase__         =      [
    "good first issue",
    "good second issue",
    "good difficult issue",
    "feature request",
    "new model",
    "wip",
]







def      _a				(						):
					__lowerCAmelCase           =	Github(os.environ["GITHUB_TOKEN"]					)
					__lowerCAmelCase           =	g.get_repo("huggingface/transformers"					)
					__lowerCAmelCase           =	repo.get_issues(state="open"					)

					for issue in open_issues:
										__lowerCAmelCase           =	sorted([comment for comment in issue.get_comments()]				,				key=lambda SCREAMING_SNAKE_CASE_					: i.created_at				,				reverse=_UpperCAmelCase					)
										__lowerCAmelCase           =	comments[0] if len(_UpperCAmelCase					) > 0 else None
										if (
										    last_comment is not None
										    and last_comment.user.login == "github-actions[bot]"
										    and (dt.utcnow() - issue.updated_at).days > 7
										    and (dt.utcnow() - issue.created_at).days >= 30
										    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()					)
										):
															# print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
															issue.edit(state="closed"					)
										elif (
										    (dt.utcnow() - issue.updated_at).days > 23
										    and (dt.utcnow() - issue.created_at).days >= 30
										    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()					)
										):
															# print(f"Would add stale comment to {issue.number}")
															issue.create_comment(
															    "This issue has been automatically marked as stale because it has not had "
															    "recent activity. If you think this still needs to be addressed "
															    "please comment on this thread.\n\nPlease note that issues that do not follow the "
															    "[contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) "
															    "are likely to be ignored."					)


if __name__ == "__main__":
					main()










from pathlib import Path

import fire
from tqdm import tqdm







def      _a				(						SCREAMING_SNAKE_CASE_							:    Dict="ro"				,				SCREAMING_SNAKE_CASE_							:    Union[str, Any]="en"				,				SCREAMING_SNAKE_CASE_							:    Optional[Any]="wmt16"				,				SCREAMING_SNAKE_CASE_							:    List[str]=None					):
					try:
										import datasets
					except (ModuleNotFoundError, ImportError):
										raise ImportError("run pip install datasets"					)
					__lowerCAmelCase           =	F"""{src_lang}-{tgt_lang}"""
					print(F"""Converting {dataset}-{pair}"""					)
					__lowerCAmelCase           =	datasets.load_dataset(SCREAMING_SNAKE_CASE_				,				SCREAMING_SNAKE_CASE_					)
					if save_dir is None:
										__lowerCAmelCase           =	F"""{dataset}-{pair}"""
					__lowerCAmelCase           =	Path(SCREAMING_SNAKE_CASE_					)
					save_dir.mkdir(exist_ok=SCREAMING_SNAKE_CASE_					)

					for split in ds.keys():
										print(F"""Splitting {split} with {ds[split].num_rows} records"""					)

										# to save to val.source, val.target like summary datasets
										__lowerCAmelCase           =	"val" if split == "validation" else split
										__lowerCAmelCase           =	save_dir.joinpath(F"""{fn}.source"""					)
										__lowerCAmelCase           =	save_dir.joinpath(F"""{fn}.target"""					)
										__lowerCAmelCase           =	src_path.open("w+"					)
										__lowerCAmelCase           =	tgt_path.open("w+"					)

										# reader is the bottleneck so writing one record at a time doesn't slow things down
										for x in tqdm(ds[split]					):
															__lowerCAmelCase           =	x["translation"]
															src_fp.write(ex[src_lang] + "\n"					)
															tgt_fp.write(ex[tgt_lang] + "\n"					)

					print(F"""Saved {dataset} dataset to {save_dir}"""					)


if __name__ == "__main__":
					fire.Fire(download_wmt_dataset)




