



'''simple docstring'''




from typing import List

import numpy as np



def    __lowerCamelCase						(      _lowercase	)   ->    int:
							UpperCAmelCase  :	Optional[Any]							  =	{key: len(_lowercase	) for key, value in gen_kwargs.items() if isinstance(_lowercase			,       _lowercase	)}
							if len(set(lists_lengths.values()	)	) > 1:
														raise RuntimeError(
														    (
														        """Sharding is ambiguous for this dataset: """
														        + """we found several data sources lists of different lengths, and we don't know over which list we should parallelize:\n"""
														        + """\n""".join(F'''\t- key {key} has length {length}''' for key, length in lists_lengths.items()	)
														        + """\nTo fix this, check the 'gen_kwargs' and make sure to use lists only for data sources, """
														        + """and use tuples otherwise. In the end there should only be one single list, or several lists with the same length."""
														    )	)
							UpperCAmelCase  :	Dict							  =	max(lists_lengths.values()			,       default=0	)
							return max(1			,       _lowercase	)



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    List[range]:
							UpperCAmelCase  :	Dict							  =	[]
							for group_idx in range(_lowercase	):
														UpperCAmelCase  :	Tuple							  =	num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
														if num_shards_to_add == 0:
																					break
														UpperCAmelCase  :	int							  =	shards_indices_per_group[-1].stop if shards_indices_per_group else 0
														UpperCAmelCase  :	List[str]							  =	range(_lowercase			,       start + num_shards_to_add	)
														shards_indices_per_group.append(_lowercase	)
							return shards_indices_per_group



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    List[dict]:
							UpperCAmelCase  :	List[Any]							  =	_number_of_shards_in_gen_kwargs(_lowercase	)
							if num_shards == 1:
														return [dict(_lowercase	)]
							else:
														UpperCAmelCase  :	int							  =	_distribute_shards(num_shards=_lowercase			,       max_num_jobs=_lowercase	)
														return [
														    {
														        key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
														        if isinstance(_lowercase			,       _lowercase	)
														        else value
														        for key, value in gen_kwargs.items()
														    }
														    for group_idx in range(len(_lowercase	)	)
														]



def    __lowerCamelCase						(      _lowercase	)   ->    dict:
							return {
							    key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
							    if isinstance(gen_kwargs_list[0][key]			,       _lowercase	)
							    else gen_kwargs_list[0][key]
							    for key in gen_kwargs_list[0]
							}



def    __lowerCamelCase						(      _lowercase			,       _lowercase	)   ->    dict:
							UpperCAmelCase  :	str							  =	{len(_lowercase	) for value in gen_kwargs.values() if isinstance(_lowercase			,       _lowercase	)}
							UpperCAmelCase  :	int							  =	{}
							for size in list_sizes:
														UpperCAmelCase  :	int							  =	list(range(_lowercase	)	)
														rng.shuffle(indices_per_size[size]	)
							# Now let's copy the gen_kwargs and shuffle the lists based on their sizes
							UpperCAmelCase  :	List[Any]							  =	dict(_lowercase	)
							for key, value in shuffled_kwargs.items():
														if isinstance(_lowercase			,       _lowercase	):
																					UpperCAmelCase  :	Dict							  =	[value[i] for i in indices_per_size[len(_lowercase	)]]
							return shuffled_kwargs






'''simple docstring'''




from datetime import datetime as dt
import os

from github import Github


a     :    int      						=					[
    """good first issue""",
    """good second issue""",
    """good difficult issue""",
    """feature request""",
    """new model""",
    """wip""",
]



def    __lowerCamelCase						(      )   ->    Dict:
							UpperCAmelCase  :	str							  =	Github(os.environ["""GITHUB_TOKEN"""]	)
							UpperCAmelCase  :	Dict							  =	g.get_repo("""huggingface/transformers"""	)
							UpperCAmelCase  :	int							  =	repo.get_issues(state="""open"""	)

							for issue in open_issues:
														UpperCAmelCase  :	Optional[int]							  =	sorted([comment for comment in issue.get_comments()]			,       key=lambda _lowercase	: i.created_at			,       reverse=_lowercase	)
														UpperCAmelCase  :	Any							  =	comments[0] if len(_lowercase	) > 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 >= 3_0
														    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 > 2_3
														    and (dt.utcnow() - issue.created_at).days >= 3_0
														    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()

