






"""simple docstring"""





import argparse
import collections
import os
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
UpperCamelCase_	:				List[Any]										= 'src/transformers'
UpperCamelCase_	:				Tuple										= 'docs/source/en'
UpperCamelCase_	:				Optional[int]										= '.'



def     __lowercase					(    a :				Tuple       ,		a :				Tuple       ,		a :				Optional[Any] )					->					Optional[Any]:
						with open(_A       ,		'''r'''       ,		encoding='''utf-8'''       ,		newline='''\n''' ) as f:
												__snake_case      :    str  			=f.readlines()
						# Find the start prompt.
						__snake_case      :    Union[str, Any]  			=0
						while not lines[start_index].startswith(_A ):
												start_index += 1
						start_index += 1

						__snake_case      :    str  			=start_index
						while not lines[end_index].startswith(_A ):
												end_index += 1
						end_index -= 1

						while len(lines[start_index] ) <= 1:
												start_index += 1
						while len(lines[end_index] ) <= 1:
												end_index -= 1
						end_index += 1
						return "".join(lines[start_index:end_index] ), start_index, end_index, lines


# Add here suffixes that are used to identify models, separated by |
UpperCamelCase_	:				Dict										= 'Model|Encoder|Decoder|ForConditionalGeneration'
# Regexes that match TF/Flax/PT model names.
UpperCamelCase_	:				Optional[int]										= re.compile(r"""TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
UpperCamelCase_	:				Optional[int]										= re.compile(r"""Flax(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")
# Will match any TF or Flax model too so need to be in an else branch afterthe two previous regexes.
UpperCamelCase_	:				str										= re.compile(r"""(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)""")


# This is to make sure the transformers module imported is the one in the repo.
UpperCamelCase_	:				List[Any]										= direct_transformers_import(TRANSFORMERS_PATH)



def     __lowercase					(    a :				List[Any] )					->					str:
						__snake_case      :    int  			=re.finditer('''.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)'''       ,		_A )
						return [m.group(0 ) for m in matches]



def     __lowercase					(    a :				Union[str, Any]       ,		a :				List[str] )					->					Optional[int]:
						__snake_case      :    List[Any]  			=2 if text == '''✅''' or text == '''❌''' else len(_A )
						__snake_case      :    Dict  			=(width - text_length) // 2
						__snake_case      :    List[str]  			=width - text_length - left_indent
						return " " * left_indent + text + " " * right_indent



def     __lowercase					(    )					->					Any:
						__snake_case      :    Optional[Any]  			=transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
						__snake_case      :    Optional[int]  			={
						    name: config_maping_names[code]
						    for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
						    if code in config_maping_names
						}
						__snake_case      :    Union[str, Any]  			={name: config.replace('''Config'''       ,		'''''' ) for name, config in model_name_to_config.items()}

						# Dictionaries flagging if each model prefix has a slow/fast tokenizer, backend in PT/TF/Flax.
						__snake_case      :    List[Any]  			=collections.defaultdict(_A )
						__snake_case      :    Dict  			=collections.defaultdict(_A )
						__snake_case      :    Optional[Any]  			=collections.defaultdict(_A )
						__snake_case      :    List[str]  			=collections.defaultdict(_A )
						__snake_case      :    str  			=collections.defaultdict(_A )

						# Let's lookup through all transformers object (once).
						for attr_name in dir(_A ):
												__snake_case      :    str  			=None
												if attr_name.endswith('''Tokenizer''' ):
																		__snake_case      :    str  			=slow_tokenizers
																		__snake_case      :    Optional[int]  			=attr_name[:-9]
												elif attr_name.endswith('''TokenizerFast''' ):
																		__snake_case      :    List[Any]  			=fast_tokenizers
																		__snake_case      :    Tuple  			=attr_name[:-13]
												elif _re_tf_models.match(_A ) is not None:
																		__snake_case      :    Optional[Any]  			=tf_models
																		__snake_case      :    List[Any]  			=_re_tf_models.match(_A ).groups()[0]
												elif _re_flax_models.match(_A ) is not None:
																		__snake_case      :    str  			=flax_models
																		__snake_case      :    Optional[Any]  			=_re_flax_models.match(_A ).groups()[0]
												elif _re_pt_models.match(_A ) is not None:
																		__snake_case      :    Any  			=pt_models
																		__snake_case      :    Optional[Any]  			=_re_pt_models.match(_A ).groups()[0]

												if lookup_dict is not None:
																		while len(_A ) > 0:
																								if attr_name in model_name_to_prefix.values():
																														__snake_case      :    List[str]  			=True
																														break
																								# Try again after removing the last word in the name
																								__snake_case      :    str  			=''''''.join(camel_case_split(_A )[:-1] )

    # Let's build that table!
						__snake_case      :    Union[str, Any]  			=list(model_name_to_config.keys() )
						model_names.sort(key=str.lower )
						__snake_case      :    int  			=['''Model''', '''Tokenizer slow''', '''Tokenizer fast''', '''PyTorch support''', '''TensorFlow support''', '''Flax Support''']
						# We'll need widths to properly display everything in the center (+2 is to leave one extra space on each side).
						__snake_case      :    Optional[Any]  			=[len(_A ) + 2 for c in columns]
						__snake_case      :    Optional[int]  			=max([len(_A ) for name in model_names] ) + 2

						# Build the table per se
						__snake_case      :    Tuple  			='''|''' + '''|'''.join([_center_text(_A       ,		_A ) for c, w in zip(_A       ,		_A )] ) + '''|\n'''
						# Use ":-----:" format to center-aligned table cell texts
						table += "|" + "|".join([''':''' + '''-''' * (w - 2) + ''':''' for w in widths] ) + "|\n"

						__snake_case      :    List[Any]  			={True: '''✅''', False: '''❌'''}
						for name in model_names:
												__snake_case      :    Union[str, Any]  			=model_name_to_prefix[name]
												__snake_case      :    List[Any]  			=[
												    name,
												    check[slow_tokenizers[prefix]],
												    check[fast_tokenizers[prefix]],
												    check[pt_models[prefix]],
												    check[tf_models[prefix]],
												    check[flax_models[prefix]],
												]
												table += "|" + "|".join([_center_text(_A       ,		_A ) for l, w in zip(_A       ,		_A )] ) + "|\n"
						return table



def     __lowercase					(    a :				str=False )					->					Optional[Any]:
						__snake_case			,				__snake_case			,				__snake_case			,				__snake_case      :    Optional[int]  			=_find_text_in_file(
						    filename=os.path.join(_A       ,		'''index.md''' )       ,		start_prompt='''<!--This table is updated automatically from the auto modules'''       ,		end_prompt='''<!-- End table-->'''       ,		)
						__snake_case      :    str  			=get_model_table_from_auto_modules()

						if current_table != new_table:
												if overwrite:
																		with open(os.path.join(_A       ,		'''index.md''' )       ,		'''w'''       ,		encoding='''utf-8'''       ,		newline='''\n''' ) as f:
																								f.writelines(lines[:start_index] + [new_table] + lines[end_index:] )
												else:
																		raise ValueError(
																		    '''The model table in the `index.md` has not been updated. Run `make fix-copies` to fix this.''' )


if __name__ == "__main__":
				UpperCamelCase_	:				int										= argparse.ArgumentParser()
				parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
				UpperCamelCase_	:				Any										= parser.parse_args()

				check_model_table(args.fix_and_overwrite)










"""simple docstring"""





import os
from datetime import datetime as dt

from github import Github


UpperCamelCase_	:				List[str]										= [
    """good first issue""",
    """good second issue""",
    """good difficult issue""",
    """enhancement""",
    """new pipeline/model""",
    """new scheduler""",
    """wip""",
]



def     __lowercase					(    )					->					Optional[Any]:
      __snake_case      :    List[Any]  			=Github(os.environ['''GITHUB_TOKEN'''] )
      __snake_case      :    int  			=g.get_repo('''huggingface/diffusers''' )
      __snake_case      :    Any  			=repo.get_issues(state='''open''' )

      for issue in open_issues:
            __snake_case      :    Dict  			=sorted(issue.get_comments()       ,		key=lambda a : i.created_at       ,		reverse=a )
            __snake_case      :    Dict  			=comments[0] if len(a ) > 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() )
            ):
                  # Closes the issue after 7 days of inactivity since the Stalebot notification.
                  issue.edit(state='''closed''' )
            elif (
                "stale" in issue.get_labels()
                and last_comment is not None
                and last_comment.user.login != "github-actions[bot]"
            ):
                  # Opens the issue if someone other than Stalebot commented.
                  issue.edit(state='''open''' )
                  issue.remove_from_labels('''stale''' )
            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() )
            ):
                  # Post a Stalebot notification after 23 days of inactivity.
                  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/diffusers/blob/main/CONTRIBUTING.md) '''
                      '''are likely to be ignored.''' )
                  issue.add_to_labels('''stale''' )


if __name__ == "__main__":
    main()


