


"""simple docstring"""






import argparse
import os
import re


_lowerCamelCase     =  'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
_lowerCamelCase     =  re.compile(R'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
_lowerCamelCase     =  re.compile(R'\s*\(\s*"(\S[^"]+)"')


def __lowercase     (      lowerCamelCase_  :      List[Any]						,					lowerCamelCase_  :      bool = False  ):
				with open(lowerCamelCase_						,					"r"						,					encoding="utf-8"  ) as f:
								SCREAMING_SNAKE_CASE__     							=				f.read()

				SCREAMING_SNAKE_CASE__     							=				content.split("\n"  )
				SCREAMING_SNAKE_CASE__     							=				[]
				SCREAMING_SNAKE_CASE__     							=				0
				while line_idx < len(lowerCamelCase_  ):
								if _re_intro_mapping.search(lines[line_idx]  ) is not None:
												SCREAMING_SNAKE_CASE__     							=				len(re.search(R"^(\s*)\S"						,					lines[line_idx]  ).groups()[0]  ) + 8
												# Start of a new mapping!
												while not lines[line_idx].startswith(" " * indent + "("  ):
																new_lines.append(lines[line_idx]  )
																line_idx += 1

												SCREAMING_SNAKE_CASE__     							=				[]
												while lines[line_idx].strip() != "]":
																# Blocks either fit in one line or not
																if lines[line_idx].strip() == "(":
																				SCREAMING_SNAKE_CASE__     							=				line_idx
																				while not lines[line_idx].startswith(" " * indent + ")"  ):
																								line_idx += 1
																				blocks.append("\n".join(lines[start_idx : line_idx + 1]  )  )
																else:
																				blocks.append(lines[line_idx]  )
																line_idx += 1

												# Sort blocks by their identifiers
												SCREAMING_SNAKE_CASE__     							=				sorted(lowerCamelCase_						,					key=lambda lowerCamelCase_  : _re_identifier.search(lowerCamelCase_  ).groups()[0]  )
												new_lines += blocks
								else:
												new_lines.append(lines[line_idx]  )
												line_idx += 1

				if overwrite:
								with open(lowerCamelCase_						,					"w"						,					encoding="utf-8"  ) as f:
												f.write("\n".join(lowerCamelCase_  )  )
				elif "\n".join(lowerCamelCase_  ) != content:
								return True


def __lowercase     (      lowerCamelCase_  :      bool = False  ):
				SCREAMING_SNAKE_CASE__     							=				[os.path.join(lowerCamelCase_						,					lowerCamelCase_  ) for f in os.listdir(lowerCamelCase_  ) if f.endswith(".py"  )]
				SCREAMING_SNAKE_CASE__     							=				[sort_auto_mapping(lowerCamelCase_						,					overwrite=lowerCamelCase_  ) for fname in fnames]

				if not overwrite and any(lowerCamelCase_  ):
								SCREAMING_SNAKE_CASE__     							=				[f for f, d in zip(lowerCamelCase_						,					lowerCamelCase_  ) if d]
								raise ValueError(
								    F'''The following files have auto mappings that need sorting: {", ".join(lowerCamelCase_  )}. Run `make style` to fix'''
								    " this."  )


if __name__ == "__main__":
	_lowerCamelCase     =  argparse.ArgumentParser()
	parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
	_lowerCamelCase     =  parser.parse_args()

	sort_all_auto_mappings(not args.check_only)




"""simple docstring"""






import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing


class 			lowerCamelCase_		(			lowercase   ):





				"""simple docstring"""







				def __init__(						self       ,		UpperCAmelCase__ = "▁"       ,		UpperCAmelCase__ = True       ,		UpperCAmelCase__ = "<unk>"       ,		UpperCAmelCase__ = "</s>"       ,		UpperCAmelCase__ = "<pad>"       ,		):
								SCREAMING_SNAKE_CASE__     							=				{
								    "pad": {"id": 0, "token": pad_token},
								    "eos": {"id": 1, "token": eos_token},
								    "unk": {"id": 2, "token": unk_token},
								}

								SCREAMING_SNAKE_CASE__     							=				[None] * len(self.special_tokens     )
								for token_dict in self.special_tokens.values():
												SCREAMING_SNAKE_CASE__     							=				token_dict["token"]

								SCREAMING_SNAKE_CASE__     							=				Tokenizer(Unigram()     )

								SCREAMING_SNAKE_CASE__     							=				normalizers.Sequence(
								    [
								        normalizers.Nmt(),
								        normalizers.NFKC(),
								        normalizers.Replace(Regex(" {2,}"     )       ,		" "     ),
								        normalizers.Lowercase(),
								    ]     )
								SCREAMING_SNAKE_CASE__     							=				pre_tokenizers.Sequence(
								    [
								        pre_tokenizers.Metaspace(replacement=UpperCAmelCase__       ,		add_prefix_space=UpperCAmelCase__     ),
								        pre_tokenizers.Digits(individual_digits=UpperCAmelCase__     ),
								        pre_tokenizers.Punctuation(),
								    ]     )
								SCREAMING_SNAKE_CASE__     							=				decoders.Metaspace(replacement=UpperCAmelCase__       ,		add_prefix_space=UpperCAmelCase__     )

								SCREAMING_SNAKE_CASE__     							=				TemplateProcessing(
								    single=f'''$A {self.special_tokens["eos"]["token"]}'''       ,		special_tokens=[(self.special_tokens["eos"]["token"], self.special_tokens["eos"]["id"])]       ,		)

								SCREAMING_SNAKE_CASE__     							=				{
								    "model": "SentencePieceUnigram",
								    "replacement": replacement,
								    "add_prefix_space": add_prefix_space,
								}

								super().__init__(UpperCAmelCase__       ,		UpperCAmelCase__     )



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = 8000       ,		UpperCAmelCase__ = True       ,		):
								SCREAMING_SNAKE_CASE__     							=				trainers.UnigramTrainer(
								    vocab_size=UpperCAmelCase__       ,		special_tokens=self.special_tokens_list       ,		show_progress=UpperCAmelCase__       ,		)

								if isinstance(UpperCAmelCase__       ,		UpperCAmelCase__     ):
												SCREAMING_SNAKE_CASE__     							=				[files]
								self._tokenizer.train(UpperCAmelCase__       ,		trainer=UpperCAmelCase__     )

								self.add_unk_id()



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = 8000       ,		UpperCAmelCase__ = True       ,		):
								SCREAMING_SNAKE_CASE__     							=				trainers.UnigramTrainer(
								    vocab_size=UpperCAmelCase__       ,		special_tokens=self.special_tokens_list       ,		show_progress=UpperCAmelCase__       ,		)

								self._tokenizer.train_from_iterator(UpperCAmelCase__       ,		trainer=UpperCAmelCase__     )

								self.add_unk_id()






				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				json.loads(self._tokenizer.to_str()     )

								SCREAMING_SNAKE_CASE__     							=				self.special_tokens["unk"]["id"]

								SCREAMING_SNAKE_CASE__     							=				Tokenizer.from_str(json.dumps(UpperCAmelCase__     )     )
