


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        _a							(			UpperCamelCase__			):

							def __init__(							self:	Optional[Any]    ,						UpperCamelCase_:	str = "▁"    ,						UpperCamelCase_:	bool = True    ,						UpperCamelCase_:	Union[str, AddedToken] = "<unk>"    ,						UpperCamelCase_:	Union[str, AddedToken] = "</s>"    ,						UpperCamelCase_:	Union[str, AddedToken] = "<pad>"    ,						)			->   int:





									"""simple docstring"""







									lowercase__            =      {
									    '''pad''': {'''id''': 0, '''token''': pad_token},
									    '''eos''': {'''id''': 1, '''token''': eos_token},
									    '''unk''': {'''id''': 2, '''token''': unk_token},
									}

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

									lowercase__            =      Tokenizer(Unigram()							)

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

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

									lowercase__            =      {
									    '''model''': '''SentencePieceUnigram''',
									    '''replacement''': replacement,
									    '''add_prefix_space''': add_prefix_space,
									}

									super().__init__(UpperCamelCase_    ,						UpperCamelCase_							)

							def       lowerCamelCase_ (							self:	Tuple    ,						UpperCamelCase_:	Union[str, List[str]]    ,						UpperCamelCase_:	int = 8_000    ,						UpperCamelCase_:	bool = True    ,						)			->   Any:





									"""simple docstring"""







									lowercase__            =      trainers.UnigramTrainer(
									    vocab_size=UpperCamelCase_    ,						special_tokens=self.special_tokens_list    ,						show_progress=UpperCamelCase_    ,						)

									if isinstance(UpperCamelCase_    ,						UpperCamelCase_							):
											lowercase__            =      [files]
									self._tokenizer.train(UpperCamelCase_    ,						trainer=UpperCamelCase_							)

									self.add_unk_id()

							def       lowerCamelCase_ (							self:	List[Any]    ,						UpperCamelCase_:	Union[Iterator[str], Iterator[Iterator[str]]]    ,						UpperCamelCase_:	int = 8_000    ,						UpperCamelCase_:	bool = True    ,						)			->   int:





									"""simple docstring"""







									lowercase__            =      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:	Any							)			->   Optional[int]:





									"""simple docstring"""







									lowercase__            =      json.loads(self._tokenizer.to_str()							)

									lowercase__            =      self.special_tokens['''unk''']['''id''']

									lowercase__            =      Tokenizer.from_str(json.dumps(UpperCamelCase_							)							)






import inspect
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_config_docstrings.py
lowerCAmelCase       =							'src/transformers'


# This is to make sure the transformers module imported is the one in the repo.
lowerCAmelCase       =							direct_transformers_import(PATH_TO_TRANSFORMERS)

lowerCAmelCase       =							transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
lowerCAmelCase       =							re.compile(R'\[(.+?)\]\((https://huggingface\.co/.+?)\)')


lowerCAmelCase       =							{
    'DecisionTransformerConfig',
    'EncoderDecoderConfig',
    'MusicgenConfig',
    'RagConfig',
    'SpeechEncoderDecoderConfig',
    'TimmBackboneConfig',
    'VisionEncoderDecoderConfig',
    'VisionTextDualEncoderConfig',
    'LlamaConfig',
}
def 			_a (      SCREAMING_SNAKE_CASE     ):


		"""simple docstring"""




		lowercase__            =      None

		# source code of `config_class`
		lowercase__            =      inspect.getsource(SCREAMING_SNAKE_CASE     )
		lowercase__            =      _re_checkpoint.findall(SCREAMING_SNAKE_CASE     )

		# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
		# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
		for ckpt_name, ckpt_link in checkpoints:
				# allow the link to end with `/`
				if ckpt_link.endswith('''/'''     ):
						lowercase__            =      ckpt_link[:-1]

				# verify the checkpoint name corresponds to the checkpoint link
				lowercase__            =      f'https://huggingface.co/{ckpt_name}'
				if ckpt_link == ckpt_link_from_name:
						lowercase__            =      ckpt_name
						break

		return checkpoint
def 			_a (      ):


		"""simple docstring"""




		lowercase__            =      []

		for config_class in list(CONFIG_MAPPING.values()     ):
				# Skip deprecated models
				if "models.deprecated" in config_class.__module__:
						continue
				lowercase__            =      get_checkpoint_from_config_class(SCREAMING_SNAKE_CASE     )

				lowercase__            =      config_class.__name__
				if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
						configs_without_checkpoint.append(SCREAMING_SNAKE_CASE     )

		if len(SCREAMING_SNAKE_CASE     ) > 0:
				lowercase__            =      '''\n'''.join(sorted(SCREAMING_SNAKE_CASE     )     )
				raise ValueError(f'The following configurations don\'t contain any valid checkpoint:\n{message}'     )


if __name__ == "__main__":
			check_config_docstrings_have_checkpoints()


