





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_camembert import CamembertTokenizer
else:
      __UpperCAmelCase	:       List[str]    	=							None


__UpperCAmelCase	:       Tuple    	=							logging.get_logger(__name__)

__UpperCAmelCase	:       List[str]    	=							{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

__UpperCAmelCase	:       List[Any]    	=							{
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    },
    "tokenizer_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/tokenizer.json",
    },
}

__UpperCAmelCase	:       Any    	=							{
    "camembert-base": 512,
}

__UpperCAmelCase	:       Optional[int]    	=							"▁"







class    __snake_case	(							__lowerCamelCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					VOCAB_FILES_NAMES
       lowerCAmelCase__						=					PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__						=					["""input_ids""", """attention_mask"""]
       lowerCAmelCase__						=					CamembertTokenizer




       def __init__(  self			:   Optional[int]							,    A			:   Optional[Any]=None							,    A			:   Tuple=None							,    A			:   int="<s>"							,    A			:   Any="</s>"							,    A			:   Optional[Any]="</s>"							,    A			:   Dict="<s>"							,    A			:   Dict="<unk>"							,    A			:   Union[str, Any]="<pad>"							,    A			:   Tuple="<mask>"							,    A			:   List[Any]=["<s>NOTUSED", "</s>NOTUSED"]							,    **A			:   Optional[Any]							,    ):
         # Mask token behave like a normal word, i.e. include the space before it
         __snake_case:						List[Any]			  =						AddedToken(A							,    lstrip=A							,    rstrip=A		) if isinstance(A							,    A		) else mask_token

         super().__init__(
             A							,    tokenizer_file=A							,    bos_token=A							,    eos_token=A							,    sep_token=A							,    cls_token=A							,    unk_token=A							,    pad_token=A							,    mask_token=A							,    additional_special_tokens=A							,    **A							,    )

         __snake_case:						List[str]			  =						vocab_file
         __snake_case:						Optional[Any]			  =						False if not self.vocab_file else True




       def 							UpperCAmelCase__			(  self			:   Any							,    A			:   List[int]							,    A			:   Optional[List[int]] = None		):

         if token_ids_a is None:
           return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         __snake_case:						List[str]			  =						[self.cls_token_id]
         __snake_case:						str			  =						[self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep




       def 							UpperCAmelCase__			(  self			:   Tuple							,    A			:   List[int]							,    A			:   Optional[List[int]] = None		):
         __snake_case:						List[str]			  =						[self.sep_token_id]
         __snake_case:						Dict			  =						[self.cls_token_id]

         if token_ids_a is None:
           return len(cls + token_ids_a + sep		) * [0]
         return len(cls + token_ids_a + sep + sep + token_ids_a + sep		) * [0]






       def 							UpperCAmelCase__			(  self			:   Union[str, Any]							,    A			:   str							,    A			:   Optional[str] = None		):
         if not self.can_save_slow_tokenizer:
           raise ValueError(
               """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
               """tokenizer."""		)

         if not os.path.isdir(A		):
           logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
           return
         __snake_case:						int			  =						os.path.join(
             A							,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)

         if os.path.abspath(self.vocab_file		) != os.path.abspath(A		):
           copyfile(self.vocab_file							,    A		)

         return (out_vocab_file,)













import argparse
from collections import defaultdict

import yaml


__UpperCAmelCase	:       int    	=							"docs/source/en/_toctree.yml"







def       A__							(   SCREAMING_SNAKE_CASE__)       ->   Dict:
  __snake_case:						Union[str, Any]			  =						defaultdict(SCREAMING_SNAKE_CASE__)
  for doc in model_doc:
    counts[doc["local"]] += 1
  __snake_case:						Dict			  =						[key for key, value in counts.items() if value > 1]

  __snake_case:						Optional[Any]			  =						[]
  for duplicate_key in duplicates:
    __snake_case:						Tuple			  =						list({doc["""title"""] for doc in model_doc if doc["""local"""] == duplicate_key})
    if len(SCREAMING_SNAKE_CASE__) > 1:
      raise ValueError(
          F'''{duplicate_key} is present several times in the documentation table of content at '''
          """`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the """
          """others.""")
    # Only add this once
    new_doc.append({"""local""": duplicate_key, """title""": titles[0]})

  # Add none duplicate-keys
  new_doc.extend([doc for doc in model_doc if counts[doc["""local"""]] == 1])

  # Sort
  return sorted(SCREAMING_SNAKE_CASE__ , key=lambda SCREAMING_SNAKE_CASE__: s["title"].lower())







def       A__							(   SCREAMING_SNAKE_CASE__=False)       ->   List[str]:
  with open(SCREAMING_SNAKE_CASE__ , encoding="""utf-8""") as f:
    __snake_case:						Optional[int]			  =						yaml.safe_load(f.read())

  # Get to the API doc
  __snake_case:						Dict			  =						0
  while content[api_idx]["title"] != "API":
    api_idx += 1
  __snake_case:						str			  =						content[api_idx]["""sections"""]

  # Then to the model doc
  __snake_case:						List[Any]			  =						0
  while api_doc[model_idx]["title"] != "Models":
    model_idx += 1

  __snake_case:						Dict			  =						api_doc[model_idx]["""sections"""]

  __snake_case:						int			  =						[(idx, section) for idx, section in enumerate(SCREAMING_SNAKE_CASE__) if """sections""" in section]
  __snake_case:						Optional[int]			  =						False
  for idx, modality_doc in modalities_docs:
    __snake_case:						Dict			  =						modality_doc["""sections"""]
    __snake_case:						List[str]			  =						clean_model_doc_toc(SCREAMING_SNAKE_CASE__)

    if old_modality_doc != new_modality_doc:
      __snake_case:						List[str]			  =						True
      if overwrite:
        __snake_case:						Dict			  =						new_modality_doc

  if diff:
    if overwrite:
      __snake_case:						Dict			  =						model_doc
      __snake_case:						int			  =						api_doc
      with open(SCREAMING_SNAKE_CASE__ , """w""" , encoding="""utf-8""") as f:
        f.write(yaml.dump(SCREAMING_SNAKE_CASE__ , allow_unicode=SCREAMING_SNAKE_CASE__))
    else:
      raise ValueError(
          """The model doc part of the table of content is not properly sorted, run `make style` to fix this.""")


if __name__ == "__main__":
      __UpperCAmelCase	:       Optional[Any]    	=							argparse.ArgumentParser()
      parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
      __UpperCAmelCase	:       str    	=							parser.parse_args()

      check_model_doc(args.fix_and_overwrite)






