



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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


a__   :					List[str] 						=      logging.get_logger(__name__)

a__   :					Any 						=      {"vocab_file": "sentencepiece.bpe.model"}

a__   :					Any 						=      {
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

a__   :					Optional[int] 						=      {
    "camembert-base": 5_12,
}

a__   :					int 						=      "▁"



class    UpperCAmelCase__(				lowerCamelCase						):

   '''simple docstring'''




   A     :	int												=     VOCAB_FILES_NAMES
   A     :	Any												=     PRETRAINED_VOCAB_FILES_MAP
   A     :	Any												=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A     :	Tuple												=     ["input_ids", "attention_mask"]


   def __init__(    self	:      Optional[Any]      ,					lowerCAmelCase	:      str      ,					lowerCAmelCase	:      Optional[Any]="<s>"      ,					lowerCAmelCase	:      int="</s>"      ,					lowerCAmelCase	:      Union[str, Any]="</s>"      ,					lowerCAmelCase	:      Optional[int]="<s>"      ,					lowerCAmelCase	:      Any="<unk>"      ,					lowerCAmelCase	:      Any="<pad>"      ,					lowerCAmelCase	:      str="<mask>"      ,					lowerCAmelCase	:      Optional[int]=["<s>NOTUSED", "</s>NOTUSED"]      ,					lowerCAmelCase	:      Optional[Dict[str, Any]] = None      ,					**lowerCAmelCase	:      Union[str, Any]      ,					)						->					None:




         """simple docstring"""

         lowercase__  =	AddedToken(lowerCAmelCase      ,					lstrip=lowerCAmelCase      ,					rstrip=lowerCAmelCase) if isinstance(lowerCAmelCase      ,					lowerCAmelCase) else mask_token

         lowercase__  =	{} if sp_model_kwargs is None else sp_model_kwargs

         super().__init__(
             bos_token=lowerCAmelCase      ,					eos_token=lowerCAmelCase      ,					unk_token=lowerCAmelCase      ,					sep_token=lowerCAmelCase      ,					cls_token=lowerCAmelCase      ,					pad_token=lowerCAmelCase      ,					mask_token=lowerCAmelCase      ,					additional_special_tokens=lowerCAmelCase      ,					sp_model_kwargs=self.sp_model_kwargs      ,					**lowerCAmelCase      ,					)
         lowercase__  =	spm.SentencePieceProcessor(**self.sp_model_kwargs)
         self.sp_model.Load(str(lowerCAmelCase))
         lowercase__  =	vocab_file
         # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
         # sentencepiece vocabulary (this is the case for <s> and </s>
         lowercase__  =	{'<s>NOTUSED': 0, '<pad>': 1, '</s>NOTUSED': 2, '<unk>': 3}
         lowercase__  =	len(self.fairseq_tokens_to_ids)
         lowercase__  =	len(self.sp_model) + len(self.fairseq_tokens_to_ids)
         lowercase__  =	{v: k for k, v in self.fairseq_tokens_to_ids.items()}


   def       UpperCAmelCase		(    self	:      List[str]      ,					lowerCAmelCase	:      List[int]      ,					lowerCAmelCase	:      Optional[List[int]] = None)						->					List[int]:




         """simple docstring"""

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


   def       UpperCAmelCase		(    self	:      Tuple      ,					lowerCAmelCase	:      List[int]      ,					lowerCAmelCase	:      Optional[List[int]] = None      ,					lowerCAmelCase	:      bool = False)						->					List[int]:




         """simple docstring"""

         if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=lowerCAmelCase      ,					token_ids_a=lowerCAmelCase      ,					already_has_special_tokens=lowerCAmelCase)

         if token_ids_a is None:
               return [1] + ([0] * len(lowerCAmelCase)) + [1]
         return [1] + ([0] * len(lowerCAmelCase)) + [1, 1] + ([0] * len(lowerCAmelCase)) + [1]


   def       UpperCAmelCase		(    self	:      List[Any]      ,					lowerCAmelCase	:      List[int]      ,					lowerCAmelCase	:      Optional[List[int]] = None)						->					List[int]:




         """simple docstring"""

         lowercase__  =	[self.sep_token_id]
         lowercase__  =	[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]


   @property
   def       UpperCAmelCase		(    self	:      Optional[Any])						->					Dict:




         """simple docstring"""

         return len(self.fairseq_tokens_to_ids) + len(self.sp_model)


   def       UpperCAmelCase		(    self	:      str)						->					Tuple:




         """simple docstring"""

         lowercase__  =	{self.convert_ids_to_tokens(lowerCAmelCase): i for i in range(self.vocab_size)}
         vocab.update(self.added_tokens_encoder)
         return vocab


   def       UpperCAmelCase		(    self	:      str      ,					lowerCAmelCase	:      str)						->					List[str]:




         """simple docstring"""

         return self.sp_model.encode(lowerCAmelCase      ,					out_type=lowerCAmelCase)


   def       UpperCAmelCase		(    self	:      List[str]      ,					lowerCAmelCase	:      Tuple)						->					List[str]:




         """simple docstring"""

         if token in self.fairseq_tokens_to_ids:
               return self.fairseq_tokens_to_ids[token]
         elif self.sp_model.PieceToId(lowerCAmelCase) == 0:
               # Convert sentence piece unk token to fairseq unk token index
               return self.unk_token_id
         return self.fairseq_offset + self.sp_model.PieceToId(lowerCAmelCase)


   def       UpperCAmelCase		(    self	:      Optional[int]      ,					lowerCAmelCase	:      Optional[int])						->					List[str]:




         """simple docstring"""

         if index in self.fairseq_ids_to_tokens:
               return self.fairseq_ids_to_tokens[index]
         return self.sp_model.IdToPiece(index - self.fairseq_offset)


   def       UpperCAmelCase		(    self	:      Union[str, Any]      ,					lowerCAmelCase	:      Union[str, Any])						->					str:




         """simple docstring"""

         lowercase__  =	[]
         lowercase__  =	''
         lowercase__  =	False
         for token in tokens:
               # make sure that special tokens are not decoded using sentencepiece model
               if token in self.all_special_tokens:
                     if not prev_is_special:
                           out_string += " "
                     out_string += self.sp_model.decode(lowerCAmelCase) + token
                     lowercase__  =	True
                     lowercase__  =	[]
               else:
                     current_sub_tokens.append(lowerCAmelCase)
                     lowercase__  =	False
         out_string += self.sp_model.decode(lowerCAmelCase)
         return out_string.strip()


   def __getstate__(    self	:      Tuple)						->					Optional[int]:




         """simple docstring"""

         lowercase__  =	self.__dict__.copy()
         lowercase__  =	None
         return state


   def __setstate__(    self	:      Optional[Any]      ,					lowerCAmelCase	:      Any)						->					Optional[Any]:




         """simple docstring"""

         lowercase__  =	d

         # for backward compatibility
         if not hasattr(self      ,					'sp_model_kwargs'):
               lowercase__  =	{}

         lowercase__  =	spm.SentencePieceProcessor(**self.sp_model_kwargs)
         self.sp_model.Load(self.vocab_file)



   def       UpperCAmelCase		(    self	:      Any      ,					lowerCAmelCase	:      str      ,					lowerCAmelCase	:      Optional[str] = None)						->					Tuple[str]:




         """simple docstring"""

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

         if os.path.abspath(self.vocab_file) != os.path.abspath(lowerCAmelCase) and os.path.isfile(self.vocab_file):
               copyfile(self.vocab_file      ,					lowerCAmelCase)
         elif not os.path.isfile(self.vocab_file):
               with open(lowerCAmelCase      ,					'wb') as fi:
                     lowercase__  =	self.sp_model.serialized_model_proto()
                     fi.write(lowerCAmelCase)

         return (out_vocab_file,)





from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands

def 	_lowerCAmelCase (    ):
      lowercase__  =	ArgumentParser('Transformers CLI tool'    ,	usage='transformers-cli <command> [<args>]'						)
      lowercase__  =	parser.add_subparsers(help='transformers-cli command helpers'						)

      # Register commands
      ConvertCommand.register_subcommand(A__						)
      DownloadCommand.register_subcommand(A__						)
      EnvironmentCommand.register_subcommand(A__						)
      RunCommand.register_subcommand(A__						)
      ServeCommand.register_subcommand(A__						)
      UserCommands.register_subcommand(A__						)
      AddNewModelCommand.register_subcommand(A__						)
      AddNewModelLikeCommand.register_subcommand(A__						)
      LfsCommands.register_subcommand(A__						)
      PTtoTFCommand.register_subcommand(A__						)

      # Let's go
      lowercase__  =	parser.parse_args()

      if not hasattr(A__    ,	'func'						):
            parser.print_help()
            exit(1						)

      # Run
      lowercase__  =	args.func(A__						)
      service.run()


if __name__ == "__main__":
       main()
