
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		     =    logging.get_logger(__name__)

_A		     =    '''▁'''

_A		     =    {'''vocab_file''': '''sentencepiece.bpe.model''', '''monolingual_vocab_file''': '''dict.txt'''}

_A		     =    {
    '''vocab_file''': {
        '''vinai/bartpho-syllable''': '''https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model''',
    },
    '''monolingual_vocab_file''': {
        '''vinai/bartpho-syllable''': '''https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt''',
    },
}

_A		     =    {'''vinai/bartpho-syllable''': 1_024}

class 						lowercase_				(				lowercase__ ):
 A__  : Optional[Any]      					=			VOCAB_FILES_NAMES
 A__  : Dict      					=			PRETRAINED_VOCAB_FILES_MAP
 A__  : Optional[int]      					=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 A__  : Dict      					=			['''input_ids''', '''attention_mask''']

 def __init__(					self   ,		__UpperCamelCase   ,		__UpperCamelCase   ,		__UpperCamelCase="<s>"   ,		__UpperCamelCase="</s>"   ,		__UpperCamelCase="</s>"   ,		__UpperCamelCase="<s>"   ,		__UpperCamelCase="<unk>"   ,		__UpperCamelCase="<pad>"   ,		__UpperCamelCase="<mask>"   ,		__UpperCamelCase = None   ,		**__UpperCamelCase   ,		):




        """simple docstring"""


        UpperCamelCase_											=				AddedToken(_a   ,		lstrip=_a   ,		rstrip=_a   ) if isinstance(_a   ,		_a   ) else mask_token

        UpperCamelCase_											=				{} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=_a   ,		eos_token=_a   ,		unk_token=_a   ,		sep_token=_a   ,		cls_token=_a   ,		pad_token=_a   ,		mask_token=_a   ,		sp_model_kwargs=self.sp_model_kwargs   ,		**_a   ,		)

        UpperCamelCase_											=				vocab_file
        UpperCamelCase_											=				monolingual_vocab_file
        UpperCamelCase_											=				spm.SentencePieceProcessor(**self.sp_model_kwargs   )
        self.sp_model.Load(str(_a   )   )

        # Load the reduced vocab

        # Keep order of special tokens for backward compatibility
        UpperCamelCase_											=				{}
        UpperCamelCase_											=				0
        for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
               if str(_a   ) not in self.fairseq_tokens_to_ids:
                      UpperCamelCase_											=				cnt
                      cnt += 1
        with open(_a   ,		"""r"""   ,		encoding="""utf-8"""   ) as f:
               for line in f.readlines():
                      UpperCamelCase_											=				line.strip().split()[0]
                      UpperCamelCase_											=				len(self.fairseq_tokens_to_ids   )
        if str(_a   ) not in self.fairseq_tokens_to_ids:
               UpperCamelCase_											=				len(self.fairseq_tokens_to_ids   )

        UpperCamelCase_											=				{v: k for k, v in self.fairseq_tokens_to_ids.items()}

 def __getstate__(					self   ):




        """simple docstring"""


        UpperCamelCase_											=				self.__dict__.copy()
        UpperCamelCase_											=				None
        UpperCamelCase_											=				self.sp_model.serialized_model_proto()
        return state

 def __setstate__(					self   ,		__UpperCamelCase   ):




        """simple docstring"""


        UpperCamelCase_											=				d

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

        UpperCamelCase_											=				spm.SentencePieceProcessor(**self.sp_model_kwargs   )
        self.sp_model.LoadFromSerializedProto(self.sp_model_proto   )

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ,		__UpperCamelCase = None   ):




        """simple docstring"""


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

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ,		__UpperCamelCase = None   ,		__UpperCamelCase = False   ):




        """simple docstring"""


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

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

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ,		__UpperCamelCase = None   ):




        """simple docstring"""


        UpperCamelCase_											=				[self.sep_token_id]
        UpperCamelCase_											=				[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 lowerCamelCase_ (					self   ):




        """simple docstring"""


        return len(self.fairseq_ids_to_tokens   )

 def lowerCamelCase_ (					self   ):




        """simple docstring"""


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

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ):




        """simple docstring"""


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

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ):




        """simple docstring"""


        if token in self.fairseq_tokens_to_ids:
               return self.fairseq_tokens_to_ids[token]
        else:
               return self.unk_token_id

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ):




        """simple docstring"""


        return self.fairseq_ids_to_tokens[index]

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ):




        """simple docstring"""


        UpperCamelCase_											=				''.join(_a   ).replace(_a   ,		""" """   ).strip()
        return out_string

 def lowerCamelCase_ (					self   ,		__UpperCamelCase   ,		__UpperCamelCase = None   ):




        """simple docstring"""


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

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

        if os.path.abspath(self.monolingual_vocab_file   ) != os.path.abspath(
            _a   ) and os.path.isfile(self.monolingual_vocab_file   ):
               copyfile(self.monolingual_vocab_file   ,		_a   )
        elif not os.path.isfile(self.monolingual_vocab_file   ):
               with open(_a   ,		"""w"""   ,		encoding="""utf-8"""   ) as fp:
                      for token in self.fairseq_tokens_to_ids:
                             if token not in self.all_special_tokens:
                                    fp.write(f'''{str(_a   )} \n'''   )

        return out_vocab_file, out_monolingual_vocab_file





'''simple docstring'''







import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union

import transformers
from transformers.testing_utils import require_tf, require_torch, slow


__lowerCAmelCase         =    logging.getLogger()







@unittest.skip('''Temporarily disable the doc tests.'''	)
@require_torch
@require_tf
@slow
class UpperCAmelCase__	( unittest.TestCase	):





  """simple docstring"""

  def   __lowercase		(		self      :     str							,_a      :     Path							,_a      :     Union[str, None] = None							,_a      :     Union[List[str], None] = None							,_a      :     Union[str, List[str], None] = None							,_a      :     bool = True							,):


     '''simple docstring'''






     _a				:	Optional[int]			=   [file for file in os.listdir(_a       ) if os.path.isfile(os.path.join(_a							,_a       )       )]

     if identifier is not None:
        _a				:	List[str]			=   [file for file in files if identifier in file]

     if n_identifier is not None:
        if isinstance(_a							,_a       ):
           for n_ in n_identifier:
              _a				:	Tuple			=   [file for file in files if n_ not in file]
        else:
           _a				:	Optional[Any]			=   [file for file in files if n_identifier not in file]

     _a				:	List[str]			=   ignore_files or []
     ignore_files.append('__init__.py'       )
     _a				:	Tuple			=   [file for file in files if file not in ignore_files]

     for file in files:
        # Open all files
        print('Testing'							,_a       )

        if only_modules:
           _a				:	Any			=   file.split('.'       )[0]
           try:
              _a				:	List[str]			=   getattr(_a							,_a       )
              _a				:	int			=   doctest.DocTestSuite(_a       )
              _a				:	Any			=   unittest.TextTestRunner().run(_a       )
              self.assertIs(len(result.failures       )							,0       )
           except AttributeError:
              logger.info(F"""{module_identifier} is not a module."""       )
        else:
           _a				:	Union[str, Any]			=   doctest.testfile(str('..' / directory / file       )							,optionflags=doctest.ELLIPSIS       )
           self.assertIs(result.failed							,0       )


  def   __lowercase		(		self      :     Any       ):


     '''simple docstring'''






     _a				:	int			=   Path('src/transformers'       )
     _a				:	List[Any]			=   'modeling'
     _a				:	Optional[Any]			=   [
         'modeling_ctrl.py',
         'modeling_tf_ctrl.py',
     ]
     self.analyze_directory(_a							,identifier=_a							,ignore_files=_a       )


  def   __lowercase		(		self      :     Optional[int]       ):


     '''simple docstring'''






     _a				:	Optional[Any]			=   Path('src/transformers'       )
     _a				:	Optional[Any]			=   'tokenization'
     self.analyze_directory(_a							,identifier=_a       )


  def   __lowercase		(		self      :     List[str]       ):


     '''simple docstring'''






     _a				:	Dict			=   Path('src/transformers'       )
     _a				:	str			=   'configuration'
     self.analyze_directory(_a							,identifier=_a       )


  def   __lowercase		(		self      :     Any       ):


     '''simple docstring'''






     _a				:	Tuple			=   Path('src/transformers'       )
     _a				:	List[Any]			=   ['configuration', 'modeling', 'tokenization']
     self.analyze_directory(_a							,n_identifier=_a       )


  def   __lowercase		(		self      :     Tuple       ):


     '''simple docstring'''






     _a				:	List[Any]			=   Path('docs/source'       )
     _a				:	List[str]			=   ['favicon.ico']
     self.analyze_directory(_a							,ignore_files=_a							,only_modules=_a       )



