




import warnings
from typing import Dict, List, Optional, Tuple

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


UpperCAmelCase_		:					Dict          =  logging.get_logger(__name__)




class 		__A   (      UpperCamelCase__      ):
						UpperCamelCase      =       ["""input_ids""", """attention_mask"""]

						def __init__(		self :Optional[int]     ,			__snake_case :int="</s>"     ,			__snake_case :List[Any]="<unk>"     ,			__snake_case :Optional[int]="<pad>"     ,			__snake_case :Any=1_25     ,			__snake_case :Optional[Any]=None     ,			**__snake_case :Optional[int]     ,			):
										'''simple docstring'''

										if extra_ids > 0 and additional_special_tokens is None:
														__magic_name__						:						Tuple										=[f"<extra_id_{i}>" for i in range(__snake_case			)]
										elif extra_ids > 0 and additional_special_tokens is not None:
														# Check that we have the right number of extra_id special tokens
														__magic_name__						:						List[Any]										=len(set(filter(lambda __snake_case			: bool("""extra_id""" in str(__snake_case			)			)     ,			__snake_case			)			)			)
														if extra_tokens != extra_ids:
																		raise ValueError(
																		    f"Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"
																		    """ provided to ByT5Tokenizer. In this case the additional_special_tokens must include the"""
																		    """ extra_ids tokens"""			)

										__magic_name__						:						Tuple										=AddedToken(__snake_case     ,			lstrip=__snake_case     ,			rstrip=__snake_case			) if isinstance(__snake_case     ,			__snake_case			) else pad_token
										__magic_name__						:						List[str]										=AddedToken(__snake_case     ,			lstrip=__snake_case     ,			rstrip=__snake_case			) if isinstance(__snake_case     ,			__snake_case			) else eos_token
										__magic_name__						:						int										=AddedToken(__snake_case     ,			lstrip=__snake_case     ,			rstrip=__snake_case			) if isinstance(__snake_case     ,			__snake_case			) else unk_token

										super().__init__(
										    eos_token=__snake_case     ,			unk_token=__snake_case     ,			pad_token=__snake_case     ,			extra_ids=__snake_case     ,			additional_special_tokens=__snake_case     ,			**__snake_case     ,			)

										__magic_name__						:						Union[str, Any]										=extra_ids

										__magic_name__						:						Tuple										=2**8  # utf is 8 bits

										# define special tokens dict
										__magic_name__						:						Dict[int, str]										={
										    self.pad_token: 0,
										    self.eos_token: 1,
										    self.unk_token: 2,
										}
										__magic_name__						:						Optional[int]										=len(self.special_tokens_encoder			)
										__magic_name__						:						Any										=len(__snake_case			)
										for i, token in enumerate(__snake_case			):
														__magic_name__						:						Union[str, Any]										=self.vocab_size + i - n
										__magic_name__						:						Dict[str, int]										={v: k for k, v in self.special_tokens_encoder.items()}

						@property
						def      A__    (		self :Optional[Any]			):
										'''simple docstring'''

										return self._utf_vocab_size + self._num_special_tokens + self._extra_ids

						def      A__    (		self :Tuple     ,			__snake_case :List[int]     ,			__snake_case :Optional[List[int]] = None     ,			__snake_case :bool = False			):
										'''simple docstring'''

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

										# normal case: some special tokens
										if token_ids_a is None:
														return ([0] * len(__snake_case			)) + [1]
										return ([0] * len(__snake_case			)) + [1] + ([0] * len(__snake_case			)) + [1]

						def      A__    (		self :Union[str, Any]     ,			__snake_case :List[int]			):
										'''simple docstring'''

										if len(__snake_case			) > 0 and token_ids[-1] == self.eos_token_id:
														warnings.warn(
														    f"This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated"
														    """ eos tokens being added."""			)
														return token_ids
										else:
														return token_ids + [self.eos_token_id]

						def      A__    (		self :Any     ,			__snake_case :List[int]     ,			__snake_case :Optional[List[int]] = None			):
										'''simple docstring'''

										__magic_name__						:						Union[str, Any]										=[self.eos_token_id]

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

						def      A__    (		self :Union[str, Any]     ,			__snake_case :List[int]     ,			__snake_case :Optional[List[int]] = None			):
										'''simple docstring'''

										__magic_name__						:						Optional[Any]										=self._add_eos_if_not_present(__snake_case			)
										if token_ids_a is None:
														return token_ids_a
										else:
														__magic_name__						:						List[str]										=self._add_eos_if_not_present(__snake_case			)
														return token_ids_a + token_ids_a

						def      A__    (		self :Tuple     ,			__snake_case :str			):
										'''simple docstring'''

										__magic_name__						:						Dict										=[chr(__snake_case			) for i in text.encode("""utf-8"""			)]
										return tokens

						def      A__    (		self :int     ,			__snake_case :List[str]			):
										'''simple docstring'''

										if token in self.special_tokens_encoder:
														__magic_name__						:						Dict										=self.special_tokens_encoder[token]
										elif token in self.added_tokens_encoder:
														__magic_name__						:						int										=self.added_tokens_encoder[token]
										elif len(__snake_case			) != 1:
														__magic_name__						:						Optional[Any]										=self.unk_token_id
										else:
														__magic_name__						:						Any										=ord(__snake_case			) + self._num_special_tokens
										return token_id

						def      A__    (		self :Optional[Any]     ,			__snake_case :int			):
										'''simple docstring'''

										if index in self.special_tokens_decoder:
														__magic_name__						:						Any										=self.special_tokens_decoder[index]
										else:
														__magic_name__						:						int										=chr(index - self._num_special_tokens			)
										return token

						def      A__    (		self :Union[str, Any]     ,			__snake_case :int			):
										'''simple docstring'''

										__magic_name__						:						Any										=B""""""
										for token in tokens:
														if token in self.special_tokens_decoder:
																		__magic_name__						:						int										=self.special_tokens_decoder[token].encode("""utf-8"""			)
														elif token in self.added_tokens_decoder:
																		__magic_name__						:						Union[str, Any]										=self.special_tokens_decoder[token].encode("""utf-8"""			)
														elif token in self.special_tokens_encoder:
																		__magic_name__						:						str										=token.encode("""utf-8"""			)
														elif token in self.added_tokens_encoder:
																		__magic_name__						:						Optional[int]										=token.encode("""utf-8"""			)
														else:
																		__magic_name__						:						Tuple										=bytes([ord(__snake_case			)]			)
														bstring += tok_string
										__magic_name__						:						str										=bstring.decode("""utf-8"""     ,			errors="""ignore"""			)
										return string


						def      A__    (		self :Tuple     ,			__snake_case :str     ,			__snake_case :Optional[str] = None			):
										'''simple docstring'''

										return ()









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


UpperCAmelCase_		 =					logging.get_logger(__name__)

UpperCAmelCase_		 =					"""▁"""

UpperCAmelCase_		 =					{"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

UpperCAmelCase_		 =					{
    """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""",
    },
}

UpperCAmelCase_		 =					{"""vinai/bartpho-syllable""": 1_0_2_4}


class 	lowerCamelCase__	(       _A):



 """simple docstring"""

 a__					: int =  VOCAB_FILES_NAMES
 a__					: Tuple =  PRETRAINED_VOCAB_FILES_MAP
 a__					: Optional[int] =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 a__					: Tuple =  ["input_ids", "attention_mask"]

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

    _A      =       {} 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			,						sp_model_kwargs=self.sp_model_kwargs			,						**__lowerCAmelCase			,						)

    _A      =       vocab_file
    _A      =       monolingual_vocab_file
    _A      =       spm.SentencePieceProcessor(**self.sp_model_kwargs      )
    self.sp_model.Load(str(__lowerCAmelCase      )      )

    # Load the reduced vocab

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

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

 def __getstate__(    self					:					Any      )   ->	List[Any]:
    _A      =       self.__dict__.copy()
    _A      =       None
    _A      =       self.sp_model.serialized_model_proto()
    return state

 def __setstate__(    self					:					Union[str, Any]			,						__lowerCAmelCase					:					Dict      )   ->	List[Any]:
    _A      =       d

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

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

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

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

 def     snake_case_      (    self					:					List[Any]			,						__lowerCAmelCase					:					List[int]			,						__lowerCAmelCase					:					Optional[List[int]] = None			,						__lowerCAmelCase					:					bool = False      )   ->	List[int]:

    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     snake_case_      (    self					:					Any			,						__lowerCAmelCase					:					List[int]			,						__lowerCAmelCase					:					Optional[List[int]] = None      )   ->	List[int]:
    _A      =       [self.sep_token_id]
    _A      =       [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     snake_case_      (    self					:					Optional[int]      )   ->	Union[str, Any]:
    return len(self.fairseq_ids_to_tokens      )

 def     snake_case_      (    self					:					Dict      )   ->	Optional[Any]:
    _A      =       {self.convert_ids_to_tokens(__lowerCAmelCase      ): i for i in range(self.vocab_size      )}
    vocab.update(self.added_tokens_encoder      )
    return vocab

 def     snake_case_      (    self					:					List[str]			,						__lowerCAmelCase					:					str      )   ->	List[str]:
    return self.sp_model.encode(__lowerCAmelCase			,						out_type=__lowerCAmelCase      )

 def     snake_case_      (    self					:					str			,						__lowerCAmelCase					:					Optional[Any]      )   ->	Dict:
    if token in self.fairseq_tokens_to_ids:
       return self.fairseq_tokens_to_ids[token]
    else:
       return self.unk_token_id

 def     snake_case_      (    self					:					int			,						__lowerCAmelCase					:					Optional[int]      )   ->	List[str]:
    return self.fairseq_ids_to_tokens[index]

 def     snake_case_      (    self					:					List[str]			,						__lowerCAmelCase					:					Union[str, Any]      )   ->	Tuple:
    _A      =       ''''''.join(__lowerCAmelCase      ).replace(__lowerCAmelCase			,						''' '''      ).strip()
    return out_string

 def     snake_case_      (    self					:					str			,						__lowerCAmelCase					:					str			,						__lowerCAmelCase					:					Optional[str] = None      )   ->	Tuple[str]:
    if not os.path.isdir(__lowerCAmelCase      ):
       logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''      )
       return
    _A      =       os.path.join(
        __lowerCAmelCase			,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
    _A      =       os.path.join(
        __lowerCAmelCase			,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''monolingual_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:
          _A      =       self.sp_model.serialized_model_proto()
          fi.write(__lowerCAmelCase      )

    if os.path.abspath(self.monolingual_vocab_file      ) != os.path.abspath(
        __lowerCAmelCase      ) and os.path.isfile(self.monolingual_vocab_file      ):
       copyfile(self.monolingual_vocab_file			,						__lowerCAmelCase      )
    elif not os.path.isfile(self.monolingual_vocab_file      ):
       with open(__lowerCAmelCase			,						'''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(__lowerCAmelCase      )} \n'''      )

    return out_vocab_file, out_monolingual_vocab_file



