





'''simple docstring'''

def    a__							(							lowercase   :	str )						->						int:





     """simple docstring"""

     assert column_title.isupper()
     _UpperCamelCase							       =			0
     _UpperCamelCase							       =			len(lowercase ) - 1
     _UpperCamelCase							       =			0

     while index >= 0:
          _UpperCamelCase							       =			(ord(column_title[index] ) - 64) * pow(26,   lowercase )
          answer += value
          power += 1
          index -= 1

     return answer


if __name__ == "__main__":
   from doctest import testmod

   testmod()







"""simple docstring"""


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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__snake_case    					=					logging.get_logger(__name__)

__snake_case    					=					'▁'

__snake_case    					=					{'vocab_file': 'sentencepiece.bpe.model'}

__snake_case    					=					{
    'vocab_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
    }
}

__snake_case    					=					{
    'facebook/xglm-564M': 2048,
}

class 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase  ):
   """simple docstring"""



   _a   :       Optional[int]									=    VOCAB_FILES_NAMES
   _a   :       Union[str, Any]									=    PRETRAINED_VOCAB_FILES_MAP
   _a   :       Dict									=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _a   :       Any									=    ['''input_ids''', '''attention_mask''']


   def __init__(						self ,     lowerCamelCase__ ,     lowerCamelCase__="<s>" ,     lowerCamelCase__="</s>" ,     lowerCamelCase__="</s>" ,     lowerCamelCase__="<s>" ,     lowerCamelCase__="<unk>" ,     lowerCamelCase__="<pad>" ,     lowerCamelCase__ = None ,     **lowerCamelCase__ ,     )      ->							None:
    lowercase__       :       List[Any]				=						{} if sp_model_kwargs is None else sp_model_kwargs

    # Compatibility with the original tokenizer
    lowercase__       :       Any				=						7
    lowercase__       :       Dict				=						[F'''<madeupword{i}>''' for i in range(self.num_madeup_words						)]

    lowercase__       :       Tuple				=						kwargs.get("""additional_special_tokens""" ,     []						)
    kwargs["additional_special_tokens"] += [
        word for word in madeup_words if word not in kwargs["additional_special_tokens"]
    ]

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

    lowercase__       :       Optional[Any]				=						spm.SentencePieceProcessor(**self.sp_model_kwargs						)
    self.sp_model.Load(str(lowerCamelCase__						)						)
    lowercase__       :       Optional[Any]				=						vocab_file

    # Original fairseq vocab and spm vocab must be "aligned":
    # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
    # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
    # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
    # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

    # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
    lowercase__       :       Optional[Any]				=						1

    # Mimic fairseq token-to-id alignment for the first 4 token
    lowercase__       :       Any				=						{"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

    lowercase__       :       Optional[int]				=						len(self.sp_model						)
    lowercase__       :       Union[str, Any]				=						{F'''<madeupword{i}>''': sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words						)}
    self.fairseq_tokens_to_ids.update(lowerCamelCase__						)

    lowercase__       :       List[str]				=						{v: k for k, v in self.fairseq_tokens_to_ids.items()}


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


   def __setstate__(						self ,     lowerCamelCase__						)      ->							Optional[int]:
    lowercase__       :       int				=						d

    # for backward compatibility
    if not hasattr(self ,     """sp_model_kwargs"""						):
     lowercase__       :       Union[str, Any]				=						{}

    lowercase__       :       Optional[int]				=						spm.SentencePieceProcessor(**self.sp_model_kwargs						)
    self.sp_model.LoadFromSerializedProto(self.sp_model_proto						)


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__ ,     lowerCamelCase__ = None						)      ->							List[int]:

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


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__ ,     lowerCamelCase__ = None ,     lowerCamelCase__ = 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__						))
    return [1] + ([0] * len(lowerCamelCase__						)) + [1, 1] + ([0] * len(lowerCamelCase__						))


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__ ,     lowerCamelCase__ = None						)      ->							List[int]:
    lowercase__       :       str				=						[self.sep_token_id]

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


   @property
   def 					UpperCAmelCase__(						self						)      ->							Union[str, Any]:
    return len(self.sp_model						) + self.fairseq_offset + self.num_madeup_words


   def 					UpperCAmelCase__(						self						)      ->							int:
    lowercase__       :       Optional[Any]				=						{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 ,     lowerCamelCase__						)      ->							List[str]:
    return self.sp_model.encode(lowerCamelCase__ ,     out_type=lowerCamelCase__						)


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__						)      ->							int:
    if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
    lowercase__       :       List[Any]				=						self.sp_model.PieceToId(lowerCamelCase__						)

    # Need to return unknown token if the SP model returned 0
    return spm_id + self.fairseq_offset if spm_id else self.unk_token_id


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__						)      ->							int:
    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 ,     lowerCamelCase__						)      ->							int:
    lowercase__       :       Dict				=						"""""".join(lowerCamelCase__						).replace(lowerCamelCase__ ,     """ """						).strip()
    return out_string







   def 					UpperCAmelCase__(						self ,     lowerCamelCase__ ,     lowerCamelCase__ = None						)      ->							Tuple[str]:
    if not os.path.isdir(lowerCamelCase__						):
     logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''						)
     return
    lowercase__       :       int				=						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__       :       Union[str, Any]				=						self.sp_model.serialized_model_proto()
      fi.write(lowerCamelCase__						)

    return (out_vocab_file,)