



'''simple docstring'''





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


_lowerCAmelCase      						=	logging.get_logger(__name__)

_lowerCAmelCase      						=	'''▁'''

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

_lowerCAmelCase      						=	{
    '''vocab_file''': {
        '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large-finetuned-conll02-dutch''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll02-spanish''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-english''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-german''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'''
        ),
    }
}

_lowerCAmelCase      						=	{
    '''xlm-roberta-base''': 512,
    '''xlm-roberta-large''': 512,
    '''xlm-roberta-large-finetuned-conll02-dutch''': 512,
    '''xlm-roberta-large-finetuned-conll02-spanish''': 512,
    '''xlm-roberta-large-finetuned-conll03-english''': 512,
    '''xlm-roberta-large-finetuned-conll03-german''': 512,
}






class        lowerCAmelCase_(				SCREAMING_SNAKE_CASE_     ):
  '''simple docstring'''




  __lowercase							:      List[str]				=      VOCAB_FILES_NAMES
  __lowercase							:      Union[str, Any]				=      PRETRAINED_VOCAB_FILES_MAP
  __lowercase							:      Union[str, Any]				=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __lowercase							:      List[str]				=      ['''input_ids''', '''attention_mask''']




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

      lowerCAmelCase__ :  Optional[Any]							      =					{} if sp_model_kwargs is None else sp_model_kwargs

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

      lowerCAmelCase__ :  List[str]							      =					spm.SentencePieceProcessor(**self.sp_model_kwargs      )
      self.sp_model.Load(str(__UpperCAmelCase      )      )
      lowerCAmelCase__ :  Tuple							      =					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'

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

      # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
      lowerCAmelCase__ :  int							      =					1

      lowerCAmelCase__ :  Dict							      =					len(self.sp_model      ) + self.fairseq_offset
      lowerCAmelCase__ :  Any							      =					{v: k for k, v in self.fairseq_tokens_to_ids.items()}




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




  def __setstate__(    self  ,__UpperCAmelCase      )    ->		str:
      lowerCAmelCase__ :  List[str]							      =					d

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

      lowerCAmelCase__ :  int							      =					spm.SentencePieceProcessor(**self.sp_model_kwargs      )
      self.sp_model.LoadFromSerializedProto(self.sp_model_proto      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		List[int]:

      if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      lowerCAmelCase__ :  List[Any]							      =					[self.cls_token_id]
      lowerCAmelCase__ :  int							      =					[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None  ,__UpperCAmelCase = False      )    ->		List[int]:

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

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




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		List[int]:
      lowerCAmelCase__ :  List[Any]							      =					[self.sep_token_id]
      lowerCAmelCase__ :  str							      =					[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      )    ->		str:
      return len(self.sp_model      ) + self.fairseq_offset + 1  # Add the <mask> token




  def 							UpperCAmelCase_	(    self      )    ->		int:
      lowerCAmelCase__ :  Optional[int]							      =					{self.convert_ids_to_tokens(__UpperCAmelCase      ): i for i in range(self.vocab_size      )}
      vocab.update(self.added_tokens_encoder      )
      return vocab




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




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		Optional[Any]:
      if token in self.fairseq_tokens_to_ids:
          return self.fairseq_tokens_to_ids[token]
      lowerCAmelCase__ :  Dict							      =					self.sp_model.PieceToId(__UpperCAmelCase      )

      # 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  ,__UpperCAmelCase      )    ->		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  ,__UpperCAmelCase      )    ->		List[str]:
      lowerCAmelCase__ :  Tuple							      =					"""""".join(__UpperCAmelCase      ).replace(__UpperCAmelCase  ,""" """      ).strip()
      return out_string






  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		Tuple[str]:
      if not os.path.isdir(__UpperCAmelCase      ):
          logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
          return
      lowerCAmelCase__ :  Optional[Any]							      =					os.path.join(
          __UpperCAmelCase  ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )

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

      return (out_vocab_file,)







'''simple docstring'''





def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase = "The quick brown fox jumps over the lazy dog"							,    ):



    """simple docstring"""





    lowerCAmelCase__ :  str							      =					set()

    # Replace all the whitespace in our sentence
    lowerCAmelCase__ :  Tuple							      =					input_str.replace(""" """							,    """"""			)
    for alpha in input_str:
        if "a" <= alpha.lower() <= "z":
            frequency.add(alpha.lower()			)
    return len(UpperCamelCase			) == 26
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase = "The quick brown fox jumps over the lazy dog"							,    ):



    """simple docstring"""





    lowerCAmelCase__ :  Any							      =					[False] * 26
    for char in input_str:
        if char.islower():
            lowerCAmelCase__ :  Optional[Any]							      =					True
        elif char.isupper():
            lowerCAmelCase__ :  Any							      =					True
    return all(UpperCamelCase			)
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase = "The quick brown fox jumps over the lazy dog"							,    ):



    """simple docstring"""





    return len({char for char in input_str.lower() if char.isalpha()}			) == 26
def    _SCREAMING_SNAKE_CASE  (       ):



    """simple docstring"""





    from timeit import timeit

    lowerCAmelCase__ :  Union[str, Any]							      =					"""from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"""
    print(timeit("""is_pangram()"""							,    setup=UpperCamelCase			)			)
    print(timeit("""is_pangram_faster()"""							,    setup=UpperCamelCase			)			)
    print(timeit("""is_pangram_fastest()"""							,    setup=UpperCamelCase			)			)
    # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
    # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()


