


'''simple docstring'''






import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


__UpperCAmelCase       							=				logging.get_logger(__name__)

__UpperCAmelCase       							=				{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__UpperCAmelCase       							=				{
    '''vocab_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/vocab.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/vocab.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/vocab.json''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/merges.txt''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/merges.txt''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/merges.txt''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/tokenizer.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/tokenizer.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json''',
        '''roberta-base-openai-detector''': (
            '''https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'''
        ),
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'''
        ),
    },
}

__UpperCAmelCase       							=				{
    '''roberta-base''': 512,
    '''roberta-large''': 512,
    '''roberta-large-mnli''': 512,
    '''distilroberta-base''': 512,
    '''roberta-base-openai-detector''': 512,
    '''roberta-large-openai-detector''': 512,
}




class 						a__							(				a__    ):





							'''simple docstring'''






							lowercase__     :  Optional[Any]      		= VOCAB_FILES_NAMES
							lowercase__     :  Dict      		= PRETRAINED_VOCAB_FILES_MAP
							lowercase__     :  Dict      		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase__     :  int      		= ["input_ids", "attention_mask"]
							lowercase__     :  Optional[int]      		= RobertaTokenizer







							def __init__(						self   ,       lowerCamelCase_=None   ,       lowerCamelCase_=None   ,       lowerCamelCase_=None   ,       lowerCamelCase_="replace"   ,       lowerCamelCase_="<s>"   ,       lowerCamelCase_="</s>"   ,       lowerCamelCase_="</s>"   ,       lowerCamelCase_="<s>"   ,       lowerCamelCase_="<unk>"   ,       lowerCamelCase_="<pad>"   ,       lowerCamelCase_="<mask>"   ,       lowerCamelCase_=False   ,       lowerCamelCase_=True   ,       **lowerCamelCase_   ,       )			->				List[Any]:
														super().__init__(
														    lowerCamelCase_   ,       lowerCamelCase_   ,       tokenizer_file=lowerCamelCase_   ,       errors=lowerCamelCase_   ,       bos_token=lowerCamelCase_   ,       eos_token=lowerCamelCase_   ,       sep_token=lowerCamelCase_   ,       cls_token=lowerCamelCase_   ,       unk_token=lowerCamelCase_   ,       pad_token=lowerCamelCase_   ,       mask_token=lowerCamelCase_   ,       add_prefix_space=lowerCamelCase_   ,       trim_offsets=lowerCamelCase_   ,       **lowerCamelCase_   ,       )

														lowerCAmelCase__			  =      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()  )
														if pre_tok_state.get('''add_prefix_space'''   ,       lowerCamelCase_  ) != add_prefix_space:
																					lowerCAmelCase__			  =      getattr(lowerCamelCase_   ,       pre_tok_state.pop('''type'''  )  )
																					lowerCAmelCase__			  =      add_prefix_space
																					lowerCAmelCase__			  =      pre_tok_class(**lowerCamelCase_  )

														lowerCAmelCase__			  =      add_prefix_space

														lowerCAmelCase__			  =      '''post_processor'''
														lowerCAmelCase__			  =      getattr(self.backend_tokenizer   ,       lowerCamelCase_   ,       lowerCamelCase_  )
														if tokenizer_component_instance:
																					lowerCAmelCase__			  =      json.loads(tokenizer_component_instance.__getstate__()  )

																					# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																					if "sep" in state:
																												lowerCAmelCase__			  =      tuple(state['''sep''']  )
																					if "cls" in state:
																												lowerCAmelCase__			  =      tuple(state['''cls''']  )

																					lowerCAmelCase__			  =      False

																					if state.get('''add_prefix_space'''   ,       lowerCamelCase_  ) != add_prefix_space:
																												lowerCAmelCase__			  =      add_prefix_space
																												lowerCAmelCase__			  =      True

																					if state.get('''trim_offsets'''   ,       lowerCamelCase_  ) != trim_offsets:
																												lowerCAmelCase__			  =      trim_offsets
																												lowerCAmelCase__			  =      True

																					if changes_to_apply:
																												lowerCAmelCase__			  =      getattr(lowerCamelCase_   ,       state.pop('''type'''  )  )
																												lowerCAmelCase__			  =      component_class(**lowerCamelCase_  )
																												setattr(self.backend_tokenizer   ,       lowerCamelCase_   ,       lowerCamelCase_  )







							@property
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				str:
														if self._mask_token is None:
																					if self.verbose:
																												logger.error('''Using mask_token, but it is not set yet.'''  )
																					return None
														return str(self._mask_token  )







							@mask_token.setter
							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_  )			->				Union[str, Any]:
														lowerCAmelCase__			  =      AddedToken(lowerCamelCase_   ,       lstrip=lowerCamelCase_   ,       rstrip=lowerCamelCase_  ) if isinstance(lowerCamelCase_   ,       lowerCamelCase_  ) else value
														lowerCAmelCase__			  =      value







							def     __SCREAMING_SNAKE_CASE				(						self   ,       *lowerCamelCase_   ,       **lowerCamelCase_  )			->				BatchEncoding:
														lowerCAmelCase__			  =      kwargs.get('''is_split_into_words'''   ,       lowerCamelCase_  )
														assert self.add_prefix_space or not is_split_into_words, (
														    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._batch_encode_plus(*lowerCamelCase_   ,       **lowerCamelCase_  )







							def     __SCREAMING_SNAKE_CASE				(						self   ,       *lowerCamelCase_   ,       **lowerCamelCase_  )			->				BatchEncoding:
														lowerCAmelCase__			  =      kwargs.get('''is_split_into_words'''   ,       lowerCamelCase_  )

														assert self.add_prefix_space or not is_split_into_words, (
														    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._encode_plus(*lowerCamelCase_   ,       **lowerCamelCase_  )







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_ = None  )			->				Tuple[str]:
														lowerCAmelCase__			  =      self._tokenizer.model.save(lowerCamelCase_   ,       name=lowerCamelCase_  )
														return tuple(lowerCamelCase_  )







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_=None  )			->				int:
														lowerCAmelCase__			  =      [self.bos_token_id] + token_ids_a + [self.eos_token_id]
														if token_ids_a is None:
																					return output

														return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







							def     __SCREAMING_SNAKE_CASE				(						self   ,       lowerCamelCase_   ,       lowerCamelCase_ = None  )			->				List[int]:
														lowerCAmelCase__			  =      [self.sep_token_id]
														lowerCAmelCase__			  =      [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]



def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->Any:
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  len(lowerCAmelCase_ )

   for i in range(n - 1 ):
      for j in range(i + 1	,    lowerCAmelCase_ ):
         if arr[i] > arr[j]:
            num_inversions += 1

   return num_inversions
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->Any:
   if len(lowerCAmelCase_ ) <= 1:
      return arr, 0
   UpperCAmelCase      					=  len(lowerCAmelCase_ ) // 2
   UpperCAmelCase      					=  arr[0:mid]
   UpperCAmelCase      					=  arr[mid:]

   UpperCAmelCase					,	UpperCAmelCase      					=  count_inversions_recursive(lowerCAmelCase_ )
   UpperCAmelCase					,	UpperCAmelCase      					=  count_inversions_recursive(lowerCAmelCase_ )
   UpperCAmelCase					,	UpperCAmelCase      					=  _count_cross_inversions(lowerCAmelCase_	,    lowerCAmelCase_ )

   UpperCAmelCase      					=  inversion_p + inversions_q + cross_inversions
   return c, num_inversions
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  []
   UpperCAmelCase      					=  UpperCAmelCase      					=  UpperCAmelCase      					=  0
   while i < len(lowerCAmelCase_ ) and j < len(lowerCAmelCase_ ):
      if p[i] > q[j]:
         # if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
         # These are all inversions. The claim emerges from the
         # property that P is sorted.
         num_inversion += len(lowerCAmelCase_ ) - i
         r.append(q[j] )
         j += 1
      else:
         r.append(p[i] )
         i += 1

   if i < len(lowerCAmelCase_ ):
      r.extend(p[i:] )
   else:
      r.extend(q[j:] )

   return r, num_inversion
def 	_UpperCamelCase					(    )    ->int:
   UpperCAmelCase      					=  [1_0, 2, 1, 5, 5, 2, 1_1]

   # this arr has 8 inversions:
   # (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

   UpperCAmelCase      					=  count_inversions_bf(lowerCAmelCase_ )
   UpperCAmelCase					,	UpperCAmelCase      					=  count_inversions_recursive(lowerCAmelCase_ )

   assert num_inversions_bf == num_inversions_recursive == 8

   print("""number of inversions = """	,    lowerCAmelCase_ )

   # testing an array with zero inversion (a sorted arr_1)

   arr_a.sort()
   UpperCAmelCase      					=  count_inversions_bf(lowerCAmelCase_ )
   UpperCAmelCase					,	UpperCAmelCase      					=  count_inversions_recursive(lowerCAmelCase_ )

   assert num_inversions_bf == num_inversions_recursive == 0
   print("""number of inversions = """	,    lowerCAmelCase_ )

   # an empty list should also have zero inversions
   UpperCAmelCase      					=  []
   UpperCAmelCase      					=  count_inversions_bf(lowerCAmelCase_ )
   UpperCAmelCase					,	UpperCAmelCase      					=  count_inversions_recursive(lowerCAmelCase_ )

   assert num_inversions_bf == num_inversions_recursive == 0
   print("""number of inversions = """	,    lowerCAmelCase_ )


if __name__ == "__main__":
 main()



