'''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_mvp import MvpTokenizer


_UpperCAmelCase    :     List[str]         =       logging.get_logger(__name__)


_UpperCAmelCase    :     List[str]         =       {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all MVP models at https://huggingface.co/models?filter=mvp
_UpperCAmelCase    :     Dict         =       {
    '''vocab_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json''',
    },
    '''added_tokens.json''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json''',
    },
    '''merges_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json''',
    },
}

_UpperCAmelCase    :     List[str]         =       {
    '''RUCAIBox/mvp''': 10_24,
}







class lowercase_       (		_UpperCamelCase			):







   """simple docstring"""

   __lowerCAmelCase         =   VOCAB_FILES_NAMES
   __lowerCAmelCase         =   PRETRAINED_VOCAB_FILES_MAP
   __lowerCAmelCase         =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __lowerCAmelCase         =   ["input_ids", "attention_mask"]
   __lowerCAmelCase         =   MvpTokenizer
   def __init__(      self      :			Tuple, UpperCamelCase__      :			Any=None, UpperCamelCase__      :			Optional[int]=None, UpperCamelCase__      :			Tuple=None, UpperCamelCase__      :			Optional[Any]="replace", UpperCamelCase__      :			Dict="<s>", UpperCamelCase__      :			Any="</s>", UpperCamelCase__      :			Tuple="</s>", UpperCamelCase__      :			int="<s>", UpperCamelCase__      :			Any="<unk>", UpperCamelCase__      :			Dict="<pad>", UpperCamelCase__      :			int="<mask>", UpperCamelCase__      :			int=False, UpperCamelCase__      :			int=True, **UpperCamelCase__      :			int, )  ->			Tuple:
        super().__init__(
            UpperCamelCase__, UpperCamelCase__, tokenizer_file=UpperCamelCase__, errors=UpperCamelCase__, bos_token=UpperCamelCase__, eos_token=UpperCamelCase__, sep_token=UpperCamelCase__, cls_token=UpperCamelCase__, unk_token=UpperCamelCase__, pad_token=UpperCamelCase__, mask_token=UpperCamelCase__, add_prefix_space=UpperCamelCase__, trim_offsets=UpperCamelCase__, **UpperCamelCase__, )

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

        _A    		=  add_prefix_space

        # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
        _A    		=  'post_processor'
        _A    		=  getattr(self.backend_tokenizer, UpperCamelCase__, UpperCamelCase__     )
        if tokenizer_component_instance:
             _A    		=  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:
                  _A    		=  tuple(state['sep']     )
             if "cls" in state:
                  _A    		=  tuple(state['cls']     )

             _A    		=  False

             if state.get('add_prefix_space', UpperCamelCase__     ) != add_prefix_space:
                  _A    		=  add_prefix_space
                  _A    		=  True

             if state.get('trim_offsets', UpperCamelCase__     ) != trim_offsets:
                  _A    		=  trim_offsets
                  _A    		=  True

             if changes_to_apply:
                  _A    		=  getattr(UpperCamelCase__, state.pop('type'     )     )
                  _A    		=  component_class(**UpperCamelCase__     )
                  setattr(self.backend_tokenizer, UpperCamelCase__, UpperCamelCase__     )
   @property
   def 	__UpperCAmelCase   (      self      :			List[Any]     )  ->			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 	__UpperCAmelCase   (      self      :			List[Any], UpperCamelCase__      :			Any     )  ->			List[str]:
        _A    		=  AddedToken(UpperCamelCase__, lstrip=UpperCamelCase__, rstrip=UpperCamelCase__     ) if isinstance(UpperCamelCase__, UpperCamelCase__     ) else value
        _A    		=  value
   def 	__UpperCAmelCase   (      self      :			str, *UpperCamelCase__      :			Dict, **UpperCamelCase__      :			Any     )  ->			BatchEncoding:
        _A    		=  kwargs.get('is_split_into_words', UpperCamelCase__     )

        if is_split_into_words and not self.add_prefix_space:
             raise ValueError(
                 f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                 'to use it with pretokenized inputs.'     )

        return super()._batch_encode_plus(*UpperCamelCase__, **UpperCamelCase__     )
   def 	__UpperCAmelCase   (      self      :			Optional[int], *UpperCamelCase__      :			Optional[int], **UpperCamelCase__      :			Any     )  ->			BatchEncoding:
        _A    		=  kwargs.get('is_split_into_words', UpperCamelCase__     )

        if is_split_into_words and not self.add_prefix_space:
             raise ValueError(
                 f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                 'to use it with pretokenized inputs.'     )

        return super()._encode_plus(*UpperCamelCase__, **UpperCamelCase__     )
   def 	__UpperCAmelCase   (      self      :			Dict, UpperCamelCase__      :			str, UpperCamelCase__      :			Optional[str] = None     )  ->			Tuple[str]:
        _A    		=  self._tokenizer.model.save(UpperCamelCase__, name=UpperCamelCase__     )
        return tuple(UpperCamelCase__     )
   def 	__UpperCAmelCase   (      self      :			Tuple, UpperCamelCase__      :			List[Any], UpperCamelCase__      :			Optional[Any]=None     )  ->			List[Any]:
        _A    		=  [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 	__UpperCAmelCase   (      self      :			List[Any], UpperCamelCase__      :			List[int], UpperCamelCase__      :			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]






def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			)->						list:



    """simple docstring"""






    if bit_count < 0:
        raise ValueError("The given input must be positive"			)

    # get the generated string sequence
    UpperCamelCase_			  =						gray_code_sequence_string(SCREAMING_SNAKE_CASE_			)
    #
    # convert them to integers
    for i in range(len(SCREAMING_SNAKE_CASE_			)			):
        UpperCamelCase_			  =						int(sequence[i]			,						2			)

    return sequence




def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			)->						list:



    """simple docstring"""






    if bit_count == 0:
        return ["0"]

    if bit_count == 1:
        return ["0", "1"]

    UpperCamelCase_			  =						1 << bit_count  # defines the length of the sequence
    # 1<< n is equivalent to 2^n

    # recursive answer will generate answer for n-1 bits
    UpperCamelCase_			  =						gray_code_sequence_string(bit_count - 1			)

    UpperCamelCase_			  =						[]

    # append 0 to first half of the smaller sequence generated
    for i in range(seq_len // 2			):
        UpperCamelCase_			  =						"0" + smaller_sequence[i]
        sequence.append(SCREAMING_SNAKE_CASE_			)

    # append 1 to second half ... start from the end of the list
    for i in reversed(range(seq_len // 2			)			):
        UpperCamelCase_			  =						"1" + smaller_sequence[i]
        sequence.append(SCREAMING_SNAKE_CASE_			)

    return sequence


if __name__ == "__main__":
 import doctest

 doctest.testmod()
