


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


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


SCREAMING_SNAKE_CASE :   str							      =				{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all MVP models at https://huggingface.co/models?filter=mvp
SCREAMING_SNAKE_CASE :   Optional[Any]							      =				{
    "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",
    },
}

SCREAMING_SNAKE_CASE :   Optional[Any]							      =				{
    "RUCAIBox/mvp": 1024,
}






class _lowerCamelCase(		_a     ):
       lowercase_				:			Union[str, Any]									=    VOCAB_FILES_NAMES
       lowercase_				:			List[Any]									=    PRETRAINED_VOCAB_FILES_MAP
       lowercase_				:			List[Any]									=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowercase_				:			Optional[Any]									=    ["""input_ids""", """attention_mask"""]
       lowercase_				:			Optional[Any]									=    MvpTokenizer
       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]:




           """simple docstring"""

           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,   )

           _lowercase :							List[Any]   	=	json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
           if pre_tok_state.get('add_prefix_space',   lowerCamelCase) != add_prefix_space:
               _lowercase :							Union[str, Any]   	=	getattr(lowerCamelCase,   pre_tok_state.pop('type'))
               _lowercase :							int   	=	add_prefix_space
               _lowercase :							List[Any]   	=	pre_tok_class(**lowerCamelCase)

           _lowercase :							List[Any]   	=	add_prefix_space

           # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
           _lowercase :							List[str]   	=	'post_processor'
           _lowercase :							Union[str, Any]   	=	getattr(self.backend_tokenizer,   lowerCamelCase,   lowerCamelCase)
           if tokenizer_component_instance:
               _lowercase :							Any   	=	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:
                   _lowercase :							Union[str, Any]   	=	tuple(state['sep'])
               if "cls" in state:
                   _lowercase :							Tuple   	=	tuple(state['cls'])

               _lowercase :							Tuple   	=	False

               if state.get('add_prefix_space',   lowerCamelCase) != add_prefix_space:
                   _lowercase :							Optional[Any]   	=	add_prefix_space
                   _lowercase :							int   	=	True

               if state.get('trim_offsets',   lowerCamelCase) != trim_offsets:
                   _lowercase :							List[str]   	=	trim_offsets
                   _lowercase :							List[str]   	=	True

               if changes_to_apply:
                   _lowercase :							Optional[int]   	=	getattr(lowerCamelCase,   state.pop('type'))
                   _lowercase :							Optional[Any]   	=	component_class(**lowerCamelCase)
                   setattr(self.backend_tokenizer,   lowerCamelCase,   lowerCamelCase)
       @property
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           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,   lowerCamelCase) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							List[Any]   	=	AddedToken(lowerCamelCase,   lstrip=lowerCamelCase,   rstrip=lowerCamelCase) if isinstance(lowerCamelCase,   lowerCamelCase) else value
           _lowercase :							List[str]   	=	value
       def     UpperCamelCase  (      self,   *lowerCamelCase,   **lowerCamelCase) ->     Any:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	kwargs.get('is_split_into_words',   lowerCamelCase)

           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(*lowerCamelCase,   **lowerCamelCase)
       def     UpperCamelCase  (      self,   *lowerCamelCase,   **lowerCamelCase) ->     List[Any]:




           """simple docstring"""

           _lowercase :							Tuple   	=	kwargs.get('is_split_into_words',   lowerCamelCase)

           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(*lowerCamelCase,   **lowerCamelCase)
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase = None) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	self._tokenizer.model.save(lowerCamelCase,   name=lowerCamelCase)
           return tuple(lowerCamelCase)
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase=None) ->     str:




           """simple docstring"""

           _lowercase :							str   	=	[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,   lowerCamelCase,   lowerCamelCase = None) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							Dict   	=	[self.sep_token_id]
           _lowercase :							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]






def        UpperCamelCase_(   lowerCamelCase_				)					->		int:
    assert (
        isinstance(lowerCamelCase_							,				lowerCamelCase_				) and number_of_steps > 0
    ), F'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
    if number_of_steps == 1:
        return 1
    _lowercase	,       _lowercase :							Dict   	=	1, 1
    for _ in range(number_of_steps - 1				):
        _lowercase	,       _lowercase :							Tuple   	=	current + previous, current
    return current


if __name__ == "__main__":
 import doctest

 doctest.testmod()


