


"""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


_snake_case          =							logging.get_logger(__name__)


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

# See all MVP models at https://huggingface.co/models?filter=mvp
_snake_case          =							{
    "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",
    },
}

_snake_case          =							{
    "RUCAIBox/mvp": 1024,
}



class   _a      (      __a ):
    a_    :				Union[str, Any]             =    VOCAB_FILES_NAMES
    a_    :				Optional[Any]             =    PRETRAINED_VOCAB_FILES_MAP
    a_    :				str             =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a_    :				List[Any]             =    ['input_ids', 'attention_mask']
    a_    :				Optional[Any]             =    MvpTokenizer
    def __init__( self							:					Optional[Any]							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=None							,					SCREAMING_SNAKE_CASE__							:					List[str]=None							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=None							,					SCREAMING_SNAKE_CASE__							:					List[str]="replace"							,					SCREAMING_SNAKE_CASE__							:					List[str]="<s>"							,					SCREAMING_SNAKE_CASE__							:					List[Any]="</s>"							,					SCREAMING_SNAKE_CASE__							:					str="</s>"							,					SCREAMING_SNAKE_CASE__							:					Any="<s>"							,					SCREAMING_SNAKE_CASE__							:					Optional[Any]="<unk>"							,					SCREAMING_SNAKE_CASE__							:					Optional[int]="<pad>"							,					SCREAMING_SNAKE_CASE__							:					int="<mask>"							,					SCREAMING_SNAKE_CASE__							:					List[str]=False							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=True							,					**SCREAMING_SNAKE_CASE__							:					Tuple							,					):
          super().__init__(
              A__							,					A__							,					tokenizer_file=A__							,					errors=A__							,					bos_token=A__							,					eos_token=A__							,					sep_token=A__							,					cls_token=A__							,					unk_token=A__							,					pad_token=A__							,					mask_token=A__							,					add_prefix_space=A__							,					trim_offsets=A__							,					**A__							,					)

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

          lowerCamelCase__           =		add_prefix_space

          # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
          lowerCamelCase__           =		'post_processor'
          lowerCamelCase__           =		getattr(self.backend_tokenizer							,					A__							,					A__				)
          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'							,					A__				) != add_prefix_space:
                      lowerCamelCase__           =		add_prefix_space
                      lowerCamelCase__           =		True

                if state.get('trim_offsets'							,					A__				) != trim_offsets:
                      lowerCamelCase__           =		trim_offsets
                      lowerCamelCase__           =		True

                if changes_to_apply:
                      lowerCamelCase__           =		getattr(A__							,					state.pop('type'				)				)
                      lowerCamelCase__           =		component_class(**A__				)
                      setattr(self.backend_tokenizer							,					A__							,					A__				)
    @property
    def      _UpperCamelCase       ( self							:					Dict				):
          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]							,					SCREAMING_SNAKE_CASE__							:					str				):
          lowerCamelCase__           =		AddedToken(A__							,					lstrip=A__							,					rstrip=A__				) if isinstance(A__							,					A__				) else value
          lowerCamelCase__           =		value
    def      _UpperCamelCase       ( self							:					List[str]							,					*SCREAMING_SNAKE_CASE__							:					int							,					**SCREAMING_SNAKE_CASE__							:					Dict				):
          lowerCamelCase__           =		kwargs.get('is_split_into_words'							,					A__				)

          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(*A__							,					**A__				)
    def      _UpperCamelCase       ( self							:					List[Any]							,					*SCREAMING_SNAKE_CASE__							:					Dict							,					**SCREAMING_SNAKE_CASE__							:					int				):
          lowerCamelCase__           =		kwargs.get('is_split_into_words'							,					A__				)

          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(*A__							,					**A__				)
    def      _UpperCamelCase       ( self							:					int							,					SCREAMING_SNAKE_CASE__							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					List[str] = None				):
          lowerCamelCase__           =		self._tokenizer.model.save(A__							,					name=A__				)
          return tuple(A__				)
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					Any							,					SCREAMING_SNAKE_CASE__							:					Any=None				):
          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      _UpperCamelCase       ( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					Any							,					SCREAMING_SNAKE_CASE__							:					Tuple = None				):
          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]







"""simple docstring"""


def   snake_case						(				_a:     int		,   _a:     list[int]		,   _a:     int							)->		int:
      '''simple docstring'''


      def count_of_possible_combinations(_a:     int							) -> int:
            if target < 0:
                  return 0
            if target == 0:
                  return 1
            return sum(count_of_possible_combinations(target - item							) for item in array							)

      return count_of_possible_combinations(_a							)



def   snake_case						(				_a:     int		,   _a:     list[int]		,   _a:     int							)->		int:
      '''simple docstring'''


      def count_of_possible_combinations_with_dp_array(
          _a:     int		,   _a:     list[int]							) -> int:
            if target < 0:
                  return 0
            if target == 0:
                  return 1
            if dp_array[target] != -1:
                  return dp_array[target]
            lowerCamelCase__           =		sum(
                count_of_possible_combinations_with_dp_array(target - item		,   _a							)
                for item in array							)
            lowerCamelCase__           =		answer
            return answer

      lowerCamelCase__           =		[-1] * (target + 1)
      return count_of_possible_combinations_with_dp_array(_a		,   _a							)



def   snake_case						(				_a:     int		,   _a:     list[int]		,   _a:     int							)->		int:
      '''simple docstring'''


      lowerCamelCase__           =		[0] * (target + 1)
      lowerCamelCase__           =		1

      for i in range(1		,   target + 1							):
            for j in range(_a							):
                  if i - array[j] >= 0:
                        dp_array[i] += dp_array[i - array[j]]

      return dp_array[target]


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   _snake_case          =							3
   _snake_case          =							5
   _snake_case          =							[1, 2, 5]
   print(combination_sum_iv(n, array, target))



