





import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation


_lowerCamelCase :    str  							= logging.get_logger(__name__)

_lowerCamelCase :    int  							= {'''tokenizer_file''': '''tokenizer.json'''}

_lowerCamelCase :    Optional[Any]  							= {
    '''tokenizer_file''': {
        '''bigscience/tokenizer''': '''https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json''',
        '''bigscience/bloom-560m''': '''https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b1''': '''https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b7''': '''https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json''',
        '''bigscience/bloom-3b''': '''https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json''',
        '''bigscience/bloom-7b1''': '''https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json''',
        '''bigscience/bloom''': '''https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json''',
    },
}


class 						lowerCamelCase       (_snake_case      ):







       """simple docstring"""




       UpperCAmelCase_      						=   VOCAB_FILES_NAMES
       UpperCAmelCase_      						=   PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase_      						=   ["input_ids", "attention_mask"]
       UpperCAmelCase_      						=   None






       def __init__( self     :					int,			_UpperCAmelCase     :					Optional[Any]=None,			_UpperCAmelCase     :					Union[str, Any]=None,			_UpperCAmelCase     :					Dict=None,			_UpperCAmelCase     :					Any="<unk>",			_UpperCAmelCase     :					Dict="<s>",			_UpperCAmelCase     :					Optional[Any]="</s>",			_UpperCAmelCase     :					List[str]="<pad>",			_UpperCAmelCase     :					Tuple=False,			_UpperCAmelCase     :					Tuple=False,			**_UpperCAmelCase     :					List[Any],			)				->			Optional[Any]:





              """simple docstring"""
              super().__init__(
                  UpperCamelCase__,			UpperCamelCase__,			tokenizer_file=UpperCamelCase__,			unk_token=UpperCamelCase__,			bos_token=UpperCamelCase__,			eos_token=UpperCamelCase__,			pad_token=UpperCamelCase__,			add_prefix_space=UpperCamelCase__,			clean_up_tokenization_spaces=UpperCamelCase__,			**UpperCamelCase__,			)
              SCREAMING_SNAKE_CASE__       :      int     =						json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()						)
              if pre_tok_state.get("add_prefix_space",			UpperCamelCase__						) != add_prefix_space:
                     SCREAMING_SNAKE_CASE__       :      str     =						getattr(UpperCamelCase__,			pre_tok_state.pop("type"						)						)
                     SCREAMING_SNAKE_CASE__       :      Optional[int]     =						add_prefix_space
                     SCREAMING_SNAKE_CASE__       :      Any     =						pre_tok_class(**UpperCamelCase__						)

              SCREAMING_SNAKE_CASE__       :      Optional[int]     =						add_prefix_space






       def  A_     ( self     :					Optional[int],			*_UpperCAmelCase     :					Any,			**_UpperCAmelCase     :					str						)				->			BatchEncoding:





              """simple docstring"""
              SCREAMING_SNAKE_CASE__       :      Optional[int]     =						kwargs.get("is_split_into_words",			UpperCamelCase__						)
              if not (self.add_prefix_space or not is_split_into_words):
                     raise Exception(
                         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  A_     ( self     :					Any,			*_UpperCAmelCase     :					Union[str, Any],			**_UpperCAmelCase     :					Tuple						)				->			BatchEncoding:





              """simple docstring"""
              SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						kwargs.get("is_split_into_words",			UpperCamelCase__						)

              if not (self.add_prefix_space or not is_split_into_words):
                     raise Exception(
                         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  A_     ( self     :					Optional[Any],			_UpperCAmelCase     :					Tuple,			_UpperCAmelCase     :					Tuple = None						)				->			Tuple[str]:





              """simple docstring"""
              SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self._tokenizer.model.save(UpperCamelCase__,			name=UpperCamelCase__						)
              return tuple(UpperCamelCase__						)






       def  A_     ( self     :					Dict,			_UpperCAmelCase     :					int						)				->			List[int]:





              """simple docstring"""
              SCREAMING_SNAKE_CASE__       :      Tuple     =						[]
              for is_user, text in conversation.iter_texts():
                     input_ids.extend(self.encode(UpperCamelCase__,			add_special_tokens=UpperCamelCase__						) + [self.eos_token_id]						)

              if len(UpperCamelCase__						) > self.model_max_length:
                     SCREAMING_SNAKE_CASE__       :      Any     =						input_ids[-self.model_max_length :]
              return input_ids













_lowerCamelCase :    dict[tuple[int, int, int], int]  							= {}




def _a (  SCREAMING_SNAKE_CASE__      :  int			,				SCREAMING_SNAKE_CASE__      :  int			,				SCREAMING_SNAKE_CASE__      :  int       )	->    int:

							'''simple docstring'''






							if late == 3 or absent == 2:
														return 0

							# if we have no days left, and have not failed any other rules,
							# we have a prize string
							if days == 0:
														return 1

							# No easy solution, so now we need to do the recursive calculation

							# First, check if the combination is already in the cache, and
							# if yes, return the stored value from there since we already
							# know the number of possible prize strings from this point on
							SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						(days, absent, late)
							if key in cache:
														return cache[key]

							# now we calculate the three possible ways that can unfold from
							# this point on, depending on our attendance today

							# 1) if we are late (but not absent), the "absent" counter stays as
							# it is, but the "late" counter increases by one
							SCREAMING_SNAKE_CASE__       :      Tuple     =						_calculate(days - 1			,				SCREAMING_SNAKE_CASE__			,				late + 1       )

							# 2) if we are absent, the "absent" counter increases by 1, and the
							# "late" counter resets to 0
							SCREAMING_SNAKE_CASE__       :      Dict     =						_calculate(days - 1			,				absent + 1			,				0       )

							# 3) if we are on time, this resets the "late" counter and keeps the
							# absent counter
							SCREAMING_SNAKE_CASE__       :      Any     =						_calculate(days - 1			,				SCREAMING_SNAKE_CASE__			,				0       )

							SCREAMING_SNAKE_CASE__       :      str     =						state_late + state_absent + state_ontime

							SCREAMING_SNAKE_CASE__       :      Optional[int]     =						prizestrings
							return prizestrings




def _a (  SCREAMING_SNAKE_CASE__      :  int = 30       )	->    int:

							'''simple docstring'''






							return _calculate(SCREAMING_SNAKE_CASE__			,				absent=0			,				late=0       )


if __name__ == "__main__":
		print(solution())






