


'''simple docstring'''


__magic_name__								=   {}




def   lowerCamelCase       (   lowerCamelCase	:   Any				,    lowerCamelCase	:   List[str]				,    lowerCamelCase	:   Tuple):


      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
      A_    :	str							 =					(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
      A_    :	Optional[int]							 =					_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
      A_    :	Optional[int]							 =					_calculate(days - 1				,    absent + 1				,    0)

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

      A_    :	List[str]							 =					state_late + state_absent + state_ontime

      A_    :	Dict							 =					prizestrings
      return prizestrings




def   lowerCamelCase       (   lowerCamelCase	:   Dict = 30):
      return _calculate(SCREAMING_SNAKE_CASE__				,    absent=0				,    late=0)


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


'''simple docstring'''
from .data_collator import (
    DataCollatorForLanguageModeling,
    DataCollatorForPermutationLanguageModeling,
    DataCollatorForSeqaSeq,
    DataCollatorForSOP,
    DataCollatorForTokenClassification,
    DataCollatorForWholeWordMask,
    DataCollatorWithPadding,
    DefaultDataCollator,
    default_data_collator,
)
from .metrics import glue_compute_metrics, xnli_compute_metrics
from .processors import (
    DataProcessor,
    InputExample,
    InputFeatures,
    SingleSentenceClassificationProcessor,
    SquadExample,
    SquadFeatures,
    SquadVaProcessor,
    SquadVaProcessor,
    glue_convert_examples_to_features,
    glue_output_modes,
    glue_processors,
    glue_tasks_num_labels,
    squad_convert_examples_to_features,
    xnli_output_modes,
    xnli_processors,
    xnli_tasks_num_labels,
)


