



'''simple docstring'''

import os
from typing import Dict, List, Union

import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs

from .tokenization_gpta import GPTaTokenizer

class __snake_case( tf.keras.layers.Layer   ):


						'''simple docstring'''



						def __init__(   self      ,			A_      ,			A_      ,			A_ = None      ,			A_ = None )      ->      Optional[Any]:
							super().__init__()
							lowerCAmelCase       =      pad_token_id
							lowerCAmelCase       =      max_length
							lowerCAmelCase       =      vocab
							lowerCAmelCase       =      merges
							lowerCAmelCase       =      BytePairTokenizer(__A      ,			__A      ,			sequence_length=__A )


						@classmethod
						def 							__snake_case       (   cls      ,			A_      ,			*A_      ,			**A_ )      ->      Any:
							lowerCAmelCase       =      [""" """.join(__A ) for m in tokenizer.bpe_ranks.keys()]
							lowerCAmelCase       =      tokenizer.get_vocab()
							return cls(__A      ,			__A      ,			*__A      ,			**__A )


						@classmethod
						def 							__snake_case       (   cls      ,			A_      ,			*A_      ,			**A_ )      ->      str:
							lowerCAmelCase       =      GPTaTokenizer.from_pretrained(__A      ,			*__A      ,			**__A )
							return cls.from_tokenizer(__A      ,			*__A      ,			**__A )


						@classmethod
						def 							__snake_case       (   cls      ,			A_ )      ->      List[str]:
							return cls(**__A )


						def 							__snake_case       (   self )      ->      Tuple:
							return {
							    "vocab": self.vocab,
							    "merges": self.merges,
							    "max_length": self.max_length,
							    "pad_token_id": self.pad_token_id,
							}




						def 							__snake_case       (   self      ,			A_      ,			A_ = None )      ->      List[str]:
							lowerCAmelCase       =      self.tf_tokenizer(__A )
							lowerCAmelCase       =      tf.ones_like(__A )

							if self.pad_token_id is not None:
								# pad the tokens up to max length
								lowerCAmelCase       =      max_length if max_length is not None else self.max_length

								if max_length is not None:
									lowerCAmelCase       =      pad_model_inputs(
									    __A      ,			max_seq_length=__A      ,			pad_value=self.pad_token_id )

							return {"attention_mask": attention_mask, "input_ids": input_ids}


UpperCAmelCase_							:					dict[tuple[int, int, int], int]		 =   {}
def 							__SCREAMING_SNAKE_CASE     (   a__    :   int			,a__    :   int			,a__    :   int       )					->				int:

	# if we are absent twice, or late 3 consecutive days,
	# no further prize strings are possible
	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 :			List[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
	__A :			Dict		    =			_calculate(days - 1			,a__			,late + 1       )

	# 2) if we are absent, the "absent" counter increases by 1, and the
	# "late" counter resets to 0
	__A :			List[str]		    =			_calculate(days - 1			,absent + 1			,0       )

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

	__A :			Optional[int]		    =			state_late + state_absent + state_ontime

	__A :			Tuple		    =			prizestrings
	return prizestrings
def 							__SCREAMING_SNAKE_CASE     (   a__    :   int = 30       )					->				int:
	return _calculate(a__			,absent=0			,late=0       )


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





