




'''simple docstring'''





import timeit


class 							_lowerCAmelCase		:




				def __init__( self		,		snake_case_							)    ->      str:







											if isinstance(snake_case_		,		snake_case_							):  # Initializes a matrix identical to the one provided.
																		SCREAMING_SNAKE_CASE			: str	     =arg
																		SCREAMING_SNAKE_CASE			: Tuple	     =len(snake_case_							)
											else:  # Initializes a square matrix of the given size and set values to zero.
																		SCREAMING_SNAKE_CASE			: Any	     =arg
																		SCREAMING_SNAKE_CASE			: Any	     =[[0 for _ in range(self.n							)] for _ in range(self.n							)]







				def __mul__( self		,		snake_case_							)    ->      List[Any]:
											SCREAMING_SNAKE_CASE			: Optional[Any]	     =Matrix(self.n							)
											for i in range(self.n							):
																		for j in range(self.n							):
																									for k in range(self.n							):
																																matrix.t[i][j] += self.t[i][k] * b.t[k][j]
											return matrix







def 						lowerCAmelCase_       (	__a	,	__a )       ->			List[str]:





							"""simple docstring"""





							SCREAMING_SNAKE_CASE			: Union[str, Any]	     =Matrix([[1, 0], [0, 1]] )
							while b > 0:
														if b & 1:
																					matrix *= a
														a *= a
														b >>= 1
							return matrix
def 						lowerCAmelCase_       (	__a	,	__a	,	__a )       ->			int:





							"""simple docstring"""





							if n == 1:
														return fa
							elif n == 2:
														return fa
							SCREAMING_SNAKE_CASE			: int	     =Matrix([[1, 1], [1, 0]] )
							SCREAMING_SNAKE_CASE			: int	     =modular_exponentiation(lowercase__	,	n - 2 )
							return fa * matrix.t[0][0] + fa * matrix.t[0][1]
def 						lowerCAmelCase_       (	__a	,	__a	,	__a )       ->			Optional[Any]:





							"""simple docstring"""





							if n == 1:
														return fa
							elif n == 2:
														return fa

							SCREAMING_SNAKE_CASE			: str	     =fa
							SCREAMING_SNAKE_CASE			: Dict	     =fa
							n -= 2

							while n > 0:
														SCREAMING_SNAKE_CASE			: Tuple	     =fn_a + fn_a, fn_a
														n -= 1

							return fn_a
def 						lowerCAmelCase_       (	)       ->			List[str]:





							"""simple docstring"""





							SCREAMING_SNAKE_CASE			: List[str]	     ="\nfrom random import randint\nfrom __main__ import fibonacci_with_matrix_exponentiation\n"
							SCREAMING_SNAKE_CASE			: Union[str, Any]	     ="fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"
							SCREAMING_SNAKE_CASE			: Optional[int]	     =timeit.timeit(setup=lowercase__	,	stmt=lowercase__	,	number=100 )
							print('''With matrix exponentiation the average execution time is '''	,	exec_time / 100 )
							return exec_time
def 						lowerCAmelCase_       (	)       ->			List[Any]:





							"""simple docstring"""





							SCREAMING_SNAKE_CASE			: Union[str, Any]	     ="\nfrom random import randint\nfrom __main__ import simple_fibonacci\n"
							SCREAMING_SNAKE_CASE			: int	     ="simple_fibonacci(randint(1,70000), 1, 1)"
							SCREAMING_SNAKE_CASE			: Union[str, Any]	     =timeit.timeit(setup=lowercase__	,	stmt=lowercase__	,	number=100 )
							print(
							    '''Without matrix exponentiation the average execution time is '''	,	exec_time / 100 )
							return exec_time
def 						lowerCAmelCase_       (	)       ->			Optional[int]:





							"""simple docstring"""





							matrix_exponentiation_time()
							simple_fibonacci_time()


if __name__ == "__main__":
							main()












import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
from ...utils import logging


_A							    =	logging.get_logger(__name__)

_A							    =	{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

_A							    =	{
    """vocab_file""": {
        """TsinghuaAI/CPM-Generate""": """https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """TsinghuaAI/CPM-Generate""": """https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json""",
    },
}


class 							_lowerCAmelCase		(     UpperCamelCase__	):




				def __init__( self		,		snake_case_=None		,		snake_case_=None		,		snake_case_=False		,		snake_case_=True		,		snake_case_=False		,		snake_case_="<s>"		,		snake_case_="</s>"		,		snake_case_="<unk>"		,		snake_case_="<sep>"		,		snake_case_="<pad>"		,		snake_case_="<cls>"		,		snake_case_="<mask>"		,		snake_case_=["<eop>", "<eod>"]		,		**snake_case_		,		)    ->      str:
											SCREAMING_SNAKE_CASE			: Optional[int]	     =AddedToken(snake_case_		,		lstrip=snake_case_		,		rstrip=snake_case_							) if isinstance(snake_case_		,		snake_case_							) else mask_token

											super().__init__(
											    vocab_file=snake_case_		,		tokenizer_file=snake_case_		,		do_lower_case=snake_case_		,		remove_space=snake_case_		,		keep_accents=snake_case_		,		bos_token=snake_case_		,		eos_token=snake_case_		,		unk_token=snake_case_		,		sep_token=snake_case_		,		pad_token=snake_case_		,		cls_token=snake_case_		,		mask_token=snake_case_		,		additional_special_tokens=snake_case_		,		**snake_case_		,		)

											SCREAMING_SNAKE_CASE			: Dict	     =3
											SCREAMING_SNAKE_CASE			: Dict	     =do_lower_case
											SCREAMING_SNAKE_CASE			: int	     =remove_space
											SCREAMING_SNAKE_CASE			: Optional[Any]	     =keep_accents
											SCREAMING_SNAKE_CASE			: Tuple	     =vocab_file
											SCREAMING_SNAKE_CASE			: Optional[Any]	     =False if not self.vocab_file else True

											try:
																		import jieba
											except ModuleNotFoundError as error:
																		raise error.__class__(
																		    '''You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '''
																		    '''See https://pypi.org/project/jieba/ for installation.'''							)
											SCREAMING_SNAKE_CASE			: str	     =jieba
											SCREAMING_SNAKE_CASE			: Dict	     =str.maketrans(''' \n'''		,		'''\u2582\u2583'''							)




				def     __a		( self		,		snake_case_		,		snake_case_ = None							)    ->      List[int]:
											SCREAMING_SNAKE_CASE			: Dict	     =[self.sep_token_id]
											SCREAMING_SNAKE_CASE			: Any	     =[self.cls_token_id]
											if token_ids_a is None:
																		return token_ids_a + sep + cls
											return token_ids_a + sep + token_ids_a + sep + cls




				def     __a		( self		,		snake_case_		,		snake_case_ = None							)    ->      List[int]:
											SCREAMING_SNAKE_CASE			: Union[str, Any]	     =[self.sep_token_id]
											SCREAMING_SNAKE_CASE			: Union[str, Any]	     =[2]

											if token_ids_a is None:
																		return len(token_ids_a + sep							) * [0] + cls_segment_id
											return len(token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1] + cls_segment_id




				def     __a		( self		,		snake_case_		,		snake_case_ = None							)    ->      Tuple[str]:
											if not self.can_save_slow_tokenizer:
																		raise ValueError(
																		    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
																		    '''tokenizer.'''							)

											if not os.path.isdir(snake_case_							):
																		logger.error(F'Vocabulary path ({save_directory}) should be a directory'							)
																		return
											SCREAMING_SNAKE_CASE			: Union[str, Any]	     =os.path.join(
											    snake_case_		,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']							)

											if os.path.abspath(self.vocab_file							) != os.path.abspath(snake_case_							):
																		copyfile(self.vocab_file		,		snake_case_							)

											return (out_vocab_file,)




				def     __a		( self		,		snake_case_		,		*snake_case_		,		**snake_case_							)    ->      Optional[Any]:
											SCREAMING_SNAKE_CASE			: int	     =[
											    ''' '''.join([x.translate(self.translator							) for x in self.jieba.cut(snake_case_		,		cut_all=snake_case_							)]							)
											    for text in batch_text_or_text_pairs
											]
											return super()._batch_encode_plus(snake_case_		,		*snake_case_		,		**snake_case_							)







				def     __a		( self		,		*snake_case_		,		**snake_case_							)    ->      str:
											SCREAMING_SNAKE_CASE			: List[Any]	     =super()._decode(*snake_case_		,		**snake_case_							)
											SCREAMING_SNAKE_CASE			: List[Any]	     =text.replace(''' '''		,		''''''							).replace('''\u2582'''		,		''' '''							).replace('''\u2583'''		,		'''\n'''							)
											return text






