




'''simple docstring'''







import timeit


class    __a :

							def __init__(							self							:       Optional[Any]    ,       __magic_name__							:       Tuple				)   ->    List[str]:







													"""simple docstring"""






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



							def __mul__(							self							:       List[Any]    ,       __magic_name__							:       int				)   ->    List[Any]:







													"""simple docstring"""
													UpperCAmelCase_     : 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_ (					SCREAMING_SNAKE_CASE__ :     List[str],     SCREAMING_SNAKE_CASE__ :     int				)	->		Optional[int]:
						UpperCAmelCase_     : str         =					Matrix([[1, 0], [0, 1]]				)
						while b > 0:
												if b & 1:
																		matrix *= a
												a *= a
												b >>= 1
						return matrix





def     lowerCamelCase_ (					SCREAMING_SNAKE_CASE__ :     List[Any],     SCREAMING_SNAKE_CASE__ :     Optional[int],     SCREAMING_SNAKE_CASE__ :     str				)	->		List[Any]:

						if n == 1:
												return fa
						elif n == 2:
												return fa
						UpperCAmelCase_     : List[str]         =					Matrix([[1, 1], [1, 0]]				)
						UpperCAmelCase_     : str         =					modular_exponentiation(SCREAMING_SNAKE_CASE__,     n - 2				)
						return fa * matrix.t[0][0] + fa * matrix.t[0][1]





def     lowerCamelCase_ (					SCREAMING_SNAKE_CASE__ :     Union[str, Any],     SCREAMING_SNAKE_CASE__ :     int,     SCREAMING_SNAKE_CASE__ :     Dict				)	->		str:

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

						UpperCAmelCase_     : int         =					fa
						UpperCAmelCase_     : Union[str, Any]         =					fa
						n -= 2

						while n > 0:
												UpperCAmelCase_  ,    UpperCAmelCase_     : str         =					fn_a + fn_a, fn_a
												n -= 1

						return fn_a





def     lowerCamelCase_ (					)	->		List[str]:
						UpperCAmelCase_     : List[Any]         =					'''
from random import randint
from __main__ import fibonacci_with_matrix_exponentiation
'''
						UpperCAmelCase_     : int         =					'''fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)'''
						UpperCAmelCase_     : Optional[int]         =					timeit.timeit(setup=SCREAMING_SNAKE_CASE__,     stmt=SCREAMING_SNAKE_CASE__,     number=100				)
						print('''With matrix exponentiation the average execution time is ''',     exec_time / 100				)
						return exec_time





def     lowerCamelCase_ (					)	->		Any:
						UpperCAmelCase_     : Tuple         =					'''
from random import randint
from __main__ import simple_fibonacci
'''
						UpperCAmelCase_     : Any         =					'''simple_fibonacci(randint(1,70000), 1, 1)'''
						UpperCAmelCase_     : Optional[Any]         =					timeit.timeit(setup=SCREAMING_SNAKE_CASE__,     stmt=SCREAMING_SNAKE_CASE__,     number=100				)
						print(
						    '''Without matrix exponentiation the average execution time is ''',     exec_time / 100				)
						return exec_time





def     lowerCamelCase_ (					)	->		List[str]:
						matrix_exponentiation_time()
						simple_fibonacci_time()


if __name__ == "__main__":
					main()












'''simple docstring'''







from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest


@require_tokenizers
class    __a (lowerCamelCase       ):
							__a   :				Any       =    SqueezeBertTokenizer
							__a   :				Dict       =    SqueezeBertTokenizerFast
							__a   :				Any       =    True

							def       UpperCAmelCase__		(							self							:       Union[str, Any]    ,       **__magic_name__							:       Dict				)   ->    int:







													"""simple docstring"""
													return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname    ,       **__magic_name__				)



							@slow
							def       UpperCAmelCase__		(							self							:       Union[str, Any]				)   ->    int:







													"""simple docstring"""
													UpperCAmelCase_     : List[str]         =					SqueezeBertTokenizer.from_pretrained('''squeezebert/squeezebert-mnli-headless'''				)

													UpperCAmelCase_     : Any         =					tokenizer.encode('''sequence builders'''    ,       add_special_tokens=__magic_name__				)
													UpperCAmelCase_     : Optional[Any]         =					tokenizer.encode('''multi-sequence build'''    ,       add_special_tokens=__magic_name__				)

													UpperCAmelCase_     : List[Any]         =					tokenizer.build_inputs_with_special_tokens(__magic_name__				)
													UpperCAmelCase_     : Any         =					tokenizer.build_inputs_with_special_tokens(__magic_name__    ,       __magic_name__				)

													assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
													assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
													    tokenizer.sep_token_id
													]





