




import timeit


class 							__SCREAMING_SNAKE_CASE				:

					def __init__(							self					,			__lowercase   ):







						'''simple docstring'''




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





					def __mul__(							self					,			__lowercase   ):







						'''simple docstring'''




						lowerCamelCase_				:						Union[str, 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    snake_case   (				A		,  A     )				->				Dict:




	'''simple docstring'''


	lowerCamelCase_				:						Dict				  =				Matrix([[1, 0], [0, 1]]     )
	while b > 0:
		if b & 1:
			matrix *= a
		a *= a
		b >>= 1
	return matrix






def    snake_case   (				A		,  A		,  A     )				->				Any:




	'''simple docstring'''


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






def    snake_case   (				A		,  A		,  A     )				->				Union[str, Any]:




	'''simple docstring'''


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

	lowerCamelCase_				:						Any				  =				fa
	lowerCamelCase_				:						List[str]				  =				fa
	n -= 2

	while n > 0:
		lowerCamelCase_  ,     lowerCamelCase_				:						Dict				  =				fn_a + fn_a, fn_a
		n -= 1

	return fn_a






def    snake_case   (				)				->				Tuple:




	'''simple docstring'''


	lowerCamelCase_				:						Any				  =				'\nfrom random import randint\nfrom __main__ import fibonacci_with_matrix_exponentiation\n'
	lowerCamelCase_				:						Union[str, Any]				  =				'fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)'
	lowerCamelCase_				:						Optional[Any]				  =				timeit.timeit(setup=A		,  stmt=A		,  number=100     )
	print('With matrix exponentiation the average execution time is '		,  exec_time / 100     )
	return exec_time






def    snake_case   (				)				->				Dict:




	'''simple docstring'''


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






def    snake_case   (				)				->				str:




	'''simple docstring'''


	matrix_exponentiation_time()
	simple_fibonacci_time()


if __name__ == "__main__":
							main()






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase__						=		{
    'configuration_sam': [
        'SAM_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SamConfig',
        'SamMaskDecoderConfig',
        'SamPromptEncoderConfig',
        'SamVisionConfig',
    ],
    'processing_sam': ['SamProcessor'],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		[
							    'SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'SamModel',
							    'SamPreTrainedModel',
							]
try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		[
							    'TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'TFSamModel',
							    'TFSamPreTrainedModel',
							]
try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		['SamImageProcessor']


if TYPE_CHECKING:
							from .configuration_sam import (
							    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    SamConfig,
							    SamMaskDecoderConfig,
							    SamPromptEncoderConfig,
							    SamVisionConfig,
							)
							from .processing_sam import SamProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_sam import SamImageProcessor

else:
							import sys

							UpperCamelCase__						=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
