





'''simple docstring'''







def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      List[Any],      SCREAMING_SNAKE_CASE__   :      Tuple )			->						list[list[int]]:
						UpperCAmelCase_      :   Optional[Any]      =	[]
						UpperCAmelCase_      :   List[str]      =	len(__UpperCAmelCase )
						for i in range(__UpperCAmelCase ):
												UpperCAmelCase_      :   Union[str, Any]      =	[]
												for j in range(__UpperCAmelCase ):
																		UpperCAmelCase_      :   str      =	0
																		for k in range(__UpperCAmelCase ):
																								UpperCAmelCase_      :   Optional[int]      =	val + matrix_a[i][k] * matrix_b[k][j]
																		list_a.append(__UpperCAmelCase )
												matrix_c.append(__UpperCAmelCase )
						return matrix_c





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      Any )			->						list[list[int]]:
						return [[int(row == column ) for column in range(__UpperCAmelCase )] for row in range(__UpperCAmelCase )]





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






						if n <= 1:
												return n
						UpperCAmelCase_      :   str      =	identity(2 )
						UpperCAmelCase_      :   Dict      =	[[1, 1], [1, 0]]
						UpperCAmelCase_      :   Any      =	n - 1
						while n > 0:
												if n % 2 == 1:
																		UpperCAmelCase_      :   Optional[int]      =	multiply(__UpperCAmelCase,      __UpperCAmelCase )
												UpperCAmelCase_      :   Union[str, Any]      =	multiply(__UpperCAmelCase,      __UpperCAmelCase )
												UpperCAmelCase_      :   Optional[Any]      =	int(n / 2 )
						return res_matrix[0][0]





def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      int )			->						int:






						if n <= 1:
												return n
						UpperCAmelCase_      :   Dict      =	0
						UpperCAmelCase_      :   Union[str, Any]      =	1
						for _ in range(2,      n + 1 ):
												UpperCAmelCase_    ,							UpperCAmelCase_      :   Union[str, Any]      =	fiba, fiba + fiba
						return fiba





def 							lowerCamelCase_   (	)			->						None:






						for ordinal in "0th 1st 2nd 3rd 10th 100th 1000th".split():
												UpperCAmelCase_      :   Union[str, Any]      =	int(''''''.join(c for c in ordinal if c in '''0123456789''' ) )  # 1000th --> 1000
												print(
												    F"""{ordinal} fibonacci number using matrix exponentiation is """
												    F"""{nth_fibonacci_matrix(__UpperCAmelCase )} and using bruteforce is """
												    F"""{nth_fibonacci_bruteforce(__UpperCAmelCase )}\n""" )
						# from timeit import timeit
						# print(timeit("nth_fibonacci_matrix(1000000)",
						#              "from main import nth_fibonacci_matrix", number=5))
						# print(timeit("nth_fibonacci_bruteforce(1000000)",
						#              "from main import nth_fibonacci_bruteforce", number=5))
						# 2.3342058970001744
						# 57.256506615000035


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCamelCase_      			=  {
    "configuration_mobilenet_v1": [
        "MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileNetV1Config",
        "MobileNetV1OnnxConfig",
    ],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_      			=  ["MobileNetV1FeatureExtractor"]
							UpperCamelCase_      			=  ["MobileNetV1ImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_      			=  [
							    "MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "MobileNetV1ForImageClassification",
							    "MobileNetV1Model",
							    "MobileNetV1PreTrainedModel",
							    "load_tf_weights_in_mobilenet_v1",
							]


if TYPE_CHECKING:
							from .configuration_mobilenet_va import (
							    MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    MobileNetVaConfig,
							    MobileNetVaOnnxConfig,
							)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
														from .image_processing_mobilenet_va import MobileNetVaImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mobilenet_va import (
														    MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MobileNetVaForImageClassification,
														    MobileNetVaModel,
														    MobileNetVaPreTrainedModel,
														    load_tf_weights_in_mobilenet_va,
														)


else:
							import sys

							UpperCamelCase_      			=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





