



def        a( A			:       list[list[int]]					,	A			:       list[list[int]]			)						->			Union[str, Any]:
					"""simple docstring"""





					a   	=  []
					a   	=  len(UpperCAmelCase__			)
					for i in range(UpperCAmelCase__			):
										a   	=  []
										for j in range(UpperCAmelCase__			):
															a   	=  0
															for k in range(UpperCAmelCase__			):
																				a   	=  val + matrix_a[i][k] * matrix_b[k][j]
															list_a.append(UpperCAmelCase__			)
										matrix_c.append(UpperCAmelCase__			)
					return matrix_c






def        a( A			:       int			)						->			List[str]:
					"""simple docstring"""





					return [[int(row == column			) for column in range(UpperCAmelCase__			)] for row in range(UpperCAmelCase__			)]






def        a( A			:       int			)						->			int:
					"""simple docstring"""





					if n <= 1:
										return n
					a   	=  identity(2			)
					a   	=  [[1, 1], [1, 0]]
					a   	=  n - 1
					while n > 0:
										if n % 2 == 1:
															a   	=  multiply(UpperCAmelCase__					,	UpperCAmelCase__			)
										a   	=  multiply(UpperCAmelCase__					,	UpperCAmelCase__			)
										a   	=  int(n / 2			)
					return res_matrix[0][0]






def        a( A			:       int			)						->			Any:
					"""simple docstring"""





					if n <= 1:
										return n
					a   	=  0
					a   	=  1
					for _ in range(2					,	n + 1			):
										a	,							a   	=  fiba, fiba + fiba
					return fiba






def        a( )						->			str:
					"""simple docstring"""





					for ordinal in "0th 1st 2nd 3rd 10th 100th 1000th".split():
										a   	=  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


A_		:  Any										=  {
    '''configuration_videomae''': ['''VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VideoMAEConfig'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  List[Any]										=  [
         '''VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''VideoMAEForPreTraining''',
         '''VideoMAEModel''',
         '''VideoMAEPreTrainedModel''',
         '''VideoMAEForVideoClassification''',
     ]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  str										=  ['''VideoMAEFeatureExtractor''']
     A_		:  Union[str, Any]										=  ['''VideoMAEImageProcessor''']

if TYPE_CHECKING:
     from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_videomae import (
              VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
              VideoMAEForPreTraining,
              VideoMAEForVideoClassification,
              VideoMAEModel,
              VideoMAEPreTrainedModel,
          )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_videomae import VideoMAEFeatureExtractor
          from .image_processing_videomae import VideoMAEImageProcessor

else:
     import sys

     A_		:  Dict										=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

