import timeit






class     _SCREAMING_SNAKE_CASE       :



   '''simple docstring'''



   def __init__(  self   ,							_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

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







   def __mul__(  self   ,							_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

      __lowerCamelCase								=				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 			A__						(  lowercase_    :  Tuple			,   lowercase_    :  Any	)     ->       List[str]:
   __lowerCamelCase								=				Matrix([[1, 0], [0, 1]]	)
   while b > 0:
      if b & 1:
         matrix *= a
      a *= a
      b >>= 1
   return matrix



def 			A__						(  lowercase_    :  int			,   lowercase_    :  Optional[Any]			,   lowercase_    :  List[Any]	)     ->       str:
   # Trivial Cases
   if n == 1:
      return fa
   elif n == 2:
      return fa
   __lowerCamelCase								=				Matrix([[1, 1], [1, 0]]	)
   __lowerCamelCase								=				modular_exponentiation(lowercase_			,   n - 2	)
   return fa * matrix.t[0][0] + fa * matrix.t[0][1]



def 			A__						(  lowercase_    :  Optional[int]			,   lowercase_    :  Tuple			,   lowercase_    :  str	)     ->       str:
   # Trivial Cases
   if n == 1:
      return fa
   elif n == 2:
      return fa

   __lowerCamelCase								=				fa
   __lowerCamelCase								=				fa
   n -= 2

   while n > 0:
      __lowerCamelCase								=				fn_a + fn_a, fn_a
      n -= 1

   return fn_a



def 			A__						(  )     ->       List[Any]:
   __lowerCamelCase								=				'\nfrom random import randint\nfrom __main__ import fibonacci_with_matrix_exponentiation\n'
   __lowerCamelCase								=				'fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)'
   __lowerCamelCase								=				timeit.timeit(setup=lowercase_			,   stmt=lowercase_			,   number=100	)
   print('With matrix exponentiation the average execution time is '			,   exec_time / 100	)
   return exec_time



def 			A__						(  )     ->       str:
   __lowerCamelCase								=				'\nfrom random import randint\nfrom __main__ import simple_fibonacci\n'
   __lowerCamelCase								=				'simple_fibonacci(randint(1,70000), 1, 1)'
   __lowerCamelCase								=				timeit.timeit(setup=lowercase_			,   stmt=lowercase_			,   number=100	)
   print(
       'Without matrix exponentiation the average execution time is '			,   exec_time / 100	)
   return exec_time



def 			A__						(  )     ->       Tuple:
   matrix_exponentiation_time()
   simple_fibonacci_time()


if __name__ == "__main__":
     main()







"""simple docstring"""







from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE  :		List[Any]        =      {
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE  :		Optional[Any]        =      ['''DeformableDetrFeatureExtractor''']
     _SCREAMING_SNAKE_CASE  :		List[str]        =      ['''DeformableDetrImageProcessor''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE  :		Union[str, Any]        =      [
         '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''DeformableDetrForObjectDetection''',
         '''DeformableDetrModel''',
         '''DeformableDetrPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
          from .image_processing_deformable_detr import DeformableDetrImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_deformable_detr import (
              DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
              DeformableDetrForObjectDetection,
              DeformableDetrModel,
              DeformableDetrPreTrainedModel,
          )

else:
     import sys

     _SCREAMING_SNAKE_CASE  :		Tuple        =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






