code: 
  
  
  
  
  """simple docstring"""
  
  import timeit
  class 			lowerCamelCase__    :
  
  
  			def __init__(     self				, SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					if isinstance(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):  # Initializes a matrix identical to the one provided.
  							snake_case		:						str								=				arg
  							snake_case		:						Tuple								=				len(SCREAMING_SNAKE_CASE							)
  					else:  # Initializes a square matrix of the given size and set values to zero.
  							snake_case		:						Any								=				arg
  							snake_case		:						Any								=				[[0 for _ in range(self.n							)] for _ in range(self.n							)]
  
  
  
  			def __mul__(     self				, SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						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   UpperCamelCase__     (		lowercase__  :     Tuple       ,     lowercase__  :     int   ):
  		snake_case		:						Union[str, Any]								=				Matrix([[1, 0], [0, 1]]   )
  		while b > 0:
  				if b & 1:
  						matrix *= a
  				a *= a
  				b >>= 1
  		return matrix
  
  
  
  def   UpperCamelCase__     (		lowercase__  :     List[str]       ,     lowercase__  :     int       ,     lowercase__  :     Any   ):
  		# Trivial Cases
  		if n == 1:
  				return fa
  		elif n == 2:
  				return fa
  		snake_case		:						int								=				Matrix([[1, 1], [1, 0]]   )
  		snake_case		:						int								=				modular_exponentiation(lowercase__       ,     n - 2   )
  		return fa * matrix.t[0][0] + fa * matrix.t[0][1]
  
  
  
  def   UpperCamelCase__     (		lowercase__  :     str       ,     lowercase__  :     Tuple       ,     lowercase__  :     Any   ):
  		# Trivial Cases
  		if n == 1:
  				return fa
  		elif n == 2:
  				return fa
  
  		snake_case		:						str								=				fa
  		snake_case		:						Dict								=				fa
  		n -= 2
  
  		while n > 0:
  				snake_case			,				snake_case		:						Tuple								=				fn_a + fn_a, fn_a
  				n -= 1
  
  		return fn_a
  
  
  
  def   UpperCamelCase__     (		):
  		snake_case		:						List[str]								=				"\nfrom random import randint\nfrom __main__ import fibonacci_with_matrix_exponentiation\n"
  		snake_case		:						Union[str, Any]								=				"fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"
  		snake_case		:						Optional[int]								=				timeit.timeit(setup=lowercase__       ,     stmt=lowercase__       ,     number=100   )
  		print("With matrix exponentiation the average execution time is "       ,     exec_time / 100   )
  		return exec_time
  
  
  
  def   UpperCamelCase__     (		):
  		snake_case		:						Union[str, Any]								=				"\nfrom random import randint\nfrom __main__ import simple_fibonacci\n"
  		snake_case		:						int								=				"simple_fibonacci(randint(1,70000), 1, 1)"
  		snake_case		:						Union[str, Any]								=				timeit.timeit(setup=lowercase__       ,     stmt=lowercase__       ,     number=100   )
  		print(
  		    "Without matrix exponentiation the average execution time is "       ,     exec_time / 100   )
  		return exec_time
  
  
  
  def   UpperCamelCase__     (		):
  		matrix_exponentiation_time()
  		simple_fibonacci_time()
  
  
  if __name__ == "__main__":
  							main()
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  import unittest
  
  import numpy as np
  import PIL
  import torch
  
  from diffusers.image_processor import VaeImageProcessor
  class 			lowerCamelCase__    (  unittest.TestCase			):
  
  
  			@property
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						int								=				1
  					snake_case		:						Dict								=				3
  					snake_case		:						int								=				8
  					snake_case		:						int								=				8
  
  					snake_case		:						List[str]								=				torch.rand((batch_size, num_channels, height, width)							)
  
  					return sample
  
  
  			def 							lowerCamelCase_				(     self				, SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					if isinstance(image[0]				, PIL.Image.Image							):
  							return np.stack([np.array(SCREAMING_SNAKE_CASE							) for i in image]				, axis=0							)
  					elif isinstance(SCREAMING_SNAKE_CASE				, torch.Tensor							):
  							return image.cpu().numpy().transpose(0				, 2				, 3				, 1							)
  					return image
  
  
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						Optional[int]								=				VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE				, do_normalize=SCREAMING_SNAKE_CASE							)
  
  					snake_case		:						Any								=				self.dummy_sample
  					snake_case		:						Optional[Any]								=				self.to_np(SCREAMING_SNAKE_CASE							)
  
  					for output_type in ["pt", "np", "pil"]:
  							snake_case		:						Optional[Any]								=				image_processor.postprocess(
  							    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type=SCREAMING_SNAKE_CASE				, )
  							snake_case		:						Optional[Any]								=				self.to_np(SCREAMING_SNAKE_CASE							)
  							snake_case		:						Any								=				(input_np * 255).round() if output_type == "pil" else input_np
  							assert (
  							    np.abs(in_np - out_np							).max() < 1E-6
  							), F'''decoded output does not match input for output_type {output_type}'''
  
  
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						Dict								=				VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE				, do_normalize=SCREAMING_SNAKE_CASE							)
  					snake_case		:						Tuple								=				self.dummy_sample.cpu().numpy().transpose(0				, 2				, 3				, 1							)
  
  					for output_type in ["pt", "np", "pil"]:
  							snake_case		:						Dict								=				image_processor.postprocess(image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type=SCREAMING_SNAKE_CASE							)
  
  							snake_case		:						Union[str, Any]								=				self.to_np(SCREAMING_SNAKE_CASE							)
  							snake_case		:						Tuple								=				(input_np * 255).round() if output_type == "pil" else input_np
  							assert (
  							    np.abs(in_np - out_np							).max() < 1E-6
  							), F'''decoded output does not match input for output_type {output_type}'''
  
  
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						Optional[Any]								=				VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE				, do_normalize=SCREAMING_SNAKE_CASE							)
  
  					snake_case		:						str								=				self.dummy_sample.cpu().numpy().transpose(0				, 2				, 3				, 1							)
  					snake_case		:						int								=				image_processor.numpy_to_pil(SCREAMING_SNAKE_CASE							)
  
  					for output_type in ["pt", "np", "pil"]:
  							snake_case		:						Dict								=				image_processor.postprocess(image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type=SCREAMING_SNAKE_CASE							)
  							for i, o in zip(SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):
  									snake_case		:						Dict								=				np.array(SCREAMING_SNAKE_CASE							)
  									snake_case		:						Tuple								=				self.to_np(SCREAMING_SNAKE_CASE							) if output_type == "pil" else (self.to_np(SCREAMING_SNAKE_CASE							) * 255).round()
  									assert (
  									    np.abs(in_np - out_np							).max() < 1E-6
  									), F'''decoded output does not match input for output_type {output_type}'''
  
  
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						Tuple								=				VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE				, do_normalize=SCREAMING_SNAKE_CASE							)
  
  					snake_case		:						List[str]								=				self.dummy_sample
  					snake_case		:						Optional[int]								=				input_pt_ad.squeeze(0							)
  
  					snake_case		:						Any								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  					snake_case		:						Union[str, Any]								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  
  					snake_case		:						Union[str, Any]								=				self.to_np(self.dummy_sample							)
  					snake_case		:						Tuple								=				input_np_ad.squeeze(0							)
  
  					snake_case		:						str								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  					snake_case		:						Union[str, Any]								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  
  					assert np.abs(out_pt_ad - out_pt_ad							).max() < 1E-6
  					assert np.abs(out_np_ad - out_np_ad							).max() < 1E-6
  
  
  
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						Optional[Any]								=				VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE				, do_normalize=SCREAMING_SNAKE_CASE							)
  
  					snake_case		:						Union[str, Any]								=				self.dummy_sample
  					snake_case		:						List[str]								=				list(SCREAMING_SNAKE_CASE							)
  
  					snake_case		:						str								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  
  					snake_case		:						Any								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  
  					snake_case		:						Dict								=				self.to_np(self.dummy_sample							)
  					list(SCREAMING_SNAKE_CASE							)
  
  					snake_case		:						str								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  
  					snake_case		:						Union[str, Any]								=				image_processor.postprocess(
  					    image_processor.preprocess(SCREAMING_SNAKE_CASE							)				, output_type="np"				, )
  
  					assert np.abs(out_pt_ad - out_pt_list							).max() < 1E-6
  					assert np.abs(out_np_ad - out_np_list							).max() < 1E-6
  
  