


"""simple docstring"""



from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros






def 					lowerCamelCase    (a_  :Any , a_  :List[Any])   ->							int:
       lowercase						:Optional[Any]											= image.shape
       lowercase						:Tuple											= cols - block_size[1] + 1
       lowercase						:Optional[Any]											= rows - block_size[0] + 1
       lowercase						:Optional[Any]											= zeros((dst_height * dst_width, block_size[1] * block_size[0]))
       lowercase						:Tuple											= 0
       for i in range(0 , a_):
              for j in range(0 , a_):
                     lowercase						:int											= ravel(image[i : i + block_size[0], j : j + block_size[1]])
                     lowercase						:str											= window
                     row += 1

       return image_array






def 					lowerCamelCase    (a_  :List[str] , a_  :Optional[Any])   ->							Tuple:
       lowercase						:int											= image.shape[0], image.shape[1]
       lowercase						:Any											= filter_kernel.shape[0]
       lowercase						:Tuple											= k_size // 2
       # Pads image with the edge values of array.
       lowercase						:List[Any]											= pad(a_ , a_ , mode='''edge''')

       # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
       lowercase						:Optional[Any]											= imacol(a_ , (k_size, k_size))

       #  turn the kernel into shape(k*k, 1)
       lowercase						:Dict											= ravel(a_)
       # reshape and get the dst image
       lowercase						:int											= dot(a_ , a_).reshape(a_ , a_)
       return dst


if __name__ == "__main__":
 # read original image
 UpperCAmelCase											=	imread(R'''../image_data/lena.jpg''')
 # turn image in gray scale value
 UpperCAmelCase											=	cvtColor(img, COLOR_BGR2GRAY)
 # Laplace operator
 UpperCAmelCase											=	array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
 UpperCAmelCase											=	img_convolve(gray, Laplace_kernel).astype(uinta)
 imshow('''Laplacian''', out)
 waitKey(0)







import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


UpperCamelCase__              =						1_0_0_0_0_0_0_0_0_0_0_0
UpperCamelCase__              =						1_0_0_0_0

UpperCamelCase__       , UpperCamelCase__              =						os.path.split(__file__)
UpperCamelCase__              =						os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))






def 					snake_case					(							A						,   A			)							->							datasets.Dataset:




	'''simple docstring'''


	lowerCamelCase_							:		int							   =							pa.Table.from_pydict({'col': [0] * chunk_size}			)
	lowerCamelCase_							:		List[str]							   =							pa.concat_tables([table] * (num_examples // chunk_size)			)
	return datasets.Dataset(A						,   fingerprint='table_100B'			)


@dataclass
class 				__SCREAMING_SNAKE_CASE							:
					_lowerCamelCase		  = 42
					_lowerCamelCase		  = 42
					_lowerCamelCase		  = 42
					_lowerCamelCase		  = 42

					def 	lowercase_							(				self					):







						'''simple docstring'''




						lowerCamelCase_							:		Optional[Any]							   =							np.random.default_rng(self.seed					)
						lowerCamelCase_							:		Any							   =							rng.integers(low=self.low ,       high=self.high ,       size=self.size					).tolist()

					def __iter__(				self					):







						'''simple docstring'''




						return iter(self._sampled_values					)





					def __len__(				self					):







						'''simple docstring'''




						return self.size






@get_duration
def 					snake_case					(							A			)							->							Optional[Any]:




	'''simple docstring'''


	lowerCamelCase_							:		Union[str, Any]							   =							dataset[0]






@get_duration
def 					snake_case					(							A			)							->							Any:




	'''simple docstring'''


	lowerCamelCase_							:		List[Any]							   =							dataset[-1]






@get_duration
def 					snake_case					(							A			)							->							Optional[Any]:




	'''simple docstring'''


	lowerCamelCase_							:		Tuple							   =							dataset[range(len(A			) // 2						,   len(A			) // 2 + 1024			)]






@get_duration
def 					snake_case					(							A			)							->							str:




	'''simple docstring'''


	lowerCamelCase_							:		List[str]							   =							dataset[RandIter(0						,   len(A			)						,   1024						,   seed=42			)]






def 					snake_case					(							)							->							List[Any]:




	'''simple docstring'''


	lowerCamelCase_							:		Tuple							   =							{'num examples': SPEED_TEST_N_EXAMPLES}
	lowerCamelCase_							:		Optional[int]							   =							(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
	print('generating dataset'			)
	lowerCamelCase_							:		List[Any]							   =							generate_100B_dataset(num_examples=A						,   chunk_size=A			)
	print('Functions'			)
	for func in functions:
		print(func.__name__			)
		lowerCamelCase_							:		str							   =							func(A			)

	with open(A						,   'wb'			) as f:
		f.write(json.dumps(A			).encode('utf-8'			)			)


if __name__ == "__main__":  # useful to run the profiler
							benchmark_table_100B()
