
"""simple docstring"""


import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey







class 						lowerCamelCase__   :





			'''simple docstring'''



			def __init__(				self	,	__UpperCAmelCase	,	__UpperCAmelCase    )					->	int:
				_lowerCAmelCase								=0
				# max greyscale value for #FFFFFF
				_lowerCAmelCase								=int(self.get_greyscale(2_55	,	2_55	,	2_55    )    )

				if not self.min_threshold < threshold < self.max_threshold:
					_lowerCAmelCase								=f'''Factor value should be from 0 to {self.max_threshold}'''
					raise ValueError(__UpperCAmelCase    )

				_lowerCAmelCase								=input_img
				_lowerCAmelCase								=threshold
				_lowerCAmelCase		,				_lowerCAmelCase								=self.input_img.shape[1], self.input_img.shape[0]

				# error table size (+4 columns and +1 row) greater than input image because of
				# lack of if statements
				_lowerCAmelCase								=[
				    [0 for _ in range(self.height + 4    )] for __ in range(self.width + 1    )
				]
				_lowerCAmelCase								=np.ones((self.width, self.height, 3)	,	np.uinta    ) * 2_55



			@classmethod
			def    _lowerCAmelCase						(				cls	,	__UpperCAmelCase	,	__UpperCAmelCase	,	__UpperCAmelCase    )					->	float:
				return 0.1_1_4 * blue + 0.5_8_7 * green + 0.2_1_2_6 * red



			def    _lowerCAmelCase						(				self    )					->	None:
				for y in range(self.height    ):
					for x in range(self.width    ):
						_lowerCAmelCase								=int(self.get_greyscale(*self.input_img[y][x]    )    )
						if self.threshold > greyscale + self.error_table[y][x]:
							_lowerCAmelCase								=(0, 0, 0)
							_lowerCAmelCase								=greyscale + self.error_table[x][y]
						else:
							_lowerCAmelCase								=(2_55, 2_55, 2_55)
							_lowerCAmelCase								=greyscale + self.error_table[x][y] - 2_55
						self.error_table[y][x + 1] += int(8 / 32 * current_error    )
						self.error_table[y][x + 2] += int(4 / 32 * current_error    )
						self.error_table[y + 1][x] += int(8 / 32 * current_error    )
						self.error_table[y + 1][x + 1] += int(4 / 32 * current_error    )
						self.error_table[y + 1][x + 2] += int(2 / 32 * current_error    )
						self.error_table[y + 1][x - 1] += int(4 / 32 * current_error    )
						self.error_table[y + 1][x - 2] += int(2 / 32 * current_error    )


if __name__ == "__main__":
			# create Burke's instances with original images in greyscale
			__A					=			[
			    Burkes(imread('image_data/lena.jpg', 1), threshold)
			    for threshold in (1, 126, 130, 140)
			]

			for burkes in burkes_instances:
						burkes.process()

			for burkes in burkes_instances:
						imshow(
						    F"""Original image with dithering threshold: {burkes.threshold}""",
						    burkes.output_img,
						)

			waitKey(0)
			destroyAllWindows()





"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A					=			logging.get_logger(__name__)

__A					=			{
    'uw-madison/nystromformer-512': 'https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}







class 						lowerCamelCase__   (   __magic_name__							):





			'''simple docstring'''
			lowerCamelCase       =						'''nystromformer'''



			def __init__(				self	,	__UpperCAmelCase=3_00_00	,	__UpperCAmelCase=7_68	,	__UpperCAmelCase=12	,	__UpperCAmelCase=12	,	__UpperCAmelCase=30_72	,	__UpperCAmelCase="gelu_new"	,	__UpperCAmelCase=0.1	,	__UpperCAmelCase=0.1	,	__UpperCAmelCase=5_10	,	__UpperCAmelCase=2	,	__UpperCAmelCase=64	,	__UpperCAmelCase=64	,	__UpperCAmelCase=65	,	__UpperCAmelCase=False	,	__UpperCAmelCase=0.0_2	,	__UpperCAmelCase=1e-5	,	__UpperCAmelCase=1	,	__UpperCAmelCase=0	,	__UpperCAmelCase=2	,	**__UpperCAmelCase	,	)					->	Union[str, Any]:
				_lowerCAmelCase								=vocab_size
				_lowerCAmelCase								=max_position_embeddings
				_lowerCAmelCase								=hidden_size
				_lowerCAmelCase								=num_hidden_layers
				_lowerCAmelCase								=num_attention_heads
				_lowerCAmelCase								=intermediate_size
				_lowerCAmelCase								=hidden_act
				_lowerCAmelCase								=hidden_dropout_prob
				_lowerCAmelCase								=attention_probs_dropout_prob
				_lowerCAmelCase								=initializer_range
				_lowerCAmelCase								=type_vocab_size
				_lowerCAmelCase								=segment_means_seq_len
				_lowerCAmelCase								=num_landmarks
				_lowerCAmelCase								=conv_kernel_size
				_lowerCAmelCase								=inv_coeff_init_option
				_lowerCAmelCase								=layer_norm_eps
				super().__init__(pad_token_id=__UpperCAmelCase	,	bos_token_id=__UpperCAmelCase	,	eos_token_id=__UpperCAmelCase	,	**__UpperCAmelCase    )



