




"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a_				:    Any										=     logging.get_logger(__name__)

a_				:    Dict										=     {
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}

class __lowercase(      __SCREAMING_SNAKE_CASE				):




					'''simple docstring'''


					__a						:						Union[str, Any]     		= 'roberta-prelayernorm'
					def __init__(    self						,	__a=50265						,	__a=768						,	__a=12						,	__a=12						,	__a=3072						,	__a="gelu"						,	__a=0.1						,	__a=0.1						,	__a=512						,	__a=2						,	__a=0.02						,	__a=1E-12						,	__a=1						,	__a=0						,	__a=2						,	__a="absolute"						,	__a=True						,	__a=None						,	**__a						,	):
								super().__init__(pad_token_id=__snake_case						,	bos_token_id=__snake_case						,	eos_token_id=__snake_case						,	**__snake_case     )

								__lowerCamelCase					:	Optional[int]	       =				vocab_size
								__lowerCamelCase					:	Dict	       =				hidden_size
								__lowerCamelCase					:	Tuple	       =				num_hidden_layers
								__lowerCamelCase					:	Optional[int]	       =				num_attention_heads
								__lowerCamelCase					:	Any	       =				hidden_act
								__lowerCamelCase					:	List[Any]	       =				intermediate_size
								__lowerCamelCase					:	Union[str, Any]	       =				hidden_dropout_prob
								__lowerCamelCase					:	str	       =				attention_probs_dropout_prob
								__lowerCamelCase					:	Tuple	       =				max_position_embeddings
								__lowerCamelCase					:	int	       =				type_vocab_size
								__lowerCamelCase					:	Optional[Any]	       =				initializer_range
								__lowerCamelCase					:	Union[str, Any]	       =				layer_norm_eps
								__lowerCamelCase					:	Dict	       =				position_embedding_type
								__lowerCamelCase					:	List[Any]	       =				use_cache
								__lowerCamelCase					:	Optional[int]	       =				classifier_dropout



class __lowercase(      __SCREAMING_SNAKE_CASE				):




					'''simple docstring'''


					@property
					def     snake_case_				(    self     ):
								if self.task == "multiple-choice":
											__lowerCamelCase					:	Optional[Any]	       =				{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
								else:
											__lowerCamelCase					:	List[str]	       =				{0: '''batch''', 1: '''sequence'''}
								return OrderedDict(
								    [
								        ('input_ids', dynamic_axis),
								        ('attention_mask', dynamic_axis),
								    ]     )









"""simple docstring"""
from cva import destroyAllWindows, imread, imshow, waitKey





def 						UpperCAmelCase				(			A__:    Tuple     )  ->     Union[str, Any]:
			# getting number of pixels in the image
			__lowerCamelCase       ,      __lowerCamelCase					:	Optional[Any]	       =				img.shape[0], img.shape[1]

			# converting each pixel's color to its negative
			for i in range(A__     ):
						for j in range(A__     ):
									__lowerCamelCase					:	Optional[Any]	       =				[255, 255, 255] - img[i][j]

			return img


if __name__ == "__main__":
					# read original image
					a_				:    Dict										=     imread('''image_data/lena.jpg''', 1)

					# convert to its negative
					a_				:    str										=     convert_to_negative(img)

					# show result image
					imshow('''negative of original image''', img)
					waitKey(0)
					destroyAllWindows()



