






"""simple docstring"""

import logging

from transformers.configuration_utils import PretrainedConfig


lowercase    			=       logging.getLogger(__name__)

class 						A_							(      snake_case_  ):
				UpperCAmelCase__        =				'''masked_bert'''







				def __init__(							self							:						List[str]						,    __lowerCamelCase							:						List[str]=3_0_5_2_2						,    __lowerCamelCase							:						List[Any]=7_6_8						,    __lowerCamelCase							:						int=1_2						,    __lowerCamelCase							:						List[Any]=1_2						,    __lowerCamelCase							:						Dict=3_0_7_2						,    __lowerCamelCase							:						Union[str, Any]="gelu"						,    __lowerCamelCase							:						int=0.1						,    __lowerCamelCase							:						Tuple=0.1						,    __lowerCamelCase							:						Tuple=5_1_2						,    __lowerCamelCase							:						Optional[Any]=2						,    __lowerCamelCase							:						int=0.02						,    __lowerCamelCase							:						str=1e-12						,    __lowerCamelCase							:						Any=0						,    __lowerCamelCase							:						List[str]="topK"						,    __lowerCamelCase							:						List[Any]="constant"						,    __lowerCamelCase							:						int=0.0						,    **__lowerCamelCase							:						List[str]						,    )				->					Dict:
										super().__init__(pad_token_id=__lowerCamelCase						,    **__lowerCamelCase	)

										__magic_name__            =     vocab_size
										__magic_name__            =     hidden_size
										__magic_name__            =     num_hidden_layers
										__magic_name__            =     num_attention_heads
										__magic_name__            =     hidden_act
										__magic_name__            =     intermediate_size
										__magic_name__            =     hidden_dropout_prob
										__magic_name__            =     attention_probs_dropout_prob
										__magic_name__            =     max_position_embeddings
										__magic_name__            =     type_vocab_size
										__magic_name__            =     initializer_range
										__magic_name__            =     layer_norm_eps
										__magic_name__            =     pruning_method
										__magic_name__            =     mask_init
										__magic_name__            =     mask_scale











"""simple docstring"""

import colorsys

from PIL import Image  # type: ignore






def _lowerCAmelCase	(  __lowerCamelCase:float ,						__lowerCamelCase:float ,						__lowerCamelCase:int   ):

						'''simple docstring'''






						__magic_name__            =     x
						__magic_name__            =     y
						for step in range(__lowerCamelCase   ):  # noqa: B007
												__magic_name__            =     a * a - b * b + x
												__magic_name__            =     2 * a * b + y
												__magic_name__            =     a_new

												# divergence happens for all complex number with an absolute value
												# greater than 4
												if a * a + b * b > 4:
																		break
						return step / (max_step - 1)






def _lowerCAmelCase	(  __lowerCamelCase:float   ):

						'''simple docstring'''






						if distance == 1:
												return (0, 0, 0)
						else:
												return (2_5_5, 2_5_5, 2_5_5)






def _lowerCAmelCase	(  __lowerCamelCase:float   ):

						'''simple docstring'''






						if distance == 1:
												return (0, 0, 0)
						else:
												return tuple(round(i * 2_5_5   ) for i in colorsys.hsv_to_rgb(__lowerCamelCase ,						1 ,						1   )   )






def _lowerCAmelCase	(  __lowerCamelCase:int = 8_0_0 ,						__lowerCamelCase:int = 6_0_0 ,						__lowerCamelCase:float = -0.6 ,						__lowerCamelCase:float = 0 ,						__lowerCamelCase:float = 3.2 ,						__lowerCamelCase:int = 5_0 ,						__lowerCamelCase:bool = True ,						):

						'''simple docstring'''






						__magic_name__            =     Image.new("RGB" ,						(image_width, image_height)   )
						__magic_name__            =     img.load()

						# loop through the image-coordinates
						for image_x in range(__lowerCamelCase   ):
												for image_y in range(__lowerCamelCase   ):
																		# determine the figure-coordinates based on the image-coordinates
																		__magic_name__            =     figure_width / image_width * image_height
																		__magic_name__            =     figure_center_x + (image_x / image_width - 0.5) * figure_width
																		__magic_name__            =     figure_center_y + (image_y / image_height - 0.5) * figure_height

																		__magic_name__            =     get_distance(__lowerCamelCase ,						__lowerCamelCase ,						__lowerCamelCase   )

																		# color the corresponding pixel based on the selected coloring-function
																		if use_distance_color_coding:
																								__magic_name__            =     get_color_coded_rgb(__lowerCamelCase   )
																		else:
																								__magic_name__            =     get_black_and_white_rgb(__lowerCamelCase   )

						return img


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			# colored version, full figure
			lowercase    			=       get_image()

			# uncomment for colored version, different section, zoomed in
			# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
			# figure_width = 0.8)

			# uncomment for black and white version, full figure
			# img = get_image(use_distance_color_coding = False)

			# uncomment to save the image
			# img.save("mandelbrot.png")

			img.show()



