
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase					:    Dict           = logging.get_logger(__name__)

lowerCAmelCase					:    Optional[int]           = {
    'microsoft/swinv2-tiny-patch4-window8-256': (
        'https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'
    ),
}


class 			SCREAMING_SNAKE_CASE__      (     snake_case_):
				lowerCAmelCase_     			=							"""swinv2"""

				lowerCAmelCase_     			=							{
				    """num_attention_heads""": """num_heads""",
				    """num_hidden_layers""": """num_layers""",
				}







				def __init__(       self						,				A_=224						,				A_=4						,				A_=3						,				A_=96						,				A_=[2, 2, 6, 2]						,				A_=[3, 6, 12, 24]						,				A_=7						,				A_=4.0						,				A_=True						,				A_=0.0						,				A_=0.0						,				A_=0.1						,				A_="gelu"						,				A_=False						,				A_=0.02						,				A_=1e-5						,				A_=32						,				**A_						,				)->		List[Any]:







											'''simple docstring'''






											super().__init__(**A_     )

											UpperCamelCase   			=     image_size
											UpperCamelCase   			=     patch_size
											UpperCamelCase   			=     num_channels
											UpperCamelCase   			=     embed_dim
											UpperCamelCase   			=     depths
											UpperCamelCase   			=     len(A_     )
											UpperCamelCase   			=     num_heads
											UpperCamelCase   			=     window_size
											UpperCamelCase   			=     mlp_ratio
											UpperCamelCase   			=     qkv_bias
											UpperCamelCase   			=     hidden_dropout_prob
											UpperCamelCase   			=     attention_probs_dropout_prob
											UpperCamelCase   			=     drop_path_rate
											UpperCamelCase   			=     hidden_act
											UpperCamelCase   			=     use_absolute_embeddings
											UpperCamelCase   			=     layer_norm_eps
											UpperCamelCase   			=     initializer_range
											UpperCamelCase   			=     encoder_stride
											# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
											# this indicates the channel dimension after the last stage of the model
											UpperCamelCase   			=     int(embed_dim * 2 ** (len(A_     ) - 1)     )
											UpperCamelCase   			=     (0, 0, 0, 0)






'''simple docstring'''
import colorsys

from PIL import Image  # type: ignore







def 		A_(     A						:		float		,     A						:		float		,     A						:		int):
							UpperCamelCase   			=     x
							UpperCamelCase   			=     y
							for step in range(A):  # noqa: B007
														UpperCamelCase   			=     a * a - b * b + x
														UpperCamelCase   			=     2 * a * b + y
														UpperCamelCase   			=     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 		A_(     A						:		float):
							if distance == 1:
														return (0, 0, 0)
							else:
														return (255, 255, 255)







def 		A_(     A						:		float):
							if distance == 1:
														return (0, 0, 0)
							else:
														return tuple(round(i * 255) for i in colorsys.hsv_to_rgb(A		,     1		,     1))







def 		A_(     A						:		int = 800		,     A						:		int = 600		,     A						:		float = -0.6		,     A						:		float = 0		,     A						:		float = 3.2		,     A						:		int = 50		,     A						:		bool = True		,     ):
							UpperCamelCase   			=     Image.new('RGB'		,     (image_width, image_height))
							UpperCamelCase   			=     img.load()

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

																					UpperCamelCase   			=     get_distance(A		,     A		,     A)

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

							return img


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						# colored version, full figure
						lowerCAmelCase					:    Any           = 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()




