
import colorsys

from PIL import Image  # type: ignore




def 							a		(				snake_case__:   float		,  snake_case__:   float		,  snake_case__:   int   ):


				'''simple docstring'''
				lowercase_	    =   x
				lowercase_	    =   y
				for step in range(snake_case__   ):  # noqa: B007
								lowercase_	    =   a * a - b * b + x
								lowercase_	    =   2 * a * b + y
								lowercase_	    =   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		(				snake_case__:   float   ):


				'''simple docstring'''
				if distance == 1:
								return (0, 0, 0)
				else:
								return (255, 255, 255)




def 							a		(				snake_case__:   float   ):


				'''simple docstring'''
				if distance == 1:
								return (0, 0, 0)
				else:
								return tuple(round(i * 255   ) for i in colorsys.hsv_to_rgb(snake_case__		,  1		,  1   )   )




def 							a		(				snake_case__:   int = 800		,  snake_case__:   int = 600		,  snake_case__:   float = -0.6		,  snake_case__:   float = 0		,  snake_case__:   float = 3.2		,  snake_case__:   int = 50		,  snake_case__:   bool = True		,  ):


				'''simple docstring'''
				lowercase_	    =   Image.new('''RGB'''		,  (image_width, image_height)   )
				lowercase_	    =   img.load()

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

												lowercase_	    =   get_distance(snake_case__		,  snake_case__		,  snake_case__   )

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

				return img


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						# colored version, full figure
						__a         =   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()











from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowerCAmelCase							:       List[str]					 =	{
    """configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase							:       str					 =	[
							    """GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """GPTBigCodeForSequenceClassification""",
							    """GPTBigCodeForTokenClassification""",
							    """GPTBigCodeForCausalLM""",
							    """GPTBigCodeModel""",
							    """GPTBigCodePreTrainedModel""",
							]

if TYPE_CHECKING:
							from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_gpt_bigcode import (
														    GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    GPTBigCodeForCausalLM,
														    GPTBigCodeForSequenceClassification,
														    GPTBigCodeForTokenClassification,
														    GPTBigCodeModel,
														    GPTBigCodePreTrainedModel,
														)


else:
							import sys

							lowerCAmelCase							:       List[str]					 =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



