


'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


a_   :      Dict				    =      logging.get_logger(__name__)

a_   :      List[str]				    =      {
    "google/bit-50": "https://huggingface.co/google/bit-50/resolve/main/config.json",
}




class 	a       (       _SCREAMING_SNAKE_CASE					,			_SCREAMING_SNAKE_CASE    ):
 _lowerCAmelCase	   =		"""bit"""
 _lowerCAmelCase	   =		["""preactivation""", """bottleneck"""]
 _lowerCAmelCase	   =		["""SAME""", """VALID"""]
 def __init__(	self ,			__magic_name__=3 ,			__magic_name__=64 ,			__magic_name__=[2_56, 5_12, 10_24, 20_48] ,			__magic_name__=[3, 4, 6, 3] ,			__magic_name__="preactivation" ,			__magic_name__="relu" ,			__magic_name__=None ,			__magic_name__=32 ,			__magic_name__=0.0 ,			__magic_name__=False ,			__magic_name__=32 ,			__magic_name__=1 ,			__magic_name__=None ,			__magic_name__=None ,			**__magic_name__ ,			)   ->							Dict:
      super().__init__(**__magic_name__  )
      if layer_type not in self.layer_types:
           raise ValueError(f'layer_type={layer_type} is not one of {",".join(self.layer_types  )}'  )
      if global_padding is not None:
           if global_padding.upper() in self.supported_padding:
                _a      =							global_padding.upper()
           else:
                raise ValueError(f'Padding strategy {global_padding} not supported'  )
      _a      =							num_channels
      _a      =							embedding_size
      _a      =							hidden_sizes
      _a      =							depths
      _a      =							layer_type
      _a      =							hidden_act
      _a      =							global_padding
      _a      =							num_groups
      _a      =							drop_path_rate
      _a      =							embedding_dynamic_padding
      _a      =							output_stride
      _a      =							width_factor

      _a      =							['stem'] + [f'stage{idx}' for idx in range(1 ,			len(__magic_name__  ) + 1  )]
      _a ,				_a      =							get_aligned_output_features_output_indices(
          out_features=__magic_name__ ,			out_indices=__magic_name__ ,			stage_names=self.stage_names  )





'''simple docstring'''






import colorsys

from PIL import Image  # type: ignore






def 		_A			(lowerCAmelCase__					:float			,  lowerCAmelCase__					:float			,  lowerCAmelCase__					:int						)				->					float:




     '''simple docstring'''



     _a      =							x
     _a      =							y
     for step in range(lowerCAmelCase__						):  # noqa: B007
          _a      =							a * a - b * b + x
          _a      =							2 * a * b + y
          _a      =							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			(lowerCAmelCase__					:float						)				->					tuple:




     '''simple docstring'''



     if distance == 1:
          return (0, 0, 0)
     else:
          return (2_55, 2_55, 2_55)






def 		_A			(lowerCAmelCase__					:float						)				->					tuple:




     '''simple docstring'''



     if distance == 1:
          return (0, 0, 0)
     else:
          return tuple(round(i * 2_55						) for i in colorsys.hsv_to_rgb(lowerCAmelCase__			,  1			,  1						)						)






def 		_A			(lowerCAmelCase__					:int = 8_00			,  lowerCAmelCase__					:int = 6_00			,  lowerCAmelCase__					:float = -0.6			,  lowerCAmelCase__					:float = 0			,  lowerCAmelCase__					:float = 3.2			,  lowerCAmelCase__					:int = 50			,  lowerCAmelCase__					:bool = True			,  )				->					Image.Image:




     '''simple docstring'''



     _a      =							Image.new('RGB'			,  (image_width, image_height)						)
     _a      =							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
               _a      =							figure_width / image_width * image_height
               _a      =							figure_center_x + (image_x / image_width - 0.5) * figure_width
               _a      =							figure_center_y + (image_y / image_height - 0.5) * figure_height

               _a      =							get_distance(lowerCAmelCase__			,  lowerCAmelCase__			,  lowerCAmelCase__						)

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

     return img


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 # colored version, full figure
 a_   :      Optional[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()

