


'''simple docstring'''






import copy
from collections import OrderedDict
from typing import Dict, Mapping

from packaging import version

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


a_   :      Optional[int]				    =      logging.get_logger(__name__)

a_   :      Any				    =      {
    "facebook/detr-resnet-50": "https://huggingface.co/facebook/detr-resnet-50/resolve/main/config.json",
    # See all DETR models at https://huggingface.co/models?filter=detr
}




class 	a       (       _SCREAMING_SNAKE_CASE    ):
 _lowerCAmelCase	   =		"""detr"""
 _lowerCAmelCase	   =		["""past_key_values"""]
 _lowerCAmelCase	   =		{
     """hidden_size""": """d_model""",
     """num_attention_heads""": """encoder_attention_heads""",
 }
 def __init__(	self ,			__magic_name__=True ,			__magic_name__=None ,			__magic_name__=3 ,			__magic_name__=1_00 ,			__magic_name__=6 ,			__magic_name__=20_48 ,			__magic_name__=8 ,			__magic_name__=6 ,			__magic_name__=20_48 ,			__magic_name__=8 ,			__magic_name__=0.0 ,			__magic_name__=0.0 ,			__magic_name__=True ,			__magic_name__="relu" ,			__magic_name__=2_56 ,			__magic_name__=0.1 ,			__magic_name__=0.0 ,			__magic_name__=0.0 ,			__magic_name__=0.0_2 ,			__magic_name__=1.0 ,			__magic_name__=False ,			__magic_name__="sine" ,			__magic_name__="resnet50" ,			__magic_name__=True ,			__magic_name__=False ,			__magic_name__=1 ,			__magic_name__=5 ,			__magic_name__=2 ,			__magic_name__=1 ,			__magic_name__=1 ,			__magic_name__=5 ,			__magic_name__=2 ,			__magic_name__=0.1 ,			**__magic_name__ ,			)   ->							Any:
      if backbone_config is not None and use_timm_backbone:
           raise ValueError('You can\'t specify both `backbone_config` and `use_timm_backbone`.'  )

      if not use_timm_backbone:
           if backbone_config is None:
                logger.info('`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'  )
                _a      =							CONFIG_MAPPING['resnet'](out_features=['stage4']  )
           elif isinstance(__magic_name__ ,			__magic_name__  ):
                _a      =							backbone_config.get('model_type'  )
                _a      =							CONFIG_MAPPING[backbone_model_type]
                _a      =							config_class.from_dict(__magic_name__  )
           # set timm attributes to None
           _a ,				_a ,				_a      =							None, None, None

      _a      =							use_timm_backbone
      _a      =							backbone_config
      _a      =							num_channels
      _a      =							num_queries
      _a      =							d_model
      _a      =							encoder_ffn_dim
      _a      =							encoder_layers
      _a      =							encoder_attention_heads
      _a      =							decoder_ffn_dim
      _a      =							decoder_layers
      _a      =							decoder_attention_heads
      _a      =							dropout
      _a      =							attention_dropout
      _a      =							activation_dropout
      _a      =							activation_function
      _a      =							init_std
      _a      =							init_xavier_std
      _a      =							encoder_layerdrop
      _a      =							decoder_layerdrop
      _a      =							encoder_layers
      _a      =							auxiliary_loss
      _a      =							position_embedding_type
      _a      =							backbone
      _a      =							use_pretrained_backbone
      _a      =							dilation
      # Hungarian matcher
      _a      =							class_cost
      _a      =							bbox_cost
      _a      =							giou_cost
      # Loss coefficients
      _a      =							mask_loss_coefficient
      _a      =							dice_loss_coefficient
      _a      =							bbox_loss_coefficient
      _a      =							giou_loss_coefficient
      _a      =							eos_coefficient
      super().__init__(is_encoder_decoder=__magic_name__ ,			**__magic_name__  )
 @property
 def 							__UpperCAmelCase						(	self  )   ->							int:
      return self.encoder_attention_heads
 @property
 def 							__UpperCAmelCase						(	self  )   ->							int:
      return self.d_model
 @classmethod
 def 							__UpperCAmelCase						(	cls ,			__magic_name__ ,			**__magic_name__  )   ->							Any:
      return cls(backbone_config=__magic_name__ ,			**__magic_name__  )




 def 							__UpperCAmelCase						(	self  )   ->							Dict[str, any]:
      _a      =							copy.deepcopy(self.__dict__  )
      if output["backbone_config"] is not None:
           _a      =							self.backbone_config.to_dict()
      _a      =							self.__class__.model_type
      return output





class 	a       (       _SCREAMING_SNAKE_CASE    ):
 _lowerCAmelCase	   =		version.parse("""1.11"""    )
 @property
 def 							__UpperCAmelCase						(	self  )   ->							Mapping[str, Mapping[int, str]]:
      return OrderedDict(
          [
              ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
              ('pixel_mask', {0: 'batch'}),
          ]  )
 @property
 def 							__UpperCAmelCase						(	self  )   ->							float:
      return 1e-5




 @property
 def 							__UpperCAmelCase						(	self  )   ->							int:
      return 12





'''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()

