from math import pi, sqrt, tan







def       A__   (						snake_case_			:		float   ):
 if side_length < 0:
  raise ValueError('''surface_area_cube() only accepts non-negative values'''   )
 return 6 * side_length**2







def       A__   (						snake_case_			:		float							,					snake_case_			:		float							,					snake_case_			:		float   ):
 if length < 0 or breadth < 0 or height < 0:
  raise ValueError('''surface_area_cuboid() only accepts non-negative values'''   )
 return 2 * ((length * breadth) + (breadth * height) + (length * height))







def       A__   (						snake_case_			:		float   ):
 if radius < 0:
  raise ValueError('''surface_area_sphere() only accepts non-negative values'''   )
 return 4 * pi * radius**2







def       A__   (						snake_case_			:		float   ):
 if radius < 0:
  raise ValueError('''surface_area_hemisphere() only accepts non-negative values'''   )
 return 3 * pi * radius**2







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if radius < 0 or height < 0:
  raise ValueError('''surface_area_cone() only accepts non-negative values'''   )
 return pi * radius * (radius + (height**2 + radius**2) ** 0.5)







def       A__   (						snake_case_			:		float							,					snake_case_			:		float							,					snake_case_			:		float   ):
 if radius_a < 0 or radius_a < 0 or height < 0:
  raise ValueError(
      '''surface_area_conical_frustum() only accepts non-negative values'''   )
 SCREAMING_SNAKE_CASE__: Optional[Any]=   (height**2 + (radius_a - radius_a) ** 2) ** 0.5
 return pi * ((slant_height * (radius_a + radius_a)) + radius_a**2 + radius_a**2)







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if radius < 0 or height < 0:
  raise ValueError('''surface_area_cylinder() only accepts non-negative values'''   )
 return 2 * pi * radius * (height + radius)







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if torus_radius < 0 or tube_radius < 0:
  raise ValueError('''surface_area_torus() only accepts non-negative values'''   )
 if torus_radius < tube_radius:
  raise ValueError(
      '''surface_area_torus() does not support spindle or self intersecting tori'''   )
 return 4 * pow(snake_case_							,					2   ) * torus_radius * tube_radius







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if length < 0 or width < 0:
  raise ValueError('''area_rectangle() only accepts non-negative values'''   )
 return length * width







def       A__   (						snake_case_			:		float   ):
 if side_length < 0:
  raise ValueError('''area_square() only accepts non-negative values'''   )
 return side_length**2







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if base < 0 or height < 0:
  raise ValueError('''area_triangle() only accepts non-negative values'''   )
 return (base * height) / 2







def       A__   (						snake_case_			:		float							,					snake_case_			:		float							,					snake_case_			:		float   ):
 if sidea < 0 or sidea < 0 or sidea < 0:
  raise ValueError('''area_triangle_three_sides() only accepts non-negative values'''   )
 elif sidea + sidea < sidea or sidea + sidea < sidea or sidea + sidea < sidea:
  raise ValueError('''Given three sides do not form a triangle'''   )
 SCREAMING_SNAKE_CASE__: Dict=   (sidea + sidea + sidea) / 2
 SCREAMING_SNAKE_CASE__: Dict=   sqrt(
     semi_perimeter
     * (semi_perimeter - sidea)
     * (semi_perimeter - sidea)
     * (semi_perimeter - sidea)   )
 return area







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if base < 0 or height < 0:
  raise ValueError('''area_parallelogram() only accepts non-negative values'''   )
 return base * height







def       A__   (						snake_case_			:		float							,					snake_case_			:		float							,					snake_case_			:		float   ):
 if basea < 0 or basea < 0 or height < 0:
  raise ValueError('''area_trapezium() only accepts non-negative values'''   )
 return 1 / 2 * (basea + basea) * height







def       A__   (						snake_case_			:		float   ):
 if radius < 0:
  raise ValueError('''area_circle() only accepts non-negative values'''   )
 return pi * radius**2







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if radius_x < 0 or radius_y < 0:
  raise ValueError('''area_ellipse() only accepts non-negative values'''   )
 return pi * radius_x * radius_y







def       A__   (						snake_case_			:		float							,					snake_case_			:		float   ):
 if diagonal_a < 0 or diagonal_a < 0:
  raise ValueError('''area_rhombus() only accepts non-negative values'''   )
 return 1 / 2 * diagonal_a * diagonal_a







def       A__   (						snake_case_			:		int							,					snake_case_			:		float   ):
 if not isinstance(snake_case_							,					snake_case_   ) or sides < 3:
  raise ValueError(
      '''area_reg_polygon() only accepts integers greater than or \
equal to three as number of sides'''   )
 elif length < 0:
  raise ValueError(
      '''area_reg_polygon() only accepts non-negative values as \
length of a side'''   )
 return (sides * length**2) / (4 * tan(pi / sides   ))
 return (sides * length**2) / (4 * tan(pi / sides   ))


if __name__ == "__main__":
      import doctest

      doctest.testmod(verbose=True)  # verbose so we can see methods missing tests

      print('[DEMO] Areas of various geometric shapes: \n')
      print(f'''Rectangle: {area_rectangle(1_0, 2_0) = }''')
      print(f'''Square: {area_square(1_0) = }''')
      print(f'''Triangle: {area_triangle(1_0, 1_0) = }''')
      print(f'''Triangle: {area_triangle_three_sides(5, 1_2, 1_3) = }''')
      print(f'''Parallelogram: {area_parallelogram(1_0, 2_0) = }''')
      print(f'''Rhombus: {area_rhombus(1_0, 2_0) = }''')
      print(f'''Trapezium: {area_trapezium(1_0, 2_0, 3_0) = }''')
      print(f'''Circle: {area_circle(2_0) = }''')
      print(f'''Ellipse: {area_ellipse(1_0, 2_0) = }''')
      print('\nSurface Areas of various geometric shapes: \n')
      print(f'''Cube: {surface_area_cube(2_0) = }''')
      print(f'''Cuboid: {surface_area_cuboid(1_0, 2_0, 3_0) = }''')
      print(f'''Sphere: {surface_area_sphere(2_0) = }''')
      print(f'''Hemisphere: {surface_area_hemisphere(2_0) = }''')
      print(f'''Cone: {surface_area_cone(1_0, 2_0) = }''')
      print(f'''Conical Frustum: {surface_area_conical_frustum(1_0, 2_0, 3_0) = }''')
      print(f'''Cylinder: {surface_area_cylinder(1_0, 2_0) = }''')
      print(f'''Torus: {surface_area_torus(2_0, 1_0) = }''')
      print(f'''Equilateral Triangle: {area_reg_polygon(3, 1_0) = }''')
      print(f'''Square: {area_reg_polygon(4, 1_0) = }''')
      print(f'''Reqular Pentagon: {area_reg_polygon(5, 1_0) = }''')







'''simple docstring'''







import copy

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


lowercase      :   Tuple      =       logging.get_logger(__name__)

lowercase      :   Dict      =       {
    """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}







class 					_a (a__	):





     '''simple docstring'''



     lowerCAmelCase_  :     str          =					"""deta"""
     lowerCAmelCase_  :     Any          =					{
         """hidden_size""": """d_model""",
         """num_attention_heads""": """encoder_attention_heads""",
     }







     def __init__(				self							,__a=None							,__a=900							,__a=2_048							,__a=6							,__a=2_048							,__a=8							,__a=6							,__a=1_024							,__a=8							,__a=0.0							,__a=True							,__a="relu"							,__a=256							,__a=0.1							,__a=0.0							,__a=0.0							,__a=0.02							,__a=1.0							,__a=True							,__a=False							,__a="sine"							,__a=5							,__a=4							,__a=4							,__a=True							,__a=300							,__a=True							,__a=True							,__a=1							,__a=5							,__a=2							,__a=1							,__a=1							,__a=5							,__a=2							,__a=0.1							,__a=0.25							,**__a							,)      ->				int:
          if backbone_config is None:
               logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""							)
               snake_case			:      int        =			CONFIG_MAPPING["""resnet"""](out_features=["""stage2""", """stage3""", """stage4"""]							)
          else:
               if isinstance(__a							,__a							):
                    snake_case			:      str        =			backbone_config.pop("""model_type"""							)
                    snake_case			:      Optional[Any]        =			CONFIG_MAPPING[backbone_model_type]
                    snake_case			:      List[Any]        =			config_class.from_dict(__a							)

          snake_case			:      Any        =			backbone_config
          snake_case			:      Optional[Any]        =			num_queries
          snake_case			:      Dict        =			max_position_embeddings
          snake_case			:      int        =			d_model
          snake_case			:      str        =			encoder_ffn_dim
          snake_case			:      Dict        =			encoder_layers
          snake_case			:      List[Any]        =			encoder_attention_heads
          snake_case			:      int        =			decoder_ffn_dim
          snake_case			:      List[Any]        =			decoder_layers
          snake_case			:      Dict        =			decoder_attention_heads
          snake_case			:      Dict        =			dropout
          snake_case			:      Dict        =			attention_dropout
          snake_case			:      List[Any]        =			activation_dropout
          snake_case			:      Dict        =			activation_function
          snake_case			:      List[Any]        =			init_std
          snake_case			:      Any        =			init_xavier_std
          snake_case			:      List[Any]        =			encoder_layerdrop
          snake_case			:      Optional[Any]        =			auxiliary_loss
          snake_case			:      Optional[int]        =			position_embedding_type
          # deformable attributes
          snake_case			:      Tuple        =			num_feature_levels
          snake_case			:      List[Any]        =			encoder_n_points
          snake_case			:      Dict        =			decoder_n_points
          snake_case			:      int        =			two_stage
          snake_case			:      Any        =			two_stage_num_proposals
          snake_case			:      List[str]        =			with_box_refine
          snake_case			:      Tuple        =			assign_first_stage
          if two_stage is True and with_box_refine is False:
               raise ValueError("""If two_stage is True, with_box_refine must be True."""							)
          # Hungarian matcher
          snake_case			:      Optional[int]        =			class_cost
          snake_case			:      int        =			bbox_cost
          snake_case			:      Optional[int]        =			giou_cost
          # Loss coefficients
          snake_case			:      str        =			mask_loss_coefficient
          snake_case			:      Any        =			dice_loss_coefficient
          snake_case			:      List[Any]        =			bbox_loss_coefficient
          snake_case			:      List[Any]        =			giou_loss_coefficient
          snake_case			:      List[str]        =			eos_coefficient
          snake_case			:      Optional[Any]        =			focal_alpha
          super().__init__(is_encoder_decoder=__a							,**__a							)







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.encoder_attention_heads







     @property
     def 			snake_case_      (				self							)      ->				int:
          return self.d_model







     def 			snake_case_      (				self							)      ->				List[str]:
          snake_case			:      List[str]        =			copy.deepcopy(self.__dict__							)
          snake_case			:      List[str]        =			self.backbone_config.to_dict()
          snake_case			:      List[Any]        =			self.__class__.model_type
          return output



