
"""simple docstring"""




import copy

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


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

UpperCAmelCase__   :					Union[str, Any]												=				{
    '''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''',
}



class 			lowerCAmelCase_		(UpperCamelCase__						):


    """simple docstring"""



    __UpperCamelCase   :		Tuple       =     """deta"""
    __UpperCamelCase   :		str       =     {
        """hidden_size""": """d_model""",
        """num_attention_heads""": """encoder_attention_heads""",
    }



    def __init__(self     , SCREAMING_SNAKE_CASE__=None     , SCREAMING_SNAKE_CASE__=9_00     , SCREAMING_SNAKE_CASE__=20_48     , SCREAMING_SNAKE_CASE__=6     , SCREAMING_SNAKE_CASE__=20_48     , SCREAMING_SNAKE_CASE__=8     , SCREAMING_SNAKE_CASE__=6     , SCREAMING_SNAKE_CASE__=10_24     , SCREAMING_SNAKE_CASE__=8     , SCREAMING_SNAKE_CASE__=0.0     , SCREAMING_SNAKE_CASE__=True     , SCREAMING_SNAKE_CASE__="relu"     , SCREAMING_SNAKE_CASE__=2_56     , SCREAMING_SNAKE_CASE__=0.1     , SCREAMING_SNAKE_CASE__=0.0     , SCREAMING_SNAKE_CASE__=0.0     , SCREAMING_SNAKE_CASE__=0.02     , SCREAMING_SNAKE_CASE__=1.0     , SCREAMING_SNAKE_CASE__=True     , SCREAMING_SNAKE_CASE__=False     , SCREAMING_SNAKE_CASE__="sine"     , SCREAMING_SNAKE_CASE__=5     , SCREAMING_SNAKE_CASE__=4     , SCREAMING_SNAKE_CASE__=4     , SCREAMING_SNAKE_CASE__=True     , SCREAMING_SNAKE_CASE__=3_00     , SCREAMING_SNAKE_CASE__=True     , SCREAMING_SNAKE_CASE__=True     , SCREAMING_SNAKE_CASE__=1     , SCREAMING_SNAKE_CASE__=5     , SCREAMING_SNAKE_CASE__=2     , SCREAMING_SNAKE_CASE__=1     , SCREAMING_SNAKE_CASE__=1     , SCREAMING_SNAKE_CASE__=5     , SCREAMING_SNAKE_CASE__=2     , SCREAMING_SNAKE_CASE__=0.1     , SCREAMING_SNAKE_CASE__=0.25     , **SCREAMING_SNAKE_CASE__     , )      ->	List[Any]:



           """simple docstring"""




           if backbone_config is None:
                  logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""					)
                  SCREAMING_SNAKE_CASE__		: Any     =     CONFIG_MAPPING["""resnet"""](out_features=["""stage2""", """stage3""", """stage4"""]					)
           else:
                  if isinstance(SCREAMING_SNAKE_CASE__     , SCREAMING_SNAKE_CASE__					):
                         SCREAMING_SNAKE_CASE__		: int     =     backbone_config.pop("""model_type"""					)
                         SCREAMING_SNAKE_CASE__		: Optional[Any]     =     CONFIG_MAPPING[backbone_model_type]
                         SCREAMING_SNAKE_CASE__		: List[Any]     =     config_class.from_dict(SCREAMING_SNAKE_CASE__					)

           SCREAMING_SNAKE_CASE__		: List[str]     =     backbone_config
           SCREAMING_SNAKE_CASE__		: Tuple     =     num_queries
           SCREAMING_SNAKE_CASE__		: List[Any]     =     max_position_embeddings
           SCREAMING_SNAKE_CASE__		: Tuple     =     d_model
           SCREAMING_SNAKE_CASE__		: Dict     =     encoder_ffn_dim
           SCREAMING_SNAKE_CASE__		: Optional[int]     =     encoder_layers
           SCREAMING_SNAKE_CASE__		: List[Any]     =     encoder_attention_heads
           SCREAMING_SNAKE_CASE__		: int     =     decoder_ffn_dim
           SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     decoder_layers
           SCREAMING_SNAKE_CASE__		: Any     =     decoder_attention_heads
           SCREAMING_SNAKE_CASE__		: List[Any]     =     dropout
           SCREAMING_SNAKE_CASE__		: Tuple     =     attention_dropout
           SCREAMING_SNAKE_CASE__		: int     =     activation_dropout
           SCREAMING_SNAKE_CASE__		: str     =     activation_function
           SCREAMING_SNAKE_CASE__		: Tuple     =     init_std
           SCREAMING_SNAKE_CASE__		: int     =     init_xavier_std
           SCREAMING_SNAKE_CASE__		: List[Any]     =     encoder_layerdrop
           SCREAMING_SNAKE_CASE__		: Tuple     =     auxiliary_loss
           SCREAMING_SNAKE_CASE__		: Optional[Any]     =     position_embedding_type
           # deformable attributes
           SCREAMING_SNAKE_CASE__		: Tuple     =     num_feature_levels
           SCREAMING_SNAKE_CASE__		: Optional[int]     =     encoder_n_points
           SCREAMING_SNAKE_CASE__		: List[Any]     =     decoder_n_points
           SCREAMING_SNAKE_CASE__		: int     =     two_stage
           SCREAMING_SNAKE_CASE__		: Tuple     =     two_stage_num_proposals
           SCREAMING_SNAKE_CASE__		: Any     =     with_box_refine
           SCREAMING_SNAKE_CASE__		: List[str]     =     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
           SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     class_cost
           SCREAMING_SNAKE_CASE__		: Optional[Any]     =     bbox_cost
           SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     giou_cost
           # Loss coefficients
           SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     mask_loss_coefficient
           SCREAMING_SNAKE_CASE__		: int     =     dice_loss_coefficient
           SCREAMING_SNAKE_CASE__		: Tuple     =     bbox_loss_coefficient
           SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     giou_loss_coefficient
           SCREAMING_SNAKE_CASE__		: Any     =     eos_coefficient
           SCREAMING_SNAKE_CASE__		: Any     =     focal_alpha
           super().__init__(is_encoder_decoder=SCREAMING_SNAKE_CASE__     , **SCREAMING_SNAKE_CASE__					)



    @property
    def 			__magic_name__					(self					)      ->	int:



           """simple docstring"""




           return self.encoder_attention_heads



    @property
    def 			__magic_name__					(self					)      ->	int:



           """simple docstring"""




           return self.d_model



    def 			__magic_name__					(self					)      ->	Dict:



           """simple docstring"""




           SCREAMING_SNAKE_CASE__		: Optional[Any]     =     copy.deepcopy(self.__dict__					)
           SCREAMING_SNAKE_CASE__		: int     =     self.backbone_config.to_dict()
           SCREAMING_SNAKE_CASE__		: Any     =     self.__class__.model_type
           return output






"""simple docstring"""




from math import pi, sqrt, tan

def lowercase_						(     _snake_case		):
							if side_length < 0:
														raise ValueError("""surface_area_cube() only accepts non-negative values"""		)
							return 6 * side_length**2

def lowercase_						(     _snake_case     ,_snake_case     ,_snake_case		):
							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 lowercase_						(     _snake_case		):
							if radius < 0:
														raise ValueError("""surface_area_sphere() only accepts non-negative values"""		)
							return 4 * pi * radius**2

def lowercase_						(     _snake_case		):
							if radius < 0:
														raise ValueError("""surface_area_hemisphere() only accepts non-negative values"""		)
							return 3 * pi * radius**2

def lowercase_						(     _snake_case     ,_snake_case		):
							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 lowercase_						(     _snake_case     ,_snake_case     ,_snake_case		):
							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__		: int     =     (height**2 + (radius_a - radius_a) ** 2) ** 0.5
							return pi * ((slant_height * (radius_a + radius_a)) + radius_a**2 + radius_a**2)

def lowercase_						(     _snake_case     ,_snake_case		):
							if radius < 0 or height < 0:
														raise ValueError("""surface_area_cylinder() only accepts non-negative values"""		)
							return 2 * pi * radius * (height + radius)

def lowercase_						(     _snake_case     ,_snake_case		):
							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 lowercase_						(     _snake_case     ,_snake_case		):
							if length < 0 or width < 0:
														raise ValueError("""area_rectangle() only accepts non-negative values"""		)
							return length * width

def lowercase_						(     _snake_case		):
							if side_length < 0:
														raise ValueError("""area_square() only accepts non-negative values"""		)
							return side_length**2

def lowercase_						(     _snake_case     ,_snake_case		):
							if base < 0 or height < 0:
														raise ValueError("""area_triangle() only accepts non-negative values"""		)
							return (base * height) / 2

def lowercase_						(     _snake_case     ,_snake_case     ,_snake_case		):
							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__		: List[str]     =     (sidea + sidea + sidea) / 2
							SCREAMING_SNAKE_CASE__		: List[Any]     =     sqrt(
							    semi_perimeter
							    * (semi_perimeter - sidea)
							    * (semi_perimeter - sidea)
							    * (semi_perimeter - sidea)		)
							return area

def lowercase_						(     _snake_case     ,_snake_case		):
							if base < 0 or height < 0:
														raise ValueError("""area_parallelogram() only accepts non-negative values"""		)
							return base * height

def lowercase_						(     _snake_case     ,_snake_case     ,_snake_case		):
							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 lowercase_						(     _snake_case		):
							if radius < 0:
														raise ValueError("""area_circle() only accepts non-negative values"""		)
							return pi * radius**2

def lowercase_						(     _snake_case     ,_snake_case		):
							if radius_x < 0 or radius_y < 0:
														raise ValueError("""area_ellipse() only accepts non-negative values"""		)
							return pi * radius_x * radius_y

def lowercase_						(     _snake_case     ,_snake_case		):
							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 lowercase_						(     _snake_case     ,_snake_case		):
							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) = }""")




