






'''simple docstring'''







import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
		pass

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase       		=      logging.get_logger(__name__)

__lowerCAmelCase       		=      {
    """kakaobrain/align-base""": """https://huggingface.co/kakaobrain/align-base/resolve/main/config.json""",
}





class 	SCREAMING_SNAKE_CASE					(					_snake_case       ):
			snake_case__  =				"""align_text_model"""






			def __init__( self      :			Any  ,						__SCREAMING_SNAKE_CASE      :			int=3_0522  ,						__SCREAMING_SNAKE_CASE      :			List[str]=768  ,						__SCREAMING_SNAKE_CASE      :			Any=12  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any]=12  ,						__SCREAMING_SNAKE_CASE      :			Tuple=3072  ,						__SCREAMING_SNAKE_CASE      :			int="gelu"  ,						__SCREAMING_SNAKE_CASE      :			List[str]=0.1  ,						__SCREAMING_SNAKE_CASE      :			Dict=0.1  ,						__SCREAMING_SNAKE_CASE      :			Dict=512  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]=2  ,						__SCREAMING_SNAKE_CASE      :			int=0.02  ,						__SCREAMING_SNAKE_CASE      :			Tuple=1e-12  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]=0  ,						__SCREAMING_SNAKE_CASE      :			Optional[int]="absolute"  ,						__SCREAMING_SNAKE_CASE      :			Any=True  ,						**__SCREAMING_SNAKE_CASE      :			Optional[Any]  ,						)			->			str:
							super().__init__(**snake_case_					)

							a_		:  Optional[int]											=      vocab_size
							a_		:  List[str]											=      hidden_size
							a_		:  Optional[int]											=      num_hidden_layers
							a_		:  Dict											=      num_attention_heads
							a_		:  List[Any]											=      hidden_act
							a_		:  Optional[int]											=      intermediate_size
							a_		:  Tuple											=      hidden_dropout_prob
							a_		:  Tuple											=      attention_probs_dropout_prob
							a_		:  Dict											=      max_position_embeddings
							a_		:  Optional[Any]											=      type_vocab_size
							a_		:  Union[str, Any]											=      initializer_range
							a_		:  Union[str, Any]											=      layer_norm_eps
							a_		:  List[str]											=      position_embedding_type
							a_		:  int											=      use_cache
							a_		:  Union[str, Any]											=      pad_token_id







			@classmethod
			def 			SCREAMING_SNAKE_CASE      ( cls      :			int  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any]  ,						**__SCREAMING_SNAKE_CASE      :			Tuple					)			->			List[str]:
							cls._set_token_in_kwargs(snake_case_					)

							a_		:  Union[str, Any]											=      cls.get_config_dict(snake_case_  ,						**snake_case_					)

							# get the text config dict if we are loading from AlignConfig
							if config_dict.get('''model_type'''					) == "align":
											a_		:  Dict											=      config_dict["text_config"]

							if "model_type" in config_dict and hasattr(cls  ,						'''model_type'''					) and config_dict["model_type"] != cls.model_type:
											logger.warning(
											    f'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
											    f'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'					)

							return cls.from_dict(snake_case_  ,						**snake_case_					)





class 	SCREAMING_SNAKE_CASE					(					_snake_case       ):
			snake_case__  =				"""align_vision_model"""






			def __init__( self      :			List[Any]  ,						__SCREAMING_SNAKE_CASE      :			List[str] = 3  ,						__SCREAMING_SNAKE_CASE      :			str = 600  ,						__SCREAMING_SNAKE_CASE      :			Dict = 2.0  ,						__SCREAMING_SNAKE_CASE      :			Dict = 3.1  ,						__SCREAMING_SNAKE_CASE      :			List[str] = 8  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any] = [3, 3, 5, 3, 5, 5, 3]  ,						__SCREAMING_SNAKE_CASE      :			int = [32, 16, 24, 40, 80, 112, 192]  ,						__SCREAMING_SNAKE_CASE      :			int = [16, 24, 40, 80, 112, 192, 320]  ,						__SCREAMING_SNAKE_CASE      :			Optional[int] = []  ,						__SCREAMING_SNAKE_CASE      :			Tuple = [1, 2, 2, 2, 1, 2, 1]  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any] = [1, 2, 2, 3, 3, 4, 1]  ,						__SCREAMING_SNAKE_CASE      :			Tuple = [1, 6, 6, 6, 6, 6, 6]  ,						__SCREAMING_SNAKE_CASE      :			Optional[int] = 0.25  ,						__SCREAMING_SNAKE_CASE      :			List[str] = "swish"  ,						__SCREAMING_SNAKE_CASE      :			List[str] = 2560  ,						__SCREAMING_SNAKE_CASE      :			List[Any] = "mean"  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any] = 0.02  ,						__SCREAMING_SNAKE_CASE      :			List[Any] = 0.001  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any] = 0.99  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any] = 0.2  ,						**__SCREAMING_SNAKE_CASE      :			Tuple  ,						)			->			Tuple:
							super().__init__(**snake_case_					)

							a_		:  Optional[int]											=      num_channels
							a_		:  Any											=      image_size
							a_		:  List[Any]											=      width_coefficient
							a_		:  Tuple											=      depth_coefficient
							a_		:  int											=      depth_divisor
							a_		:  Any											=      kernel_sizes
							a_		:  Dict											=      in_channels
							a_		:  Union[str, Any]											=      out_channels
							a_		:  Optional[int]											=      depthwise_padding
							a_		:  Optional[Any]											=      strides
							a_		:  Union[str, Any]											=      num_block_repeats
							a_		:  Tuple											=      expand_ratios
							a_		:  Tuple											=      squeeze_expansion_ratio
							a_		:  Union[str, Any]											=      hidden_act
							a_		:  int											=      hidden_dim
							a_		:  Optional[Any]											=      pooling_type
							a_		:  Union[str, Any]											=      initializer_range
							a_		:  List[str]											=      batch_norm_eps
							a_		:  Optional[int]											=      batch_norm_momentum
							a_		:  str											=      drop_connect_rate
							a_		:  str											=      sum(snake_case_					) * 4







			@classmethod
			def 			SCREAMING_SNAKE_CASE      ( cls      :			List[str]  ,						__SCREAMING_SNAKE_CASE      :			List[str]  ,						**__SCREAMING_SNAKE_CASE      :			Optional[int]					)			->			str:
							cls._set_token_in_kwargs(snake_case_					)

							a_		:  List[Any]											=      cls.get_config_dict(snake_case_  ,						**snake_case_					)

							# get the vision config dict if we are loading from AlignConfig
							if config_dict.get('''model_type'''					) == "align":
											a_		:  List[Any]											=      config_dict["vision_config"]

							if "model_type" in config_dict and hasattr(cls  ,						'''model_type'''					) and config_dict["model_type"] != cls.model_type:
											logger.warning(
											    f'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
											    f'{cls.model_type}. This is not supported for all configurations of models and can yield errors.'					)

							return cls.from_dict(snake_case_  ,						**snake_case_					)





class 	SCREAMING_SNAKE_CASE					(					_snake_case       ):
			snake_case__  =				"""align"""
			snake_case__  =				True






			def __init__( self      :			List[str]  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]=None  ,						__SCREAMING_SNAKE_CASE      :			Union[str, Any]=None  ,						__SCREAMING_SNAKE_CASE      :			Dict=640  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any]=1.0  ,						__SCREAMING_SNAKE_CASE      :			int=0.02  ,						**__SCREAMING_SNAKE_CASE      :			Tuple  ,						)			->			Optional[Any]:
							super().__init__(**snake_case_					)

							if text_config is None:
											a_		:  Union[str, Any]											=      {}
											logger.info('''text_config is None. Initializing the AlignTextConfig with default values.'''					)

							if vision_config is None:
											a_		:  int											=      {}
											logger.info('''vision_config is None. Initializing the AlignVisionConfig with default values.'''					)

							a_		:  str											=      AlignTextConfig(**snake_case_					)
							a_		:  Dict											=      AlignVisionConfig(**snake_case_					)

							a_		:  int											=      projection_dim
							a_		:  int											=      temperature_init_value
							a_		:  Dict											=      initializer_range






			@classmethod
			def 			SCREAMING_SNAKE_CASE      ( cls      :			Optional[Any]  ,						__SCREAMING_SNAKE_CASE      :			List[str]  ,						__SCREAMING_SNAKE_CASE      :			List[str]  ,						**__SCREAMING_SNAKE_CASE      :			Optional[Any]					)			->			str:
							return cls(text_config=text_config.to_dict()  ,						vision_config=vision_config.to_dict()  ,						**snake_case_					)







			def 			SCREAMING_SNAKE_CASE      ( self      :			List[str]					)			->			Tuple:
							a_		:  Optional[Any]											=      copy.deepcopy(self.__dict__					)
							a_		:  List[str]											=      self.text_config.to_dict()
							a_		:  Dict											=      self.vision_config.to_dict()
							a_		:  Dict											=      self.__class__.model_type
							return output











'''simple docstring'''







from math import pi, sqrt, tan





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





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





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





def 		_UpperCAmelCase   (							__A							:   float						,		__A							:   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 		_UpperCAmelCase   (							__A							:   float						,		__A							:   float						,		__A							:   float      ):
				if radius_a < 0 or radius_a < 0 or height < 0:
								raise ValueError(
								    '''surface_area_conical_frustum() only accepts non-negative values'''      )
				a_		:  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 		_UpperCAmelCase   (							__A							:   float						,		__A							:   float      ):
				if radius < 0 or height < 0:
								raise ValueError('''surface_area_cylinder() only accepts non-negative values'''      )
				return 2 * pi * radius * (height + radius)





def 		_UpperCAmelCase   (							__A							:   float						,		__A							:   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(__A						,		2      ) * torus_radius * tube_radius





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





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





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





def 		_UpperCAmelCase   (							__A							:   float						,		__A							:   float						,		__A							:   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'''      )
				a_		:  int											=      (sidea + sidea + sidea) / 2
				a_		:  Optional[Any]											=      sqrt(
				    semi_perimeter
				    * (semi_perimeter - sidea)
				    * (semi_perimeter - sidea)
				    * (semi_perimeter - sidea)      )
				return area





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





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





def 		_UpperCAmelCase   (							__A							:   float						,		__A							:   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 		_UpperCAmelCase   (							__A							:   float						,		__A							:   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 		_UpperCAmelCase   (							__A							:   int						,		__A							:   float      ):
				if not isinstance(__A						,		__A      ) 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(10, 20) = }""")
		print(F"""Square: {area_square(10) = }""")
		print(F"""Triangle: {area_triangle(10, 10) = }""")
		print(F"""Triangle: {area_triangle_three_sides(5, 12, 13) = }""")
		print(F"""Parallelogram: {area_parallelogram(10, 20) = }""")
		print(F"""Rhombus: {area_rhombus(10, 20) = }""")
		print(F"""Trapezium: {area_trapezium(10, 20, 30) = }""")
		print(F"""Circle: {area_circle(20) = }""")
		print(F"""Ellipse: {area_ellipse(10, 20) = }""")
		print('\nSurface Areas of various geometric shapes: \n')
		print(F"""Cube: {surface_area_cube(20) = }""")
		print(F"""Cuboid: {surface_area_cuboid(10, 20, 30) = }""")
		print(F"""Sphere: {surface_area_sphere(20) = }""")
		print(F"""Hemisphere: {surface_area_hemisphere(20) = }""")
		print(F"""Cone: {surface_area_cone(10, 20) = }""")
		print(F"""Conical Frustum: {surface_area_conical_frustum(10, 20, 30) = }""")
		print(F"""Cylinder: {surface_area_cylinder(10, 20) = }""")
		print(F"""Torus: {surface_area_torus(20, 10) = }""")
		print(F"""Equilateral Triangle: {area_reg_polygon(3, 10) = }""")
		print(F"""Square: {area_reg_polygon(4, 10) = }""")
		print(F"""Reqular Pentagon: {area_reg_polygon(5, 10) = }""")




