
from math import pi, sqrt, tan


def 			UpperCamelCase					(    __lowerCamelCase     : List[Any]    ):
       if side_length < 0:
              raise ValueError("surface_area_cube() only accepts non-negative values"    )
       return 6 * side_length**2


def 			UpperCamelCase					(    __lowerCamelCase     : Union[str, Any]				,					__lowerCamelCase     : int				,					__lowerCamelCase     : List[Any]    ):
       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					(    __lowerCamelCase     : str    ):
       if radius < 0:
              raise ValueError("surface_area_sphere() only accepts non-negative values"    )
       return 4 * pi * radius**2


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


def 			UpperCamelCase					(    __lowerCamelCase     : Any				,					__lowerCamelCase     : Optional[int]    ):
       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					(    __lowerCamelCase     : Optional[int]				,					__lowerCamelCase     : str				,					__lowerCamelCase     : str    ):
       if radius_a < 0 or radius_a < 0 or height < 0:
              raise ValueError(
                  "surface_area_conical_frustum() only accepts non-negative values"    )
       snake_case       :   Tuple							=      (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					(    __lowerCamelCase     : str				,					__lowerCamelCase     : Dict    ):
       if radius < 0 or height < 0:
              raise ValueError("surface_area_cylinder() only accepts non-negative values"    )
       return 2 * pi * radius * (height + radius)


def 			UpperCamelCase					(    __lowerCamelCase     : List[str]				,					__lowerCamelCase     : Optional[Any]    ):
       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(__lowerCamelCase				,					2    ) * torus_radius * tube_radius


def 			UpperCamelCase					(    __lowerCamelCase     : int				,					__lowerCamelCase     : Optional[int]    ):
       if length < 0 or width < 0:
              raise ValueError("area_rectangle() only accepts non-negative values"    )
       return length * width


def 			UpperCamelCase					(    __lowerCamelCase     : List[str]    ):
       if side_length < 0:
              raise ValueError("area_square() only accepts non-negative values"    )
       return side_length**2


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


def 			UpperCamelCase					(    __lowerCamelCase     : Optional[int]				,					__lowerCamelCase     : List[str]				,					__lowerCamelCase     : List[str]    ):
       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"    )
       snake_case       :   Optional[int]							=      (sidea + sidea + sidea) / 2
       snake_case       :   List[Any]							=      sqrt(
           semi_perimeter
           * (semi_perimeter - sidea)
           * (semi_perimeter - sidea)
           * (semi_perimeter - sidea)    )
       return area


def 			UpperCamelCase					(    __lowerCamelCase     : List[Any]				,					__lowerCamelCase     : List[Any]    ):
       if base < 0 or height < 0:
              raise ValueError("area_parallelogram() only accepts non-negative values"    )
       return base * height


def 			UpperCamelCase					(    __lowerCamelCase     : Tuple				,					__lowerCamelCase     : Tuple				,					__lowerCamelCase     : Tuple    ):
       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					(    __lowerCamelCase     : str    ):
       if radius < 0:
              raise ValueError("area_circle() only accepts non-negative values"    )
       return pi * radius**2


def 			UpperCamelCase					(    __lowerCamelCase     : Any				,					__lowerCamelCase     : Union[str, Any]    ):
       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					(    __lowerCamelCase     : Union[str, Any]				,					__lowerCamelCase     : Optional[int]    ):
       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					(    __lowerCamelCase     : str				,					__lowerCamelCase     : List[Any]    ):
       if not isinstance(__lowerCamelCase				,					__lowerCamelCase    ) 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) = }')









import math

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


__lowerCAmelCase		       =							logging.get_logger(__name__)

__lowerCAmelCase		       =							{
    '''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json''',
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}





class   __a			(    __UpperCamelCase      ):
 __lowercase :							Optional[int]        = 'data2vec-audio'
 def __init__(   self				, lowerCAmelCase__=32				, lowerCAmelCase__=768				, lowerCAmelCase__=12				, lowerCAmelCase__=12				, lowerCAmelCase__=3_072				, lowerCAmelCase__="gelu"				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.0				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.1				, lowerCAmelCase__=0.0_2				, lowerCAmelCase__=1E-5				, lowerCAmelCase__="gelu"				, lowerCAmelCase__=(512, 512, 512, 512, 512, 512, 512)				, lowerCAmelCase__=(5, 2, 2, 2, 2, 2, 2)				, lowerCAmelCase__=(10, 3, 3, 3, 3, 2, 2)				, lowerCAmelCase__=False				, lowerCAmelCase__=16				, lowerCAmelCase__=19				, lowerCAmelCase__=5				, lowerCAmelCase__=0.0_5				, lowerCAmelCase__=10				, lowerCAmelCase__=2				, lowerCAmelCase__=0.0				, lowerCAmelCase__=10				, lowerCAmelCase__=0				, lowerCAmelCase__="sum"				, lowerCAmelCase__=False				, lowerCAmelCase__=False				, lowerCAmelCase__=256				, lowerCAmelCase__=(512, 512, 512, 512, 1_500)				, lowerCAmelCase__=(5, 3, 3, 1, 1)				, lowerCAmelCase__=(1, 2, 3, 1, 1)				, lowerCAmelCase__=512				, lowerCAmelCase__=0				, lowerCAmelCase__=1				, lowerCAmelCase__=2				, lowerCAmelCase__=False				, lowerCAmelCase__=3				, lowerCAmelCase__=2				, lowerCAmelCase__=3				, lowerCAmelCase__=None				, **lowerCAmelCase__				, )					->				Optional[int]:




        '''simple docstring'''
        super().__init__(**lowerCAmelCase__				, pad_token_id=lowerCAmelCase__				, bos_token_id=lowerCAmelCase__				, eos_token_id=lowerCAmelCase__ )
        lowercase__:   int  			=   hidden_size
        lowercase__:   str  			=   feat_extract_activation
        lowercase__:   List[Any]  			=   list(lowerCAmelCase__ )
        lowercase__:   Optional[int]  			=   list(lowerCAmelCase__ )
        lowercase__:   int  			=   list(lowerCAmelCase__ )
        lowercase__:   Union[str, Any]  			=   conv_bias
        lowercase__:   int  			=   num_conv_pos_embeddings
        lowercase__:   List[str]  			=   num_conv_pos_embedding_groups
        lowercase__:   List[Any]  			=   conv_pos_kernel_size
        lowercase__:   Optional[Any]  			=   len(self.conv_dim )
        lowercase__:   List[str]  			=   num_hidden_layers
        lowercase__:   List[str]  			=   intermediate_size
        lowercase__:   Tuple  			=   hidden_act
        lowercase__:   Any  			=   num_attention_heads
        lowercase__:   Optional[int]  			=   hidden_dropout
        lowercase__:   List[str]  			=   attention_dropout
        lowercase__:   int  			=   activation_dropout
        lowercase__:   Dict  			=   feat_proj_dropout
        lowercase__:   str  			=   final_dropout
        lowercase__:   List[str]  			=   layerdrop
        lowercase__:   str  			=   layer_norm_eps
        lowercase__:   Union[str, Any]  			=   initializer_range
        lowercase__:   Union[str, Any]  			=   vocab_size
        lowercase__:   Any  			=   use_weighted_layer_sum

        if (
            (len(self.conv_stride ) != self.num_feat_extract_layers)
            or (len(self.conv_kernel ) != self.num_feat_extract_layers)
            or (len(self.conv_dim ) != self.num_feat_extract_layers)
        ):
               raise ValueError(
                   'Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =='
                   ' `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ='
                   F' {len(self.conv_dim )}`, `len(config.conv_stride) = {len(self.conv_stride )}`,'
                   F' `len(config.conv_kernel) = {len(self.conv_kernel )}`.' )

        # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
        lowercase__:   List[str]  			=   mask_time_prob
        lowercase__:   Tuple  			=   mask_time_length
        lowercase__:   List[Any]  			=   mask_time_min_masks
        lowercase__:   Optional[int]  			=   mask_feature_prob
        lowercase__:   Union[str, Any]  			=   mask_feature_length
        lowercase__:   List[str]  			=   mask_feature_min_masks

        # ctc loss
        lowercase__:   Union[str, Any]  			=   ctc_loss_reduction
        lowercase__:   str  			=   ctc_zero_infinity

        # adapter
        lowercase__:   str  			=   add_adapter
        lowercase__:   List[Any]  			=   adapter_kernel_size
        lowercase__:   Tuple  			=   adapter_stride
        lowercase__:   Dict  			=   num_adapter_layers
        lowercase__:   Optional[Any]  			=   output_hidden_size or hidden_size

        # SequenceClassification-specific parameter. Feel free to ignore for other classes.
        lowercase__:   List[Any]  			=   classifier_proj_size

        # XVector-specific parameters. Feel free to ignore for other classes.
        lowercase__:   int  			=   list(lowerCAmelCase__ )
        lowercase__:   Dict  			=   list(lowerCAmelCase__ )
        lowercase__:   int  			=   list(lowerCAmelCase__ )
        lowercase__:   str  			=   xvector_output_dim
 @property
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Optional[int]:




        '''simple docstring'''
        return math.prod(self.conv_stride )


