'''simple docstring'''

from math import pi, sqrt, tan







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







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







def __UpperCamelCase( _A       :					float	,      _A       :					float     ):
   '''simple docstring'''
   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     ):
   '''simple docstring'''
   if radius_a < 0 or radius_a < 0 or height < 0:
      raise ValueError(
          '''surface_area_conical_frustum() only accepts non-negative values'''     )
   UpperCAmelCase__				:					List[str] 					=	(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     ):
   '''simple docstring'''
   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     ):
   '''simple docstring'''
   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     ):
   '''simple docstring'''
   if length < 0 or width < 0:
      raise ValueError('''area_rectangle() only accepts non-negative values'''     )
   return length * width







def __UpperCamelCase( _A       :					float     ):
   '''simple docstring'''
   if side_length < 0:
      raise ValueError('''area_square() only accepts non-negative values'''     )
   return side_length**2







def __UpperCamelCase( _A       :					float	,      _A       :					float     ):
   '''simple docstring'''
   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     ):
   '''simple docstring'''
   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'''     )
   UpperCAmelCase__				:					Tuple 					=	(sidea + sidea + sidea) / 2
   UpperCAmelCase__				:					Union[str, Any] 					=	sqrt(
       semi_perimeter
       * (semi_perimeter - sidea)
       * (semi_perimeter - sidea)
       * (semi_perimeter - sidea)     )
   return area







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







def __UpperCamelCase( _A       :					float	,      _A       :					float     ):
   '''simple docstring'''
   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     ):
   '''simple docstring'''
   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     ):
   '''simple docstring'''
   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) = }""")





'''simple docstring'''

from __future__ import absolute_import, division, print_function, unicode_literals

from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss

from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.roberta.modeling_roberta import (
    ROBERTA_INPUTS_DOCSTRING,
    ROBERTA_START_DOCSTRING,
    RobertaEmbeddings,
)

from .modeling_highway_bert import BertPreTrainedModel, DeeBertModel, HighwayException, entropy


@add_start_docstrings(
    '''The RoBERTa Model transformer with early exiting (DeeRoBERTa). '''		,lowerCAmelCase		,)
class 					_lowercase						(   lowerCAmelCase ):
      '''simple docstring'''


      UpperCAmelCase_   :   int   				= RobertaConfig
      UpperCAmelCase_   :   Tuple   				= '''roberta'''




      def __init__(					self       ,lowerCamelCase_				)      ->      List[Any]:



         '''simple docstring'''



         super().__init__(lowerCamelCase_				)

         UpperCAmelCase__				:					Optional[Any] 					=	RobertaEmbeddings(lowerCamelCase_				)
         self.init_weights()




@add_start_docstrings(
    '''RoBERTa Model (with early exiting - DeeRoBERTa) with a classifier on top,
    also takes care of multi-layer training. '''		,lowerCAmelCase		,)
class 					_lowercase						(   lowerCAmelCase ):
      '''simple docstring'''


      UpperCAmelCase_   :   Tuple   				= RobertaConfig
      UpperCAmelCase_   :   Optional[Any]   				= '''roberta'''




      def __init__(					self       ,lowerCamelCase_				)      ->      str:



         '''simple docstring'''



         super().__init__(lowerCamelCase_				)
         UpperCAmelCase__				:					Any 					=	config.num_labels
         UpperCAmelCase__				:					Union[str, Any] 					=	config.num_hidden_layers

         UpperCAmelCase__				:					str 					=	DeeRobertaModel(lowerCamelCase_				)
         UpperCAmelCase__				:					Optional[int] 					=	nn.Dropout(config.hidden_dropout_prob				)
         UpperCAmelCase__				:					Union[str, Any] 					=	nn.Linear(config.hidden_size       ,self.config.num_labels				)




      @add_start_docstrings_to_model_forward(lowerCamelCase_				)
      def 		lowerCAmelCase__       (					self       ,lowerCamelCase_=None       ,lowerCamelCase_=None       ,lowerCamelCase_=None       ,lowerCamelCase_=None       ,lowerCamelCase_=None       ,lowerCamelCase_=None       ,lowerCamelCase_=None       ,lowerCamelCase_=-1       ,lowerCamelCase_=False       ,)      ->      Optional[Any]:



         '''simple docstring'''



         UpperCAmelCase__				:					Tuple 					=	self.num_layers
         try:
            UpperCAmelCase__				:					Union[str, Any] 					=	self.roberta(
                lowerCamelCase_       ,attention_mask=lowerCamelCase_       ,token_type_ids=lowerCamelCase_       ,position_ids=lowerCamelCase_       ,head_mask=lowerCamelCase_       ,inputs_embeds=lowerCamelCase_       ,)

            UpperCAmelCase__				:					List[Any] 					=	outputs[1]

            UpperCAmelCase__				:					Tuple 					=	self.dropout(lowerCamelCase_				)
            UpperCAmelCase__				:					Any 					=	self.classifier(lowerCamelCase_				)
            UpperCAmelCase__				:					Optional[int] 					=	(logits,) + outputs[2:]  # add hidden states and attention if they are here
         except HighwayException as e:
            UpperCAmelCase__				:					int 					=	e.message
            UpperCAmelCase__				:					Optional[int] 					=	e.exit_layer
            UpperCAmelCase__				:					Optional[int] 					=	outputs[0]

         if not self.training:
            UpperCAmelCase__				:					Dict 					=	entropy(lowerCamelCase_				)
            UpperCAmelCase__				:					List[Any] 					=	[]
            UpperCAmelCase__				:					str 					=	[]
         if labels is not None:
            if self.num_labels == 1:
               #  We are doing regression
               UpperCAmelCase__				:					str 					=	MSELoss()
               UpperCAmelCase__				:					Union[str, Any] 					=	loss_fct(logits.view(-1				)       ,labels.view(-1				)				)
            else:
               UpperCAmelCase__				:					Any 					=	CrossEntropyLoss()
               UpperCAmelCase__				:					Optional[Any] 					=	loss_fct(logits.view(-1       ,self.num_labels				)       ,labels.view(-1				)				)

            # work with highway exits
            UpperCAmelCase__				:					List[str] 					=	[]
            for highway_exit in outputs[-1]:
               UpperCAmelCase__				:					Optional[int] 					=	highway_exit[0]
               if not self.training:
                  highway_logits_all.append(lowerCamelCase_				)
                  highway_entropy.append(highway_exit[2]				)
               if self.num_labels == 1:
                  #  We are doing regression
                  UpperCAmelCase__				:					Any 					=	MSELoss()
                  UpperCAmelCase__				:					Optional[Any] 					=	loss_fct(highway_logits.view(-1				)       ,labels.view(-1				)				)
               else:
                  UpperCAmelCase__				:					Any 					=	CrossEntropyLoss()
                  UpperCAmelCase__				:					int 					=	loss_fct(highway_logits.view(-1       ,self.num_labels				)       ,labels.view(-1				)				)
               highway_losses.append(lowerCamelCase_				)

            if train_highway:
               UpperCAmelCase__				:					Dict 					=	(sum(highway_losses[:-1]				),) + outputs
               # exclude the final highway, of course
            else:
               UpperCAmelCase__				:					Dict 					=	(loss,) + outputs
         if not self.training:
            UpperCAmelCase__				:					Tuple 					=	outputs + ((original_entropy, highway_entropy), exit_layer)
            if output_layer >= 0:
               UpperCAmelCase__				:					int 					=	(
                   (outputs[0],) + (highway_logits_all[output_layer],) + outputs[2:]
               )  # use the highway of the last layer

         return outputs  # (loss), logits, (hidden_states), (attentions), entropy




