

'''simple docstring'''
import math
import time

from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics


if is_torch_tpu_available(check_device=False):
     import torch_xla.core.xla_model as xm
     import torch_xla.debug.metrics as met







class 				A__       (			__snake_case    ):





  def __init__(						self :      Optional[int]				,   *_a :      int				,   _a :      Optional[Any]=None				,   _a :      List[str]=None				,   **_a :      str					)      ->       Optional[int]:





       '''simple docstring'''






       super().__init__(*snake_case_				,   **snake_case_					)
       _SCREAMING_SNAKE_CASE				       =eval_examples
       _SCREAMING_SNAKE_CASE				       =post_process_function





  def 		A    (						self :      str				,   _a :      List[Any]=None				,   _a :      str=None				,   _a :      str=None				,   _a :      Any = "eval"					)      ->       List[str]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE				       =self.eval_dataset if eval_dataset is None else eval_dataset
       _SCREAMING_SNAKE_CASE				       =self.get_eval_dataloader(snake_case_					)
       _SCREAMING_SNAKE_CASE				       =self.eval_examples if eval_examples is None else eval_examples

       # Temporarily disable metric computation, we will do it in the loop here.
       _SCREAMING_SNAKE_CASE				       =self.compute_metrics
       _SCREAMING_SNAKE_CASE				       =None
       _SCREAMING_SNAKE_CASE				       =self.prediction_loop if self.args.use_legacy_prediction_loop else self.evaluation_loop
       _SCREAMING_SNAKE_CASE				       =time.time()
       try:
            _SCREAMING_SNAKE_CASE				       =eval_loop(
                snake_case_				,   description='Evaluation'				,   prediction_loss_only=True if compute_metrics is None else None				,   ignore_keys=snake_case_				,   metric_key_prefix=snake_case_				,   )
       finally:
            _SCREAMING_SNAKE_CASE				       =compute_metrics
       _SCREAMING_SNAKE_CASE				       =self.args.eval_batch_size * self.args.world_size
       if f"{metric_key_prefix}_jit_compilation_time" in output.metrics:
            start_time += output.metrics[f"{metric_key_prefix}_jit_compilation_time"]
       output.metrics.update(
           speed_metrics(
               snake_case_				,   snake_case_				,   num_samples=output.num_samples				,   num_steps=math.ceil(output.num_samples / total_batch_size					)				,   )					)
       if self.post_process_function is not None and self.compute_metrics is not None and self.args.should_save:
            # Only the main node write the results by default
            _SCREAMING_SNAKE_CASE				       =self.post_process_function(snake_case_				,   snake_case_				,   output.predictions					)
            _SCREAMING_SNAKE_CASE				       =self.compute_metrics(snake_case_					)

            # Prefix all keys with metric_key_prefix + '_'
            for key in list(metrics.keys()					):
                 if not key.startswith(f"{metric_key_prefix}_"					):
                      _SCREAMING_SNAKE_CASE				       =metrics.pop(snake_case_					)
            metrics.update(output.metrics					)
       else:
            _SCREAMING_SNAKE_CASE				       =output.metrics

       if self.args.should_log:
            # Only the main node log the results by default
            self.log(snake_case_					)

       if self.args.tpu_metrics_debug or self.args.debug:
            # tpu-comment: Logging debug metrics for PyTorch/XLA (compile, execute times, ops, etc.)
            xm.master_print(met.metrics_report()					)

       _SCREAMING_SNAKE_CASE				       =self.callback_handler.on_evaluate(self.args				,   self.state				,   self.control				,   snake_case_					)
       return metrics





  def 		A    (						self :      Union[str, Any]				,   _a :      Tuple				,   _a :      List[str]				,   _a :      Optional[int]=None				,   _a :      List[str] = "test"					)      ->       Union[str, Any]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE				       =self.get_test_dataloader(snake_case_					)

       # Temporarily disable metric computation, we will do it in the loop here.
       _SCREAMING_SNAKE_CASE				       =self.compute_metrics
       _SCREAMING_SNAKE_CASE				       =None
       _SCREAMING_SNAKE_CASE				       =self.prediction_loop if self.args.use_legacy_prediction_loop else self.evaluation_loop
       _SCREAMING_SNAKE_CASE				       =time.time()
       try:
            _SCREAMING_SNAKE_CASE				       =eval_loop(
                snake_case_				,   description='Prediction'				,   prediction_loss_only=True if compute_metrics is None else None				,   ignore_keys=snake_case_				,   metric_key_prefix=snake_case_				,   )
       finally:
            _SCREAMING_SNAKE_CASE				       =compute_metrics
       _SCREAMING_SNAKE_CASE				       =self.args.eval_batch_size * self.args.world_size
       if f"{metric_key_prefix}_jit_compilation_time" in output.metrics:
            start_time += output.metrics[f"{metric_key_prefix}_jit_compilation_time"]
       output.metrics.update(
           speed_metrics(
               snake_case_				,   snake_case_				,   num_samples=output.num_samples				,   num_steps=math.ceil(output.num_samples / total_batch_size					)				,   )					)

       if self.post_process_function is None or self.compute_metrics is None:
            return output

       _SCREAMING_SNAKE_CASE				       =self.post_process_function(snake_case_				,   snake_case_				,   output.predictions				,   'predict'					)
       _SCREAMING_SNAKE_CASE				       =self.compute_metrics(snake_case_					)

       # Prefix all keys with metric_key_prefix + '_'
       for key in list(metrics.keys()					):
            if not key.startswith(f"{metric_key_prefix}_"					):
                 _SCREAMING_SNAKE_CASE				       =metrics.pop(snake_case_					)
       metrics.update(output.metrics					)
       return PredictionOutput(predictions=predictions.predictions				,   label_ids=predictions.label_ids				,   metrics=snake_case_					)







from math import pi, sqrt, tan





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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'				)
    _A     =							(height**2 + (radius_a - radius_a) ** 2) ** 0.5
    return pi * ((slant_height * (radius_a + radius_a)) + radius_a**2 + radius_a**2)





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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(_SCREAMING_SNAKE_CASE							,     2				) * torus_radius * tube_radius





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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'				)
    _A     =							(sidea + sidea + sidea) / 2
    _A     =							sqrt(
        semi_perimeter
        * (semi_perimeter - sidea)
        * (semi_perimeter - sidea)
        * (semi_perimeter - sidea)				)
    return area





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




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





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> 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 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




    if not isinstance(_SCREAMING_SNAKE_CASE							,     _SCREAMING_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(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) = }")





