
import torch

from diffusers import EulerAncestralDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest


class   __lowerCAmelCase		(		UpperCamelCase_ ):



      """simple docstring"""







      A__		:     Dict       				=      (EulerAncestralDiscreteScheduler,)
      A__		:     List[Any]       				=      1_0




      def 						snake_case_     ( self						:    Dict			,    **_snake_case						:    Union[str, Any]			):
          __lowercase						:     Any		      =    {
              '''num_train_timesteps''': 1100,
              '''beta_start''': 0.00_01,
              '''beta_end''': 0.02,
              '''beta_schedule''': '''linear''',
          }

          config.update(**__SCREAMING_SNAKE_CASE			)
          return config




      def 						snake_case_     ( self						:    Any			):
          for timesteps in [10, 50, 100, 1000]:
              self.check_over_configs(num_train_timesteps=__SCREAMING_SNAKE_CASE			)




      def 						snake_case_     ( self						:    List[Any]			):
          for beta_start, beta_end in zip([0.0_00_01, 0.00_01, 0.0_01]			,    [0.00_02, 0.0_02, 0.02]			):
              self.check_over_configs(beta_start=__SCREAMING_SNAKE_CASE			,    beta_end=__SCREAMING_SNAKE_CASE			)




      def 						snake_case_     ( self						:    str			):
          for schedule in ["linear", "scaled_linear"]:
              self.check_over_configs(beta_schedule=__SCREAMING_SNAKE_CASE			)




      def 						snake_case_     ( self						:    Tuple			):
          for prediction_type in ["epsilon", "v_prediction"]:
              self.check_over_configs(prediction_type=__SCREAMING_SNAKE_CASE			)




      def 						snake_case_     ( self						:    List[Any]			):
          __lowercase						:     str		      =    self.scheduler_classes[0]
          __lowercase						:     List[Any]		      =    self.get_scheduler_config()
          __lowercase						:     int		      =    scheduler_class(**__SCREAMING_SNAKE_CASE			)

          scheduler.set_timesteps(self.num_inference_steps			)

          __lowercase						:     int		      =    torch.manual_seed(0			)

          __lowercase						:     Union[str, Any]		      =    self.dummy_model()
          __lowercase						:     Any		      =    self.dummy_sample_deter * scheduler.init_noise_sigma.cpu()
          __lowercase						:     int		      =    sample.to(__SCREAMING_SNAKE_CASE			)

          for i, t in enumerate(scheduler.timesteps			):
              __lowercase						:     Optional[int]		      =    scheduler.scale_model_input(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			)

              __lowercase						:     List[Any]		      =    model(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			)

              __lowercase						:     str		      =    scheduler.step(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			,    generator=__SCREAMING_SNAKE_CASE			)
              __lowercase						:     Any		      =    output.prev_sample

          __lowercase						:     Optional[int]		      =    torch.sum(torch.abs(__SCREAMING_SNAKE_CASE			)			)
          __lowercase						:     Optional[int]		      =    torch.mean(torch.abs(__SCREAMING_SNAKE_CASE			)			)

          assert abs(result_sum.item() - 152.3192			) < 1E-2
          assert abs(result_mean.item() - 0.19_83			) < 1E-3




      def 						snake_case_     ( self						:    int			):
          __lowercase						:     str		      =    self.scheduler_classes[0]
          __lowercase						:     List[str]		      =    self.get_scheduler_config(prediction_type='''v_prediction'''			)
          __lowercase						:     Union[str, Any]		      =    scheduler_class(**__SCREAMING_SNAKE_CASE			)

          scheduler.set_timesteps(self.num_inference_steps			)

          __lowercase						:     List[Any]		      =    torch.manual_seed(0			)

          __lowercase						:     int		      =    self.dummy_model()
          __lowercase						:     int		      =    self.dummy_sample_deter * scheduler.init_noise_sigma
          __lowercase						:     List[Any]		      =    sample.to(__SCREAMING_SNAKE_CASE			)

          for i, t in enumerate(scheduler.timesteps			):
              __lowercase						:     Optional[int]		      =    scheduler.scale_model_input(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			)

              __lowercase						:     Any		      =    model(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			)

              __lowercase						:     str		      =    scheduler.step(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			,    generator=__SCREAMING_SNAKE_CASE			)
              __lowercase						:     List[Any]		      =    output.prev_sample

          __lowercase						:     List[str]		      =    torch.sum(torch.abs(__SCREAMING_SNAKE_CASE			)			)
          __lowercase						:     List[Any]		      =    torch.mean(torch.abs(__SCREAMING_SNAKE_CASE			)			)

          assert abs(result_sum.item() - 108.4439			) < 1E-2
          assert abs(result_mean.item() - 0.14_12			) < 1E-3




      def 						snake_case_     ( self						:    Union[str, Any]			):
          __lowercase						:     Optional[int]		      =    self.scheduler_classes[0]
          __lowercase						:     Union[str, Any]		      =    self.get_scheduler_config()
          __lowercase						:     Optional[Any]		      =    scheduler_class(**__SCREAMING_SNAKE_CASE			)

          scheduler.set_timesteps(self.num_inference_steps			,    device=__SCREAMING_SNAKE_CASE			)
          __lowercase						:     List[str]		      =    torch.manual_seed(0			)

          __lowercase						:     Tuple		      =    self.dummy_model()
          __lowercase						:     Any		      =    self.dummy_sample_deter * scheduler.init_noise_sigma.cpu()
          __lowercase						:     Optional[Any]		      =    sample.to(__SCREAMING_SNAKE_CASE			)

          for t in scheduler.timesteps:
              __lowercase						:     List[Any]		      =    scheduler.scale_model_input(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			)

              __lowercase						:     Optional[int]		      =    model(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			)

              __lowercase						:     Dict		      =    scheduler.step(__SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			,    __SCREAMING_SNAKE_CASE			,    generator=__SCREAMING_SNAKE_CASE			)
              __lowercase						:     Optional[Any]		      =    output.prev_sample

          __lowercase						:     Tuple		      =    torch.sum(torch.abs(__SCREAMING_SNAKE_CASE			)			)
          __lowercase						:     Optional[Any]		      =    torch.mean(torch.abs(__SCREAMING_SNAKE_CASE			)			)

          assert abs(result_sum.item() - 152.3192			) < 1E-2
          assert abs(result_mean.item() - 0.19_83			) < 1E-3




from __future__ import annotations

from math import pi, pow


def       UpperCAmelCase_					(  __lowerCAmelCase		)	->  float:
    if side_length < 0:
        raise ValueError('''vol_cube() only accepts non-negative values'''		)
    return pow(__lowerCAmelCase		,   3		)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or radius < 0:
        raise ValueError('''vol_spherical_cap() only accepts non-negative values'''		)
    # Volume is 1/3 pi * height squared * (3 * radius - height)
    return 1 / 3 * pi * pow(__lowerCAmelCase		,   2		) * (3 * radius - height)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if radius_a < 0 or radius_a < 0 or centers_distance < 0:
        raise ValueError('''vol_spheres_intersect() only accepts non-negative values'''		)
    if centers_distance == 0:
        return vol_sphere(min(__lowerCAmelCase		,   __lowerCAmelCase		)		)

    __lowercase						:     Dict		      =    (
        (radius_a - radius_a + centers_distance)
        * (radius_a + radius_a - centers_distance)
        / (2 * centers_distance)
    )
    __lowercase						:     Optional[int]		      =    (
        (radius_a - radius_a + centers_distance)
        * (radius_a + radius_a - centers_distance)
        / (2 * centers_distance)
    )

    return vol_spherical_cap(__lowerCAmelCase		,   __lowerCAmelCase		) + vol_spherical_cap(__lowerCAmelCase		,   __lowerCAmelCase		)


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

    if radius_a <= 0 or radius_a <= 0 or centers_distance < 0:
        raise ValueError(
            '''vol_spheres_union() only accepts non-negative values, non-zero radius'''		)

    if centers_distance == 0:
        return vol_sphere(max(__lowerCAmelCase		,   __lowerCAmelCase		)		)

    return (
        vol_sphere(__lowerCAmelCase		)
        + vol_sphere(__lowerCAmelCase		)
        - vol_spheres_intersect(__lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)
    )


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if width < 0 or height < 0 or length < 0:
        raise ValueError('''vol_cuboid() only accepts non-negative values'''		)
    return float(width * height * length		)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or area_of_base < 0:
        raise ValueError('''vol_cone() only accepts non-negative values'''		)
    return area_of_base * height / 3.0


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or radius < 0:
        raise ValueError('''vol_right_circ_cone() only accepts non-negative values'''		)
    return pi * pow(__lowerCAmelCase		,   2		) * height / 3.0


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or area_of_base < 0:
        raise ValueError('''vol_prism() only accepts non-negative values'''		)
    return float(area_of_base * height		)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or area_of_base < 0:
        raise ValueError('''vol_pyramid() only accepts non-negative values'''		)
    return area_of_base * height / 3.0


def       UpperCAmelCase_					(  __lowerCAmelCase		)	->  float:
    if radius < 0:
        raise ValueError('''vol_sphere() only accepts non-negative values'''		)
    # Volume is 4/3 * pi * radius cubed
    return 4 / 3 * pi * pow(__lowerCAmelCase		,   3		)


def       UpperCAmelCase_					(  __lowerCAmelCase		)	->  float:
    if radius < 0:
        raise ValueError('''vol_hemisphere() only accepts non-negative values'''		)
    # Volume is radius cubed * pi * 2/3
    return pow(__lowerCAmelCase		,   3		) * pi * 2 / 3


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or radius < 0:
        raise ValueError('''vol_circular_cylinder() only accepts non-negative values'''		)
    # Volume is radius squared * height * pi
    return pow(__lowerCAmelCase		,   2		) * height * pi


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    # Volume - (outer_radius squared - inner_radius squared) * pi * height
    if inner_radius < 0 or outer_radius < 0 or height < 0:
        raise ValueError(
            '''vol_hollow_circular_cylinder() only accepts non-negative values'''		)
    if outer_radius <= inner_radius:
        raise ValueError('''outer_radius must be greater than inner_radius'''		)
    return pi * (pow(__lowerCAmelCase		,   2		) - pow(__lowerCAmelCase		,   2		)) * height


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    # Volume is 1/3 * pi * height *
    #           (radius_1 squared + radius_2 squared + radius_1 * radius_2)
    if radius_a < 0 or radius_a < 0 or height < 0:
        raise ValueError('''vol_conical_frustum() only accepts non-negative values'''		)
    return (
        1
        / 3
        * pi
        * height
        * (pow(__lowerCAmelCase		,   2		) + pow(__lowerCAmelCase		,   2		) + radius_a * radius_a)
    )


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if torus_radius < 0 or tube_radius < 0:
        raise ValueError('''vol_torus() only accepts non-negative values'''		)
    return 2 * pow(__lowerCAmelCase		,   2		) * torus_radius * pow(__lowerCAmelCase		,   2		)


def       UpperCAmelCase_					(  )	->  Optional[Any]:
    print('''Volumes:'''		)
    print(F'Cube: {vol_cube(2		) = }'		)  # = 8
    print(F'Cuboid: {vol_cuboid(2		,   2		,   2		) = }'		)  # = 8
    print(F'Cone: {vol_cone(2		,   2		) = }'		)  # ~= 1.33
    print(F'Right Circular Cone: {vol_right_circ_cone(2		,   2		) = }'		)  # ~= 8.38
    print(F'Prism: {vol_prism(2		,   2		) = }'		)  # = 4
    print(F'Pyramid: {vol_pyramid(2		,   2		) = }'		)  # ~= 1.33
    print(F'Sphere: {vol_sphere(2		) = }'		)  # ~= 33.5
    print(F'Hemisphere: {vol_hemisphere(2		) = }'		)  # ~= 16.75
    print(F'Circular Cylinder: {vol_circular_cylinder(2		,   2		) = }'		)  # ~= 25.1
    print(F'Torus: {vol_torus(2		,   2		) = }'		)  # ~= 157.9
    print(F'Conical Frustum: {vol_conical_frustum(2		,   2		,   4		) = }'		)  # ~= 58.6
    print(F'Spherical cap: {vol_spherical_cap(1		,   2		) = }'		)  # ~= 5.24
    print(F'Spheres intersetion: {vol_spheres_intersect(2		,   2		,   1		) = }'		)  # ~= 21.21
    print(F'Spheres union: {vol_spheres_union(2		,   2		,   1		) = }'		)  # ~= 45.81
    print(
        F'Hollow Circular Cylinder: {vol_hollow_circular_cylinder(1		,   2		,   3		) = }'		)  # ~= 28.3


if __name__ == "__main__":
 main()


