





'''simple docstring'''

import unittest

import numpy as np
import torch

from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()

class       UpperCAmelCase (						unittest.TestCase  ):




		@property
		def 				UpperCAmelCase__   (self      :	List[Any]				)					-> Optional[Any]:
						torch.manual_seed(0				)
						lowercase         = UNetaDModel(
						    block_out_channels=(3_2, 6_4)							,			layers_per_block=2							,			sample_size=3_2							,			in_channels=3							,			out_channels=3							,			down_block_types=("DownBlock2D", "AttnDownBlock2D")							,			up_block_types=("AttnUpBlock2D", "UpBlock2D")							,			)
						return model





		def 				UpperCAmelCase__   (self      :	Union[str, Any]				)					-> Optional[int]:
						lowercase         = self.dummy_uncond_unet
						lowercase         = ScoreSdeVeScheduler()

						lowercase         = ScoreSdeVePipeline(unet=_SCREAMING_SNAKE_CASE							,			scheduler=_SCREAMING_SNAKE_CASE				)
						sde_ve.to(_SCREAMING_SNAKE_CASE				)
						sde_ve.set_progress_bar_config(disable=_SCREAMING_SNAKE_CASE				)

						lowercase         = torch.manual_seed(0				)
						lowercase         = sde_ve(num_inference_steps=2							,			output_type="numpy"							,			generator=_SCREAMING_SNAKE_CASE				).images

						lowercase         = torch.manual_seed(0				)
						lowercase         = sde_ve(num_inference_steps=2							,			output_type="numpy"							,			generator=_SCREAMING_SNAKE_CASE							,			return_dict=_SCREAMING_SNAKE_CASE				)[
						    0
						]

						lowercase         = image[0, -3:, -3:, -1]
						lowercase         = image_from_tuple[0, -3:, -3:, -1]

						assert image.shape == (1, 3_2, 3_2, 3)
						lowercase         = np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]				)

						assert np.abs(image_slice.flatten() - expected_slice				).max() < 1e-2
						assert np.abs(image_from_tuple_slice.flatten() - expected_slice				).max() < 1e-2




@slow
@require_torch
class       UpperCAmelCase (						unittest.TestCase  ):




		def 				UpperCAmelCase__   (self      :	int				)					-> Optional[Any]:
						lowercase         = "google/ncsnpp-church-256"
						lowercase         = UNetaDModel.from_pretrained(_SCREAMING_SNAKE_CASE				)

						lowercase         = ScoreSdeVeScheduler.from_pretrained(_SCREAMING_SNAKE_CASE				)

						lowercase         = ScoreSdeVePipeline(unet=_SCREAMING_SNAKE_CASE							,			scheduler=_SCREAMING_SNAKE_CASE				)
						sde_ve.to(_SCREAMING_SNAKE_CASE				)
						sde_ve.set_progress_bar_config(disable=_SCREAMING_SNAKE_CASE				)

						lowercase         = torch.manual_seed(0				)
						lowercase         = sde_ve(num_inference_steps=1_0							,			output_type="numpy"							,			generator=_SCREAMING_SNAKE_CASE				).images

						lowercase         = image[0, -3:, -3:, -1]

						assert image.shape == (1, 2_5_6, 2_5_6, 3)

						lowercase         = np.array([0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0]				)

						assert np.abs(image_slice.flatten() - expected_slice				).max() < 1e-2











'''simple docstring'''

import functools







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				if not isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) or not all(isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) for day in days							):
								raise ValueError("The parameter days should be a list of integers"							)

				if len(lowerCAmelCase_							) != 3 or not all(isinstance(lowerCAmelCase_		,							lowerCAmelCase_							) for cost in costs							):
								raise ValueError("The parameter costs should be a list of three integers"							)

				if len(lowerCAmelCase_							) == 0:
								return 0

				if min(lowerCAmelCase_							) <= 0:
								raise ValueError("All days elements should be greater than 0"							)

				if max(lowerCAmelCase_							) >= 366:
								raise ValueError("All days elements should be less than 366"							)

				lowercase         = set(lowerCAmelCase_							)

				@functools.cache
				def dynamic_programming(lowerCAmelCase_							) -> int:
								if index > 365:
												return 0

								if index not in days_set:
												return dynamic_programming(index + 1							)

								return min(
								    costs[0] + dynamic_programming(index + 1							)		,							costs[1] + dynamic_programming(index + 7							)		,							costs[2] + dynamic_programming(index + 30							)		,							)

				return dynamic_programming(1							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()




