



'''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 				_lowercase(						self					)    ->    List[str]:
								torch.manual_seed(0					)
								UpperCAmelCase  :	Tuple							  =	UNetaDModel(
								    block_out_channels=(32, 64)	,	layers_per_block=2	,	sample_size=32	,	in_channels=3	,	out_channels=3	,	down_block_types=("""DownBlock2D""", """AttnDownBlock2D""")	,	up_block_types=("""AttnUpBlock2D""", """UpBlock2D""")	,	)
								return model






	def 				_lowercase(						self					)    ->    Dict:
								UpperCAmelCase  :	Tuple							  =	self.dummy_uncond_unet
								UpperCAmelCase  :	Dict							  =	ScoreSdeVeScheduler()

								UpperCAmelCase  :	int							  =	ScoreSdeVePipeline(unet=A	,	scheduler=A					)
								sde_ve.to(A					)
								sde_ve.set_progress_bar_config(disable=A					)

								UpperCAmelCase  :	Tuple							  =	torch.manual_seed(0					)
								UpperCAmelCase  :	Any							  =	sde_ve(num_inference_steps=2	,	output_type="""numpy"""	,	generator=A					).images

								UpperCAmelCase  :	Optional[int]							  =	torch.manual_seed(0					)
								UpperCAmelCase  :	Dict							  =	sde_ve(num_inference_steps=2	,	output_type="""numpy"""	,	generator=A	,	return_dict=A					)[
								    0
								]

								UpperCAmelCase  :	Union[str, Any]							  =	image[0, -3:, -3:, -1]
								UpperCAmelCase  :	str							  =	image_from_tuple[0, -3:, -3:, -1]

								assert image.shape == (1, 32, 32, 3)
								UpperCAmelCase  :	Dict							  =	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 				_lowercase(						self					)    ->    int:
								UpperCAmelCase  :	List[str]							  =	"""google/ncsnpp-church-256"""
								UpperCAmelCase  :	Dict							  =	UNetaDModel.from_pretrained(A					)

								UpperCAmelCase  :	List[str]							  =	ScoreSdeVeScheduler.from_pretrained(A					)

								UpperCAmelCase  :	Any							  =	ScoreSdeVePipeline(unet=A	,	scheduler=A					)
								sde_ve.to(A					)
								sde_ve.set_progress_bar_config(disable=A					)

								UpperCAmelCase  :	Tuple							  =	torch.manual_seed(0					)
								UpperCAmelCase  :	Optional[Any]							  =	sde_ve(num_inference_steps=10	,	output_type="""numpy"""	,	generator=A					).images

								UpperCAmelCase  :	Optional[int]							  =	image[0, -3:, -3:, -1]

								assert image.shape == (1, 256, 256, 3)

								UpperCAmelCase  :	List[Any]							  =	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'''




a     :    Tuple      						=					[sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]



def    __lowerCamelCase						(      _lowercase	)   ->    int:
							UpperCAmelCase  :	str							  =	0
							while number:
														# Increased Speed Slightly by checking every 5 digits together.
														sum_of_digits_squared += DIGITS_SQUARED[number % 1_0_0_0_0_0]
														number //= 1_0_0_0_0_0

							return sum_of_digits_squared


# There are 2 Chains made,
# One ends with 89 with the chain member 58 being the one which when declared first,
# there will be the least number of iterations for all the members to be checked.

# The other one ends with 1 and has only one element 1.

# So 58 and 1 are chosen to be declared at the starting.

# Changed dictionary to an array to quicken the solution
a     :    list[bool | None]      						=					[None] * 1_0_0_0_0_0_0_0
a     :    Optional[Any]      						=					True
a     :    List[Any]      						=					False



def    __lowerCamelCase						(      _lowercase	)   ->    bool:

							if CHAINS[number - 1] is not None:
														return CHAINS[number - 1]  # type: ignore

							UpperCAmelCase  :	List[str]							  =	chain(next_number(_lowercase	)	)
							UpperCAmelCase  :	Tuple							  =	number_chain

							while number < 1_0_0_0_0_0_0_0:
														UpperCAmelCase  :	List[str]							  =	number_chain
														number *= 1_0

							return number_chain



def    __lowerCamelCase						(      _lowercase = 1_0_0_0_0_0_0_0	)   ->    int:
							for i in range(1			,       _lowercase	):
														if CHAINS[i] is None:
																					chain(i + 1	)

							return CHAINS[:number].count(_lowercase	)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							print(F'''{solution() = }''')

