

'''simple docstring'''

import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest







class lowerCamelCase      (						_SCREAMING_SNAKE_CASE							):
				snake_case_           =   (VQDiffusionScheduler,)

				def 				_lowerCamelCase						(					self,	**lowercase_   )						->       Tuple:
					snake_case							 =				{
					    'num_vec_classes': 4097,
					    'num_train_timesteps': 100,
					}

					config.update(**__A   )
					return config

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Any:
					snake_case							 =				4
					snake_case							 =				8
					snake_case							 =				8

					snake_case							 =				torch.randint(0,	__A,	(batch_size, height * width)   )

					return sample

				@property
				def 				_lowerCamelCase						(					self   )						->       Optional[Any]:
					assert False

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       Tuple:
					def model(lowercase_,	lowercase_,	*lowercase_   ):
						snake_case , snake_case							 =				sample.shape
						snake_case							 =				torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)   )
						snake_case							 =				F.log_softmax(logits.double(),	dim=1   ).float()
						return return_value

					return model

				def 				_lowerCamelCase						(					self   )						->       Dict:
					for timesteps in [2, 5, 100, 1000]:
						self.check_over_configs(num_train_timesteps=__A   )

				def 				_lowerCamelCase						(					self   )						->       List[str]:
					for num_vec_classes in [5, 100, 1000, 4000]:
						self.check_over_configs(num_vec_classes=__A   )

				def 				_lowerCamelCase						(					self   )						->       List[str]:
					for t in [0, 50, 99]:
						self.check_over_forward(time_step=__A   )






				def 				_lowerCamelCase						(					self   )						->       str:
					pass








'''simple docstring'''

lowerCAmelCase_						   =			{0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

lowerCAmelCase_						   =			{0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}

def     __magic_name__       ( A					,   A					,   A							)			->		list:
	snake_case							 =				True
	snake_case							 =				[]

	for neighbour in graph[vert]:
		if not visited[neighbour]:
			connected_verts += dfs(A					,   A					,   A							)

	return [vert, *connected_verts]

def     __magic_name__       ( A							)			->		list:
	snake_case							 =				len(A							)
	snake_case							 =				graph_size * [False]
	snake_case							 =				[]

	for i in range(A							):
		if not visited[i]:
			snake_case							 =				dfs(A					,   A					,   A							)
			components_list.append(A							)

	return components_list


if __name__ == "__main__":
						import doctest

						doctest.testmod()





