


"""simple docstring"""
import unittest

import torch

from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow


SCREAMING_SNAKE_CASE :    str									=				False



class 			_UpperCAmelCase (							unittest.TestCase				):






		'''simple docstring'''

		def 				SCREAMING_SNAKE_CASE  (self				,       a_=32					):





			'''simple docstring'''

			set_seed(0					)
			__snake_case	:						List[Any]						=				UNetaDModel(sample_size=lowercase_				,       in_channels=3				,       out_channels=3					)
			__snake_case	:						int						=				torch.optim.SGD(model.parameters()				,       lr=0.0001					)
			return model, optimizer



		@slow
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						List[str]						=				'cpu'  # ensure full determinism without setting the CUBLAS_WORKSPACE_CONFIG env variable
			__snake_case	:						Any						=				DDPMScheduler(
			    num_train_timesteps=10_00				,       beta_start=0.0001				,       beta_end=0.02				,       beta_schedule='''linear'''				,       clip_sample=lowercase_				,       )
			__snake_case	:						Dict						=				DDIMScheduler(
			    num_train_timesteps=10_00				,       beta_start=0.0001				,       beta_end=0.02				,       beta_schedule='''linear'''				,       clip_sample=lowercase_				,       )

			assert ddpm_scheduler.config.num_train_timesteps == ddim_scheduler.config.num_train_timesteps

			# shared batches for DDPM and DDIM
			set_seed(0					)
			__snake_case	:						Optional[Any]						=				[torch.randn((4, 3, 32, 32)					).clip(-1				,       1					).to(lowercase_					) for _ in range(4					)]
			__snake_case	:						List[Any]						=				[torch.randn((4, 3, 32, 32)					).to(lowercase_					) for _ in range(4					)]
			__snake_case	:						List[Any]						=				[torch.randint(0				,       10_00				,       (4,)					).long().to(lowercase_					) for _ in range(4					)]

			# train with a DDPM scheduler
			__snake_case	:						str						=				self.get_model_optimizer(resolution=32					)
			model.train().to(lowercase_					)
			for i in range(4					):
				optimizer.zero_grad()
				__snake_case	:						Any						=				ddpm_scheduler.add_noise(clean_images[i]				,       noise[i]				,       timesteps[i]					)
				__snake_case	:						Any						=				model(lowercase_				,       timesteps[i]					).sample
				__snake_case	:						List[str]						=				torch.nn.functional.mse_loss(lowercase_				,       noise[i]					)
				loss.backward()
				optimizer.step()
			del model, optimizer

			# recreate the model and optimizer, and retry with DDIM
			__snake_case	:						Tuple						=				self.get_model_optimizer(resolution=32					)
			model.train().to(lowercase_					)
			for i in range(4					):
				optimizer.zero_grad()
				__snake_case	:						List[str]						=				ddim_scheduler.add_noise(clean_images[i]				,       noise[i]				,       timesteps[i]					)
				__snake_case	:						List[str]						=				model(lowercase_				,       timesteps[i]					).sample
				__snake_case	:						Optional[int]						=				torch.nn.functional.mse_loss(lowercase_				,       noise[i]					)
				loss.backward()
				optimizer.step()
			del model, optimizer

			self.assertTrue(torch.allclose(lowercase_				,       lowercase_				,       atol=1E-5					)					)
			self.assertTrue(torch.allclose(lowercase_				,       lowercase_				,       atol=1E-5					)					)









# using dfs for finding eulerian path traversal




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Any		,			SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      Optional[int]=None     ):
       '''simple docstring'''





       _lowerCamelCase       :		Optional[Any]		=(path or []) + [u]
       for v in graph[u]:
              if visited_edge[u][v] is False:
                     _lowerCamelCase	,     _lowerCamelCase       :		Dict		=True, True
                     _lowerCamelCase       :		Optional[Any]		=dfs(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       return path




def 	a_      (    SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      Optional[Any]     ):
       '''simple docstring'''





       _lowerCamelCase       :		Union[str, Any]		=0
       _lowerCamelCase       :		Union[str, Any]		=-1
       for i in range(SCREAMING_SNAKE_CASE__     ):
              if i not in graph.keys():
                     continue
              if len(graph[i]     ) % 2 == 1:
                     odd_degree_nodes += 1
                     _lowerCamelCase       :		Tuple		=i
       if odd_degree_nodes == 0:
              return 1, odd_node
       if odd_degree_nodes == 2:
              return 2, odd_node
       return 3, odd_node




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Union[str, Any]		,			SCREAMING_SNAKE_CASE__					:      Any     ):
       '''simple docstring'''





       _lowerCamelCase       :		Tuple		=[[False for _ in range(max_node + 1     )] for _ in range(max_node + 1     )]
       _lowerCamelCase	,     _lowerCamelCase       :		Optional[int]		=check_circuit_or_path(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       if check == 3:
              print('graph is not Eulerian'     )
              print('no path'     )
              return
       _lowerCamelCase       :		Any		=1
       if check == 2:
              _lowerCamelCase       :		Tuple		=odd_node
              print('graph has a Euler path'     )
       if check == 1:
              print('graph has a Euler cycle'     )
       _lowerCamelCase       :		int		=dfs(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       print(SCREAMING_SNAKE_CASE__     )




def 	a_      (    ):
       '''simple docstring'''





       _lowerCamelCase       :		Union[str, Any]		={1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
       _lowerCamelCase       :		str		={1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
       _lowerCamelCase       :		List[Any]		={1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
       _lowerCamelCase       :		Any		={1: [2, 3], 2: [1, 3], 3: [1, 2]}
       _lowerCamelCase       :		Dict		={
           1: [],
           2: []
           # all degree is zero
       }
       _lowerCamelCase       :		str		=10
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )


if __name__ == "__main__":
 main()


