



class 			_lowercase							:





	"""simple docstring"""




	def __init__(self	, lowerCamelCase_	):
						"""simple docstring"""

						a        =     data
						a        =     None
						a        =     None




	def __str__(self	):
						"""simple docstring"""

						return F'''{self.data}'''




class 			_lowercase							:





	"""simple docstring"""




	def __init__(self	):
						"""simple docstring"""

						a        =     None
						a        =     None




	def __iter__(self	):
						"""simple docstring"""

						a        =     self.head
						while node:
											yield node.data
											a        =     node.next




	def __str__(self	):
						"""simple docstring"""

						return "->".join([str(lowerCamelCase_	) for item in self]	)




	def __len__(self	):
						"""simple docstring"""

						return sum(1 for _ in self	)




	def   UpperCamelCase_ (self	, lowerCamelCase_	):
						"""simple docstring"""

						self.insert_at_nth(0	, lowerCamelCase_	)




	def   UpperCamelCase_ (self	, lowerCamelCase_	):
						"""simple docstring"""

						self.insert_at_nth(len(self	)	, lowerCamelCase_	)




	def   UpperCamelCase_ (self	, lowerCamelCase_	, lowerCamelCase_	):
						"""simple docstring"""

						a        =     len(self	)

						if not 0 <= index <= length:
											raise IndexError("list index out of range"	)
						a        =     Node(lowerCamelCase_	)
						if self.head is None:
											a        =     a        =     new_node
						elif index == 0:
											a        =     new_node
											a        =     self.head
											a        =     new_node
						elif index == length:
											a        =     new_node
											a        =     self.tail
											a        =     new_node
						else:
											a        =     self.head
											for _ in range(0	, lowerCamelCase_	):
																a        =     temp.next
											a        =     new_node
											a        =     temp.previous
											a        =     temp
											a        =     new_node




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						return self.delete_at_nth(0	)




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						return self.delete_at_nth(len(self	) - 1	)




	def   UpperCamelCase_ (self	, lowerCamelCase_	):
						"""simple docstring"""

						a        =     len(self	)

						if not 0 <= index <= length - 1:
											raise IndexError("list index out of range"	)
						a        =     self.head  # default first node
						if length == 1:
											a        =     a        =     None
						elif index == 0:
											a        =     self.head.next
											a        =     None
						elif index == length - 1:
											a        =     self.tail
											a        =     self.tail.previous
											a        =     None
						else:
											a        =     self.head
											for _ in range(0	, lowerCamelCase_	):
																a        =     temp.next
											a        =     temp
											a        =     temp.previous
											a        =     temp.next
						return delete_node.data




	def   UpperCamelCase_ (self	, lowerCamelCase_	):
						"""simple docstring"""

						a        =     self.head

						while current.data != data:  # Find the position to delete
											if current.next:
																a        =     current.next
											else:  # We have reached the end an no value matches
																raise ValueError("No data matching given value"	)

						if current == self.head:
											self.delete_head()

						elif current == self.tail:
											self.delete_tail()

						else:  # Before: 1 <--> 2(current) <--> 3
											a        =     current.next  # 1 --> 3
											a        =     current.previous  # 1 <--> 3
						return data




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						return len(self	) == 0






def 					a(   )	-> None:
					"""simple docstring"""





					a        =     DoublyLinkedList()
					assert linked_list.is_empty() is True
					assert str(A ) == ""

					try:
										linked_list.delete_head()
										raise AssertionError  # This should not happen.
					except IndexError:
										assert True  # This should happen.

					try:
										linked_list.delete_tail()
										raise AssertionError  # This should not happen.
					except IndexError:
										assert True  # This should happen.

					for i in range(10 ):
										assert len(A ) == i
										linked_list.insert_at_nth(A				,  i + 1 )
					assert str(A ) == "->".join(str(A ) for i in range(1				,  11 ) )

					linked_list.insert_at_head(0 )
					linked_list.insert_at_tail(11 )
					assert str(A ) == "->".join(str(A ) for i in range(0				,  12 ) )

					assert linked_list.delete_head() == 0
					assert linked_list.delete_at_nth(9 ) == 10
					assert linked_list.delete_tail() == 11
					assert len(A ) == 9
					assert str(A ) == "->".join(str(A ) for i in range(1				,  10 ) )


if __name__ == "__main__":
				from doctest import testmod

				testmod()





import torch

from diffusers import EulerAncestralDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest



class 			_lowercase							(     lowerCAmelCase			):





	"""simple docstring"""
	__A					=							(EulerAncestralDiscreteScheduler,)
	__A					=							10




	def   UpperCamelCase_ (self	, **lowerCamelCase_	):
						"""simple docstring"""

						a        =     {
						    "num_train_timesteps": 1100,
						    "beta_start": 0.0001,
						    "beta_end": 0.02,
						    "beta_schedule": "linear",
						}

						config.update(**lowerCamelCase_	)
						return config




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						for timesteps in [10, 50, 100, 1000]:
											self.check_over_configs(num_train_timesteps=lowerCamelCase_	)




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						for beta_start, beta_end in zip([0.0_0001, 0.0001, 0.001]	, [0.0002, 0.002, 0.02]	):
											self.check_over_configs(beta_start=lowerCamelCase_	, beta_end=lowerCamelCase_	)




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						for schedule in ["linear", "scaled_linear"]:
											self.check_over_configs(beta_schedule=lowerCamelCase_	)




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						for prediction_type in ["epsilon", "v_prediction"]:
											self.check_over_configs(prediction_type=lowerCamelCase_	)




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						a        =     self.scheduler_classes[0]
						a        =     self.get_scheduler_config()
						a        =     scheduler_class(**lowerCamelCase_	)

						scheduler.set_timesteps(self.num_inference_steps	)

						a        =     torch.manual_seed(0	)

						a        =     self.dummy_model()
						a        =     self.dummy_sample_deter * scheduler.init_noise_sigma.cpu()
						a        =     sample.to(lowerCamelCase_	)

						for i, t in enumerate(scheduler.timesteps	):
											a        =     scheduler.scale_model_input(lowerCamelCase_	, lowerCamelCase_	)

											a        =     model(lowerCamelCase_	, lowerCamelCase_	)

											a        =     scheduler.step(lowerCamelCase_	, lowerCamelCase_	, lowerCamelCase_	, generator=lowerCamelCase_	)
											a        =     output.prev_sample

						a        =     torch.sum(torch.abs(lowerCamelCase_	)	)
						a        =     torch.mean(torch.abs(lowerCamelCase_	)	)

						assert abs(result_sum.item() - 152.3192	) < 1E-2
						assert abs(result_mean.item() - 0.1983	) < 1E-3




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						a        =     self.scheduler_classes[0]
						a        =     self.get_scheduler_config(prediction_type="v_prediction"	)
						a        =     scheduler_class(**lowerCamelCase_	)

						scheduler.set_timesteps(self.num_inference_steps	)

						a        =     torch.manual_seed(0	)

						a        =     self.dummy_model()
						a        =     self.dummy_sample_deter * scheduler.init_noise_sigma
						a        =     sample.to(lowerCamelCase_	)

						for i, t in enumerate(scheduler.timesteps	):
											a        =     scheduler.scale_model_input(lowerCamelCase_	, lowerCamelCase_	)

											a        =     model(lowerCamelCase_	, lowerCamelCase_	)

											a        =     scheduler.step(lowerCamelCase_	, lowerCamelCase_	, lowerCamelCase_	, generator=lowerCamelCase_	)
											a        =     output.prev_sample

						a        =     torch.sum(torch.abs(lowerCamelCase_	)	)
						a        =     torch.mean(torch.abs(lowerCamelCase_	)	)

						assert abs(result_sum.item() - 108.4439	) < 1E-2
						assert abs(result_mean.item() - 0.1412	) < 1E-3




	def   UpperCamelCase_ (self	):
						"""simple docstring"""

						a        =     self.scheduler_classes[0]
						a        =     self.get_scheduler_config()
						a        =     scheduler_class(**lowerCamelCase_	)

						scheduler.set_timesteps(self.num_inference_steps	, device=lowerCamelCase_	)
						a        =     torch.manual_seed(0	)

						a        =     self.dummy_model()
						a        =     self.dummy_sample_deter * scheduler.init_noise_sigma.cpu()
						a        =     sample.to(lowerCamelCase_	)

						for t in scheduler.timesteps:
											a        =     scheduler.scale_model_input(lowerCamelCase_	, lowerCamelCase_	)

											a        =     model(lowerCamelCase_	, lowerCamelCase_	)

											a        =     scheduler.step(lowerCamelCase_	, lowerCamelCase_	, lowerCamelCase_	, generator=lowerCamelCase_	)
											a        =     output.prev_sample

						a        =     torch.sum(torch.abs(lowerCamelCase_	)	)
						a        =     torch.mean(torch.abs(lowerCamelCase_	)	)

						assert abs(result_sum.item() - 152.3192	) < 1E-2
						assert abs(result_mean.item() - 0.1983	) < 1E-3
