

"""simple docstring"""





import tempfile

import torch

from diffusers import (
    DEISMultistepScheduler,
    DPMSolverMultistepScheduler,
    DPMSolverSinglestepScheduler,
    UniPCMultistepScheduler,
)

from .test_schedulers import SchedulerCommonTest







class 				SCREAMING_SNAKE_CASE					(		a_       ):






					"""simple docstring"""



					lowercase__				 =       (DEISMultistepScheduler,)
					lowercase__				 =       (("num_inference_steps", 25),)







					def        __lowerCAmelCase (       self			:				Optional[Any]   ,**lowercase_			:				List[str]		):
						lowerCAmelCase__	:						List[Any]  				=	{
						    '''num_train_timesteps''': 1_0_0_0,
						    '''beta_start''': 0.0001,
						    '''beta_end''': 0.02,
						    '''beta_schedule''': '''linear''',
						    '''solver_order''': 2,
						}

						config.update(**lowercase_		)
						return config







					def        __lowerCAmelCase (       self			:				Union[str, Any]   ,lowercase_			:				Optional[int]=0   ,**lowercase_			:				Any		):
						lowerCAmelCase__	:						List[Any]  				=	dict(self.forward_default_kwargs		)
						lowerCAmelCase__	:						Union[str, Any]  				=	kwargs.pop('''num_inference_steps'''   ,lowercase_		)
						lowerCAmelCase__	:						Union[str, Any]  				=	self.dummy_sample
						lowerCAmelCase__	:						str  				=	0.1 * sample
						lowerCAmelCase__	:						Tuple  				=	[residual + 0.2, residual + 0.15, residual + 0.10]

						for scheduler_class in self.scheduler_classes:
							lowerCAmelCase__	:						List[Any]  				=	self.get_scheduler_config(**lowercase_		)
							lowerCAmelCase__	:						Optional[Any]  				=	scheduler_class(**lowercase_		)
							scheduler.set_timesteps(lowercase_		)
							# copy over dummy past residuals
							lowerCAmelCase__	:						str  				=	dummy_past_residuals[: scheduler.config.solver_order]

							with tempfile.TemporaryDirectory() as tmpdirname:
								scheduler.save_config(lowercase_		)
								lowerCAmelCase__	:						Optional[Any]  				=	scheduler_class.from_pretrained(lowercase_		)
								new_scheduler.set_timesteps(lowercase_		)
								# copy over dummy past residuals
								lowerCAmelCase__	:						Optional[int]  				=	dummy_past_residuals[: new_scheduler.config.solver_order]

							lowerCAmelCase__				,lowerCAmelCase__	:						int  				=	sample, sample
							for t in range(lowercase_   ,time_step + scheduler.config.solver_order + 1		):
								lowerCAmelCase__	:						Tuple  				=	scheduler.step(lowercase_   ,lowercase_   ,lowercase_   ,**lowercase_		).prev_sample
								lowerCAmelCase__	:						int  				=	new_scheduler.step(lowercase_   ,lowercase_   ,lowercase_   ,**lowercase_		).prev_sample

								assert torch.sum(torch.abs(output - new_output		)		) < 1E-5, "Scheduler outputs are not identical"







					def        __lowerCAmelCase (       self			:				List[str]		):
						pass







					def        __lowerCAmelCase (       self			:				Union[str, Any]   ,lowercase_			:				str=0   ,**lowercase_			:				List[Any]		):
						lowerCAmelCase__	:						List[Any]  				=	dict(self.forward_default_kwargs		)
						lowerCAmelCase__	:						Union[str, Any]  				=	kwargs.pop('''num_inference_steps'''   ,lowercase_		)
						lowerCAmelCase__	:						Optional[int]  				=	self.dummy_sample
						lowerCAmelCase__	:						Any  				=	0.1 * sample
						lowerCAmelCase__	:						Tuple  				=	[residual + 0.2, residual + 0.15, residual + 0.10]

						for scheduler_class in self.scheduler_classes:
							lowerCAmelCase__	:						str  				=	self.get_scheduler_config()
							lowerCAmelCase__	:						str  				=	scheduler_class(**lowercase_		)
							scheduler.set_timesteps(lowercase_		)

							# copy over dummy past residuals (must be after setting timesteps)
							lowerCAmelCase__	:						Tuple  				=	dummy_past_residuals[: scheduler.config.solver_order]

							with tempfile.TemporaryDirectory() as tmpdirname:
								scheduler.save_config(lowercase_		)
								lowerCAmelCase__	:						Any  				=	scheduler_class.from_pretrained(lowercase_		)
								# copy over dummy past residuals
								new_scheduler.set_timesteps(lowercase_		)

								# copy over dummy past residual (must be after setting timesteps)
								lowerCAmelCase__	:						Optional[Any]  				=	dummy_past_residuals[: new_scheduler.config.solver_order]

							lowerCAmelCase__	:						Tuple  				=	scheduler.step(lowercase_   ,lowercase_   ,lowercase_   ,**lowercase_		).prev_sample
							lowerCAmelCase__	:						Any  				=	new_scheduler.step(lowercase_   ,lowercase_   ,lowercase_   ,**lowercase_		).prev_sample

							assert torch.sum(torch.abs(output - new_output		)		) < 1E-5, "Scheduler outputs are not identical"







					def        __lowerCAmelCase (       self			:				Dict   ,lowercase_			:				str=None   ,**lowercase_			:				str		):
						if scheduler is None:
							lowerCAmelCase__	:						Tuple  				=	self.scheduler_classes[0]
							lowerCAmelCase__	:						List[Any]  				=	self.get_scheduler_config(**lowercase_		)
							lowerCAmelCase__	:						Tuple  				=	scheduler_class(**lowercase_		)

						lowerCAmelCase__	:						Tuple  				=	self.scheduler_classes[0]
						lowerCAmelCase__	:						Optional[int]  				=	self.get_scheduler_config(**lowercase_		)
						lowerCAmelCase__	:						List[str]  				=	scheduler_class(**lowercase_		)

						lowerCAmelCase__	:						Union[str, Any]  				=	1_0
						lowerCAmelCase__	:						Dict  				=	self.dummy_model()
						lowerCAmelCase__	:						int  				=	self.dummy_sample_deter
						scheduler.set_timesteps(lowercase_		)

						for i, t in enumerate(scheduler.timesteps		):
							lowerCAmelCase__	:						Optional[int]  				=	model(lowercase_   ,lowercase_		)
							lowerCAmelCase__	:						int  				=	scheduler.step(lowercase_   ,lowercase_   ,lowercase_		).prev_sample

						return sample







					def        __lowerCAmelCase (       self			:				Dict		):
						lowerCAmelCase__	:						Union[str, Any]  				=	dict(self.forward_default_kwargs		)

						lowerCAmelCase__	:						Dict  				=	kwargs.pop('''num_inference_steps'''   ,lowercase_		)

						for scheduler_class in self.scheduler_classes:
							lowerCAmelCase__	:						str  				=	self.get_scheduler_config()
							lowerCAmelCase__	:						Optional[int]  				=	scheduler_class(**lowercase_		)

							lowerCAmelCase__	:						int  				=	self.dummy_sample
							lowerCAmelCase__	:						int  				=	0.1 * sample

							if num_inference_steps is not None and hasattr(lowercase_   ,'''set_timesteps'''		):
								scheduler.set_timesteps(lowercase_		)
							elif num_inference_steps is not None and not hasattr(lowercase_   ,'''set_timesteps'''		):
								lowerCAmelCase__	:						Tuple  				=	num_inference_steps

							# copy over dummy past residuals (must be done after set_timesteps)
							lowerCAmelCase__	:						Dict  				=	[residual + 0.2, residual + 0.15, residual + 0.10]
							lowerCAmelCase__	:						int  				=	dummy_past_residuals[: scheduler.config.solver_order]

							lowerCAmelCase__	:						str  				=	scheduler.timesteps[5]
							lowerCAmelCase__	:						Optional[Any]  				=	scheduler.timesteps[6]

							lowerCAmelCase__	:						Dict  				=	scheduler.step(lowercase_   ,lowercase_   ,lowercase_   ,**lowercase_		).prev_sample
							lowerCAmelCase__	:						List[str]  				=	scheduler.step(lowercase_   ,lowercase_   ,lowercase_   ,**lowercase_		).prev_sample

							self.assertEqual(output_a.shape   ,sample.shape		)
							self.assertEqual(output_a.shape   ,output_a.shape		)







					def        __lowerCAmelCase (       self			:				int		):
						# make sure that iterating over schedulers with same config names gives same results
						# for defaults
						lowerCAmelCase__	:						str  				=	DEISMultistepScheduler(**self.get_scheduler_config()		)
						lowerCAmelCase__	:						str  				=	self.full_loop(scheduler=lowercase_		)
						lowerCAmelCase__	:						Optional[int]  				=	torch.mean(torch.abs(lowercase_		)		)

						assert abs(result_mean.item() - 0.2_3916		) < 1E-3

						lowerCAmelCase__	:						Dict  				=	DPMSolverSinglestepScheduler.from_config(scheduler.config		)
						lowerCAmelCase__	:						List[Any]  				=	DPMSolverMultistepScheduler.from_config(scheduler.config		)
						lowerCAmelCase__	:						str  				=	UniPCMultistepScheduler.from_config(scheduler.config		)
						lowerCAmelCase__	:						Dict  				=	DEISMultistepScheduler.from_config(scheduler.config		)

						lowerCAmelCase__	:						List[Any]  				=	self.full_loop(scheduler=lowercase_		)
						lowerCAmelCase__	:						int  				=	torch.mean(torch.abs(lowercase_		)		)

						assert abs(result_mean.item() - 0.2_3916		) < 1E-3







					def        __lowerCAmelCase (       self			:				Optional[int]		):
						for timesteps in [2_5, 5_0, 1_0_0, 9_9_9, 1_0_0_0]:
							self.check_over_configs(num_train_timesteps=lowercase_		)







					def        __lowerCAmelCase (       self			:				Tuple		):
						self.check_over_configs(thresholding=lowercase_		)
						for order in [1, 2, 3]:
							for solver_type in ["logrho"]:
								for threshold in [0.5, 1.0, 2.0]:
									for prediction_type in ["epsilon", "sample"]:
										self.check_over_configs(
										    thresholding=lowercase_   ,prediction_type=lowercase_   ,sample_max_value=lowercase_   ,algorithm_type='''deis'''   ,solver_order=lowercase_   ,solver_type=lowercase_   ,)







					def        __lowerCAmelCase (       self			:				List[str]		):
						for prediction_type in ["epsilon", "v_prediction"]:
							self.check_over_configs(prediction_type=lowercase_		)







					def        __lowerCAmelCase (       self			:				List[Any]		):
						for algorithm_type in ["deis"]:
							for solver_type in ["logrho"]:
								for order in [1, 2, 3]:
									for prediction_type in ["epsilon", "sample"]:
										self.check_over_configs(
										    solver_order=lowercase_   ,solver_type=lowercase_   ,prediction_type=lowercase_   ,algorithm_type=lowercase_   ,)
										lowerCAmelCase__	:						str  				=	self.full_loop(
										    solver_order=lowercase_   ,solver_type=lowercase_   ,prediction_type=lowercase_   ,algorithm_type=lowercase_   ,)
										assert not torch.isnan(lowercase_		).any(), "Samples have nan numbers"







					def        __lowerCAmelCase (       self			:				List[Any]		):
						self.check_over_configs(lower_order_final=lowercase_		)
						self.check_over_configs(lower_order_final=lowercase_		)







					def        __lowerCAmelCase (       self			:				Union[str, Any]		):
						for num_inference_steps in [1, 2, 3, 5, 1_0, 5_0, 1_0_0, 9_9_9, 1_0_0_0]:
							self.check_over_forward(num_inference_steps=lowercase_   ,time_step=0		)







					def        __lowerCAmelCase (       self			:				Any		):
						lowerCAmelCase__	:						Optional[Any]  				=	self.full_loop()
						lowerCAmelCase__	:						Any  				=	torch.mean(torch.abs(lowercase_		)		)

						assert abs(result_mean.item() - 0.2_3916		) < 1E-3







					def        __lowerCAmelCase (       self			:				int		):
						lowerCAmelCase__	:						Tuple  				=	self.full_loop(prediction_type='''v_prediction'''		)
						lowerCAmelCase__	:						Optional[int]  				=	torch.mean(torch.abs(lowercase_		)		)

						assert abs(result_mean.item() - 0.091		) < 1E-3







					def        __lowerCAmelCase (       self			:				str		):
						lowerCAmelCase__	:						Union[str, Any]  				=	self.scheduler_classes[0]
						lowerCAmelCase__	:						Union[str, Any]  				=	self.get_scheduler_config(thresholding=lowercase_   ,dynamic_thresholding_ratio=0		)
						lowerCAmelCase__	:						Optional[Any]  				=	scheduler_class(**lowercase_		)

						lowerCAmelCase__	:						Optional[Any]  				=	1_0
						lowerCAmelCase__	:						Optional[Any]  				=	self.dummy_model()
						lowerCAmelCase__	:						str  				=	self.dummy_sample_deter.half()
						scheduler.set_timesteps(lowercase_		)

						for i, t in enumerate(scheduler.timesteps		):
							lowerCAmelCase__	:						List[Any]  				=	model(lowercase_   ,lowercase_		)
							lowerCAmelCase__	:						Optional[Any]  				=	scheduler.step(lowercase_   ,lowercase_   ,lowercase_		).prev_sample

						assert sample.dtype == torch.floataa







"""simple docstring"""





__UpperCamelCase  :      Optional[Any]							      =		[
    9_9_9,
    8_0_0,
    7_9_9,
    6_0_0,
    5_9_9,
    5_0_0,
    4_0_0,
    3_9_9,
    3_7_7,
    3_5_5,
    3_3_3,
    3_1_1,
    2_8_8,
    2_6_6,
    2_4_4,
    2_2_2,
    2_0_0,
    1_9_9,
    1_7_7,
    1_5_5,
    1_3_3,
    1_1_1,
    8_8,
    6_6,
    4_4,
    2_2,
    0,
]

__UpperCamelCase  :      Tuple							      =		[
    9_9_9,
    9_7_6,
    9_5_2,
    9_2_8,
    9_0_5,
    8_8_2,
    8_5_8,
    8_5_7,
    8_1_0,
    7_6_2,
    7_1_5,
    7_1_4,
    5_7_2,
    4_2_9,
    4_2_8,
    2_8_6,
    2_8_5,
    2_3_8,
    1_9_0,
    1_4_3,
    1_4_2,
    1_1_8,
    9_5,
    7_1,
    4_7,
    2_4,
    0,
]

__UpperCamelCase  :      Optional[int]							      =		[
    9_9_9,
    9_8_8,
    9_7_7,
    9_6_6,
    9_5_5,
    9_4_4,
    9_3_3,
    9_2_2,
    9_1_1,
    9_0_0,
    8_9_9,
    8_7_9,
    8_5_9,
    8_4_0,
    8_2_0,
    8_0_0,
    7_9_9,
    7_6_6,
    7_3_3,
    7_0_0,
    6_9_9,
    6_5_0,
    6_0_0,
    5_9_9,
    5_0_0,
    4_9_9,
    4_0_0,
    3_9_9,
    3_5_0,
    3_0_0,
    2_9_9,
    2_6_6,
    2_3_3,
    2_0_0,
    1_9_9,
    1_7_9,
    1_5_9,
    1_4_0,
    1_2_0,
    1_0_0,
    9_9,
    8_8,
    7_7,
    6_6,
    5_5,
    4_4,
    3_3,
    2_2,
    1_1,
    0,
]

__UpperCamelCase  :      Tuple							      =		[
    9_9_9,
    9_9_5,
    9_9_2,
    9_8_9,
    9_8_5,
    9_8_1,
    9_7_8,
    9_7_5,
    9_7_1,
    9_6_7,
    9_6_4,
    9_6_1,
    9_5_7,
    9_5_6,
    9_5_1,
    9_4_7,
    9_4_2,
    9_3_7,
    9_3_3,
    9_2_8,
    9_2_3,
    9_1_9,
    9_1_4,
    9_1_3,
    9_0_8,
    9_0_3,
    8_9_7,
    8_9_2,
    8_8_7,
    8_8_1,
    8_7_6,
    8_7_1,
    8_7_0,
    8_6_4,
    8_5_8,
    8_5_2,
    8_4_6,
    8_4_0,
    8_3_4,
    8_2_8,
    8_2_7,
    8_2_0,
    8_1_3,
    8_0_6,
    7_9_9,
    7_9_2,
    7_8_5,
    7_8_4,
    7_7_7,
    7_7_0,
    7_6_3,
    7_5_6,
    7_4_9,
    7_4_2,
    7_4_1,
    7_3_3,
    7_2_4,
    7_1_6,
    7_0_7,
    6_9_9,
    6_9_8,
    6_8_8,
    6_7_7,
    6_6_6,
    6_5_6,
    6_5_5,
    6_4_5,
    6_3_4,
    6_2_3,
    6_1_3,
    6_1_2,
    5_9_8,
    5_8_4,
    5_7_0,
    5_6_9,
    5_5_5,
    5_4_1,
    5_2_7,
    5_2_6,
    5_0_5,
    4_8_4,
    4_8_3,
    4_6_2,
    4_4_0,
    4_3_9,
    3_9_6,
    3_9_5,
    3_5_2,
    3_5_1,
    3_0_8,
    3_0_7,
    2_6_4,
    2_6_3,
    2_2_0,
    2_1_9,
    1_7_6,
    1_3_2,
    8_8,
    4_4,
    0,
]

__UpperCamelCase  :      str							      =		[
    9_9_9,
    9_9_7,
    9_9_5,
    9_9_2,
    9_9_0,
    9_8_8,
    9_8_6,
    9_8_4,
    9_8_1,
    9_7_9,
    9_7_7,
    9_7_5,
    9_7_2,
    9_7_0,
    9_6_8,
    9_6_6,
    9_6_4,
    9_6_1,
    9_5_9,
    9_5_7,
    9_5_6,
    9_5_4,
    9_5_1,
    9_4_9,
    9_4_6,
    9_4_4,
    9_4_1,
    9_3_9,
    9_3_6,
    9_3_4,
    9_3_1,
    9_2_9,
    9_2_6,
    9_2_4,
    9_2_1,
    9_1_9,
    9_1_6,
    9_1_4,
    9_1_3,
    9_1_0,
    9_0_7,
    9_0_5,
    9_0_2,
    8_9_9,
    8_9_6,
    8_9_3,
    8_9_1,
    8_8_8,
    8_8_5,
    8_8_2,
    8_7_9,
    8_7_7,
    8_7_4,
    8_7_1,
    8_7_0,
    8_6_7,
    8_6_4,
    8_6_1,
    8_5_8,
    8_5_5,
    8_5_2,
    8_4_9,
    8_4_6,
    8_4_3,
    8_4_0,
    8_3_7,
    8_3_4,
    8_3_1,
    8_2_8,
    8_2_7,
    8_2_4,
    8_2_1,
    8_1_7,
    8_1_4,
    8_1_1,
    8_0_8,
    8_0_4,
    8_0_1,
    7_9_8,
    7_9_5,
    7_9_1,
    7_8_8,
    7_8_5,
    7_8_4,
    7_8_0,
    7_7_7,
    7_7_4,
    7_7_0,
    7_6_6,
    7_6_3,
    7_6_0,
    7_5_6,
    7_5_2,
    7_4_9,
    7_4_6,
    7_4_2,
    7_4_1,
    7_3_7,
    7_3_3,
    7_3_0,
    7_2_6,
    7_2_2,
    7_1_8,
    7_1_4,
    7_1_0,
    7_0_7,
    7_0_3,
    6_9_9,
    6_9_8,
    6_9_4,
    6_9_0,
    6_8_5,
    6_8_1,
    6_7_7,
    6_7_3,
    6_6_9,
    6_6_4,
    6_6_0,
    6_5_6,
    6_5_5,
    6_5_0,
    6_4_6,
    6_4_1,
    6_3_6,
    6_3_2,
    6_2_7,
    6_2_2,
    6_1_8,
    6_1_3,
    6_1_2,
    6_0_7,
    6_0_2,
    5_9_6,
    5_9_1,
    5_8_6,
    5_8_0,
    5_7_5,
    5_7_0,
    5_6_9,
    5_6_3,
    5_5_7,
    5_5_1,
    5_4_5,
    5_3_9,
    5_3_3,
    5_2_7,
    5_2_6,
    5_1_9,
    5_1_2,
    5_0_5,
    4_9_8,
    4_9_1,
    4_8_4,
    4_8_3,
    4_7_4,
    4_6_6,
    4_5_7,
    4_4_9,
    4_4_0,
    4_3_9,
    4_2_8,
    4_1_8,
    4_0_7,
    3_9_6,
    3_9_5,
    3_8_1,
    3_6_6,
    3_5_2,
    3_5_1,
    3_3_0,
    3_0_8,
    3_0_7,
    2_8_6,
    2_6_4,
    2_6_3,
    2_4_2,
    2_2_0,
    2_1_9,
    1_7_6,
    1_7_5,
    1_3_2,
    1_3_1,
    8_8,
    4_4,
    0,
]

__UpperCamelCase  :      Dict							      =		[
    9_9_9,
    9_9_1,
    9_8_2,
    9_7_4,
    9_6_6,
    9_5_8,
    9_5_0,
    9_4_1,
    9_3_3,
    9_2_5,
    9_1_6,
    9_0_8,
    9_0_0,
    8_9_9,
    8_7_4,
    8_5_0,
    8_2_5,
    8_0_0,
    7_9_9,
    7_0_0,
    6_0_0,
    5_0_0,
    4_0_0,
    3_0_0,
    2_0_0,
    1_0_0,
    0,
]

__UpperCamelCase  :      int							      =		[
    9_9_9,
    9_9_2,
    9_8_5,
    9_7_8,
    9_7_1,
    9_6_4,
    9_5_7,
    9_4_9,
    9_4_2,
    9_3_5,
    9_2_8,
    9_2_1,
    9_1_4,
    9_0_7,
    9_0_0,
    8_9_9,
    8_7_9,
    8_5_9,
    8_4_0,
    8_2_0,
    8_0_0,
    7_9_9,
    7_6_6,
    7_3_3,
    7_0_0,
    6_9_9,
    6_5_0,
    6_0_0,
    5_9_9,
    5_0_0,
    4_9_9,
    4_0_0,
    3_9_9,
    3_0_0,
    2_9_9,
    2_0_0,
    1_9_9,
    1_0_0,
    9_9,
    0,
]

__UpperCamelCase  :      Optional[int]							      =		[
    9_9_9,
    9_9_6,
    9_9_2,
    9_8_9,
    9_8_5,
    9_8_2,
    9_7_9,
    9_7_5,
    9_7_2,
    9_6_8,
    9_6_5,
    9_6_1,
    9_5_8,
    9_5_5,
    9_5_1,
    9_4_8,
    9_4_4,
    9_4_1,
    9_3_8,
    9_3_4,
    9_3_1,
    9_2_7,
    9_2_4,
    9_2_0,
    9_1_7,
    9_1_4,
    9_1_0,
    9_0_7,
    9_0_3,
    9_0_0,
    8_9_9,
    8_9_1,
    8_8_4,
    8_7_6,
    8_6_9,
    8_6_1,
    8_5_3,
    8_4_6,
    8_3_8,
    8_3_0,
    8_2_3,
    8_1_5,
    8_0_8,
    8_0_0,
    7_9_9,
    7_8_8,
    7_7_7,
    7_6_6,
    7_5_5,
    7_4_4,
    7_3_3,
    7_2_2,
    7_1_1,
    7_0_0,
    6_9_9,
    6_8_8,
    6_7_7,
    6_6_6,
    6_5_5,
    6_4_4,
    6_3_3,
    6_2_2,
    6_1_1,
    6_0_0,
    5_9_9,
    5_8_5,
    5_7_1,
    5_5_7,
    5_4_2,
    5_2_8,
    5_1_4,
    5_0_0,
    4_9_9,
    4_8_5,
    4_7_1,
    4_5_7,
    4_4_2,
    4_2_8,
    4_1_4,
    4_0_0,
    3_9_9,
    3_7_9,
    3_5_9,
    3_4_0,
    3_2_0,
    3_0_0,
    2_9_9,
    2_7_9,
    2_5_9,
    2_4_0,
    2_2_0,
    2_0_0,
    1_9_9,
    1_6_6,
    1_3_3,
    1_0_0,
    9_9,
    6_6,
    3_3,
    0,
]




