




'''simple docstring'''



import torch

from diffusers import EulerAncestralDiscreteScheduler
from diffusers.utils import torch_device

from .test_schedulers import SchedulerCommonTest





class     lowerCAmelCase   ( __lowerCAmelCase):
       __lowercase  :      Union[str, Any]        =			(EulerAncestralDiscreteScheduler,)
       __lowercase  :      Optional[Any]        =			10


       def       lowerCAmelCase      (   self    ,  **__SCREAMING_SNAKE_CASE  )      ->  Any:



            '''simple docstring'''




            __snake_case    					=  {
                '''num_train_timesteps''': 1100,
                '''beta_start''': 0.0_001,
                '''beta_end''': 0.02,
                '''beta_schedule''': '''linear''',
            }

            config.update(**__SCREAMING_SNAKE_CASE  )
            return config


       def       lowerCAmelCase      (   self  )      ->  Optional[Any]:



            '''simple docstring'''




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


       def       lowerCAmelCase      (   self  )      ->  Union[str, Any]:



            '''simple docstring'''




            for beta_start, beta_end in zip([0.00_001, 0.0_001, 0.001]    ,  [0.0_002, 0.002, 0.02]  ):
                 self.check_over_configs(beta_start=__SCREAMING_SNAKE_CASE    ,  beta_end=__SCREAMING_SNAKE_CASE  )


       def       lowerCAmelCase      (   self  )      ->  Dict:



            '''simple docstring'''




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


       def       lowerCAmelCase      (   self  )      ->  List[str]:



            '''simple docstring'''




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


       def       lowerCAmelCase      (   self  )      ->  Any:



            '''simple docstring'''




            __snake_case    					=  self.scheduler_classes[0]
            __snake_case    					=  self.get_scheduler_config()
            __snake_case    					=  scheduler_class(**__SCREAMING_SNAKE_CASE  )

            scheduler.set_timesteps(self.num_inference_steps  )

            __snake_case    					=  torch.manual_seed(0  )

            __snake_case    					=  self.dummy_model()
            __snake_case    					=  self.dummy_sample_deter * scheduler.init_noise_sigma.cpu()
            __snake_case    					=  sample.to(__SCREAMING_SNAKE_CASE  )

            for i, t in enumerate(scheduler.timesteps  ):
                 __snake_case    					=  scheduler.scale_model_input(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )

                 __snake_case    					=  model(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )

                 __snake_case    					=  scheduler.step(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  generator=__SCREAMING_SNAKE_CASE  )
                 __snake_case    					=  output.prev_sample

            __snake_case    					=  torch.sum(torch.abs(__SCREAMING_SNAKE_CASE  )  )
            __snake_case    					=  torch.mean(torch.abs(__SCREAMING_SNAKE_CASE  )  )

            assert abs(result_sum.item() - 152.3_192  ) < 1E-2
            assert abs(result_mean.item() - 0.1_983  ) < 1E-3


       def       lowerCAmelCase      (   self  )      ->  Tuple:



            '''simple docstring'''




            __snake_case    					=  self.scheduler_classes[0]
            __snake_case    					=  self.get_scheduler_config(prediction_type='''v_prediction'''  )
            __snake_case    					=  scheduler_class(**__SCREAMING_SNAKE_CASE  )

            scheduler.set_timesteps(self.num_inference_steps  )

            __snake_case    					=  torch.manual_seed(0  )

            __snake_case    					=  self.dummy_model()
            __snake_case    					=  self.dummy_sample_deter * scheduler.init_noise_sigma
            __snake_case    					=  sample.to(__SCREAMING_SNAKE_CASE  )

            for i, t in enumerate(scheduler.timesteps  ):
                 __snake_case    					=  scheduler.scale_model_input(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )

                 __snake_case    					=  model(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )

                 __snake_case    					=  scheduler.step(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  generator=__SCREAMING_SNAKE_CASE  )
                 __snake_case    					=  output.prev_sample

            __snake_case    					=  torch.sum(torch.abs(__SCREAMING_SNAKE_CASE  )  )
            __snake_case    					=  torch.mean(torch.abs(__SCREAMING_SNAKE_CASE  )  )

            assert abs(result_sum.item() - 108.4_439  ) < 1E-2
            assert abs(result_mean.item() - 0.1_412  ) < 1E-3




       def       lowerCAmelCase      (   self  )      ->  Dict:



            '''simple docstring'''




            __snake_case    					=  self.scheduler_classes[0]
            __snake_case    					=  self.get_scheduler_config()
            __snake_case    					=  scheduler_class(**__SCREAMING_SNAKE_CASE  )

            scheduler.set_timesteps(self.num_inference_steps    ,  device=__SCREAMING_SNAKE_CASE  )
            __snake_case    					=  torch.manual_seed(0  )

            __snake_case    					=  self.dummy_model()
            __snake_case    					=  self.dummy_sample_deter * scheduler.init_noise_sigma.cpu()
            __snake_case    					=  sample.to(__SCREAMING_SNAKE_CASE  )

            for t in scheduler.timesteps:
                 __snake_case    					=  scheduler.scale_model_input(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )

                 __snake_case    					=  model(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE  )

                 __snake_case    					=  scheduler.step(__SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  __SCREAMING_SNAKE_CASE    ,  generator=__SCREAMING_SNAKE_CASE  )
                 __snake_case    					=  output.prev_sample

            __snake_case    					=  torch.sum(torch.abs(__SCREAMING_SNAKE_CASE  )  )
            __snake_case    					=  torch.mean(torch.abs(__SCREAMING_SNAKE_CASE  )  )

            assert abs(result_sum.item() - 152.3_192  ) < 1E-2
            assert abs(result_mean.item() - 0.1_983  ) < 1E-3












'''simple docstring'''



from ..utils import deprecate
from .attention_processor import (  # noqa: F401
    Attention,
    AttentionProcessor,
    AttnAddedKVProcessor,
    AttnProcessor2_0,
    LoRAAttnProcessor,
    LoRALinearLayer,
    LoRAXFormersAttnProcessor,
    SlicedAttnAddedKVProcessor,
    SlicedAttnProcessor,
    XFormersAttnProcessor,
)
from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401


deprecate(
    '''cross_attention''',
    '''0.20.0''',
    '''Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.''',
    standard_warn=False,
)


UpperCAmelCase_       :  Optional[int]      =		AttentionProcessor





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  Optional[int]:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  Any:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  Tuple:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  Optional[Any]:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  Optional[int]:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  Tuple:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  int:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  List[str]:



            '''simple docstring'''




            __snake_case    					=  F'''{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"  )  )} instead.'''
            deprecate('''cross_attention'''    ,  '''0.20.0'''    ,  __SCREAMING_SNAKE_CASE    ,  standard_warn=__SCREAMING_SNAKE_CASE  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )






