


import torch

from diffusers import DDPMScheduler

from .test_schedulers import SchedulerCommonTest






class _lowerCamelCase(		_a     ):
       lowercase_				:			Dict									=    (DDPMScheduler,)
       def     UpperCamelCase  (      self,   **lowerCamelCase) ->     int:




           """simple docstring"""

           _lowercase :							List[str]   	=	{
               'num_train_timesteps': 10_00,
               'beta_start': 0.0_0_0_1,
               'beta_end': 0.0_2,
               'beta_schedule': 'linear',
               'variance_type': 'fixed_small',
               'clip_sample': True,
           }

           config.update(**lowerCamelCase)
           return config
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           for timesteps in [1, 5, 1_00, 10_00]:
               self.check_over_configs(num_train_timesteps=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           for beta_start, beta_end in zip([0.0_0_0_1, 0.0_0_1, 0.0_1, 0.1],   [0.0_0_2, 0.0_2, 0.2, 2]):
               self.check_over_configs(beta_start=lowerCamelCase,   beta_end=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           for schedule in ["linear", "squaredcos_cap_v2"]:
               self.check_over_configs(beta_schedule=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           for variance in ["fixed_small", "fixed_large", "other"]:
               self.check_over_configs(variance_type=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           for clip_sample in [True, False]:
               self.check_over_configs(clip_sample=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           self.check_over_configs(thresholding=lowerCamelCase)
           for threshold in [0.5, 1.0, 2.0]:
               for prediction_type in ["epsilon", "sample", "v_prediction"]:
                   self.check_over_configs(
                       thresholding=lowerCamelCase,   prediction_type=lowerCamelCase,   sample_max_value=lowerCamelCase,   )
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           for prediction_type in ["epsilon", "sample", "v_prediction"]:
               self.check_over_configs(prediction_type=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           for t in [0, 5_00, 9_99]:
               self.check_over_forward(time_step=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							List[Any]   	=	self.scheduler_classes[0]
           _lowercase :							Dict   	=	self.get_scheduler_config()
           _lowercase :							Dict   	=	scheduler_class(**lowerCamelCase)

           assert torch.sum(torch.abs(scheduler._get_variance(0) - 0.0)) < 1E-5
           assert torch.sum(torch.abs(scheduler._get_variance(4_87) - 0.0_0_9_7_9)) < 1E-5
           assert torch.sum(torch.abs(scheduler._get_variance(9_99) - 0.0_2)) < 1E-5
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase :							str   	=	self.scheduler_classes[0]
           _lowercase :							List[str]   	=	self.get_scheduler_config()
           _lowercase :							str   	=	scheduler_class(**lowerCamelCase)

           _lowercase :							List[Any]   	=	len(lowerCamelCase)

           _lowercase :							List[Any]   	=	self.dummy_model()
           _lowercase :							Optional[Any]   	=	self.dummy_sample_deter
           _lowercase :							int   	=	torch.manual_seed(0)

           for t in reversed(range(lowerCamelCase)):
               # 1. predict noise residual
               _lowercase :							Any   	=	model(lowerCamelCase,   lowerCamelCase)

               # 2. predict previous mean of sample x_t-1
               _lowercase :							Tuple   	=	scheduler.step(lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   generator=lowerCamelCase).prev_sample

               # if t > 0:
               #     noise = self.dummy_sample_deter
               #     variance = scheduler.get_variance(t) ** (0.5) * noise
               #
               # sample = pred_prev_sample + variance
               _lowercase :							Dict   	=	pred_prev_sample

           _lowercase :							Tuple   	=	torch.sum(torch.abs(lowerCamelCase))
           _lowercase :							Optional[Any]   	=	torch.mean(torch.abs(lowerCamelCase))

           assert abs(result_sum.item() - 2_5_8.9_6_0_6) < 1E-2
           assert abs(result_mean.item() - 0.3_3_7_2) < 1E-3
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	self.scheduler_classes[0]
           _lowercase :							Union[str, Any]   	=	self.get_scheduler_config(prediction_type='v_prediction')
           _lowercase :							Dict   	=	scheduler_class(**lowerCamelCase)

           _lowercase :							List[Any]   	=	len(lowerCamelCase)

           _lowercase :							Optional[int]   	=	self.dummy_model()
           _lowercase :							Optional[Any]   	=	self.dummy_sample_deter
           _lowercase :							Tuple   	=	torch.manual_seed(0)

           for t in reversed(range(lowerCamelCase)):
               # 1. predict noise residual
               _lowercase :							Optional[int]   	=	model(lowerCamelCase,   lowerCamelCase)

               # 2. predict previous mean of sample x_t-1
               _lowercase :							List[str]   	=	scheduler.step(lowerCamelCase,   lowerCamelCase,   lowerCamelCase,   generator=lowerCamelCase).prev_sample

               # if t > 0:
               #     noise = self.dummy_sample_deter
               #     variance = scheduler.get_variance(t) ** (0.5) * noise
               #
               # sample = pred_prev_sample + variance
               _lowercase :							int   	=	pred_prev_sample

           _lowercase :							Tuple   	=	torch.sum(torch.abs(lowerCamelCase))
           _lowercase :							Optional[Any]   	=	torch.mean(torch.abs(lowerCamelCase))

           assert abs(result_sum.item() - 2_0_2.0_2_9_6) < 1E-2
           assert abs(result_mean.item() - 0.2_6_3_1) < 1E-3
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Any   	=	self.scheduler_classes[0]
           _lowercase :							List[Any]   	=	self.get_scheduler_config()
           _lowercase :							int   	=	scheduler_class(**lowerCamelCase)

           _lowercase :							List[Any]   	=	[1_00, 87, 50, 1, 0]

           scheduler.set_timesteps(timesteps=lowerCamelCase)

           _lowercase :							Tuple   	=	scheduler.timesteps

           for i, timestep in enumerate(lowerCamelCase):
               if i == len(lowerCamelCase) - 1:
                   _lowercase :							Tuple   	=	-1
               else:
                   _lowercase :							Dict   	=	timesteps[i + 1]

               _lowercase :							Union[str, Any]   	=	scheduler.previous_timestep(lowerCamelCase)
               _lowercase :							Any   	=	prev_t.item()

               self.assertEqual(lowerCamelCase,   lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	self.scheduler_classes[0]
           _lowercase :							List[str]   	=	self.get_scheduler_config()
           _lowercase :							Union[str, Any]   	=	scheduler_class(**lowerCamelCase)

           _lowercase :							List[Any]   	=	[1_00, 87, 50, 51, 0]

           with self.assertRaises(lowerCamelCase,   msg='`custom_timesteps` must be in descending order.'):
               scheduler.set_timesteps(timesteps=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           _lowercase :							Any   	=	self.scheduler_classes[0]
           _lowercase :							Union[str, Any]   	=	self.get_scheduler_config()
           _lowercase :							Optional[int]   	=	scheduler_class(**lowerCamelCase)

           _lowercase :							Optional[Any]   	=	[1_00, 87, 50, 1, 0]
           _lowercase :							List[Any]   	=	len(lowerCamelCase)

           with self.assertRaises(lowerCamelCase,   msg='Can only pass one of `num_inference_steps` or `custom_timesteps`.'):
               scheduler.set_timesteps(num_inference_steps=lowerCamelCase,   timesteps=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							List[Any]   	=	self.scheduler_classes[0]
           _lowercase :							Any   	=	self.get_scheduler_config()
           _lowercase :							Dict   	=	scheduler_class(**lowerCamelCase)

           _lowercase :							Union[str, Any]   	=	[scheduler.config.num_train_timesteps]

           with self.assertRaises(
               lowerCamelCase,   msg='`timesteps` must start before `self.config.train_timesteps`: {scheduler.config.num_train_timesteps}}',   ):
               scheduler.set_timesteps(timesteps=lowerCamelCase)






import unittest

from diffusers.models.unet_ad_blocks import *  # noqa F403
from diffusers.utils import torch_device

from .test_unet_blocks_common import UNetBlockTesterMixin






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    DownBlockaD  # noqa F405
       lowercase_				:			List[str]									=    """down"""
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           _lowercase :							str   	=	[-0.0_2_3_2, -0.9_8_6_9, 0.8_0_5_4, -0.0_6_3_7, -0.1_6_8_8, -1.4_2_6_4, 0.4_4_7_0, -1.3_3_9_4, 0.0_9_0_4]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Optional[Any]									=    ResnetDownsampleBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	[0.0_7_1_0, 0.2_4_1_0, -0.7_3_2_0, -1.0_7_5_7, -1.1_3_4_3, 0.3_5_4_0, -0.0_1_3_3, -0.2_5_7_6, 0.0_9_4_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Any									=    AttnDownBlockaD  # noqa F405
       lowercase_				:			Dict									=    """down"""
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	[0.0_6_3_6, 0.8_9_6_4, -0.6_2_3_4, -1.0_1_3_1, 0.0_8_4_4, 0.4_9_3_5, 0.3_4_3_7, 0.0_9_1_1, -0.2_9_5_7]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    CrossAttnDownBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """down"""
       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase	,       _lowercase :							int   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							int   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							List[str]   	=	[0.2_2_3_8, -0.7_3_9_6, -0.2_2_5_5, -0.3_8_2_9, 0.1_9_2_5, 1.1_6_6_5, 0.0_6_0_3, -0.7_2_9_5, 0.1_9_8_3]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Dict									=    SimpleCrossAttnDownBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           return super().get_dummy_input(include_encoder_hidden_states=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase	,       _lowercase :							Dict   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Optional[Any]   	=	32
           return init_dict, inputs_dict




       @unittest.skipIf(torch_device == 'mps',   'MPS result is not consistent')
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							Tuple   	=	[0.7_9_2_1, -0.0_9_9_2, -0.1_9_6_2, -0.7_6_9_5, -0.4_2_4_2, 0.7_8_0_4, 0.4_7_3_7, 0.2_7_6_5, 0.3_3_3_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    SkipDownBlockaD  # noqa F405
       lowercase_				:			Union[str, Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_skip_sample=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           _lowercase :							int   	=	[-0.0_8_4_5, -0.2_0_8_7, -0.2_4_6_5, 0.0_9_7_1, 0.1_9_0_0, -0.0_4_8_4, 0.2_6_6_4, 0.4_1_7_9, 0.5_0_6_9]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    AttnSkipDownBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           return super().get_dummy_input(include_skip_sample=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	[0.5_5_3_9, 0.1_6_0_9, 0.4_9_2_4, 0.0_5_3_7, -0.1_9_9_5, 0.4_0_5_0, 0.0_9_7_9, -0.2_7_2_1, -0.0_6_4_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			str									=    DownEncoderBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							Dict   	=	{
               'in_channels': 32,
               'out_channels': 32,
           }
           _lowercase :							int   	=	self.dummy_input
           return init_dict, inputs_dict




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




           """simple docstring"""

           _lowercase :							List[str]   	=	[1.1_1_0_2, 0.5_3_0_2, 0.4_8_7_2, -0.0_0_2_3, -0.8_0_4_2, 0.0_4_8_3, -0.3_4_8_9, -0.5_6_3_2, 0.7_6_2_6]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			int									=    AttnDownEncoderBlockaD  # noqa F405
       lowercase_				:			Tuple									=    """down"""
       @property
       def     UpperCamelCase  (      self) ->     Tuple:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Any   	=	{
               'in_channels': 32,
               'out_channels': 32,
           }
           _lowercase :							Optional[int]   	=	self.dummy_input
           return init_dict, inputs_dict




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




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	[0.8_9_6_6, -0.1_4_8_6, 0.8_5_6_8, 0.8_1_4_1, -0.9_0_4_6, -0.1_3_4_2, -0.0_9_7_2, -0.7_4_1_7, 0.1_5_3_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			int									=    UNetMidBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """mid"""
       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							int   	=	{
               'in_channels': 32,
               'temb_channels': 1_28,
           }
           _lowercase :							Optional[Any]   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase :							Dict   	=	[-0.1_0_6_2, 1.7_2_4_8, 0.3_4_9_4, 1.4_5_6_9, -0.0_9_1_0, -1.2_4_2_1, -0.9_9_8_4, 0.6_7_3_6, 1.0_0_2_8]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Dict									=    UNetMidBlockaDCrossAttn  # noqa F405
       lowercase_				:			Dict									=    """mid"""
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase	,       _lowercase :							Union[str, Any]   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Any   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Dict   	=	[0.0_1_8_7, 2.4_2_2_0, 0.4_4_8_4, 1.1_2_0_3, -0.6_1_2_1, -1.5_1_2_2, -0.8_2_7_0, 0.7_8_5_1, 1.8_3_3_5]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[Any]									=    UNetMidBlockaDSimpleCrossAttn  # noqa F405
       lowercase_				:			Any									=    """mid"""
       @property
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           return super().get_dummy_input(include_encoder_hidden_states=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase	,       _lowercase :							str   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							List[str]   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							int   	=	[0.7_1_4_3, 1.9_9_7_4, 0.5_4_4_8, 1.3_9_7_7, 0.1_2_8_2, -1.1_2_3_7, -1.4_2_3_8, 0.5_5_3_0, 0.8_8_8_0]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[Any]									=    UpBlockaD  # noqa F405
       lowercase_				:			List[str]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase :							Any   	=	[-0.2_0_4_1, -0.4_1_6_5, -0.3_0_2_2, 0.0_0_4_1, -0.6_6_2_8, -0.7_0_5_3, 0.1_9_2_8, -0.0_3_2_5, 0.0_5_2_3]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    ResnetUpsampleBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase :							List[Any]   	=	[0.2_2_8_7, 0.3_5_4_9, -0.1_3_4_6, 0.4_7_9_7, -0.1_7_1_5, -0.9_6_4_9, 0.7_3_0_5, -0.5_8_6_4, -0.6_2_4_4]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Dict									=    CrossAttnUpBlockaD  # noqa F405
       lowercase_				:			List[str]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           _lowercase	,       _lowercase :							Union[str, Any]   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Tuple   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Dict   	=	[-0.1_4_0_3, -0.3_5_1_5, -0.0_4_2_0, -0.1_4_2_5, 0.3_1_6_7, 0.5_0_9_4, -0.2_1_8_1, 0.5_9_3_1, 0.5_5_8_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Optional[int]									=    SimpleCrossAttnUpBlockaD  # noqa F405
       lowercase_				:			List[Any]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase,   include_encoder_hidden_states=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           _lowercase	,       _lowercase :							int   	=	super().prepare_init_args_and_inputs_for_common()
           _lowercase :							Dict   	=	32
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           _lowercase :							List[str]   	=	[0.2_6_4_5, 0.1_4_8_0, 0.0_9_0_9, 0.8_0_4_4, -0.9_7_5_8, -0.9_0_8_3, 0.0_9_9_4, -1.1_4_5_3, -0.7_4_0_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    AttnUpBlockaD  # noqa F405
       lowercase_				:			Optional[int]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       @unittest.skipIf(torch_device == 'mps',   'MPS result is not consistent')
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	[0.0_9_7_9, 0.1_3_2_6, 0.0_0_2_1, 0.0_6_5_9, 0.2_2_4_9, 0.0_0_5_9, 0.1_1_3_2, 0.5_9_5_2, 0.1_0_3_3]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    SkipUpBlockaD  # noqa F405
       lowercase_				:			Optional[Any]									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	[-0.0_8_9_3, -0.1_2_3_4, -0.1_5_0_6, -0.0_3_3_2, 0.0_1_2_3, -0.0_2_1_1, 0.0_5_6_6, 0.0_1_4_3, 0.0_3_6_2]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			int									=    AttnSkipUpBlockaD  # noqa F405
       lowercase_				:			Any									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           return super().get_dummy_input(include_res_hidden_states_tuple=lowerCamelCase)




       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Tuple   	=	[0.0_3_6_1, 0.0_6_1_7, 0.2_7_8_7, -0.0_3_5_0, 0.0_3_4_2, 0.3_4_2_1, -0.0_8_4_3, 0.0_9_1_3, 0.3_0_1_5]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			List[str]									=    UpDecoderBlockaD  # noqa F405
       lowercase_				:			int									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Optional[int]:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	{'in_channels': 32, 'out_channels': 32}

           _lowercase :							Optional[Any]   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							List[Any]   	=	[0.4_4_0_4, 0.1_9_9_8, -0.9_8_8_6, -0.3_3_2_0, -0.3_1_2_8, -0.7_0_3_4, -0.6_9_5_5, -0.2_3_3_8, -0.3_1_3_7]
           super().test_output(lowerCamelCase)






class _lowerCamelCase(		_a,				unittest.TestCase     ):
       lowercase_				:			Any									=    AttnUpDecoderBlockaD  # noqa F405
       lowercase_				:			str									=    """up"""
       @property
       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           return super().get_dummy_input(include_temb=lowerCamelCase)
       def     UpperCamelCase  (      self) ->     Any:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	{'in_channels': 32, 'out_channels': 32}

           _lowercase :							List[Any]   	=	self.dummy_input
           return init_dict, inputs_dict




       def     UpperCamelCase  (      self) ->     str:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	[0.6_7_3_8, 0.4_4_9_1, 0.1_0_5_5, 1.0_7_1_0, 0.7_3_1_6, 0.3_3_3_9, 0.3_3_5_2, 0.1_0_2_3, 0.3_5_6_8]
           super().test_output(lowerCamelCase)


