



'''simple docstring'''




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     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				DownBlockaD  # noqa F405
	lowercase    =				'down'





	def 				_lowercase(						self					)    ->    int:
								UpperCAmelCase  :	Union[str, Any]							  =	[-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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				ResnetDownsampleBlockaD  # noqa F405
	lowercase    =				'down'





	def 				_lowercase(						self					)    ->    Union[str, Any]:
								UpperCAmelCase  :	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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				AttnDownBlockaD  # noqa F405
	lowercase    =				'down'





	def 				_lowercase(						self					)    ->    Tuple:
								UpperCAmelCase  :	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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				CrossAttnDownBlockaD  # noqa F405
	lowercase    =				'down'





	def 				_lowercase(						self					)    ->    List[Any]:
								UpperCAmelCase  ,  UpperCAmelCase  :	Dict							  =	super().prepare_init_args_and_inputs_for_common()
								UpperCAmelCase  :	Optional[int]							  =	32
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    Optional[Any]:
								UpperCAmelCase  :	Any							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				SimpleCrossAttnDownBlockaD  # noqa F405
	lowercase    =				'down'





	@property
	def 				_lowercase(						self					)    ->    List[Any]:
								return super().get_dummy_input(include_encoder_hidden_states=A					)





	def 				_lowercase(						self					)    ->    Tuple:
								UpperCAmelCase  ,  UpperCAmelCase  :	Dict							  =	super().prepare_init_args_and_inputs_for_common()
								UpperCAmelCase  :	int							  =	32
								return init_dict, inputs_dict






	@unittest.skipIf(torch_device == """mps"""	,	"""MPS result is not consistent"""					)
	def 				_lowercase(						self					)    ->    str:
								UpperCAmelCase  :	str							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				SkipDownBlockaD  # noqa F405
	lowercase    =				'down'





	@property
	def 				_lowercase(						self					)    ->    int:
								return super().get_dummy_input(include_skip_sample=A					)






	def 				_lowercase(						self					)    ->    int:
								UpperCAmelCase  :	List[str]							  =	[-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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				AttnSkipDownBlockaD  # noqa F405
	lowercase    =				'down'





	@property
	def 				_lowercase(						self					)    ->    Any:
								return super().get_dummy_input(include_skip_sample=A					)






	def 				_lowercase(						self					)    ->    Union[str, Any]:
								UpperCAmelCase  :	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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				DownEncoderBlockaD  # noqa F405
	lowercase    =				'down'





	@property
	def 				_lowercase(						self					)    ->    Union[str, Any]:
								return super().get_dummy_input(include_temb=A					)





	def 				_lowercase(						self					)    ->    Any:
								UpperCAmelCase  :	Tuple							  =	{
								    """in_channels""": 32,
								    """out_channels""": 32,
								}
								UpperCAmelCase  :	Tuple							  =	self.dummy_input
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    Dict:
								UpperCAmelCase  :	List[Any]							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				AttnDownEncoderBlockaD  # noqa F405
	lowercase    =				'down'





	@property
	def 				_lowercase(						self					)    ->    Optional[Any]:
								return super().get_dummy_input(include_temb=A					)





	def 				_lowercase(						self					)    ->    Tuple:
								UpperCAmelCase  :	Any							  =	{
								    """in_channels""": 32,
								    """out_channels""": 32,
								}
								UpperCAmelCase  :	Any							  =	self.dummy_input
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    List[str]:
								UpperCAmelCase  :	List[str]							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				UNetMidBlockaD  # noqa F405
	lowercase    =				'mid'





	def 				_lowercase(						self					)    ->    Optional[int]:
								UpperCAmelCase  :	Dict							  =	{
								    """in_channels""": 32,
								    """temb_channels""": 128,
								}
								UpperCAmelCase  :	Dict							  =	self.dummy_input
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    Any:
								UpperCAmelCase  :	Tuple							  =	[-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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				UNetMidBlockaDCrossAttn  # noqa F405
	lowercase    =				'mid'





	def 				_lowercase(						self					)    ->    List[str]:
								UpperCAmelCase  ,  UpperCAmelCase  :	List[str]							  =	super().prepare_init_args_and_inputs_for_common()
								UpperCAmelCase  :	Any							  =	32
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    str:
								UpperCAmelCase  :	int							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				UNetMidBlockaDSimpleCrossAttn  # noqa F405
	lowercase    =				'mid'





	@property
	def 				_lowercase(						self					)    ->    Any:
								return super().get_dummy_input(include_encoder_hidden_states=A					)





	def 				_lowercase(						self					)    ->    List[Any]:
								UpperCAmelCase  ,  UpperCAmelCase  :	Optional[Any]							  =	super().prepare_init_args_and_inputs_for_common()
								UpperCAmelCase  :	Optional[int]							  =	32
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    Dict:
								UpperCAmelCase  :	List[str]							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				UpBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    str:
								return super().get_dummy_input(include_res_hidden_states_tuple=A					)






	def 				_lowercase(						self					)    ->    Union[str, Any]:
								UpperCAmelCase  :	Optional[int]							  =	[-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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				ResnetUpsampleBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    Optional[int]:
								return super().get_dummy_input(include_res_hidden_states_tuple=A					)






	def 				_lowercase(						self					)    ->    Dict:
								UpperCAmelCase  :	Dict							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				CrossAttnUpBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    List[str]:
								return super().get_dummy_input(include_res_hidden_states_tuple=A					)





	def 				_lowercase(						self					)    ->    Tuple:
								UpperCAmelCase  ,  UpperCAmelCase  :	Any							  =	super().prepare_init_args_and_inputs_for_common()
								UpperCAmelCase  :	str							  =	32
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    Optional[int]:
								UpperCAmelCase  :	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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				SimpleCrossAttnUpBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    List[str]:
								return super().get_dummy_input(include_res_hidden_states_tuple=A	,	include_encoder_hidden_states=A					)





	def 				_lowercase(						self					)    ->    Tuple:
								UpperCAmelCase  ,  UpperCAmelCase  :	Optional[int]							  =	super().prepare_init_args_and_inputs_for_common()
								UpperCAmelCase  :	Tuple							  =	32
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    Optional[Any]:
								UpperCAmelCase  :	Tuple							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				AttnUpBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    List[str]:
								return super().get_dummy_input(include_res_hidden_states_tuple=A					)






	@unittest.skipIf(torch_device == """mps"""	,	"""MPS result is not consistent"""					)
	def 				_lowercase(						self					)    ->    Any:
								UpperCAmelCase  :	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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				SkipUpBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    int:
								return super().get_dummy_input(include_res_hidden_states_tuple=A					)






	def 				_lowercase(						self					)    ->    Optional[int]:
								UpperCAmelCase  :	int							  =	[-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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				AttnSkipUpBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    Dict:
								return super().get_dummy_input(include_res_hidden_states_tuple=A					)






	def 				_lowercase(						self					)    ->    List[Any]:
								UpperCAmelCase  :	List[Any]							  =	[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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				UpDecoderBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    Union[str, Any]:
								return super().get_dummy_input(include_temb=A					)





	def 				_lowercase(						self					)    ->    List[Any]:
								UpperCAmelCase  :	Union[str, Any]							  =	{"""in_channels""": 32, """out_channels""": 32}

								UpperCAmelCase  :	Tuple							  =	self.dummy_input
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    Tuple:
								UpperCAmelCase  :	Union[str, 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(A					)




class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				AttnUpDecoderBlockaD  # noqa F405
	lowercase    =				'up'





	@property
	def 				_lowercase(						self					)    ->    Dict:
								return super().get_dummy_input(include_temb=A					)





	def 				_lowercase(						self					)    ->    str:
								UpperCAmelCase  :	str							  =	{"""in_channels""": 32, """out_channels""": 32}

								UpperCAmelCase  :	Union[str, Any]							  =	self.dummy_input
								return init_dict, inputs_dict






	def 				_lowercase(						self					)    ->    int:
								UpperCAmelCase  :	str							  =	[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(A					)






'''simple docstring'''




from sklearn.metrics import mean_squared_error

import datasets


a     :    Union[str, Any]      						=					"""\
@article{scikit-learn,
 title={Scikit-learn: Machine Learning in {P}ython},
 author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
 journal={Journal of Machine Learning Research},
 volume={12},
 pages={2825--2830},
 year={2011}
}
"""

a     :    int      						=					"""\
Mean Squared Error(MSE) is the average of the square of difference between the predicted
and actual values.
"""


a     :    int      						=					"""
Args:
    predictions: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Estimated target values.
    references: array-like of shape (n_samples,) or (n_samples, n_outputs)
        Ground truth (correct) target values.
    sample_weight: array-like of shape (n_samples,), default=None
        Sample weights.
    multioutput: {\"raw_values\", \"uniform_average\"} or array-like of shape (n_outputs,), default=\"uniform_average\"
        Defines aggregating of multiple output values. Array-like value defines weights used to average errors.

        \"raw_values\" : Returns a full set of errors in case of multioutput input.

        \"uniform_average\" : Errors of all outputs are averaged with uniform weight.

    squared : bool, default=True
        If True returns MSE value, if False returns RMSE (Root Mean Squared Error) value.

Returns:
    mse : mean squared error.
Examples:

    >>> mse_metric = datasets.load_metric(\"mse\")
    >>> predictions = [2.5, 0.0, 2, 8]
    >>> references = [3, -0.5, 2, 7]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {'mse': 0.375}
    >>> rmse_result = mse_metric.compute(predictions=predictions, references=references, squared=False)
    >>> print(rmse_result)
    {'mse': 0.6123724356957945}

    If you're using multi-dimensional lists, then set the config as follows :

    >>> mse_metric = datasets.load_metric(\"mse\", \"multilist\")
    >>> predictions = [[0.5, 1], [-1, 1], [7, -6]]
    >>> references = [[0, 2], [-1, 2], [8, -5]]
    >>> results = mse_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {'mse': 0.7083333333333334}
    >>> results = mse_metric.compute(predictions=predictions, references=references, multioutput='raw_values')
    >>> print(results) # doctest: +NORMALIZE_WHITESPACE
    {'mse': array([0.41666667, 1. ])}
"""

@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION   ,  _KWARGS_DESCRIPTION    )
class     UpperCamelCase_				(							datasets.Metric    ):





	def 				_lowercase(						self					)    ->    List[str]:
								return datasets.MetricInfo(
								    description=_DESCRIPTION	,	citation=_CITATION	,	inputs_description=_KWARGS_DESCRIPTION	,	features=datasets.Features(self._get_feature_types()					)	,	reference_urls=[
								        """https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html"""
								    ]	,	)





	def 				_lowercase(						self					)    ->    List[Any]:
								if self.config_name == "multilist":
															return {
															    "predictions": datasets.Sequence(datasets.Value("""float"""					)					),
															    "references": datasets.Sequence(datasets.Value("""float"""					)					),
															}
								else:
															return {
															    "predictions": datasets.Value("""float"""					),
															    "references": datasets.Value("""float"""					),
															}






	def 				_lowercase(						self	,	A	,	A	,	A=None	,	A="uniform_average"	,	A=True					)    ->    List[Any]:
								UpperCAmelCase  :	List[Any]							  =	mean_squared_error(
								    A	,	A	,	sample_weight=A	,	multioutput=A	,	squared=A					)

								return {"mse": mse}

