


'''simple docstring'''







import unittest

import numpy as np


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	np.ndarray    ,_UpperCAmelCase	:	np.ndarray    ,_UpperCAmelCase	:	np.ndarray    ,_UpperCAmelCase	:	np.ndarray | None = None    ,)  ->			np.ndarray:
       _a    : int     					=np.shape(_UpperCAmelCase  )
       _a    : Optional[Any]     					=np.shape(_UpperCAmelCase  )
       _a    : Optional[Any]     					=np.shape(_UpperCAmelCase  )

       if shape_a[0] != shape_b[0]:
              _a    : int     					=(
                  """Expected the same number of rows for A and B. """
                  F"Instead found A of size {shape_a} and B of size {shape_b}"
              )
              raise ValueError(_UpperCAmelCase  )

       if shape_b[1] != shape_c[1]:
              _a    : List[Any]     					=(
                  """Expected the same number of columns for B and C. """
                  F"Instead found B of size {shape_b} and C of size {shape_c}"
              )
              raise ValueError(_UpperCAmelCase  )

       _a    : Tuple     					=pseudo_inv
       if a_inv is None:
              try:
                     _a    : str     					=np.linalg.inv(_UpperCAmelCase  )
              except np.linalg.LinAlgError:
                     raise ValueError(
                         """Input matrix A is not invertible. Cannot compute Schur complement."""  )

       return mat_c - mat_b.T @ a_inv @ mat_b







class A__       (						unittest.TestCase      ):






      def __UpperCAmelCase       ( self			:Any	)       ->					None:




             '''simple docstring'''
             _a    : Tuple     					=np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]	)
             _a    : Union[str, Any]     					=np.array([[0, 3], [3, 0], [2, 3]]	)
             _a    : List[Any]     					=np.array([[2, 1], [6, 3]]	)

             _a    : int     					=schur_complement(SCREAMING_SNAKE_CASE     ,						SCREAMING_SNAKE_CASE     ,						SCREAMING_SNAKE_CASE	)

             _a    : Tuple     					=np.block([[a, b], [b.T, c]]	)

             _a    : Tuple     					=np.linalg.det(SCREAMING_SNAKE_CASE	)
             _a    : Dict     					=np.linalg.det(SCREAMING_SNAKE_CASE	)
             _a    : List[str]     					=np.linalg.det(SCREAMING_SNAKE_CASE	)

             self.assertAlmostEqual(SCREAMING_SNAKE_CASE     ,						det_a * det_s	)






      def __UpperCAmelCase       ( self			:Union[str, Any]	)       ->					None:




             '''simple docstring'''
             _a    : Optional[Any]     					=np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]	)
             _a    : Union[str, Any]     					=np.array([[0, 3], [3, 0], [2, 3]]	)
             _a    : List[str]     					=np.array([[2, 1], [6, 3]]	)

             with self.assertRaises(SCREAMING_SNAKE_CASE	):
                    schur_complement(SCREAMING_SNAKE_CASE     ,						SCREAMING_SNAKE_CASE     ,						SCREAMING_SNAKE_CASE	)






      def __UpperCAmelCase       ( self			:str	)       ->					None:




             '''simple docstring'''
             _a    : str     					=np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]	)
             _a    : int     					=np.array([[0, 3], [3, 0], [2, 3]]	)
             _a    : Tuple     					=np.array([[2, 1, 3], [6, 3, 5]]	)

             with self.assertRaises(SCREAMING_SNAKE_CASE	):
                    schur_complement(SCREAMING_SNAKE_CASE     ,						SCREAMING_SNAKE_CASE     ,						SCREAMING_SNAKE_CASE	)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   unittest.main()






'''simple docstring'''







# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel  # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    '''stable diffusion controlnet''',
    '''0.22.0''',
    '''Importing `StableDiffusionControlNetPipeline` or `MultiControlNetModel` from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import StableDiffusionControlNetPipeline` instead.''',
    standard_warn=False,
    stacklevel=3,
)


