
'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


_UpperCAmelCase :   List[str]			    =	logging.get_logger(__name__)

_UpperCAmelCase :   Any			    =	{
    """facebook/convnextv2-tiny-1k-224""": """https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json""",
}

class       UpperCAmelCase					(       snake_case_	,		snake_case_			):





		"""simple docstring"""





		A__	: Optional[Any]    =     'convnextv2'
		def __init__(     self	,       _snake_case=3	,       _snake_case=4	,       _snake_case=4	,       _snake_case=None	,       _snake_case=None	,       _snake_case="gelu"	,       _snake_case=0.02	,       _snake_case=1E-12	,       _snake_case=0.0	,       _snake_case=224	,       _snake_case=None	,       _snake_case=None	,       **_snake_case	,       )					->     List[Any]:
				super().__init__(**_snake_case  )

				_UpperCamelCase							:			Optional[Any]     =   num_channels
				_UpperCamelCase							:			Dict     =   patch_size
				_UpperCamelCase							:			str     =   num_stages
				_UpperCamelCase							:			str     =   [96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
				_UpperCamelCase							:			Optional[Any]     =   [3, 3, 9, 3] if depths is None else depths
				_UpperCamelCase							:			int     =   hidden_act
				_UpperCamelCase							:			Dict     =   initializer_range
				_UpperCamelCase							:			Optional[int]     =   layer_norm_eps
				_UpperCamelCase							:			Dict     =   drop_path_rate
				_UpperCamelCase							:			int     =   image_size
				_UpperCamelCase							:			List[str]     =   ['''stem'''] + [F'''stage{idx}''' for idx in range(1	,       len(self.depths  ) + 1  )]
				_UpperCamelCase,				_UpperCamelCase							:			Any     =   get_aligned_output_features_output_indices(
				    out_features=_snake_case	,       out_indices=_snake_case	,       stage_names=self.stage_names  )













import unittest

import numpy as np





def 		__UpperCAmelCase     (	a_				,	a_				,	a_				,	a_ = None				,	):
							snake_case_           =				np.shape(a_)
							snake_case_           =				np.shape(a_)
							snake_case_           =				np.shape(a_)

							if shape_a[0] != shape_b[0]:
														snake_case_           =				(
														    '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(a_)

							if shape_b[1] != shape_c[1]:
														snake_case_           =				(
														    '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(a_)

							snake_case_           =				pseudo_inv
							if a_inv is None:
														try:
																					snake_case_           =				np.linalg.inv(a_)
														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 					UpperCamelCase_ (     unittest.TestCase							):



	'''simple docstring'''




	def 				_UpperCamelCase     (			self   )			->       None:
								snake_case_           =				np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]   )
								snake_case_           =				np.array([[0, 3], [3, 0], [2, 3]]   )
								snake_case_           =				np.array([[2, 1], [6, 3]]   )

								snake_case_           =				schur_complement(a			,     a			,     a   )

								snake_case_           =				np.block([[a, b], [b.T, c]]   )

								snake_case_           =				np.linalg.det(a   )
								snake_case_           =				np.linalg.det(a   )
								snake_case_           =				np.linalg.det(a   )

								self.assertAlmostEqual(a			,     det_a * det_s   )




	def 				_UpperCamelCase     (			self   )			->       None:
								snake_case_           =				np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]   )
								snake_case_           =				np.array([[0, 3], [3, 0], [2, 3]]   )
								snake_case_           =				np.array([[2, 1], [6, 3]]   )

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






	def 				_UpperCamelCase     (			self   )			->       None:
								snake_case_           =				np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]   )
								snake_case_           =				np.array([[0, 3], [3, 0], [2, 3]]   )
								snake_case_           =				np.array([[2, 1, 3], [6, 3, 5]]   )

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


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	unittest.main()





