



import unittest

import numpy as np

def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						np.ndarray						,  SCREAMING_SNAKE_CASE__     :						np.ndarray						,  SCREAMING_SNAKE_CASE__     :						np.ndarray						,  SCREAMING_SNAKE_CASE__     :						np.ndarray | None = None						,  )  ->       np.ndarray:





     '''simple docstring'''

     _UpperCAmelCase      :     List[Any]        =   np.shape(SCREAMING_SNAKE_CASE__    )
     _UpperCAmelCase      :     List[str]        =   np.shape(SCREAMING_SNAKE_CASE__    )
     _UpperCAmelCase      :     Optional[Any]        =   np.shape(SCREAMING_SNAKE_CASE__    )

     if shape_a[0] != shape_b[0]:
          _UpperCAmelCase      :     Any        =   (
              "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(SCREAMING_SNAKE_CASE__    )

     if shape_b[1] != shape_c[1]:
          _UpperCAmelCase      :     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(SCREAMING_SNAKE_CASE__    )

     _UpperCAmelCase      :     List[str]        =   pseudo_inv
     if a_inv is None:
          try:
               _UpperCAmelCase      :     Any        =   np.linalg.inv(SCREAMING_SNAKE_CASE__    )
          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						):



      def 						snake_case_ (					self					:     List[str]						):
           _UpperCAmelCase      :     Optional[Any]        =   np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]						)
           _UpperCAmelCase      :     Any        =   np.array([[0, 3], [3, 0], [2, 3]]						)
           _UpperCAmelCase      :     Any        =   np.array([[2, 1], [6, 3]]						)

           _UpperCAmelCase      :     List[Any]        =   schur_complement(A					,     A					,     A						)

           _UpperCAmelCase      :     Optional[Any]        =   np.block([[a, b], [b.T, c]]						)

           _UpperCAmelCase      :     Tuple        =   np.linalg.det(A						)
           _UpperCAmelCase      :     Optional[int]        =   np.linalg.det(A						)
           _UpperCAmelCase      :     Union[str, Any]        =   np.linalg.det(A						)

           self.assertAlmostEqual(A					,     det_a * det_s						)



      def 						snake_case_ (					self					:     Dict						):
           _UpperCAmelCase      :     Tuple        =   np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]						)
           _UpperCAmelCase      :     str        =   np.array([[0, 3], [3, 0], [2, 3]]						)
           _UpperCAmelCase      :     Any        =   np.array([[2, 1], [6, 3]]						)

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



      def 						snake_case_ (					self					:     List[Any]						):
           _UpperCAmelCase      :     Optional[int]        =   np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]						)
           _UpperCAmelCase      :     Dict        =   np.array([[0, 3], [3, 0], [2, 3]]						)
           _UpperCAmelCase      :     str        =   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()





"""simple docstring"""




import importlib
import inspect
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_lowerCAmelCase    : Dict							=							"src/transformers"


# This is to make sure the transformers module imported is the one in the repo.
_lowerCAmelCase    : List[Any]							=							importlib.util.spec_from_file_location(
    "transformers",
    os.path.join(PATH_TO_TRANSFORMERS, "__init__.py"),
    submodule_search_locations=[PATH_TO_TRANSFORMERS],
)
_lowerCAmelCase    : Tuple							=							spec.loader.load_module()

_lowerCAmelCase    : Tuple							=							transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
_lowerCAmelCase    : Optional[int]							=							re.compile("\[(.+?)\]\((https://huggingface\.co/.+?)\)")


_lowerCAmelCase    : Optional[int]							=							{
    "CLIPConfigMixin",
    "DecisionTransformerConfigMixin",
    "EncoderDecoderConfigMixin",
    "RagConfigMixin",
    "SpeechEncoderDecoderConfigMixin",
    "VisionEncoderDecoderConfigMixin",
    "VisionTextDualEncoderConfigMixin",
}

def 						__snake_case						(				)  ->       Dict:





     '''simple docstring'''

     _UpperCAmelCase      :     List[str]        =   []

     for config_class in list(CONFIG_MAPPING.values()    ):
          _UpperCAmelCase      :     Union[str, Any]        =   False

          # source code of `config_class`
          _UpperCAmelCase      :     Optional[int]        =   inspect.getsource(SCREAMING_SNAKE_CASE__    )
          _UpperCAmelCase      :     List[Any]        =   _re_checkpoint.findall(SCREAMING_SNAKE_CASE__    )

          for checkpoint in checkpoints:
               # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
               # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
               _UpperCAmelCase    ,	_UpperCAmelCase      :     List[Any]        =   checkpoint

               # verify the checkpoint name corresponds to the checkpoint link
               _UpperCAmelCase      :     Optional[Any]        =   f'https://huggingface.co/{ckpt_name}'
               if ckpt_link == ckpt_link_from_name:
                    _UpperCAmelCase      :     Optional[Any]        =   True
                    break

          _UpperCAmelCase      :     int        =   config_class.__name__
          if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
               configs_without_checkpoint.append(SCREAMING_SNAKE_CASE__    )

     if len(SCREAMING_SNAKE_CASE__    ) > 0:
          _UpperCAmelCase      :     List[str]        =   "\n".join(sorted(SCREAMING_SNAKE_CASE__    )    )
          raise ValueError(f'The following configurations don\'t contain any valid checkpoint:\n{message}'    )


if __name__ == "__main__":
 check_config_docstrings_have_checkpoints()
