



import numpy as np



def       lowercase       (   SCREAMING_SNAKE_CASE__       :	np.ndarray				,       SCREAMING_SNAKE_CASE__       :	np.ndarray				,       SCREAMING_SNAKE_CASE__       :	float = 1e-1_2				,       SCREAMING_SNAKE_CASE__       :	int = 100				,       )  ->     tuple[float, np.ndarray]:
 assert np.shape(SCREAMING_SNAKE_CASE__				)[0] == np.shape(SCREAMING_SNAKE_CASE__				)[1]
 # Ensure proper dimensionality.
 assert np.shape(SCREAMING_SNAKE_CASE__				)[0] == np.shape(SCREAMING_SNAKE_CASE__				)[0]
 # Ensure inputs are either both complex or both real
 assert np.iscomplexobj(SCREAMING_SNAKE_CASE__				) == np.iscomplexobj(SCREAMING_SNAKE_CASE__				)
 _snake_case    :  Tuple					=					np.iscomplexobj(SCREAMING_SNAKE_CASE__				)
 if is_complex:
  # Ensure complex input_matrix is Hermitian
  assert np.array_equal(SCREAMING_SNAKE_CASE__				,       input_matrix.conj().T				)

 # Set convergence to False. Will define convergence when we exceed max_iterations
 # or when we have small changes from one iteration to next.

 _snake_case    :  Optional[Any]					=					False
 _snake_case    :  str					=					0
 _snake_case    :  Tuple					=					0
 _snake_case    :  Tuple					=					1e1_2

 while not convergence:
  # Multiple matrix by the vector.
  _snake_case    :  int					=					np.dot(SCREAMING_SNAKE_CASE__				,       SCREAMING_SNAKE_CASE__				)
  # Normalize the resulting output vector.
  _snake_case    :  int					=					w / np.linalg.norm(SCREAMING_SNAKE_CASE__				)
  # Find rayleigh quotient
  # (faster than usual b/c we know vector is normalized already)
  _snake_case    :  Optional[Any]					=					vector.conj().T if is_complex else vector.T
  _snake_case    :  List[str]					=					np.dot(SCREAMING_SNAKE_CASE__				,       np.dot(SCREAMING_SNAKE_CASE__				,       SCREAMING_SNAKE_CASE__				)				)

  # Check convergence.
  _snake_case    :  int					=					np.abs(lambda_ - lambda_previous				) / lambda_
  iterations += 1

  if error <= error_tol or iterations >= max_iterations:
   _snake_case    :  List[str]					=					True

  _snake_case    :  Dict					=					lambda_

 if is_complex:
  _snake_case    :  Union[str, Any]					=					np.real(lambda_				)

 return lambda_, vector



def       lowercase       (   )  ->     None:
 _snake_case    :  List[Any]					=					np.array([[41, 4, 20], [4, 26, 30], [20, 30, 50]]				)
 _snake_case    :  Optional[Any]					=					np.array([41, 4, 20]				)
 _snake_case    :  int					=					real_input_matrix.astype(np.complexaaa				)
 _snake_case    :  int					=					np.triu(1j * complex_input_matrix				,       1				)
 complex_input_matrix += imag_matrix
 complex_input_matrix += -1 * imag_matrix.T
 _snake_case    :  int					=					np.array([41, 4, 20]				).astype(np.complexaaa				)

 for problem_type in ["real", "complex"]:
  if problem_type == "real":
   _snake_case    :  Union[str, Any]					=					real_input_matrix
   _snake_case    :  Dict					=					real_vector
  elif problem_type == "complex":
   _snake_case    :  Tuple					=					complex_input_matrix
   _snake_case    :  Optional[Any]					=					complex_vector

  # Our implementation.
  _snake_case	,    _snake_case    :  List[str]					=					power_iteration(SCREAMING_SNAKE_CASE__				,       SCREAMING_SNAKE_CASE__				)

  # Numpy implementation.

  # Get eigenvalues and eigenvectors using built-in numpy
  # eigh (eigh used for symmetric or hermetian matrices).
  _snake_case	,    _snake_case    :  str					=					np.linalg.eigh(SCREAMING_SNAKE_CASE__				)
  # Last eigenvalue is the maximum one.
  _snake_case    :  Dict					=					eigen_values[-1]
  # Last column in this matrix is eigenvector corresponding to largest eigenvalue.
  _snake_case    :  List[str]					=					eigen_vectors[:, -1]

  # Check our implementation and numpy gives close answers.
  assert np.abs(eigen_value - eigen_value_max				) <= 1e-6
  # Take absolute values element wise of each eigenvector.
  # as they are only unique to a minus sign.
  assert np.linalg.norm(np.abs(SCREAMING_SNAKE_CASE__				) - np.abs(SCREAMING_SNAKE_CASE__				)				) <= 1e-6


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  test_power_iteration()





import argparse
import os
import re


a__    =	"""src/transformers/models/auto"""


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
a__    =	re.compile(R"""[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict""")
# re pattern that matches identifiers in mappings
a__    =	re.compile(R"""\s*\(\s*\"(\S[^\"]+)\"""")



def       lowercase       (   SCREAMING_SNAKE_CASE__       :	int				,       SCREAMING_SNAKE_CASE__       :	bool = False				)  ->     Optional[Any]:
 with open(SCREAMING_SNAKE_CASE__				,       """r"""				,       encoding="""utf-8"""				) as f:
  _snake_case    :  int					=					f.read()

 _snake_case    :  str					=					content.split("""\n"""				)
 _snake_case    :  List[str]					=					[]
 _snake_case    :  int					=					0
 while line_idx < len(SCREAMING_SNAKE_CASE__				):
  if _re_intro_mapping.search(lines[line_idx]				) is not None:
   _snake_case    :  Union[str, Any]					=					len(re.search(R"""^(\s*)\S"""				,       lines[line_idx]				).groups()[0]				) + 8
   # Start of a new mapping!
   while not lines[line_idx].startswith(""" """ * indent + """("""				):
    new_lines.append(lines[line_idx]				)
    line_idx += 1

   _snake_case    :  int					=					[]
   while lines[line_idx].strip() != "]":
    # Blocks either fit in one line or not
    if lines[line_idx].strip() == "(":
     _snake_case    :  Optional[Any]					=					line_idx
     while not lines[line_idx].startswith(""" """ * indent + """)"""				):
      line_idx += 1
     blocks.append("""\n""".join(lines[start_idx : line_idx + 1]				)				)
    else:
     blocks.append(lines[line_idx]				)
    line_idx += 1

   # Sort blocks by their identifiers
   _snake_case    :  int					=					sorted(SCREAMING_SNAKE_CASE__				,       key=lambda SCREAMING_SNAKE_CASE__				: _re_identifier.search(SCREAMING_SNAKE_CASE__				).groups()[0]				)
   new_lines += blocks
  else:
   new_lines.append(lines[line_idx]				)
   line_idx += 1

 if overwrite:
  with open(SCREAMING_SNAKE_CASE__				,       """w"""				,       encoding="""utf-8"""				) as f:
   f.write("""\n""".join(SCREAMING_SNAKE_CASE__				)				)
 elif "\n".join(SCREAMING_SNAKE_CASE__				) != content:
  return True



def       lowercase       (   SCREAMING_SNAKE_CASE__       :	bool = False				)  ->     int:
 _snake_case    :  List[Any]					=					[os.path.join(SCREAMING_SNAKE_CASE__				,       SCREAMING_SNAKE_CASE__				) for f in os.listdir(SCREAMING_SNAKE_CASE__				) if f.endswith(""".py"""				)]
 _snake_case    :  str					=					[sort_auto_mapping(SCREAMING_SNAKE_CASE__				,       overwrite=SCREAMING_SNAKE_CASE__				) for fname in fnames]

 if not overwrite and any(SCREAMING_SNAKE_CASE__				):
  _snake_case    :  List[Any]					=					[f for f, d in zip(SCREAMING_SNAKE_CASE__				,       SCREAMING_SNAKE_CASE__				) if d]
  raise ValueError(
      F'''The following files have auto mappings that need sorting: {', '.join(SCREAMING_SNAKE_CASE__				)}. Run `make style` to fix'''
      """ this."""				)


if __name__ == "__main__":
  a__    =	argparse.ArgumentParser()
  parser.add_argument("""--check_only""", action="""store_true""", help="""Whether to only check or fix style.""")
  a__    =	parser.parse_args()

  sort_all_auto_mappings(not args.check_only)
