

'''simple docstring'''







from __future__ import annotations

from typing import Any


class        A__   :



    def __init__(       self		,					UpperCamelCase__		,					UpperCamelCase__		,					UpperCamelCase__ = 0							)    ->   None:





           '''simple docstring'''
           A_       ,      A_						       =   row, column
           A_						       =   [[default_value for c in range(UpperCamelCase__							)] for r in range(UpperCamelCase__							)]



    def __str__(       self							)    ->   str:





           '''simple docstring'''
           A_						       =   f'''Matrix consist of {self.row} rows and {self.column} columns\n'''

           # Make string identifier
           A_						       =   0
           for row_vector in self.array:
                  for obj in row_vector:
                         A_						       =   max(UpperCamelCase__		,					len(str(UpperCamelCase__							)							)							)
           A_						       =   f'''%{max_element_length}s'''

           # Make string and return
           def single_line(UpperCamelCase__							) -> str:
                  nonlocal string_format_identifier
                  A_						       =   """["""
                  line += ", ".join(string_format_identifier % (obj,) for obj in row_vector							)
                  line += "]"
                  return line

           s += "\n".join(single_line(UpperCamelCase__							) for row_vector in self.array							)
           return s



    def __repr__(       self							)    ->   str:





           '''simple docstring'''
           return str(self							)



    def        snake_case_      (       self		,					UpperCamelCase__							)    ->   bool:





           '''simple docstring'''
           if not (isinstance(UpperCamelCase__		,					(list, tuple)							) and len(UpperCamelCase__							) == 2):
                  return False
           elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
                  return False
           else:
                  return True



    def __getitem__(       self		,					UpperCamelCase__							)    ->   Any:





           '''simple docstring'''
           assert self.validate_indicies(UpperCamelCase__							)
           return self.array[loc[0]][loc[1]]



    def __setitem__(       self		,					UpperCamelCase__		,					UpperCamelCase__							)    ->   None:





           '''simple docstring'''
           assert self.validate_indicies(UpperCamelCase__							)
           A_						       =   value



    def __add__(       self		,					UpperCamelCase__							)    ->   Matrix:





           '''simple docstring'''
           assert isinstance(UpperCamelCase__		,					UpperCamelCase__							)
           assert self.row == another.row and self.column == another.column

           # Add
           A_						       =   Matrix(self.row		,					self.column							)
           for r in range(self.row							):
                  for c in range(self.column							):
                         A_						       =   self[r, c] + another[r, c]
           return result



    def __neg__(       self							)    ->   Matrix:





           '''simple docstring'''
           A_						       =   Matrix(self.row		,					self.column							)
           for r in range(self.row							):
                  for c in range(self.column							):
                         A_						       =   -self[r, c]
           return result



    def __sub__(       self		,					UpperCamelCase__							)    ->   Matrix:





           '''simple docstring'''
           return self + (-another)



    def __mul__(       self		,					UpperCamelCase__							)    ->   Matrix:





           '''simple docstring'''

           if isinstance(UpperCamelCase__		,					(int, float)							):  # Scalar multiplication
                  A_						       =   Matrix(self.row		,					self.column							)
                  for r in range(self.row							):
                         for c in range(self.column							):
                                A_						       =   self[r, c] * another
                  return result
           elif isinstance(UpperCamelCase__		,					UpperCamelCase__							):  # Matrix multiplication
                  assert self.column == another.row
                  A_						       =   Matrix(self.row		,					another.column							)
                  for r in range(self.row							):
                         for c in range(another.column							):
                                for i in range(self.column							):
                                       result[r, c] += self[r, i] * another[i, c]
                  return result
           else:
                  A_						       =   f'''Unsupported type given for another ({type(UpperCamelCase__							)})'''
                  raise TypeError(UpperCamelCase__							)



    def        snake_case_      (       self							)    ->   Matrix:





           '''simple docstring'''
           A_						       =   Matrix(self.column		,					self.row							)
           for r in range(self.row							):
                  for c in range(self.column							):
                         A_						       =   self[r, c]
           return result







    def        snake_case_      (       self		,					UpperCamelCase__		,					UpperCamelCase__							)    ->   Any:





           '''simple docstring'''
           assert isinstance(UpperCamelCase__		,					UpperCamelCase__							) and isinstance(UpperCamelCase__		,					UpperCamelCase__							)
           assert self.row == self.column == u.row == v.row  # u, v should be column vector
           assert u.column == v.column == 1  # u, v should be column vector

           # Calculate
           A_						       =   v.transpose()
           A_						       =   (v_t * self * u)[0, 0] + 1
           if numerator_factor == 0:
                  return None  # It's not invertable
           return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":
      def    UpperCAmelCase__     (   )      ->      None:
             # a^(-1)
             A_						       =   Matrix(3,							3,							0					)
             for i in range(3					):
                    A_						       =   1
             print(F'''a^(-1) is {ainv}'''					)
             # u, v
             A_						       =   Matrix(3,							1,							0					)
             A_       ,      A_       ,      A_						       =   1, 2, -3
             A_						       =   Matrix(3,							1,							0					)
             A_       ,      A_       ,      A_						       =   4, -2, 5
             print(F'''u is {u}'''					)
             print(F'''v is {v}'''					)
             print(F'''uv^T is {u * v.transpose()}'''					)
             # Sherman Morrison
             print(F'''(a + uv^T)^(-1) is {ainv.sherman_morrison(UpperCAmelCase__,							UpperCAmelCase__					)}'''					)
      def    UpperCAmelCase__     (   )      ->      None:
             import doctest

             doctest.testmod()







      testa()



'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available


__lowerCamelCase									=     {
    '''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase									=     [
          '''ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''ErnieForCausalLM''',
          '''ErnieForMaskedLM''',
          '''ErnieForMultipleChoice''',
          '''ErnieForNextSentencePrediction''',
          '''ErnieForPreTraining''',
          '''ErnieForQuestionAnswering''',
          '''ErnieForSequenceClassification''',
          '''ErnieForTokenClassification''',
          '''ErnieModel''',
          '''ErniePreTrainedModel''',
      ]

if TYPE_CHECKING:
      from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_ernie import (
                ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
                ErnieForCausalLM,
                ErnieForMaskedLM,
                ErnieForMultipleChoice,
                ErnieForNextSentencePrediction,
                ErnieForPreTraining,
                ErnieForQuestionAnswering,
                ErnieForSequenceClassification,
                ErnieForTokenClassification,
                ErnieModel,
                ErniePreTrainedModel,
            )

else:
      import sys

      __lowerCamelCase									=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
