





"""simple docstring"""






from __future__ import annotations

from decimal import Decimal

from numpy import array

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       list[list[float]]:






       """simple docstring"""




       _UpperCAmelCase     =     Decimal

       # Check if the provided matrix has 2 rows and 2 columns
       # since this implementation only works for 2x2 matrices
       if len(SCREAMING_SNAKE_CASE							) == 2 and len(matrix[0]							) == 2 and len(matrix[1]							) == 2:
              # Calculate the determinant of the matrix
              _UpperCAmelCase     =     float(
                  d(matrix[0][0]							) * d(matrix[1][1]							) - d(matrix[1][0]							) * d(matrix[0][1]							)							)
              if determinant == 0:
                     raise ValueError('This matrix has no inverse.'							)

              # Creates a copy of the matrix with swapped positions of the elements
              _UpperCAmelCase     =     [[0.0, 0.0], [0.0, 0.0]]
              _UpperCAmelCase    ,							_UpperCAmelCase     =     matrix[1][1], matrix[0][0]
              _UpperCAmelCase    ,							_UpperCAmelCase     =     -matrix[1][0], -matrix[0][1]

              # Calculate the inverse of the matrix
              return [
                  [(float(d(SCREAMING_SNAKE_CASE							)							) / determinant) or 0.0 for n in row] for row in swapped_matrix
              ]
       elif (
           len(SCREAMING_SNAKE_CASE							) == 3
           and len(matrix[0]							) == 3
           and len(matrix[1]							) == 3
           and len(matrix[2]							) == 3
       ):
              # Calculate the determinant of the matrix using Sarrus rule
              _UpperCAmelCase     =     float(
                  (
                      (d(matrix[0][0]							) * d(matrix[1][1]							) * d(matrix[2][2]							))
                      + (d(matrix[0][1]							) * d(matrix[1][2]							) * d(matrix[2][0]							))
                      + (d(matrix[0][2]							) * d(matrix[1][0]							) * d(matrix[2][1]							))
                  )
                  - (
                      (d(matrix[0][2]							) * d(matrix[1][1]							) * d(matrix[2][0]							))
                      + (d(matrix[0][1]							) * d(matrix[1][0]							) * d(matrix[2][2]							))
                      + (d(matrix[0][0]							) * d(matrix[1][2]							) * d(matrix[2][1]							))
                  )							)
              if determinant == 0:
                     raise ValueError('This matrix has no inverse.'							)

              # Creating cofactor matrix
              _UpperCAmelCase     =     [
                  [d(0.0							), d(0.0							), d(0.0							)],
                  [d(0.0							), d(0.0							), d(0.0							)],
                  [d(0.0							), d(0.0							), d(0.0							)],
              ]
              _UpperCAmelCase     =     (d(matrix[1][1]							) * d(matrix[2][2]							)) - (
                  d(matrix[1][2]							) * d(matrix[2][1]							)
              )
              _UpperCAmelCase     =     -(
                  (d(matrix[1][0]							) * d(matrix[2][2]							)) - (d(matrix[1][2]							) * d(matrix[2][0]							))
              )
              _UpperCAmelCase     =     (d(matrix[1][0]							) * d(matrix[2][1]							)) - (
                  d(matrix[1][1]							) * d(matrix[2][0]							)
              )
              _UpperCAmelCase     =     -(
                  (d(matrix[0][1]							) * d(matrix[2][2]							)) - (d(matrix[0][2]							) * d(matrix[2][1]							))
              )
              _UpperCAmelCase     =     (d(matrix[0][0]							) * d(matrix[2][2]							)) - (
                  d(matrix[0][2]							) * d(matrix[2][0]							)
              )
              _UpperCAmelCase     =     -(
                  (d(matrix[0][0]							) * d(matrix[2][1]							)) - (d(matrix[0][1]							) * d(matrix[2][0]							))
              )
              _UpperCAmelCase     =     (d(matrix[0][1]							) * d(matrix[1][2]							)) - (
                  d(matrix[0][2]							) * d(matrix[1][1]							)
              )
              _UpperCAmelCase     =     -(
                  (d(matrix[0][0]							) * d(matrix[1][2]							)) - (d(matrix[0][2]							) * d(matrix[1][0]							))
              )
              _UpperCAmelCase     =     (d(matrix[0][0]							) * d(matrix[1][1]							)) - (
                  d(matrix[0][1]							) * d(matrix[1][0]							)
              )

              # Transpose the cofactor matrix (Adjoint matrix)
              _UpperCAmelCase     =     array(SCREAMING_SNAKE_CASE							)
              for i in range(3							):
                     for j in range(3							):
                            _UpperCAmelCase     =     cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
              _UpperCAmelCase     =     array(SCREAMING_SNAKE_CASE							)
              for i in range(3							):
                     for j in range(3							):
                            inverse_matrix[i][j] /= d(SCREAMING_SNAKE_CASE							)

        # Calculate the inverse of the matrix
              return [[float(d(SCREAMING_SNAKE_CASE							)							) or 0.0 for n in row] for row in inverse_matrix]
       raise ValueError('Please provide a matrix of size 2x2 or 3x3.'							)













"""simple docstring"""






from datetime import datetime

import matplotlib.pyplot as plt
import torch

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       for param in module.parameters():
              _UpperCAmelCase     =     False

def       __lowerCamelCase    (       )		->       Dict:






       """simple docstring"""




       _UpperCAmelCase     =     'cuda' if torch.cuda.is_available() else 'cpu'
       if torch.backends.mps.is_available() and torch.backends.mps.is_built():
              _UpperCAmelCase     =     'mps'
       if device == "mps":
              print(
                  'WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'
                  ' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'
                  ' with generations.'							)
       return device

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       str:






       """simple docstring"""




       _UpperCAmelCase     =     plt.imshow(SCREAMING_SNAKE_CASE							)
       fig.axes.get_xaxis().set_visible(SCREAMING_SNAKE_CASE							)
       fig.axes.get_yaxis().set_visible(SCREAMING_SNAKE_CASE							)
       plt.show()


def       __lowerCamelCase    (       )		->       Dict:






       """simple docstring"""




       _UpperCAmelCase     =     datetime.now()
       _UpperCAmelCase     =     current_time.strftime('%H:%M:%S'							)
       return timestamp






