
from __future__ import annotations

from decimal import Decimal

from numpy import array







def        A__					(						lowerCamelCase						)  ->	Tuple:
				UpperCamelCase_:							Dict	=						Decimal

				# Check if the provided matrix has 2 rows and 2 columns
				# since this implementation only works for 2x2 matrices
				if len(lowerCamelCase						) == 2 and len(matrix[0]						) == 2 and len(matrix[1]						) == 2:
								# Calculate the determinant of the matrix
								UpperCamelCase_:							str	=						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_:							str	=						[[0.0, 0.0], [0.0, 0.0]]
								UpperCamelCase_,   UpperCamelCase_:							Optional[int]	=						matrix[1][1], matrix[0][0]
								UpperCamelCase_,   UpperCamelCase_:							List[str]	=						-matrix[1][0], -matrix[0][1]

								# Calculate the inverse of the matrix
								return [
								    [(float(d(lowerCamelCase						)						) / determinant) or 0.0 for n in row] for row in swapped_matrix
								]
				elif (
				    len(lowerCamelCase						) == 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_:							Optional[int]	=						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_:							Union[str, Any]	=						[
								    [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_:							Union[str, Any]	=						(d(matrix[1][1]						) * d(matrix[2][2]						)) - (
								    d(matrix[1][2]						) * d(matrix[2][1]						)
								)
								UpperCamelCase_:							Dict	=						-(
								    (d(matrix[1][0]						) * d(matrix[2][2]						)) - (d(matrix[1][2]						) * d(matrix[2][0]						))
								)
								UpperCamelCase_:							Tuple	=						(d(matrix[1][0]						) * d(matrix[2][1]						)) - (
								    d(matrix[1][1]						) * d(matrix[2][0]						)
								)
								UpperCamelCase_:							str	=						-(
								    (d(matrix[0][1]						) * d(matrix[2][2]						)) - (d(matrix[0][2]						) * d(matrix[2][1]						))
								)
								UpperCamelCase_:							Dict	=						(d(matrix[0][0]						) * d(matrix[2][2]						)) - (
								    d(matrix[0][2]						) * d(matrix[2][0]						)
								)
								UpperCamelCase_:							List[Any]	=						-(
								    (d(matrix[0][0]						) * d(matrix[2][1]						)) - (d(matrix[0][1]						) * d(matrix[2][0]						))
								)
								UpperCamelCase_:							str	=						(d(matrix[0][1]						) * d(matrix[1][2]						)) - (
								    d(matrix[0][2]						) * d(matrix[1][1]						)
								)
								UpperCamelCase_:							Optional[int]	=						-(
								    (d(matrix[0][0]						) * d(matrix[1][2]						)) - (d(matrix[0][2]						) * d(matrix[1][0]						))
								)
								UpperCamelCase_:							Dict	=						(d(matrix[0][0]						) * d(matrix[1][1]						)) - (
								    d(matrix[0][1]						) * d(matrix[1][0]						)
								)

								# Transpose the cofactor matrix (Adjoint matrix)
								UpperCamelCase_:							List[Any]	=						array(lowerCamelCase						)
								for i in range(3						):
												for j in range(3						):
																UpperCamelCase_:							Any	=						cofactor_matrix[j][i]

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

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








lowerCamelCase_						: Optional[Any]         =  """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

lowerCamelCase_						: Union[str, Any]         =  [{"""type""": """code""", """content""": INSTALL_CONTENT}]
lowerCamelCase_						: Optional[Any]         =  {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}






