Book4_Power-of-Matrix | Iris Book : From Addition Subtraction Multiplication

def matrix_triangular_solve(matrix, rhs, lower=True, adjoint=False, name=None):
  """Solve systems of linear equations with upper or lower triangular matrices.

  `matrix` is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions form
  square  

def _is_matrix_spd(matrix: np.ndarray) -> bool:
    """
    Returns True if input matrix is symmetric positive definite.
    Returns False otherwise.

    For a matrix to be SPD, all eigenvalues must be positive.

    >>> import numpy as   

def is_hermitian(matrix: np.ndarray) -> bool:
    """
    Checks if a matrix is Hermitian.
    >>> import numpy as np
    >>> A = np.array([
    ... [2,    2+1j, 4],
    ... [2-1j,  3,  1j],
    ... [4,    -1j,  1]])
    >>