input: Write a python function to solve a system of linear equations using the least-squares method.
  assert solve_least_squares(np.matrix([[2, 5], [1, 2]]), np.matrix([[10], [8]])) == (6.0, 1.0)
  assert solve_least_squares(np.matrix([[1, 1], [1, -1]]), np.matrix([[4], [2]])) == (3.0, 1.0)
  assert solve_least_squares(np.matrix([[1, 2], [3, 4]]), np.matrix([[5], [11]])) == (1.0, 2.0)
output: import numpy as np
  
  def solve_least_squares(A, B):
      x, residuals, rank, s = np.linalg.lstsq(A, B, rcond=None)
      return tuple(x.flatten().tolist())