import numpy as np

def gaussian_elimination(A, b):
    n=len(b)
    aug_matrix = np.hstack([A.astype(float),b.reshape(n,1).astype(float)])
    for col in range(n-1):
        for row in range(col+1,n):
            factor=aug_matrix[row,col]/aug_matrix[col,col]
            aug_matrix[row,:]=aug_matrix[row,:]-factor*aug_matrix[col,:]
    x = np.zeros(n, dtype=float)  
    x[-1]=aug_matrix[-1,-1]/aug_matrix[-1,-2]
    for i in range(n-2,-1,-1):
        sum_val=np.dot(aug_matrix[i,i+1:n],x[i+1:n])
        x[i]=(aug_matrix[i,-1]-sum_val)/aug_matrix[i,i]
    return x


if __name__ == "__main__":
    A = np.array(eval(input()), dtype=float)
    b = np.array(eval(input()), dtype=float)
    x = gaussian_elimination(A, b)
    print(x.tolist())