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())