from sklearn import linear_model

X = []
y = []
shape = list(map(int, input().split()))
new_X = []

for _ in range(shape[1]):
    parts = list(map(float, input().split()))
    X.append(parts[:shape[0]])
    y.append(parts[-1])
    
for _ in range(int(input())):
    new_X.append(list(map(float, input().split())))
    
lm = linear_model.LinearRegression()
lm.fit(X, y)
y_hat = lm.predict(new_X)
for y in y_hat:
    print(f'{y:.2f}')