多输入通道

对每个通道和对应卷积核互相关运算后求和

def corr2d_multi_in(X, K):
    # 先遍历“X”和“K”的第0个维度(通道维度),再把它们加在一起
    return sum(d2l.corr2d(x, k) for x, k in zip(X, K))
X = torch.tensor([[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0], [6.0, 7.0, 8.0]],
	             [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]])
K = torch.tensor([[[0.0, 1.0], [2.0, 3.0]],
				 [[1.0, 2.0], [3.0, 4.0]]])
 
corr2d_multi_in(X, K)