Thanks for your reply. Actually, I would like to explore the importance of the channel-wise features by summing up the channel-wise weights for a  group=3 Conv.
I tried to calculate a group=3 3x3 conv’s sum of weights by this,
            mid1_1 = net.conv1[-3].weight.data.shape[1]//3
            mid1_2 = net.conv1[-3].weight.data.shape[1]//3*2
            conv1_g1_ws = torch.sum(net.conv1[-3].weight.data[:mid1_1, :mid1_1, :, :])
            conv1_g2_ws = torch.sum(net.conv1[-3].weight.data[mid1_1:mid1_2, mid1_1:mid1_2, :, :])
            conv1_g3_ws = torch.sum(net.conv1[-3].weight.data[mid1_2:, mid1_2:, :, :])

Am I right? Many thanks for your advice.