pointnet.py 文件源码

def forward(self, x):
        batchsize = x.size()[0]
        x = F.relu(self.bn1(self.conv1(x))) # bz x 256 x 2048 
        x = F.relu(self.bn2(self.conv2(x))) # bz x 1024 x 2048
        x = self.mp1(x) # bz x 1024 x 1
        x = x.view(-1, 1024)

        x = F.relu(self.bn3(self.fc1(x))) # bz x 512 
        x = F.relu(self.bn4(self.fc2(x))) # bz x 256
        x = self.fc3(x) # bz x (128*128) 
        # identity transform
        # bz x (128*128)
        iden = Variable(torch.from_numpy(np.eye(128).astype(np.float32))).view(1,128*128).repeat(batchsize,1)
        if x.is_cuda:
            iden = iden.cuda()
        x = x + iden
        x = x.view(-1, 128, 128) # bz x 3 x 3 
        return x