Method __init__

networks/module.py:438–443

(self, in_channels=32,hid_channels=1,out_channels=1,relu=True)

        return x
class AggWeightNetVolume(nn.Module):
    def __init__(self, in_channels=32,hid_channels=1,out_channels=1,relu=True):
        super(AggWeightNetVolume, self).__init__()
        self.w_net = nn.Sequential(
            Conv3d(in_channels, hid_channels, kernel_size=1, stride=1, padding=0,relu=relu),
            Conv3d(hid_channels, out_channels, kernel_size=1, stride=1, padding=0,relu=relu)
        )

    def forward(self, x):
        """