bug in SPDIncreaseDim, when SPD matrix size increases in SPDTransform

[alekseic]

I tried to create a somewhat unconventional SPDnet, where the size of SPD matrix first diminishes, and then increases back to original, in the manner of U-nets used for image segmentation. Here's my net that does 52x52->36x36->52x52:

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.trans1 = SPDTransform(52, 36)  #  first do some reduction
        self.trans2 = SPDTransform(36, 52)  #  then expand back to original size
        self.relu1 = nn.ReLU()
        self.relu2 = nn.ReLU()

    def forward(self, x):
        x = self.trans1(x)
        x = self.relu1(x)
        x = self.trans2(x)
        x = self.relu2(x)
        return x

When doing a forward pass with a batch of size 8x52x52, I get this error:

File "/home/anaconda3/lib/python3.6/site-packages/spdnet/spd.py", line 49, in forward output = torch.baddbmm(eye, torch.bmm(input, eye.transpose(1,2)), add)

RuntimeError: The expanded size of the tensor (52) must match the existing size (36) at non-singleton dimension 2. Target sizes: [8, 36, 52]. Tensor sizes: [8, 52, 36]

This happens in the forward part of SPDIncreaseDim. Could you please point me out what I'm doing wrong, or how should I change my code or your source code to get correct behaviour? Thanks!

[adavoudi]

Thanks for reporting. It was due to a change in the Pytorch API for the torch.baddbmm function. I've fixed it.

[alekseic]

Thanks, it works now!