SPDRectified() makes the model output consistent

[Flzjler]

When I added SPDRectified() to my model, I found that the output of the model remained consistent for all samples. But after I remove the layer, the output is normal.

My code is as follows:

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.trans = SPDTransform(16, 10)
        self.rect = SPDRectified()
        self.tangent = SPDTangentSpace(10)
        self.linear = nn.Linear(55, 2, bias=False)

    def forward(self, x):
        a = self.trans(x)
        b = self.rect(a)
        c = self.tangent(b)
        d = self.linear(c)
        return d

if __name__ == '__main__':
    data = scipy.io.loadmat('./db.mat')['data']
    data = torch.from_numpy(data).to(torch.float)

    model = Net()
    pred = model(data)
    print(pred)

When I added SPDRectified(), the ouput is:

tensor([[0.6507, 4.6896],
        [0.6507, 4.6896],
        [0.6507, 4.6896]], grad_fn=<MmBackward0>)

When I delete SPDRectified(), the ouput is:

tensor([[-3.0920,  1.4963],
        [-3.1109,  1.5340],
        [-3.0174,  1.5908]], grad_fn=<MmBackward0>)

Why does this happen, is it because of the data?