I’m coding a timeseries autoencoder that reconstructs the elements of the input reverse order, one at a time. I’m using the torch.cat operation to concatenate each element back into sequence form.
        # reconstruct remaining elements
        for i in range(1, self.seq_len):
            hs_i, cs_i = self.cell(x_i, (hs_i, cs_i))
            x_i = self.dense(hs_i)
            x = torch.cat([x, x_i])
        
        return x
        

I noticed that the output has grad_fn=<CatBackward>.
I was wondering why the autograd system would track things like collecting elements into a sequence? Will this mess with my backprop when it’s time to train?