hi, i have a problem here, i got a sequence of Variables which are the outputs of the bi-directional RNN, and i stacked them into a matrix `xs_h`

whose dimension is `(seq_length, batch_size, hidden_size)`

, them i want to update the matrix `xs_h`

by convoluting on two slices in `xs_h`

, some codes are as follows:

`new_xs_h = xs_h.clone()`

`vp, vc = xs_h[idx_0, bidx], xs_h[idx_1, bidx]`

`x = tc.stack([self.f1(vp), self.f2(vc)], dim=1)[None, :, :]`

`new_xs_h[idx_1, bidx] = self.tanh(self.l_f2(self.conv(x).squeeze()))`

actually, i want to update the Variable `xs_h`

and then let the new updated matrix `new_xs_h`

get into my computation graph again. However, i got following errors when i call `backward()`

after the running of above code:

`RuntimeError: element 0 of variables does not require grad and does not have a grad_fn`

i do not kown why, any reply will be appreciated.

thanks.