Hi,

I have no idea how to build a recurrent layer which looks like this and the autograd can run smoothly.

**x** is a 1-d tensor create by previous layer, in each time step **t**, the kernel will stride one step and do convolution with **x** until `time_step = len(x)`

, the result of the convolution becomes one value and add with **xt**, **xt** should be update by each time step, then becomes the input of next time step.

After the convolutional recurrent layer, for the autograd part, generate data x and real data only use L1loss (which means `real data - x`

).

Thanks in advance,

Zeyilain