Hi, I got a question regarding the implementation of RNNs. In my implementation, the input to RNN at next time-step is basically the output of the RNN at previous timestep augmented with some external input. However, I was going through pytorch examples on RNNs (e.g., image captioning) and it seems we need to input the whole sequence of inputs at once into RNN as the input tensor should be of shape (seq_len, batch, input_size)  which means my implementation wouldn’t be possible to implement. Is it correct or is there anyway to implement the architecture shown below?