diyang opened a new issue #10805: SKIP RNN is incorrect in LSTnet URL: https://github.com/apache/incubator-mxnet/issues/10805 Thanks for your example and source code, it helps me a lot to develop my own LSTnet. However, I have noticed that there are some flaws in the implementation of Skip RNN of yours. The following is your way of implementing Skip RNN `#################### # Skip-RNN Component #################### stacked_rnn_cells = mx.rnn.SequentialRNNCell() for i, recurrent_cell in enumerate(skiprcells): stacked_rnn_cells.add(recurrent_cell) stacked_rnn_cells.add(mx.rnn.DropoutCell(dropout)) outputs, states = stacked_rnn_cells.unroll(length=q, inputs=cnn_reg_features, merge_outputs=False) # Take output from cells p steps apart p = int(seasonal_period / time_interval) output_indices = list(range(0, q, p)) outputs.reverse() skip_outputs = [outputs[i] for i in output_indices] skip_rnn_features = mx.sym.concat(*skip_outputs, dim=1) ` What I have noticed is that this way will not actually create a skip rnn, and what's this RNN doing is to select the hidden output of the first hour of every day in a week. According to the paper, what it should like is that input variants regarding every hour of any given day should pair with the hidden output regarding the same hour of the previous day. mx.rnn.SequentialRNNCell can not handle this type of recurrent, you might need to make your own native way to formuate this type of RNN.
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