D-EM: line 127 of run_inner_rnn() in nem_model.py: preds, h_new = self.cell((reshaped_masked_deltas, input_data), h_old) # add input_data as context # preds, h_new = self.cell(reshaped_masked_deltas, h_old) line 394 of build_network() in network.py: # DEBUG cell = NEMOutputDiscriWrapper(cell, out_size, "multi_rnn_cell/cell_0/EMCell_discri") line of 371 of NEMOutputDiscriWrapper in network.py: dense2 = tf.layers.dense(inputs=dense1, units=784*3, activation=tf.nn.relu) # *3 because the k:=3
D-RNN-EM: 127 same with the bove line 469 of build_network() in network.py: # DEBUG cell = NEMOutputDiscriWrapper(cell, out_size, "multi_rnn_cell/cell_0/EMCell_discri")
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