Cell state in memory_bank

Working with the OpenNMT-py framework I have come across a puzzling thing. I can only seem to extract a hidden state from a seq2seq LSTM model, not the cell state. The encoder class in onmt/encoders/rnn_encoder.py returns enc_state, memory_bank, lengths. The hidden states are in memory_bank with size [sentence_length,batch_size,hidden_dim]. So where is the cell state?

It’s in enc_state (as the name suggests) which is the second output of the LSTM layer:

https://pytorch.org/docs/stable/nn.html#torch.nn.LSTM