code: public Map<String, INDArray> rnnActivateUsingStoredState(INDArray[] inputs, boolean training,
                                                               boolean storeLastForTBPTT) {
          return ffToLayerActivationsDetached(training, FwdPassType.RNN_ACTIVATE_WITH_STORED_STATE, storeLastForTBPTT, vertices.length-1,
                  null, inputs, inputMaskArrays, labelMaskArrays, true);
      }
docs: Similar to rnnTimeStep and feedForward() methods. Difference here is that this method:<br>
  (a) like rnnTimeStep does forward pass using stored state for RNN layers, and<br>
  (b) unlike rnnTimeStep does not modify the RNN layer state<br>
  Therefore multiple calls to this method with the same input should have the same output.<br>
  Typically used during training only. Use rnnTimeStep for prediction/forward pass at test time.
  
  @param inputs            Input to network
  @param training          Whether training or not
  @param storeLastForTBPTT set to true if used as part of truncated BPTT training
  @return Activations for each layer (including input, as per feedforward() etc)