Before revision:  We also added attention layer at top of rnn layer in our model to compute the  attention scores of each hidden layer corresponding to each input timestep. The attention score for each timestep were computed as an average score given to all the features associated with the timestep. These attention scores added interpretability at both timestep level and the features associated with the timesteps .
After revision:  We also added attention layer at top of rnn layer in our model to compute the attention scores of each hidden layer corresponding to each input timestamp. These feature ranking and attention scores added interpretability at both timestep level and the features associated with the timesteps .