Shobhit_Narayanan
It is mentioned that the input dimension is n x d. But if the first hidden layer is treated as the first input how can the dimensions match?
1 reply
It is mentioned that the input dimension is n x d. But if the first hidden layer is treated as the first input how can the dimensions match?
1 reply
The input dimensions (& hence their respective weight’s dimension) for the 1st layer and the subsequent layers (i.e. 2nd 3rd etc…) are not same. We cannot reuse the code of 1-layer RNN/GRU/LSTM (as in Chapter 8, 9.1, 9.2) by stacking them up to form multi-layer RNNs.
We need to write separate code for 1st layer RNNs and subsequent layer RNNs, exactly due to the difference you mentioned.
And Hence the Exercise 1. 
My solutions to the exs: 10.3