LSTM hidden layer computation about grid-lstm HOT 2 OPEN

I also have a question about weight sharing: for the time LSTM in your example, weights are not shared between layers (they are shared in time only, thanks to clones) while for the depth LSTM, weights are shared between layers and time. This makes a lot a sense, in fact.

But it surprised me at first read because the "tied N-LSTM" is, by definition, sharing weight along all dimensions.

Either

1. NOT cloning weights of the depth LSTM in times, or
2. share also the weights of the time LSTM in depth
   would be more coherent... do you have any idea also ?

Thanks,

from grid-lstm.

I think the paper said the same weight for the time and depth of LSTM. You can refer to the paper 4.3.

from grid-lstm.