The input vectors are then passed to the LSTM recurrent layer, which computes a compositional representation − → h t at every time step t by performing nonlinear transformations of the current input x t and the output of the previous time step − → h t−1 .
the recurrent layer in a LSTM RNN is constituted with hidden units called memory blocks.