You can check this question for further information, although it is based on Keras-1.x API.
Basically, the unit
means the dimension of the inner cells in LSTM. Because in LSTM, the dimension of inner cell (C_t and C_{t-1} in the graph), output mask (o_t in the graph) and hidden/output state (h_t in the graph) should have the SAME dimension, therefore you output’s dimension should be unit
-length as well.
And LSTM
in Keras only define exactly one LSTM block, whose cells is of unit
-length. If you set return_sequence=True
, it will return something with shape: (batch_size, timespan, unit)
. If false
, then it just return the last output in shape (batch_size, unit)
.
As for the input, you should provide input for every timestamp. Basically, the shape is like (batch_size, timespan, input_dim)
, where input_dim
can be different from the unit
. If you just want to provide input at the first step, you can simply pad your data with zeros at other time steps.