Computation of sequences of variable length sequences for RNN

Question

Assume a recurrent neural network with sequences of variable length as input. To achieve efficiency, sequences of the same length can be combined to minimize the number of additions to each batch called forging. How can this be implemented in Keras?

For reference, the Tensorflow Seq2Seq Tutorial that uses legacy ops contains this, but its code should be simplified in Keras with fewer lines of code.