Lighter on memory: LSTMs store information in their cell gates so
if the input sequence is long, much more memory is used by the
LSTM network. Comparatively, TCNs are relatively straightforward
because they are comprised of several layers that all share their own
respective filters. Compared to LSTMs, TCNs are much lighter to run
in regards to their memory usage.
However, TCNs do carry some disadvantages:
•
Memory usage during evaluation mode: RNNs only need to
know some input xt to generate a prediction, since they maintain
a summary of everything they learned through their hidden state
vectors. In comparison, TCNs need the entire sequence up until the
current point again to make an evaluation, leading to potentially
higher memory usage than an RNN.
Chapter 7 temporal Convolutional networks
259
•
Do'stlaringiz bilan baham: |