Hm, Conceptually it seems like the multi-stage training might be the way to go.  This is my first every pytorch model, and I just picked up python in January so what is “easy” for some, is likely dependent on experience .
I trained this network in a different NN language, but am really pushing to get it to work so that I can capitalize on the large dataset GLoVE provides.  Do you have any recommendations for an example model that uses multi-stage training?
class BiDir(torch.nn.Module):
def **init** (self, weights, emb_dim, hid_dim, rnn_num_layers=2):
super(). **init** ()
[/quote]