So remember the 4-tuple of indices (word, pos_tag, dep_tag and dir) that I mentioned? I change this 4 tuple so that instead of the word index, I pass the embedding vector of the word and keep the other 3 params in the tuple (pos_tag, dep_tag and dir) the exact same. This way, i don’t have to load the entire embeddings file in the pytorch Embeddings layer, and only do it for the words I am training my model on.
Hope that clarifies my use case now. Sorry for not explaining it well earlier!