I will be more specific. Thanks for your help so far btw 
input_matrix = fasttext_model.get_input_matrix()  # numpy
num_emb, emb_dim = input_matrix.shape
self.embbag = nn.EmbeddingBag(num_emb, emb_dim)

What is inside this input_matrix?
word vectors for EVERY possible word and 3 letter sequence seen in train? or word vectors for words only? If the former, then the matrix will be too big to fit in memory, if the latter, OOV words that would have a fastText representation won’t have one, since wont be saved in the self.embbag matrix, correct?
I hope I made myself clear