Expected Behavior

I want to convert torch.nn.Linear modules to weight drop linear modules in my model (possibly big), and I want to train my model with multi-GPUs. However, I have RuntimeError in my sample code. First, I have _weight_drop() which drops some part of weights in torch.nn.Linear (see the code below).

Actual Behavior

RuntimeError: arguments are located on different GPUs at /

I add a function(according the code in the tutorial4) to calculate the bleu score, but i get the vey low score(0.09), could you tell me why?
This is code to calculate bleu:

def translate_sentence(sentence, src_field, trg_field, model, device, max_len = 50):
    
    model.eval()
        
    if isinstance(sentence, str):
        nlp = spacy.load('de')
        tokens = [token.te

I'm studying 5_3_Document_Classification_with_CNN.

The make_embedding_matrix helper docs say that it should be fed in a list of words in the dataset. However, for the embedding matrix to return the correct embedding of a word from pretrained embeddings, the word list should be fed in the same order as in the vocabulary. Furthermore, there should be no gaps in the word indices in the vocabulary