Hi, I am the first time using the pack_padded_sequence ,  and it seems to input the sequence length in a decreasing order. Here is the default pack_padded_sequence package from official website
torch.nn.utils.rnn.pack_padded_sequence(input, lengths, batch_first=False, enforce_sorted=True)


enforce_sorted: if  True , the input is expected to contain sequences sorted by length in a decreasing order. If  False , the input will get sorted unconditionally. Default:  True


It also mentions that enforce_sorted = True is only necessary for ONNX export., what is this mean? If I want to input the length without sorting, can I simply set it to False?
below is my idea of implement
# in dataset class; 
#return the question idx after padding and the original question length
class VQADataset(Dataset):
    def __getitem__(self, idx):
        return sample{'question': question, 'length':len(qst_token)}
    
# in model class
class model(nn.Module):
    def forward(self, qst, qst_length):
        word = self.embedding(qst) 
        qst_length = qst_length.tolist()             
        packed = rnn.pack_padded_sequence(word , qst_length, batch_first=True)

So, the length of question will be different every batch. can I simply set the enforce_sorted  into False ?