I am trying to do NN based on this article 
Or based on the standard nn.transformer module
I have numbers instead of words. The size of one sequence is 5. At the output(I have three neurons), I need to predict three values (0, 1, 2). That is, at each step I take a window of size 5 and predict 0 or 1 or 2. In fact, this is a classification into 3 classes. Can I use the standard nn.transformer module and use my data instead of words? Or what do you advise me to do?
I am trying to do NN based on this article 
If you consider my example based on the nn.transformer module
Instead of words, I use a vector of numbers of size 7. I want to send this vector instead of the word directly to the nn.transformer module
The size of my sequence is always 5.
How can I make a simple example to check the functionality of the code? I do not understand what E. is
import torch import torch.nn as nn class Trans(nn.Module): def __init__(self, src_vocab, tgt_vocab): super(Trans, self).__init__() self.tr = nn.Transformer(src_vocab, tgt_vocab) def forward(self, src, tgt): out = self.tr(src, tgt) return out net = Trans(5,1) #src=5 (window), tgt=1 ('0' or '1' or '2') sr = torch.randn(5, 1, 7) #src: (S, N, E) E-?? tg = torch.tensor([0], dtype=torch.long) #tgt: (T, N, E) outputs = net(sr, tg) #output: (T, N, E)