Hi, thank you for your recommendation.
This is a good tutorial but I am confused at the moment about the training process, especially the attention.
I used Tensorflow before and I am new to Pytorch. I know the attention should be implemented manually instead of a wrapper.
I am wondering how to train the model. In the tutorial and probably this link, https://github.com/spro/practical-pytorch/blob/master/seq2seq-translation/seq2seq-translation-batched.ipynb 10, @spro  it seems the rnn sequence should also be iterated manually, as it shows something like “for t in range(max_target_length):”. So how about the batch iteration in an epoch? Is it here, ‘for iter in range(1, n_iters + 1):’?
Basically, from my understanding, the training of seq2seq in Pytorch, might be two loops: 1) the batch loop in an epoch, 2) the sequence loop in one batch for feeding word by word until the end of a sequence (maybe max_time). Is it right? I am new to pytorch, and a little bit confused. I tried lstm for mnist classification as beginner program. It seems that the lstm can be used in a sequence style instead of feeding word by word. That is why I get stuck here.
Could you help me with it?  @hughperkins @spro