The pytorch tutorial 16 on seq2seq translation mentions something about the decoder. It says

In the simplest seq2seq decoder we use only last output of the encoder. This last output is sometimes called the  context vector  as it encodes context from the entire sequence. This context vector is used as the initial hidden state of the decoder.

The documentation 10 of nn.GRU mentions that it returns → output, h_n
Which one these (output, h_n) signify context vector?
I am using GRU for classifying sentences between two classes, say between positive and negative class. Which one of (output, h_n) would be useful for this classification?