well saying to look at the docs was not meant to be mean (too blunt maybe, I apologize).
I agree with you that it should complain about the dimension of the input not being 3!
In the code (torch/nn/modules/rnn.py) the batch size is from input.size(1) (as it is not packed), but when checking for the input size in check_forward_args, as the batch size is given, it assumes
it is packed and then it is happy with an input of dimension 2!
I did not check further, but I guess broadcast magic makes it work during forward, as you matched its dim1 to the expected number of features.
EDIT: it does not complain in version ‘0.3.0.post4’ (time to update…)