borelien / entailment-neural-attention-lstm-tf Goto Github PK

Hi,

In network.py, (line no 73)

h = o*tf.tanh(x=self.c[-1])

is correct? In the paper, h is derived by o and c which have the same timestamp, t.
It should be changed to h = o*tf.tanh(c)?

For something this complex that other people might want to use this is criminally underdocumented.
It would be nice if I didn't have to go through the entire code to figure out how the trained model should be used.
You are also missing a requirements.txt, so who knows whether this is going to work a couple of years from now, not to mention the fact that I have no idea what dependencies the code has in the first place.
If you are still maintaining the project I would really appreciate at least a user guide, but some docstrings would also be more than welcome.

Would you please clarify if the implementation reproduces the results reported in the paper or not? Thanks,