getting NaN values in ndcg

[Ellyuca]

Hi, I am playing around with the vae_cf implementation and I tried to my dataset, instead of the ML-20M. It has the same structure (userid, itemid, ratings) and I made sure data type are the same. I left all the pre-processing part as it is. I am using google colab to run the code. When I use the ML-20M dataset everything works just fine. Instead, when I try to train the model using my dataset, I get nan values in ndcg_dist list.

Here i copy/paste the error i get: InvalidArgumentErrorTraceback (most recent call last)

in () 82 ndcgs_vad.append(ndcg_) 83 print("printing ndcg_var: ", ndcg_var) ---> 84 merged_valid_val = sess.run(merged_valid, feed_dict={ndcg_var: ndcg_, ndcg_dist_var: ndcg_dist}) 85 print("printing feed_dict:", feed_dict) 86 summary_writer.add_summary(merged_valid_val, epoch)

3 frames

/usr/local/lib/python2.7/dist-packages/tensorflow_core/python/client/session.pyc in _do_call(self, fn, *args) 1382 '\nsession_config.graph_options.rewrite_options.' 1383 'disable_meta_optimizer = True') -> 1384 raise type(e)(node_def, op, message) 1385 1386 def _extend_graph(self):

InvalidArgumentError: Nan in summary histogram for: ndcg_at_k_hist_validation [[node ndcg_at_k_hist_validation (defined at /usr/local/lib/python2.7/dist-packages/tensorflow_core/python/framework/ops.py:1748) ]]

Does anyone have any clue what is the cause of this issue? I would really appreciate any kind of advice and suggestions you may give me.

Thank you very much. Have a great day.

[jpc327]

Hello, Did you ever resolve this issue? I'm encountering the same error. Thanks!

[Ellyuca]

Hi. It's been months since I last worked on this project. I couldn't find any definitive solution so what I did was to ignore the dcg with zero as value which was causing a division by zero error and creating NaNs. It's not the best solution but it was the only way I could make it work.

Good luck with everything. I hope you'll be able to find a better way to solve the issue. If you do find a better solution let me know as well.

Have a great day. Best, Alina.

[shhoff]

Ellyuca Thanks for your concern! I have very similar problem here... Also find other sources but not satisfied solution:( I also solve the problem by adding 1e-6 to each division term hehe:) If I can find better solution, I'll contact again! Thanks for your great intuition!