Vikrant Goyal

I am getting this error while training. Traning command: python train.py -data ../data/word_with_pos_only -save_model ../models/word_with_pos_only_emb12 -layers 6 -rnn_size 512 -word_vec_size 500 -transformer_ff 2048 -heads 8 -encoder_type transformer -decoder_type transformer -position_encoding...

I figured out that if I use rnn_size to be equal to the total word_vec_size (i.e including feature dimensions), then it works. But the problem is I have to use...

@vince62s Hi, I have two problems:- 1) When using transformer model, if I choose the word_vec_size to be different than rnn_size, then it throws error. For example, use rnn_size=512 &...

@vince62s Yes that works fine because the total vec_size will come out to be 512 only (Therefore no conflicting issues with rrn_size). But the actual problem is: For example, if...

Hi @eduamf The "word features" thing works if you want same feature vec size for all features.

@vince62s I have updated (locally) the OpenNMT code to incorporate word features on the source side. It trains without any errors but fails on testing. The error seems to occur...

@vince62s The issue is solved & is working on my end. Please check the PR that I have submitted. After this I will also look into target side features if...