layer6ai-labs / dropoutnet Goto Github PK

When I execute main.py, I get：Allocation of 5224220000 exceeds 10% of system memory.
Why?

Is there an updated version of this implementation? Unfortunately my lab doesn't support tf1 in our servers. Hoping to find a keras/tf2/pytorch implementation as I wanted to explore dropoutnet for an academic research. Thank you!

Hi , Thanks for sharing the code along with paper for this interesting approach. Could you also please explain the preprocessing part for user,item content and user,item preference array(U.csv.bin,V.csv.bin). For preference vectors , is it SVD used to get latent representations? For content vectors, it is mentioned that after cleaning and transforming all categorical inputs into 1-of-n representation they ended up with 831 user features and 2738 item features.
What were the cleaning steps and how did you end up with 831 and 2738 features? Maybe if possible, please share the code.