GRU4Rec is the original Theano implementation of the algorithm in "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016 and its follow-up "Recurrent Neural Networks with Top-k Gains for Session-based Recommendations". The code is optimized for execution on the GPU.
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Problems about the input of the model during training and testing. #18
Hello, @hidasib
I have read your paper but I am not sure about some details about the model's input at training and testing time. Could you please check my following descriptions of my understanding.
At training step, if the mini-batch size is 1, according to your figure, the first input vector of the model should be i{1,1}, i{2,1}, i{3,1}, and the corresponding labels of these three timesteps should be i{1,2}, i{2,2}, i{3,2}.
Then at testing time, for session 1, the input of the model should be i{1,1}, i{1,2}, i_{1,3}
Please let me know if I made any mistakes. Thank you very much in advance!
Hello, @hidasib I have read your paper but I am not sure about some details about the model's input at training and testing time. Could you please check my following descriptions of my understanding.
At training step, if the mini-batch size is 1, according to your figure, the first input vector of the model should be i{1,1}, i{2,1}, i{3,1}, and the corresponding labels of these three timesteps should be i{1,2}, i{2,2}, i{3,2}.
Then at testing time, for session 1, the input of the model should be i{1,1}, i{1,2}, i_{1,3}
Please let me know if I made any mistakes. Thank you very much in advance!