carpedm20
Hidden State of RNN (not averaged ?)
Hello guys ,
Thank you very much for this work 👍 ! I have a quick question about the code :
Why in the cell method you output output, h[self.args.num_blocks - 1]. It looks like the h is only one loose end , whereas in the paper it looks like h = output = average over the loose ends.
In the Appendix of the paper, it says the cell receive the RNN signal $x^(t)$ at its current time step the output $h^{(t−1)}_D$ from the cell at the previous time step. So I think there is nothing wrong with the code.
@kamilbs @NewGod ,Hi,Can you run this code successfilly? When I run it by : python main.py --network_type cnn --dataset cifar10 --controller_optim momentum --controller_lr_cosine=True --controller_lr_max 0.05 --controller_lr_min 0.0001 --entropy_coeff 0.1,I met some errors． What I want to do is find cnn arvhitectures and make them visualized.Would you please tell me what changes Ishould do to the code before I run it. Thank s for your reply.
