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Code optimization for dropout operation
Thanks for your nice work. I just read through the code and find a small problem in dropout operation:
https://github.com/hkust-vgd/shellnet/blob/fe5cf5f3806e618c23e161b0fb8a57387268df78/shellconv.py#L119
Actually this dropout operation has no effect if you don't pass training=is_training
to it. The default value for training
parameter is False
so it will return the input untouched.
But it's ok, it doesn’t influence the experiment. Maybe you can fix it in your spare time, or just remove dropout
to make code clearer.