random uniform choosing of k in k-shot in training about snail-pytorch

[ericjang]

I implemented it in a fork of this repo: ericjang@7710e39

It wasn't clear to me from reading the paper how exactly random K-shot is implemented, since the number of parameters in a TC block is dependent on K. So I implemented this by zeroing out random.randint(0, K-1)*N of each minibatch at training time.

[eambutu]

Good catch, let me update that and update the numbers based off of that.

[kyz20]

Good catch, let me update that and update the numbers based off of that.

So have you already updated the code of this ?

[ericjang]

Emailed Nikhil Mishra, he's informed me that the "random uniform choosing of k in k-shot in training" did not make the model perform better, it was just a trick so they could evaluate 1 shot and 5 shot without re-training the model. The discrepancy in performance doesn't seem to reside there.