Comments (2)
I was able to dig into finding the pretraining code, and was able to find scripts for that, which I have pushed to the "pretrain" branch.
Unfortunately, I was not able to find exactly the code that was used in our final experiments, but was able to find enough to verify that pretraining used the correct class set, and did not use any other pretrained weights. There are details around the number of resnet layers used (3 or 4) that I wasn't able to find, and may even have been deleted at this point, but was able to get the script running again. Hope this is able to help.
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But you can turn off the pre-trained mode in the code, right?
Don't know if the author used the pre-trained model in the paper:)
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Related Issues (12)
- difference between paper and implement HOT 4
- how long we need to train? HOT 1
- I am interested in your work. But I just train a 4-conv layer with your method, and log esimated the left time is 40 days. Could you release the model reported in your paper, thx
- is there any reproducibility problem? HOT 9
- it seems difficult to reproduce HOT 1
- code problem HOT 1
- Why i can't run the code with default setting HOT 17
- How to use multi graphics card to run it
- How to implement Concentrator, Projector and Reshaper when use ResNet18 as backbone HOT 2
- I think the author pre-trained the model using 64 meta-training set + 16 meta-testing set, that's the reason of high performance. HOT 1
- Is the result difficult to reproduce? HOT 1
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from few-shot-ctm.