Comments (2)
The following should work:
python ./train.py --dataset cross --model Conv4 --method baseline --train_aug
python ./save_feature.py --dataset cross --model Conv4 --method baseline --train_aug
python ./test.py --dataset cross --model Conv4 --method baseline --train_aug
You could check io_utils.py
and train.py
for more detail.
from closerlookfewshot.
@johnnyasd12 Thank you so much for the hint! Looking at the code, dataset cross does look like the right command line parameter to go for domain adaptation test.
from closerlookfewshot.
Related Issues (20)
- Training accuracies are low and their gaps are big when Conv4 backbone is used.
- Question on feature_loader.py:32,33
- The stop_epoch number of maml
- Larger batch size for CUBS.
- Query Regarding Figure 5.
- TypeError: super() argument 1 must be type, not classobj
- assert params.num_classes >= 1597, 'class number need to be larger than max label id in base class' HOT 5
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- errro _pickle.PicklingError HOT 1
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from closerlookfewshot.