Hello, I am a beginner in deep learning and just learnt the fast.ai library last week for an ongoing image classification competition. The competition features a large dataset (100k+) with many categories (~40) and a relatively dirty dataset. I was trying to explore with different pretrained models of varying complexity as well as augmentations. I managed to get it working (though only after several hours of debugging!) with a ResNext101 model from the pytorchcv model zoo, using cnn_learner and a custom_head. While I currently have a decent score on the public leaderboard, I am still far from the threshold score needed to earn full points from the organiser (it is a series of challenges). I want to do my best to get there.
Currently, even after several hours of sweating and head-scratching, I failed to add in extra augmentations that other fast.ai users have developed, found in this amazing github repo: https://github.com/oguiza/fastai_extensions
Specifically, I wanted to make use of the various blend augmentations, especially progressive sprinkles, having read posts by LessW2020 (who, by the way, is truly amazing). However, whenever I try to add the
.blend(**kwargs) method to my cnn_learner, it throws:
AttributeError: 'Learner' object has no attribute 'blend' , and I cannot continue. I also get a
'Learner' object has no attribute 'batch_loss_filter' when I try to use the Batch Loss Filter callback to try to accelerate my training.
While this has been extremely frustrating as googling did not give me the answers, I suspect it is because I am using cnn_learner, and not Learner, and there are some inherent differences between them, although I cannot find the documentation that exactly specifies what are the differences…only a comment or two in the forums saying something about how cnn_learner is better optimised for learning than Learner.
Could anyone explain what are the differences between these two, and if this difference will cause me a hit in accuracy, how can I change the settings of Learner() to make it essentially a replica of cnn_learner so that I can access all these cool extensions?
Thanks and cheers.