Lesson 3 In-Class Discussion ✅

Part 1 (2019)
608

While running this code chunk:

data = (src.transform(tfms, size=256)
        .databunch().normalize(imagenet_stats))

learn.data = data
data.train_ds[0][0].shape

learn.freeze()

learn.lr_find()
learn.recorder.plot()

This is where we resize the images to 256 to improve the f-score - but I’m running into CUDA Out of memory issues, despite restarting the kernel. I am also just loading the saved weights from the previous run, and thus not re-running any model. I’m using GCP Compute instance for training my models. Does anyone have a workaround for this?

1 Like