Basic class handling tweaks of the training loop by changing a `Learner` in various events
CSVLogger(fname = "history.csv", append = FALSE)
file name
append or not
None
if (FALSE) {
URLs_MNIST_SAMPLE()
# transformations
tfms = aug_transforms(do_flip = FALSE)
path = 'mnist_sample'
bs = 20
#load into memory
data = ImageDataLoaders_from_folder(path, batch_tfms = tfms, size = 26, bs = bs)
learn = cnn_learner(data, resnet18(), metrics = accuracy, path = getwd())
learn %>% fit_one_cycle(2, cbs = CSVLogger())
}