Sorry for the late reply.
I’ve tried that
# train_set and valid_set are like [(tensor size 784, label), ...]
dl = DataLoader(train_set, batch_size=bs, shuffle=True)
valid_dl = DataLoader(valid_set, batch_size=bs)
dls = DataLoaders(dl, valid_dl)
learn = cnn_learner(dls, resnet34, metrics=error_rate, normalize=False, n_out=10, loss_func=CrossEntropyLossFlat())
learn.fine_tune(1)
but it doesn’t work, it says
RuntimeError: Expected 4-dimensional input for 4-dimensional weight [64, 3, 7, 7], but got 2-dimensional input of size [500, 784] instead
500 is the batch size, 784 is the total pixels of the image, 28x28.