howto_make_predictions_on_test_set

Source : http://forums.fast.ai/t/dog-breed-identification-challenge/7464/144?u=pierreguillou

The following methodology works to make predictions on the test set when it was not initially given to the data object. 
A idea : you must rerun your object data with test_name='test' and then, with learn.set_data(data).

The 3 lines of code are :

data = ImageClassifierData.from_csv(PATH, 
                                        'train', f'{label_csv}',
                                         test_name='test',
                                         num_workers=4,
                                         val_idxs=val_idxs, 
                                         suffix='.jpg', 
                                         tfms=tfms, 
                                         bs=bs)
learn.set_data(data)
log_preds,y = learn.TTA(is_test=True)