p_transform=p_transform, data_prep_fun=data_prep_function_valid, label_prep_fun=label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) import tta tta = tta.LosslessTTA(p_augmentation) tta_test_data_iterator = data_iterators.TTADataGenerator( dataset='test-jpg', tta=tta, duplicate_label=False, img_ids=test_ids, p_transform=p_transform, data_prep_fun=data_prep_function_valid, label_prep_fun=label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) tta_test2_data_iterator = data_iterators.TTADataGenerator( dataset='test2-jpg', tta=tta, duplicate_label=False, img_ids=test2_ids, p_transform=p_transform, data_prep_fun=data_prep_function_valid, label_prep_fun=label_prep_function, rng=rng,
img_ids=valid_ids, p_transform=p_transform, data_prep_fun=data_prep_function_valid, label_prep_fun=label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) tta = tta.LosslessTTA(p_augmentation) tta_valid_data_iterator = data_iterators.TTADataGenerator( dataset='train-jpg', tta=tta, img_ids=valid_ids, p_transform=p_transform, data_prep_fun=data_prep_function_valid, label_prep_fun=label_prep_function, rng=rng, full_batch=False, random=False, infinite=False) test_data_iterator = data_iterators.DataGenerator( dataset='test-jpg', batch_size=chunk_size, img_ids=test_ids, p_transform=p_transform, data_prep_fun=data_prep_function_valid, label_prep_fun=label_prep_function, rng=rng, full_batch=False,