+ # We will store the generated quizzes for each number of
+ # correct prediction
+ recorded = dict([(n, []) for n in range(len(models) + 1)])
+
+ model_indexes = []
+ sum_logits, sum_nb_c_quizzes = 0, 0
+
+ while (
+ sum([x.size(0) for x in recorded[args.nb_correct_to_validate]])
+ < nb_for_train + nb_for_test
+ ):
+ nb_to_validate = nb_for_train + nb_for_test
+
+ if len(model_indexes) == 0:
+ model_indexes = [i.item() for i in torch.randperm(len(models))]
+
+ model = models[model_indexes.pop()]