return quizzes
def save_some_examples(self, result_dir, prefix=""):
- nb, nrow = 128, 4
+ nb, nrow = 256, 8
for t in self.all_tasks:
print(t.__name__)
quizzes = self.generate_w_quizzes_(nb, tasks=[t])
parser.add_argument("--max_fail_to_validate", type=int, default=3)
-parser.add_argument("--accuracy_to_make_c_quizzes", type=float, default=0.98)
+parser.add_argument("--accuracy_to_make_c_quizzes", type=float, default=0.95)
parser.add_argument("--proba_understands", type=float, default=0.95)
while bag_len(records) < wanted_nb:
model = copy_for_inference(models[torch.randint(len(models), (1,)).item()])
+ generator_id = model.id
c_quizzes = ae_generate(model, template, mask_generate)
e = "???"
log_string(
- f"nb_generated {bag_len(records)} model {model.id} (finishes {e} -- {int((nb_generated * 3600)/duration)}/h)"
+ f"nb_generated {bag_len(records)} model {generator_id} (finishes {e} -- {int((nb_generated * 3600)/duration)}/h)"
)
duration = time.perf_counter() - start_time