+def oneshot(model, learning_rate_scheduler, task):
+ t = model.training
+ model.eval()
+ mazes = task.test_input[:32].clone()
+ mazes[:, task.height * task.width :] = 0
+ output = eval_mygpt(model, mazes, prompt_len=task.height * task.width)
+ output = F.softmax(output, dim=2)
+ print(f"{output.size()=}")
+ proba_path = output[:, task.height * task.width :, 4].reshape(
+ -1, task.height, task.width
+ )
+ mazes = mazes[:, : task.height * task.width].reshape(-1, task.height, task.width)
+ # targets = targets.reshape(-1, task.height, task.width)
+ filename = f"oneshot.png"
+ maze.save_image(
+ os.path.join(args.result_dir, filename),
+ mazes=mazes,
+ score_paths=proba_path,
+ # score_truth=targets,
+ )
+ log_string(f"wrote {filename}")
+
+
+def oneshot_old(gpt, learning_rate_scheduler, task):