# main.py
from lightning.pytorch.cli import LightningCLI
from lightning.pytorch.callbacks import ModelCheckpoint
from lightning.fabric import seed_everything
from Algorithms import ActorCritic
from Tasks import TwentyQuestions
import torch
torch.backends.cuda.matmul.allow_tf32 = True  # 启用 TF32 加速
torch.backends.cudnn.allow_tf32 = True
from torch.cuda.amp import GradScaler  # 如果用 AMP

seed_everything(42)

def cli_main():
    checkpoint_callback = ModelCheckpoint(
        dirpath="models",
        every_n_train_steps=200,
        every_n_epochs=0,
        save_top_k=1,
        save_last=True            # 同时保存最后一个模型
    )
    cli = LightningCLI(
        save_config_kwargs={"overwrite": True},
        trainer_defaults={  # 添加 trainer 默认配置
            "callbacks": [checkpoint_callback],
            "limit_val_batches": 0,
            "val_check_interval": None
        }
    )
    exit(0)

if __name__ == "__main__":
    cli_main()