feat: inference_mode + torch.compile(default)

- torch.no_grad() → torch.inference_mode()（禁梯度+禁版本追踪，更快）
- torch.compile(mode='default')：纯算子融合，不用 CUDA Graph，兼容动态 batch 形状

代码/code/infer.py

@@ -519,6 +519,11 @@ def load_model(ckpt_path, device='cuda:0'):
 
     model.to(dev)
     model.eval()
+
+    # === torch.compile(default)：算子融合，不用 CUDA Graph，兼容动态 batch 形状 ===
+    model = torch.compile(model, mode="default")
+    print("[INFO] torch.compile applied (mode=default)")
+
     print(f"[INFO] Model ready. Device: {dev}")
 
     return model, dev
@@ -703,7 +708,7 @@ def main():
     all_probs = []
     time_sum = 0.0
 
-    with torch.no_grad():
+    with torch.inference_mode():
         for batch in tqdm(all_batches, desc="Inference"):
             batch = move_batch_to_device(batch, dev)
             pred_mask = batch["pred_mask"].bool()