fix(actpred): ONNX opset 升级 + NumPy 兼容 + 断点续训 + MobileNetV2 离线弹性

- export_onnx: opset 17→18，dynamic_axes 改 dynamic_shapes 消除弃用警告
- predict: action_stats 改为 torch tensor，消除 NumPy 2.0 __array_wrap__ 警告
- train/pretrain: 每 epoch 保存 last.pt，新增 --resume 断点续训练
- model: MobileNetEncoder 下载失败时回退到已缓存权重
- _set.sh: 安装时预缓存 MobileNetV2 权重，失败给出明确指引
- test: 新增 TestResumeCheckpoint（2 用例），总计 58 测试全绿

actpred/export_onnx.py

@@ -1,5 +1,6 @@
 import argparse
 import torch
+from torch.export import Dim
 from config import parse_checkpoint_config
 from model import ActionPredictor
 
@@ -23,17 +24,17 @@ def main():
         1, data_cfg.frame_len, 3, data_cfg.image_size, data_cfg.image_size)
     dummy_history = torch.randn(1, data_cfg.history_len, data_cfg.action_dim)
 
+    batch = Dim("batch")
     torch.onnx.export(
         model, (dummy_images, dummy_history),
         args.output,
         input_names=["images", "action_history"],
         output_names=["predicted_action"],
-        dynamic_axes={
-            "images": {0: "batch"},
-            "action_history": {0: "batch"},
-            "predicted_action": {0: "batch"},
+        dynamic_shapes={
+            "images": {0: batch},
+            "action_history": {0: batch},
         },
-        opset_version=17,
+        opset_version=18,
     )
     print(f"ONNX model exported to: {args.output}")