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/_set.sh

@@ -15,3 +15,22 @@ pip install onnxscript onnxruntime -i https://pypi.tuna.tsinghua.edu.cn/simple
 
 pip check
 mkdir -p checkpoints data
+
+# Pre-download MobileNetV2 weights for offline fine-tuning (optional, skip if backbone=simple)
+python3 -c "
+import torch, sys, os
+hub_dir = torch.hub.get_dir()
+cache = os.path.join(hub_dir, 'checkpoints', 'mobilenet_v2-b0353104.pth')
+if os.path.exists(cache):
+    print(f'MobileNetV2 weights already cached: {cache}')
+    sys.exit(0)
+url = 'https://download.pytorch.org/models/mobilenet_v2-b0353104.pth'
+try:
+    torch.hub.load_state_dict_from_url(url, model_dir=os.path.join(hub_dir, 'checkpoints'))
+    print('MobileNetV2 weights cached to: ' + cache)
+except Exception as e:
+    print(f'WARNING: MobileNetV2 weights download failed: {e}')
+    print('  backbone=simple still works; for mobilenet, manually download from:')
+    print(f'  {url}')
+    print(f'  and place at: {cache}')
+" || echo "WARNING: MobileNetV2 weight pre-download skipped"