modify paddlelite docs

docs/train/instance_segmentation.md

@@ -10,9 +10,9 @@ PaddleX目前提供了MaskRCNN实例分割模型结构,多种backbone模型，
 
 | 模型(点击获取代码)               | Box MMAP/Seg MMAP | 模型大小 | GPU预测速度 | Arm预测速度 | 备注 |
 | :----------------  | :------- | :------- | :---------  | :---------  | :-----    |
-| [MaskRCNN-ResNet50-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/instance_segmentation/mask_r50_fpn.py)   |  36.5%/32.2%   |   170.0MB    |  160.185ms       |   -    | 模型精度高，适用于服务端部署   |
-| [MaskRCNN-ResNet18-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/instance_segmentation/mask_r18_fpn.py)   |  -/-   |   120.0MB    |  -       |   -    | 模型精度高，适用于服务端部署   |
-| [MaskRCNN-HRNet-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/instance_segmentation/mask_hrnet_fpn.py)   |  -/-   |   116.MB    |  -       |   -    | 模型精度高，预测速度快，适用于服务端部署   |
+| [MaskRCNN-ResNet50-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/instance_segmentation/mask_rcnn_r50_fpn.py)   |  36.5%/32.2%   |   170.0MB    |  160.185ms       |   -    | 模型精度高，适用于服务端部署   |
+| [MaskRCNN-ResNet18-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/instance_segmentation/mask_rcnn_r18_fpn.py)   |  -/-   |   120.0MB    |  -       |   -    | 模型精度高，适用于服务端部署   |
+| [MaskRCNN-HRNet-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/instance_segmentation/mask_rcnn_hrnet_fpn.py)   |  -/-   |   116.MB    |  -       |   -    | 模型精度高，预测速度快，适用于服务端部署   |
 
 
 ## 开始训练

docs/train/object_detection.md

@@ -13,9 +13,9 @@ PaddleX目前提供了FasterRCNN和YOLOv3两种检测结构,多种backbone模型
 | [YOLOv3-MobileNetV1](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/yolov3_mobilenetv1.py) |  29.3%  |  99.2MB  |  15.442ms   | -  |  模型小，预测速度快，适用于低性能或移动端设备   |
 | [YOLOv3-MobileNetV3](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/yolov3_mobilenetv3.py)        | 31.6%  | 100.7MB   |  143.322ms  | -  |  模型小，移动端上预测速度有优势   |
 | [YOLOv3-DarkNet53](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/yolov3_darknet53.py)     | 38.9  | 249.2MB   | 42.672ms   | -  |  模型较大，预测速度快，适用于服务端   |
-| [FasterRCNN-ResNet50-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/faster_r50_fpn.py)   |  37.2%   |   136.0MB    |  197.715ms       |   -    | 模型精度高，适用于服务端部署   |
-| [FasterRCNN-ResNet18-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/faster_r18_fpn.py)   |  -   |   -    |  -       |   -    | 模型精度高，适用于服务端部署   |
-| [FasterRCNN-HRNet-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/faster_hrnet_fpn.py)   |  36.0%   |   115.MB    |  81.592ms       |   -    | 模型精度高，预测速度快，适用于服务端部署   |
+| [FasterRCNN-ResNet50-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/faster_rcnn_r50_fpn.py)   |  37.2%   |   136.0MB    |  197.715ms       |   -    | 模型精度高，适用于服务端部署   |
+| [FasterRCNN-ResNet18-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/faster_rcnn_r18_fpn.py)   |  -   |   -    |  -       |   -    | 模型精度高，适用于服务端部署   |
+| [FasterRCNN-HRNet-FPN](https://github.com/PaddlePaddle/PaddleX/blob/doc/tutorials/train/object_detection/faster_rcnn_hrnet_fpn.py)   |  36.0%   |   115.MB    |  81.592ms       |   -    | 模型精度高，预测速度快，适用于服务端部署   |
 
 
 ## 开始训练