Questions related to the dataset annotation and multi-gpu training results

[Reagan1311]

Hi, thanks for the great work! After running some experiments, I found two issues.

1. Some of the annotations are not correct. Here I show some examples (left model: prediction, right model: GT). (The top two shelves have no annotation of "contain") (The pourable annotation lies on the bottom of the bottle) (The grasp annotation lies on the bottleneck) (Grasp annotations are quite different for visually similar bottles)

2. The results vary a lot when using different numbers of GPU, and it seems single GPU got the best performance. What's the reason?

	PointNet++
8 gpu	Test :: test mAP: 0.433250, test mAUC: 0.856608, test maIOU: 0.057118, test MSE: 0.071557
4 gpu	Test :: test mAP: 0.437279, test mAUC: 0.845381, test maIOU: 0.116516, test MSE: 0.065208
1 gpu	Test :: test mAP: 0.481856, test mAUC: 0.876145, test maIOU: 0.183885, test MSE: 0.058885