Different values for accuracy (validation and testing)

### Checklist

- [X] I have searched for [similar issues](https://github.com/isl-org/Open3D-ML/issues).
- [X] I have tested with the [latest development wheel](http://www.open3d.org/docs/latest/getting_started.html#development-version-pip).
- [X] I have checked the [release documentation](http://www.open3d.org/docs/release/) and the [latest documentation](http://www.open3d.org/docs/latest/) (for `master` branch).

### Describe the issue

I'm trying to train point transformer on a dataset based on S3DIS.
in the last epoch of the training process, I get a value for accuracy and miou as follows:

INFO - 2022-03-11 10:36:05,257 - semantic_segmentation - Mean acc train: 0.950 eval: 0.933
INFO - 2022-03-11 10:36:05,258 - semantic_segmentation - Mean IoU train: 0.901 eval: 0.902

But when I test my model on the same sample, I get new values for accuracy and miou:
Overall Testing Accuracy : 0.6765742520464817, mIoU : 0.6481393184649503

I'm using pipeline.run_test() to test my model.

I think the value of accuracy is being calculated differently in these stages.

Is there any solution to this problem?

Thank you!

### Steps to reproduce the bug

```python
model = ml3d.models.PointTransformer(**cfg.model)
pipeline = ml3d.pipelines.SemanticSegmentation(model=model, dataset=dataset, device="gpu", **cfg.pipeline)
pipeline.run_train()

# the following lines give the value of accuracy and MIoU in the last epoch:
pipeline.metric_val.acc()
pipeline.metric_val.iou()

# this line of code gives different values of accuracy and MIoU on the same sample of data
pipeline.run_test()
```

### Error message

_No response_

### Expected behavior

the value of acc and MIoU in the last epoch should be equal to the values coming from the function run_test since the same sample for validation and testing has been used.