Can I do semantic segmentation on my point cloud?

### 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).

### My Question

The following code is written in the README file.

```
# load the parameters.
pipeline.load_ckpt(ckpt_path=ckpt_path)

test_split = dataset.get_split("test")
data = test_split.get_data(0)

# run inference on a single example.
# returns dict with 'predict_labels' and 'predict_scores'.
result = pipeline.run_inference(data)

```
I want to use pipeline.run_inference to my own data that doesn't have labels.
Is it possible ?

When I enter my point cloud in the [data] section, I get the following error

torch.tensor(data['label']), model.cfg.num_classes,
KeyError: 'label'

My CODE
```
pcd = o3d.io.read_point_cloud("../pointcloud/test.ply")
points = np.asarray(pcd.points)
data = {
'point': points,
'feat': None,
}
result = pipeline.run_inference(data)

```
Please tell me the reason why this error occurs.
Thank you for your cooperation.