Running `scripts/run_pipeline.py` torch and semantic kitti results in pickling error

Checklist

[X] I have searched for similar issues.
[X] I have tested with the latest development wheel.
[X] I have checked the release documentation and the latest documentation (for main branch).

Describe the issue

trying to run the training pipeline with torch, RandLaNet and semantic kitti results in pickling error: python scripts/run_pipeline.py torch -c ml3d/configs/randlanet_semantickitti.yml --dataset_path /<path/to>/semantic_kitti/

Steps to reproduce the bug

`$python scripts/run_pipeline.py torch -c ml3d/configs/randlanet_semantickitti.yml --dataset_path /<path/to>/semantic_kitti/`

Error message

regular arguments
backend: gloo
batch_size: null
cfg_dataset: null
cfg_file: ml3d/configs/randlanet_semantickitti.yml
cfg_model: null
cfg_pipeline: null
ckpt_path: null
dataset: null
dataset_path: /media/nikste/SSD_030_06/semantic_kitti/
device: cuda
device_ids:
- '0'
framework: torch
host: localhost
main_log_dir: null
max_epochs: null
mode: null
model: null
node_rank: 0
nodes: 1
pipeline: SemanticSegmentation
port: '12355'
seed: 0
split: train

extra arguments
{}

open3d-ml/venv/lib/python3.10/site-packages/torch/cuda/__init__.py:107: UserWarning: CUDA initialization: CUDA unknown error - this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero. (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:109.)
  return torch._C._cuda_getDeviceCount() > 0
INFO - 2024-02-17 19:11:23,311 - semantic_segmentation - DEVICE : cpu
INFO - 2024-02-17 19:11:23,311 - semantic_segmentation - Logging in file : ./logs/RandLANet_SemanticKITTI_torch/log_train_2024-02-17_19-11-23.txt
INFO - 2024-02-17 19:11:23,332 - semantickitti - Found 19130 pointclouds for train
INFO - 2024-02-17 19:11:24,468 - semantickitti - Found 4071 pointclouds for validation
INFO - 2024-02-17 19:11:24,723 - semantic_segmentation - Initializing from scratch.
INFO - 2024-02-17 19:11:24,724 - semantic_segmentation - Writing summary in train_log/00002_RandLANet_SemanticKITTI_torch.
INFO - 2024-02-17 19:11:24,724 - semantic_segmentation - Started training
INFO - 2024-02-17 19:11:24,724 - semantic_segmentation - === EPOCH 0/100 ===
training:   0%|                                                                                                                                            | 0/4783 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "open3d-ml/scripts/run_pipeline.py", line 261, in <module>
    sys.exit(main())
  File "open3d-ml/scripts/run_pipeline.py", line 192, in main
    pipeline.run_train()
  File "open3d-ml/venv/lib/python3.10/site-packages/open3d/_ml3d/torch/pipelines/semantic_segmentation.py", line 405, in run_train
    for step, inputs in enumerate(tqdm(train_loader, desc='training')):
  File "open3d-ml/venv/lib/python3.10/site-packages/tqdm/std.py", line 1182, in __iter__
    for obj in iterable:
  File "open3d-ml/venv/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 441, in __iter__
    return self._get_iterator()
  File "open3d-ml/venv/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 388, in _get_iterator
    return _MultiProcessingDataLoaderIter(self)
  File "open3d-ml/venv/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1042, in __init__
    w.start()
  File "/usr/lib/python3.10/multiprocessing/process.py", line 121, in start
    self._popen = self._Popen(self)
  File "/usr/lib/python3.10/multiprocessing/context.py", line 224, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "/usr/lib/python3.10/multiprocessing/context.py", line 300, in _Popen
    return Popen(process_obj)
  File "/usr/lib/python3.10/multiprocessing/popen_forkserver.py", line 35, in __init__
    super().__init__(process_obj)
  File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 19, in __init__
    self._launch(process_obj)
  File "/usr/lib/python3.10/multiprocessing/popen_forkserver.py", line 47, in _launch
    reduction.dump(process_obj, buf)
  File "/usr/lib/python3.10/multiprocessing/reduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
AttributeError: Can't pickle local object 'SemSegRandomSampler.get_point_sampler.<locals>._random_centered_gen'

Expected behavior

No response

Open3D, Python and System information

- Operating system: ubuntu

Additional information