code: def __init__(self, option, model_type, dataset, modules):
      super(PVCNN, self).__init__(option)
      self._weight_classes = dataset.weight_classes
  
      self.model = pvcnn.PVCNN(option, model_type, dataset, modules)
  
      self.loss_names = ["loss_seg"]
  
file_path: torch-points3d/torch_points3d/models/segmentation/pvcnn.py
imports: import logging
  import torch.nn.functional
  import torch
  from torch_points3d.modules.PVCNN import pvcnn
  from torch_points3d.models.base_model import BaseModel
  from torch_points3d.datasets.segmentation import IGNORE_LABEL
  from torchsparse import SparseTensor
label_desc: Use image node_id 1 to create a new PVCNN object from inherited base classes: BaseModel with example: obj = PVCNN(option, model_type, dataset, modules)