code: def __init__(self, option, model_type, dataset, modules):
      super(Minkowski_Baseline_Model, self).__init__(option)
      self._weight_classes = dataset.weight_classes
      self.model = initialize_minkowski_unet(
          option.model_name,
          dataset.feature_dimension,
          dataset.num_classes,
          **option.get("extra_options", {}),
      )
      self.loss_names = ["loss_seg"]
  
file_path: torch-points3d/torch_points3d/models/segmentation/minkowski.py
imports: import logging
  import torch.nn.functional
  import torch
  from torch_points3d.modules.MinkowskiEngine import *
  from torch_points3d.models.base_architectures import UnwrappedUnetBasedModel
  from torch_points3d.models.base_model import BaseModel
  from torch_points3d.datasets.segmentation import IGNORE_LABEL
  from torch_points3d.applications.minkowski import Minkowski
label_desc: Use image node_id 1 to create a new Minkowski_Baseline_Model object from inherited base classes: BaseModel with example: obj = Minkowski_Baseline_Model(option, model_type, dataset, modules)