code: def __init__(self, option, model_type, dataset, modules):
      BaseMinkowski.__init__(self, option, model_type, dataset, modules)
  
      self.model = initialize_minkowski_unet(
          option.model_name,
          in_channels=dataset.feature_dimension,
          out_channels=option.out_channels,
          D=option.D,
          conv1_kernel_size=option.conv1_kernel_size,
      )
  
imports: import logging
  import torch
  from torch_geometric.data import Data
  from torch_points3d.modules.MinkowskiEngine import *
  from torch_points3d.models.base_architectures import UnwrappedUnetBasedModel
  from torch_points3d.models.registration.base import FragmentBaseModel
  from torch.nn import Sequential, Linear, LeakyReLU, Dropout
  from torch_points3d.core.common_modules import FastBatchNorm1d, Seq
label_desc: Use image node_id 1 to create a new Minkowski_Baseline_Model_Fragment object from inherited base classes: BaseMinkowski with example: obj = Minkowski_Baseline_Model_Fragment(option, model_type, dataset, modules)