code: def __init__(self, option, model_type, dataset, modules):
      # Last Layer
      BaseMS_SparseConv3d.__init__(
          self, option, model_type, dataset, modules
      )
      option_unet = option.option_unet
      num_scales = option_unet.num_scales
      self.unet = nn.ModuleList()
      for i in range(num_scales):
          module = UnetMSparseConv3d(
              option_unet.backbone,
              input_nc=option_unet.input_nc,
              grid_size=option_unet.grid_size[i],
              pointnet_nn=getattr(option_unet, "pointnet_nn", None),
              post_mlp_nn=getattr(
                  option_unet, "post_mlp_nn", [64, 64, 32]
              ),
              pre_mlp_nn=getattr(option_unet, "pre_mlp_nn", None),
              add_pos=getattr(option_unet, "add_pos", False),
              add_pre_x=getattr(option_unet, "add_pre_x", False),
              aggr=getattr(option_unet, "aggr", None),
              backend=option.backend,
          )
          self.unet.add_module(name=str(i), module=module)
      # Last MLP layer
      assert option.mlp_cls is not None
      last_mlp_opt = option.mlp_cls
      self.FC_layer = Seq()
      for i in range(1, len(last_mlp_opt.nn)):
          self.FC_layer.append(
              Sequential(
                  *[
                      Linear(
                          last_mlp_opt.nn[i - 1],
                          last_mlp_opt.nn[i],
                          bias=False,
                      ),
                      FastBatchNorm1d(
                          last_mlp_opt.nn[i],
                          momentum=last_mlp_opt.bn_momentum,
                      ),
                      LeakyReLU(0.2),
                  ]
              )
          )
  
imports: import torch
  import torch.nn
  from torch.nn import LeakyReLU, Linear, Sequential
  from torch_geometric.nn.pool.consecutive import consecutive_cluster
  from torch_geometric.nn import voxel_grid
  from torch_geometric.data import Batch
  from torch_scatter import scatter_max, scatter_mean
  from torch_points3d.applications.sparseconv3d import SparseConv3d
  from torch_points3d.core.common_modules import FastBatchNorm1d, Seq
  from torch_points3d.core.common_modules import MLP
  from torch_points3d.models.registration.base import FragmentBaseModel
label_desc: Use image node_id 1 to create a new MS_SparseConv3d object from inherited base classes: BaseMS_SparseConv3d with example: obj = MS_SparseConv3d(option, model_type, dataset, modules)