code: def __init__(self):
      super(MockModel_, self).__init__(
          DictConfig({"conv_type": "Dummy"})
      )
  
      self._channels = [12, 12, 12, 17]
      self.nn = MLP(self._channels)
  
imports: import unittest
  import torch
  import omegaconf
  from omegaconf import OmegaConf, DictConfig
  from torch.nn import Sequential, Linear, ReLU, LeakyReLU, BatchNorm1d, Dropout
  import os
  import sys
  from torch_geometric.data import Data
  from torch_points3d.models.base_model import BaseModel
  from test.mockdatasets import MockDatasetGeometric
  from torch_points3d.models.model_factory import instantiate_model
label_desc: Use image node_id 1 to create a new MockModel_ object from inherited base classes: BaseModel with example: obj = MockModel_()