code: def __init__(self):
      super().__init__(DictConfig({"conv_type": "dummy"}))
  
      self.model1 = MockLossModule(
          {
              "mock_loss_1": torch.tensor(0.5),
              "mock_loss_2": torch.tensor(0.3),
          }
      )
  
      self.model2 = MockLossModule(
          {
              "mock_loss_3": torch.tensor(1.0),
          }
      )
  
imports: import unittest
  import numpy
  import numpy.testing
  import torch
  import os
  import sys
  from collections import defaultdict
  from omegaconf import DictConfig
  from torch_points3d.models.base_model import BaseModel, BaseInternalLossModule
  from torch_points3d.modules.PointNet.modules import PointNetSTN3D
label_desc: Use image node_id 1 to create a new MockModel object from inherited base classes: BaseModel with example: obj = MockModel()