code: def __init__(self):
      self.iter = 0
      self.losses = [
          {"loss_1": 1, "loss_2": 2},
          {"loss_1": 1, "loss_2": 2},
          {"loss_1": 1, "loss_2": 2},
      ]
      self.outputs = [
          np.asarray([[0, 1, 0, 0], [0, 1, 0, 0]]),
          np.asarray([[0, 0, 1, 0], [0, 0, 1, 0]]),
          np.asarray([[0, 0, 1, 0]]),
      ]
      self.labels = [
          np.asarray([1, 1]),
          np.asarray([2, 2]),
          np.asarray([3]),
      ]
      self.batch_idx = [
          np.asarray([0, 1]),
          np.asarray([0, 1]),
          np.asarray([0]),
      ]
      self.conv_type = "DENSE"
  
file_path: torch-points3d/test/test_shapenetparttracker.py
imports: import unittest
  import numpy
  import os
  import sys
  from torch_points3d.metrics.shapenet_part_tracker import ShapenetPartTracker
label_desc: Use image node_id 1 to create a new MockModel object  with example: obj = MockModel()