code: def __init__(self):
      self.iter = 0
      self.losses = [
          {"loss_1": 1, "loss_2": 2},
          {"loss_1": 2, "loss_2": 2},
          {"loss_1": 1, "loss_2": 2},
          {"loss_1": 1, "loss_2": 2},
      ]
      self.outputs = [
          torch.tensor([[0, 1], [0, 1]]),
          torch.tensor([[1, 0], [1, 0]]),
          torch.tensor([[1, 0], [1, 0]]),
          torch.tensor([[1, 0], [1, 0], [1, 0]]),
      ]
      self.labels = [
          torch.tensor([1, 1]),
          torch.tensor([1, 1]),
          torch.tensor([1, 1]),
          torch.tensor([0, 0, -100]),
      ]
      self.batch_idx = [
          torch.tensor([0, 1]),
          torch.tensor([0, 1]),
          torch.tensor([0, 1]),
          torch.tensor([0, 0, 1]),
      ]
  
imports: import unittest
  import os
  import torch
  import sys
  import numpy
  import numpy.testing
  from torch_geometric.data import Data
  from torch_points3d.core.data_transform import SaveOriginalPosId
  from torch_points3d.metrics.segmentation_tracker import SegmentationTracker
  from torch_points3d.metrics.segmentation_helpers import SegmentationVoter
  from torch_points3d.metrics.classification_tracker import ClassificationTracker
  from torch_points3d.metrics.s3dis_tracker import S3DISTracker
label_desc: Use image node_id 1 to create a new MockModel object  with example: obj = MockModel()