docstr: Factory method for the tracker
  Arguments:
      wandb_log - Log using weight and biases
      tensorboard_log - Log using tensorboard
  Returns:
      [BaseTracker] -- tracker
docstr_tok: ["Factory","method","for","the","tracker","Arguments",":","wandb_log","-","Log","using","weight","and","biases","tensorboard_log","-","Log","using","tensorboard","Returns",":","[","BaseTracker","]","--","tracker"]
code: def get_tracker(self, wandb_log: bool, tensorboard_log: bool):
      """Factory method for the tracker
      Arguments:
          wandb_log - Log using weight and biases
          tensorboard_log - Log using tensorboard
      Returns:
          [BaseTracker] -- tracker
      """
      return ClassificationTracker(
          self, wandb_log=wandb_log, use_tensorboard=tensorboard_log
      )
  
imports: import os.path
  import os
  import shutil
  import torch
  from torch_geometric.datasets import ModelNet
  from torch_geometric.data import DataLoader, InMemoryDataset, extract_zip, Data
  import torch_geometric.transforms
  from torch_geometric.io import read_txt_array
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.metrics.classification_tracker import ClassificationTracker
  from torch_points3d.utils.download import download_url
label_desc: Use image node_id 2 for calling the ModelNetDataset obj's underlying member method code with example usage: obj.get_tracker(wandb_log, tensorboard_log) and returns: ClassificationTracker