code: def on_train_begin(self, logs: Dict) -> None:
      for (
          layer_name,
          layer_params,
      ) in self.model.network.named_parameters():
          self._update_layers_to_track(layer_name, layer_params)
      self.tracker = WeightsGradientsStatsTracker(self.number_layers)
  
imports: from typing import Dict, Iterable, List, Tuple
  import numpy
  import torch
  from poutyne.framework.callbacks.callbacks import Callback
label_desc: Use image node_id 3 for calling the GradientTracker obj's underlying member method code with example usage: obj.on_train_begin(logs) without return types