code: def test_weight_threshold_pruning():
      model = deepcopy(mock_model)
  
      pruner = WeightThresholdPruner(model, train_loader, test_loader)
      pruner.prune(
          num_iterations=2,
          train_epochs=1,
          save_models=True,
          threshold=0.1,
      )
      pruner.get_pruning_statistics(
          model_path="pruned_model_iteration_0.pt", verbose=True
      )
  
imports: from copy import deepcopy
  from torch.utils.data import DataLoader
  from KD_Lib.Pruning import LotteryTicketsPruner, WeightThresholdPruner
  from .utils import MockImageClassifier, MockVisionDataset
label_desc: Use image node_id 2 for calling a global function with example usage: test_weight_threshold_pruning() without return types