code: def test_torch_level_pruner(self):
      model = TorchModel()
      optimizer = torch.optim.SGD(
          model.parameters(), lr=0.01, momentum=0.5
      )
      configure_list = [{"sparsity": 0.8, "op_types": ["default"]}]
      LevelPruner(model, configure_list, optimizer).compress()
  
imports: from unittest import TestCase, main
  import numpy
  import torch
  import torch.nn.functional
  import schema
  from aup.compression.torch.pruning import *
  from aup.compression.torch.quantization import *
  import math
label_desc: Use image node_id 2 for calling the CompressorTestCase obj's underlying member method code with example usage: obj.test_torch_level_pruner() without return types