code: def test_complexity_calculation_resnext(self) -> None:
      model_configs = get_test_model_configs()
      # make sure there are three configs returned
      self.assertEqual(len(model_configs), 3)
  
      # expected values which allow minor deviations from model changes
      # we only test at the 10^6 scale
      expected_m_flops = [4122, 7850, 8034]
      expected_m_params = [25, 44, 44]
      expected_m_activations = [11, 16, 21]
  
      for model_config, m_flops, m_params, m_activations in zip(
          model_configs,
          expected_m_flops,
          expected_m_params,
          expected_m_activations,
      ):
          model = build_model(model_config)
          self.assertEqual(
              compute_activations(model) // 10**6, m_activations
          )
          self.assertEqual(compute_flops(model) // 10**6, m_flops)
          self.assertEqual(count_params(model) // 10**6, m_params)
  
imports: import unittest
  import torch
  import torch.nn
  from classy_vision.generic.profiler import compute_activations, compute_flops, count_params, get_shape
  from classy_vision.models import build_model
  from test.generic.config_utils import get_test_model_configs
label_desc: Use image node_id 1 for calling the TestProfilerFunctions obj's underlying member method code with example usage: obj.test_complexity_calculation_resnext() without return types