code: def test_action_recognition_r2plus1d_models():
      use_cuda = True
      if torch.cuda.device_count() == 0:
          use_cuda = False
  
      models = [
          "r2plus1d_v1_resnet18_kinetics400",
          "r2plus1d_v1_resnet34_kinetics400",
          "r2plus1d_v1_resnet50_kinetics400",
          "r2plus1d_v2_resnet152_kinetics400",
          "r2plus1d_v1_resnet101_kinetics400",
          "r2plus1d_v1_resnet152_kinetics400",
      ]
  
      x = torch.rand(2, 3, 16, 112, 112)
      _test_model_list(
          models, use_cuda, x, pretrained=False, num_classes=400
      )
  
      models = [
          "r2plus1d_v1_resnet18_kinetics400",
          "r2plus1d_v1_resnet34_kinetics400",
          "r2plus1d_v1_resnet50_kinetics400",
          "r2plus1d_v2_resnet152_kinetics400",
      ]
      _test_model_list(
          models, use_cuda, x, pretrained=True, num_classes=400
      )
  
file_path: gluon-cv/tests/model_zoo_torch/test_model_zoo_torch.py
imports: from __future__ import print_function
  import warnings
  import logging
  import torch
  import torch.nn
  from gluoncv.torch.model_zoo import get_model, get_model_list
  from gluoncv.torch.engine.config import get_cfg_defaults
label_desc: Use image node_id 4 for calling a global function with example usage: test_action_recognition_r2plus1d_models() without return types