code: def test_action_recognition_i3d_slow_models():
      use_cuda = True
      if torch.cuda.device_count() == 0:
          use_cuda = False
  
      models = [
          "i3d_slow_resnet50_f32s2_kinetics400",
          "i3d_slow_resnet101_f32s2_kinetics400",
      ]
      x = torch.rand(2, 3, 32, 224, 224)
      _test_model_list(
          models, use_cuda, x, pretrained=False, num_classes=400
      )
      _test_model_list(
          models, use_cuda, x, pretrained=True, num_classes=400
      )
  
      models = [
          "i3d_slow_resnet50_f8s8_kinetics400",
          "i3d_slow_resnet101_f8s8_kinetics400",
      ]
      x = torch.rand(2, 3, 8, 224, 224)
      _test_model_list(
          models, use_cuda, x, pretrained=False, num_classes=400
      )
      _test_model_list(
          models, use_cuda, x, pretrained=True, num_classes=400
      )
  
      models = [
          "i3d_slow_resnet50_f16s4_kinetics400",
          "i3d_slow_resnet101_f16s4_kinetics400",
      ]
      x = torch.rand(2, 3, 16, 224, 224)
      _test_model_list(
          models, use_cuda, x, pretrained=False, num_classes=400
      )
      _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 7 for calling a global function with example usage: test_action_recognition_i3d_slow_models() without return types