code: def test_lightning_yolo_validate(
      fridge_ds, backbone, light_model_cls
  ):
      _, valid_ds = fridge_ds
      valid_dl = models.ultralytics.yolov5.valid_dl(
          valid_ds, batch_size=3, num_workers=0, shuffle=False
      )
      model = models.ultralytics.yolov5.model(
          num_classes=5,
          img_size=384,
          backbone=backbone(pretrained=True),
      )
      metrics = [COCOMetric(metric_type=COCOMetricType.bbox)]
      light_model = light_model_cls(model, metrics=metrics)
      gpus = 1 if torch.cuda.is_available() else 0
      trainer = pl.Trainer(max_epochs=1, gpus=gpus)
  
      trainer.validate(light_model, valid_dl)
  
imports: import pytest
  from icevision.all import *
  from icevision.models.ultralytics.yolov5.backbones import *
label_desc: Use image node_id 2 for calling a global function with example usage: test_lightning_yolo_validate(fridge_ds, backbone, light_model_cls) without return types