code: def test_lightining_faster_rcnn_logs_losses_during_training_step(
      fridge_faster_rcnn_dls, fridge_faster_rcnn_model, light_model_cls
  ):
      with torch.set_grad_enabled(True):
          train_dl, _ = fridge_faster_rcnn_dls
          light_model = light_model_cls(
              fridge_faster_rcnn_model, metrics=None
          )
          for batch in train_dl:
              break
  
          light_model.training_step(batch, 0)
  
          assert list(light_model.logs.keys()) == ["train_loss"]
  
file_path: icevision/tests/models/torchvision_models/faster_rcnn/lightning/test_train.py
imports: import pytest
  import random
  from icevision.all import *
  from icevision.models.torchvision import faster_rcnn
label_desc: Use image node_id 4 for calling a global function with example usage: test_lightining_faster_rcnn_logs_losses_during_training_step(fridge_faster_rcnn_dls, fridge_faster_rcnn_model, light_model_cls) without return types