code: def show_results(
      model: nn.Module,
      dataset: Dataset,
      detection_threshold: float = 0.5,
      num_samples: int = 6,
      ncols: int = 3,
      denormalize_fn: Optional[callable] = denormalize_imagenet,
      show: bool = True,
      device: Optional[torch.device] = None,
  ) -> None:
      return base_show_results(
          predict_fn=predict,
          model=model,
          dataset=dataset,
          num_samples=num_samples,
          ncols=ncols,
          denormalize_fn=denormalize_fn,
          show=show,
          detection_threshold=detection_threshold,
          device=device,
      )
  
file_path: icevision/icevision/models/torchvision/retinanet/show_results.py
imports: from icevision.imports import *
  from icevision.utils import *
  from icevision.core import *
  from icevision.data import *
  from icevision.models.base_show_results import base_show_results
  from icevision.models.interpretation import Interpretation
  from icevision.models.torchvision.dataloaders import valid_dl, infer_dl
  from icevision.models.torchvision.retinanet.prediction import predict, predict_from_dl
label_desc: Use image node_id 1 for calling a global function with example usage: show_results(model, dataset, detection_threshold, num_samples, ncols, denormalize_fn, show, device) and returns: base_show_results