code: def base_show_results(
      predict_fn: callable,
      model: nn.Module,
      dataset: Dataset,
      num_samples: int = 6,
      ncols: int = 3,
      denormalize_fn: Optional[callable] = denormalize_imagenet,
      show: bool = True,
      **predict_kwargs,
  ) -> None:
      records = random.choices(dataset, k=num_samples)
      preds = predict_fn(model, records, **predict_kwargs)
  
      show_preds(
          preds,
          denormalize_fn=denormalize_fn,
          ncols=ncols,
          show=show,
      )
  
imports: from icevision.imports import *
  from icevision.utils import *
  from icevision.core import *
  from icevision.visualize import *
  from icevision.data import *
label_desc: Use image node_id 1 for calling a global function with example usage: base_show_results(predict_fn, model, dataset, num_samples, ncols, denormalize_fn, show) without return types