code: def predict(model, images, image_transform=None, device=None):
      logits = pytorch_utils.batch_predict(
          model,
          images,
          input_transform=image_transform or get_image_transform(),
          device=device,
      )
      probs = pytorch_utils.logits2probabilities(
          logits
      )  # 2-dim array, one column per class, one row per input
      return probs
  
file_path: tensorwatch/tensorwatch/imagenet_utils.py
imports: from torchvision import transforms
  from .None import pytorch_utils
  import json, os
label_desc: Use image node_id 5 for calling a global function with example usage: predict(model, images, image_transform, device) and returns: probs