code: def __call__(
      self, batch: Dict[str, np.ndarray]
  ) -> Dict[str, np.ndarray]:
      inputs = torch.from_numpy(batch["image"]).half().cuda()
      with torch.no_grad():
          outputs = self.model(inputs)
          predictions = torch.argmax(outputs, dim=1).cpu()
      batch["predictions"] = predictions
      return batch
  
file_path: ray/release/nightly_tests/dataset/inference.py
imports: import json
  import os
  import time
  from typing import Any, Dict
  import numpy
  import torch
  from torchvision import transforms
  from torchvision.models import resnet50
  import ray
label_desc: Use image node_id 2 for calling the ImageClassifier obj's underlying member method code with example usage: obj.__call__(batch) and returns: batch