code: def main():
      pathlib.Path.mkdir(
          pathlib.Path(constants.DATA_DIRECTORY),
          parents=True,
          exist_ok=True,
      )
      transform = transforms.Compose(
          [
              transforms.ToTensor(),
              transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
          ]
      )
      lock = filelock.FileLock(constants.LOCK_FILE)
      with lock:
          inference_data = tv.datasets.CIFAR10(
              root=constants.DATA_DIRECTORY,
              train=False,
              download=True,
              transform=transform,
          )
  
      experimental.torch_batch_process(
          MyProcessor,
          inference_data,
          batch_size=200,
          checkpoint_interval=5,
      )
  
file_path: determined/examples/features/torch_batch_process_core_api_comparison/torch_batch_process_inference.py
imports: import os
  import pathlib
  import constants
  import filelock
  import model
  import torch
  import torchvision
  import torchvision.transforms
  from determined.pytorch import experimental
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types