docstr: This function will be called with every batch of data in the dataset
  
  Arguments:
      batch: a batch of data of the dataset passed into torch_batch_process
      batch_idx: index of the batch. Note that index is per worker. For example, if there are
          8 batches of data to process and 4 workers, each worker would get two batches of
          data (batch_idx = 0 and batch_idx = 1)
code: def process_batch(self, batch: Any, batch_idx: int) -> None:
      """
      This function will be called with every batch of data in the dataset
  
      Arguments:
          batch: a batch of data of the dataset passed into torch_batch_process
          batch_idx: index of the batch. Note that index is per worker. For example, if there are
              8 batches of data to process and 4 workers, each worker would get two batches of
              data (batch_idx = 0 and batch_idx = 1)
      """
      pass
  
imports: import abc
  import json
  import logging
  import math
  import os
  import pathlib
  import uuid
  import warnings
  from typing import TYPE_CHECKING, Any, ContextManager, Dict, Optional, Set, Sized, Type
  import torch
  import torch.distributed
  from torch import nn
  from torch.utils import data
  import determined
  from determined import common, core, pytorch
label_desc: Use image node_id 2 for calling the TorchBatchProcessor obj's underlying member method code with example usage: obj.process_batch(batch, batch_idx) without return types