code: def get_inference_batch_size(cfg: Any) -> int:
      """Calculates inference batch size
  
      Args:
          cfg: config with all the hyperparameters
      Returns:
          Inference batch size
      """
  
      if cfg.prediction.batch_size_inference != 0:
          return cfg.prediction.batch_size_inference
      else:
          return cfg.training.batch_size
  
imports: import logging
  import math
  import os
  from typing import Any, DefaultDict, Dict, List, Optional, Tuple, Union, no_type_check
  import networkx
  import numpy
  import pandas
  import pyarrow.parquet
  import torch
  from sklearn.model_selection import GroupShuffleSplit, train_test_split
  from torch import distributed
  from torch.utils.data import DataLoader, Sampler, SequentialSampler
  from llm_studio.src.datasets.conversation_chain_handler import ConversationChainHandler
  from llm_studio.src.utils.exceptions import LLMDataException
  from llm_studio.src.utils.utils import PatchedAttribute, set_seed
label_desc: Use image node_id 17 for calling a global function with example usage: get_inference_batch_size(cfg) and returns: cfg, cfg