code: def setup_inference_data(
      self, input_file, batch_size=1, num_samples=-1, num_workers=2
  ):
      dataloader_cfg = {
          "batch_size": batch_size,
          "file": input_file,
          "shuffle": False,
          "num_samples": num_samples,
          "num_workers": num_workers,
          "pin_memory": False,
          "drop_last": False,
      }
      dataloader_cfg = OmegaConf.create(dataloader_cfg)
      inference_dl = self._setup_dataloader_from_config(
          cfg=dataloader_cfg, mode=INFERENCE_MODE
      )
  
      return inference_dl
  
file_path: NeMo/nemo/collections/nlp/models/question_answering/qa_base_model.py
imports: from typing import Optional
  import torch
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from nemo.collections.nlp.data.question_answering.data_processor.qa_processing import EVALUATION_MODE, INFERENCE_MODE, TRAINING_MODE
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.utils import logging
label_desc: Use image node_id 5 for calling the BaseQAModel obj's underlying member method code with example usage: obj.setup_inference_data(input_file, batch_size, num_samples, num_workers) and returns: inference_dl