code: def _inference(self, inference_dl, device):
      outputs = []
      for i, batch in enumerate(inference_dl):
          (
              input_ids,
              input_attn_mask,
              unique_ids,
              training_mask_end,
          ) = batch
          input_ids, input_attn_mask, training_mask_end = (
              tensor.to(device)
              for tensor in [
                  input_ids,
                  input_attn_mask,
                  training_mask_end,
              ]
          )
          (
              input_ids,
              input_attn_mask,
              labels,
              generated_texts,
          ) = self._prep_inference_labels(
              input_ids, input_attn_mask, training_mask_end, device
          )
  
          _, per_sample_perplexity = self.forward(
              input_ids, input_attn_mask, labels
          )
          labels[labels == -100] = self.tokenizer.tokenizer.pad_token_id
  
          outputs.append(
              {
                  "unique_ids": unique_ids,
                  "per_sample_perplexity": per_sample_perplexity,
                  "generated_answers": generated_texts,
              }
          )
  
      return outputs
  
imports: import collections
  from typing import List, Optional
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from transformers import AutoModelForCausalLM
  from nemo.collections.nlp.data.question_answering.data_processor.qa_processing import QAProcessor
  from nemo.collections.nlp.data.question_answering.dataset.qa_gpt_dataset import GPTQADataset
  from nemo.collections.nlp.metrics.qa_metrics import QAMetrics
  from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import MegatronGPTModel
  from nemo.collections.nlp.models.question_answering.qa_base_model import BaseQAModel
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.utils import logging
label_desc: Use image node_id 12 for calling the GPTQAModel obj's underlying member method code with example usage: obj._inference(inference_dl, device) and returns: outputs