code: def _extend_inputs(inputs, extra):
      """Extend input arguments with an extra column"""
      input_ids = inputs["input_ids"]
      attention_mask = inputs["attention_mask"]
      extra = torch.atleast_2d(
          torch.tensor(extra, dtype=torch.long, device=input_ids.device)
      )
      inputs_extended = inputs.copy()
  
      inputs_extended["input_ids"] = torch.cat(
          (input_ids, extra), dim=-1
      )
      inputs_extended["attention_mask"] = torch.cat(
          (attention_mask, torch.ones_like(extra)), dim=-1
      )
      return inputs_extended
  
imports: import importlib
  import warnings
  from string import Formatter
  import numpy
  import torch
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils import check_random_state
  from sklearn.utils.validation import check_is_fitted
  from transformers import AutoConfig, AutoTokenizer, LogitsProcessor
  from skorch.exceptions import LowProbabilityError
  from skorch.llm.prompts import DEFAULT_PROMPT_FEW_SHOT, DEFAULT_PROMPT_ZERO_SHOT, DELIM
label_desc: Use image node_id 3 for calling a global function with example usage: _extend_inputs(inputs, extra) and returns: inputs_extended