class_docstr: Helper class that caches model generations
  
  For label ids, if one token sequence is [1, 2, 3] and the next token
  sequence is [1, 2, 4], for the 2nd sequence, the generation will retrieve
  the cached logits for [1, 2] and only generate [4].
  
  Set use_caching=False to disable it, e.g. for debugging.
class_docstr_tok: ["Helper","class","that","caches","model","generations","For","label","ids",",","if","one","token","sequence","is","[","1",",","2",",","3","]","and","the","next","token","sequence","is","[","1",",","2",",","4","]",",","for","the","2nd","sequence",",","the","generation","will","retrieve","the","cached","logits","for","[","1",",","2","]","and","only","generate","[","4","]",".","Set","use_caching=False","to","disable","it",",","e.g",".","for","debugging","."]
code: def _make_key(self, kwargs):
      input_ids = kwargs["input_ids"]
      input_id = input_ids[0].tolist()
      key = str(input_id)
      return key
  
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 the _CacheModelWrapper obj's underlying member method code with example usage: obj._make_key(kwargs) and returns: key