code: def _wrap_eval_tuples(
      eval_set=None, eval_sample_weight=None, eval_init_score=None
  ):
      if not eval_set:
          return None
  
      tps = []
      for (data, label), weight, score in zip(
          eval_set,
          eval_sample_weight or itertools.repeat(None),
          eval_init_score or itertools.repeat(None),
      ):
          tps.append(TrainTuple(data, label, weight, score))
      return tps
  
imports: import enum
  import itertools
  from collections import namedtuple
  import numpy
  import pandas
  from ....dataframe import DataFrame, Series
  from ....tensor import tensor
label_desc: Use image node_id 7 for calling the LGBMScikitLearnBase obj's underlying member method code with example usage: obj._wrap_eval_tuples(eval_set, eval_sample_weight, eval_init_score) and returns: tps, None