code: def _validate_data(self, data, name):
      if callable(data):
          data = data(self.config)
          if not isinstance(data, tuple) or isinstance(data, list):
              invalidInputError(
                  False,
                  f"You must input a data create function which returns a tuple"
                  f" or a list of (x, y) for {name} in XGBoost. Your function"
                  f" returns a {data.__class__.__name__} instead",
              )
          if len(data) != 2:
              invalidInputError(
                  False,
                  f"You must input a data create function which returns a tuple"
                  f" or a list containing two elements of (x, y) for {name} in"
                  f" XGBoost. Your data create function returns {len(data)}"
                  f" elements instead",
              )
  
      if not (isinstance(data, tuple) or isinstance(data, list)):
          invalidInputError(
              False,
              f"You must input a tuple or a list of (x, y) for {name} in XGBoost."
              f"Got {data.__class__.__name__}",
          )
      if len(data) != 2:
          invalidInputError(
              False,
              f"You must input a tuple or a list containing two elements of (x, y)."
              f"Got {len(data)} elements for {name} in XGBoost",
          )
      return data
  
imports: from bigdl.orca.common import SafePickle
  import pandas
  from xgboost.sklearn import XGBRegressor
  from xgboost.sklearn import XGBClassifier
  from bigdl.orca.automl.metrics import Evaluator
  from bigdl.orca.automl.model.abstract import BaseModel, ModelBuilder
  from bigdl.dllib.utils.log4Error import invalidInputError
  import logging
label_desc: Use image node_id 5 for calling the XGBoost obj's underlying member method code with example usage: obj._validate_data(data, name) and returns: data