code: def _split_data(self):
      from sklearn.model_selection import train_test_split
  
      (
          self.x_train,
          self.x_test,
          self.y_train,
          self.y_test,
      ) = train_test_split(
          self._x, self._y, test_size=0.20, random_state=42
      )
      (
          self.x_train,
          self.x_valid,
          self.y_train,
          self.y_valid,
      ) = train_test_split(
          self.x_train, self.y_train, test_size=0.40, random_state=42
      )
  
imports: import torch
  from lightning.pytorch.core.datamodule import LightningDataModule
  from lightning_utilities.core.imports import RequirementCache
  from torch.utils.data import DataLoader
  from tests_pytorch.helpers.datasets import MNIST, SklearnDataset, TrialMNIST
label_desc: Use image node_id 2 for calling the SklearnDataModule obj's underlying member method code with example usage: obj._split_data() without return types