code: def test_prepare_for_training(self):
      ds = DatasetForText2Text(
          [
              Text2TextRecord(text="mock", annotation="mock"),
              Text2TextRecord(text="mock"),
          ]
          * 10
      )
      train = ds.prepare_for_training(train_size=1, seed=42)
  
      assert isinstance(train, datasets.Dataset)
      assert set(train.column_names) == set(["id", "text", "target"])
      assert len(train) == 10
      assert train[1]["text"] == "mock"
      assert train[1]["target"] == "mock"
      assert train.features["text"] == datasets.Value("string")
      assert train.features["target"] == datasets.Value("string")
  
      train_test = ds.prepare_for_training(train_size=0.5, seed=42)
      assert len(train_test["train"]) == 5
      assert len(train_test["test"]) == 5
      for split in ["train", "test"]:
          assert set(train_test[split].column_names) == set(
              ["id", "text", "target"]
          )
  
imports: import copy
  import os
  import sys
  from time import sleep
  import datasets
  import pandas
  import pytest
  import spacy
  from argilla.client.datasets import DatasetBase, DatasetForText2Text, DatasetForTextClassification, DatasetForTokenClassification, WrongRecordTypeError, read_datasets, read_pandas
  from argilla.client.models import Text2TextRecord, TextClassificationRecord, TokenClassificationRecord
  from argilla.datasets import TextClassificationSettings
label_desc: Use image node_id 6 for calling the TestDatasetForText2Text obj's underlying member method code with example usage: obj.test_prepare_for_training() without return types