code: def test_remove_columns(self):
      dset = self._create_dummy_dataset_dict(multiple_columns=True)
      dset = dset.remove_columns(column_names="col_1")
      for dset_split in dset.values():
          self.assertEqual(dset_split.num_columns, 1)
          self.assertListEqual(list(dset_split.column_names), ["col_2"])
  
      dset = self._create_dummy_dataset_dict(multiple_columns=True)
      dset = dset.remove_columns(column_names=["col_1", "col_2"])
      for dset_split in dset.values():
          self.assertEqual(dset_split.num_columns, 0)
  
      dset = self._create_dummy_dataset_dict(multiple_columns=True)
      for dset_split in dset.values():
          dset_split._format_columns = ["col_1", "col_2"]
      dset = dset.remove_columns(column_names=["col_1"])
      for dset_split in dset.values():
          self.assertListEqual(dset_split._format_columns, ["col_2"])
          self.assertEqual(dset_split.num_columns, 1)
          self.assertListEqual(list(dset_split.column_names), ["col_2"])
      del dset
  
imports: import os
  import tempfile
  from unittest import TestCase
  import numpy
  import pandas
  import pytest
  from datasets import load_from_disk
  from datasets.arrow_dataset import Dataset
  from datasets.dataset_dict import DatasetDict, IterableDatasetDict
  from datasets.features import ClassLabel, Features, Sequence, Value
  from datasets.iterable_dataset import IterableDataset
  from datasets.splits import NamedSplit
  from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_tf, require_torch
label_desc: Use image node_id 14 for calling the DatasetDictTest obj's underlying member method code with example usage: obj.test_remove_columns() without return types