code: def test_data_merge_tables(output_tables):
      """Test merge of tables of various number of predict columns."""
      merged_data = DataMerger.get(output_tables).merge()
  
      first_table = output_tables[0]
      assert np.equal(merged_data.idx, first_table.idx).all()
      assert merged_data.target.shape == first_table.target.shape
      expected_shape = (
          len(first_table.predict),
          sum(table.predict.shape[-1] for table in output_tables),
      )
      assert merged_data.features.shape == expected_shape
      assert np.allclose(
          merged_data.features,
          np.hstack([table.predict for table in output_tables]),
      )
  
imports: import operator
  from itertools import product, repeat
  from typing import List
  import numpy
  import pytest
  from examples.simple.regression.regression_with_tuning import get_regression_dataset
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.data.merge.data_merger import DataMerger
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
label_desc: Use image node_id 6 for calling a global function with example usage: test_data_merge_tables(output_tables) without return types