code: def unequal_outputs_table():
      """Function for simple case with non-equal outputs in list"""
      idx_1 = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
      idx_2 = np.array([2, 3, 4, 5, 6, 7, 8, 9])
  
      task = Task(TaskTypesEnum.regression)
      generated_target = np.random.sample((len(idx_1), 1))
      generated_features = np.random.sample((len(idx_1), 2))
  
      list_with_outputs = []
      for idx, data_flow_len in zip([idx_1, idx_2], [1, 0]):
          data_info = SupplementaryData(data_flow_length=data_flow_len)
          output_data = OutputData(
              idx=idx,
              features=generated_features[idx, :],
              predict=generated_target[idx, :],
              task=task,
              target=generated_target[idx, :],
              data_type=DataTypesEnum.table,
              supplementary_data=data_info,
          )
          list_with_outputs.append(output_data)
  
      return list_with_outputs
  
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 3 for calling a global function with example usage: unequal_outputs_table() and returns: list_with_outputs