code: def data_with_nans_in_target_column():
      """Generate InputData with np.nan values in target column"""
      task = Task(TaskTypesEnum.regression)
      features = np.array(
          [[1, 2], [2, 2], [0, 3], [2, 3], [3, 4], [1, 3]]
      )
      target = np.array([[0], [1], [np.nan], [np.nan], [4], [5]])
      train_input = InputData(
          idx=np.array([0, 1, 2, 3, 4, 5]),
          features=features,
          target=target,
          task=task,
          data_type=DataTypesEnum.table,
          supplementary_data=SupplementaryData(),
      )
  
      return train_input
  
imports: import numpy
  from fedot import Fedot
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.preprocessing.data_types import TYPE_TO_ID
label_desc: Use image node_id 4 for calling a global function with example usage: data_with_nans_in_target_column() and returns: train_input