code: def test_api_check_data_correct():
      """Check that data preparing correctly using API methods
      Attention! During test execution the following warning arises
      "Columns number and types numbers do not match."
  
      This happens because the data are prepared for the predict stage
       without going through the fitting stage
      """
      task = Task(TaskTypesEnum.regression)
  
      # Get data
      task_type, x_train, x_test, y_train, y_test = get_split_data()
      path_to_train, path_to_test = get_split_data_paths()
      train_data, test_data, threshold = get_dataset(task_type)
  
      string_data_input = ApiDataProcessor(task).define_data(
          features=path_to_train, target="target"
      )
      array_data_input = ApiDataProcessor(task).define_data(
          features=x_train, target=x_test
      )
      fedot_data_input = ApiDataProcessor(task).define_data(
          features=train_data
      )
      assert (
          not isinstance(string_data_input, InputData)
          or isinstance(array_data_input, InputData)
          or isinstance(fedot_data_input, InputData)
      )
  
file_path: FEDOT/test/unit/api/test_main_api.py
imports: import numpy
  import pandas
  import pytest
  from fedot import Fedot
  from fedot.api.api_utils.api_data import ApiDataProcessor
  from fedot.core.data.data import InputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
  from test.data.datasets import data_with_binary_features_and_categorical_target, get_dataset, load_categorical_multidata, get_split_data_paths, get_split_data, get_multimodal_ts_data, load_categorical_unimodal
label_desc: Use image node_id 4 for calling a global function with example usage: test_api_check_data_correct() without return types