code: def test_pipeline_with_custom_fitted_node():
      train_input, predict_input = get_input_data()
      pipeline = get_fitting_custom_pipeline()
      pipeline.fit_from_scratch(train_input)
      predicted_centered = pipeline.predict(predict_input)
  
      assert predicted_centered is not None
  
imports: import logging
  import os
  import shutil
  from copy import deepcopy
  from typing import Any
  import numpy
  import pandas
  from examples.advanced.time_series_forecasting.custom_model_tuning import get_fitting_custom_pipeline
  from examples.simple.pipeline_import_export import create_correct_path
  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.multi_modal import MultiModalData
  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, TsForecastingParams
label_desc: Use image node_id 10 for calling a global function with example usage: test_pipeline_with_custom_fitted_node() without return types