code: def check_stratify(train, test):
      deltas = [
          np.unique(np.sort(train.target), return_counts=True)[1],
          np.unique(np.sort(test.target), return_counts=True)[1],
      ]
      return np.allclose(*[delta / sum(delta) for delta in deltas])
  
imports: from functools import partial
  from typing import Callable
  import numpy
  import pandas
  import pytest
  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.optimisers.objective.data_source_splitter import DataSourceSplitter
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import split_data
  from fedot.core.data.cv_folds import cv_generator
  from test.unit.pipelines.test_decompose_pipelines import get_classification_data
  from test.unit.tasks.test_forecasting import get_ts_data
label_desc: Use image node_id 9 for calling a global function with example usage: check_stratify(train, test) and returns: np