code: def test_api_in_sample_multimodal_ts_predict_correct(
      validation_blocks,
  ):
      forecast_length = 5
      historical_data, target = get_multimodal_ts_data()
  
      model = Fedot(
          problem="ts_forecasting",
          **TESTS_MAIN_API_DEFAULT_PARAMS,
          task_params=TsForecastingParams(
              forecast_length=forecast_length
          ),
      )
      model.fit(
          features=historical_data,
          target=target,
          predefined_model="auto",
      )
      ts_forecast = model.predict(
          historical_data, validation_blocks=validation_blocks
      )
      assert (
          len(ts_forecast) == forecast_length * validation_blocks
          if validation_blocks
          else forecast_length
      )
  
imports: import os
  import shutil
  from copy import deepcopy
  import numpy
  import pandas
  import pytest
  from golem.core.dag.graph_utils import graph_structure
  from sklearn.datasets import load_iris
  from sklearn.preprocessing import LabelEncoder
  from examples.simple.time_series_forecasting.ts_pipelines import ts_complex_ridge_smoothing_pipeline
  from fedot import Fedot
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.tasks import TsForecastingParams
  from test.data.datasets import get_dataset, get_multimodal_ts_data, load_categorical_unimodal, load_categorical_multidata
  from test.unit.common_tests import is_predict_ignores_target
  from test.unit.tasks.test_multi_ts_forecast import get_multi_ts_data
label_desc: Use image node_id 6 for calling a global function with example usage: test_api_in_sample_multimodal_ts_predict_correct(validation_blocks) without return types