code: def test_multi_modal_pipeline():
      path = fedot_project_root().joinpath(
          "test", "data", "multi_modal"
      )
      task = Task(TaskTypesEnum.classification)
      images_size = (128, 128)
  
      fit_data = prepare_multi_modal_data(path, task, images_size)
      pipeline = generate_multi_modal_pipeline(fit_data)
  
      pipeline.fit(fit_data)
      prediction = pipeline.predict(fit_data)
  
      assert prediction is not None
  
file_path: FEDOT/test/integration/multimodal/test_multimodal.py
imports: import pytest
  from examples.advanced.multi_modal_pipeline import prepare_multi_modal_data
  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.pipelines.pipeline_builder import PipelineBuilder
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root
  from test.integration.models.test_model import get_data_for_testing
label_desc: Use image node_id 3 for calling a global function with example usage: test_multi_modal_pipeline() without return types