code: def generate_multi_modal_pipeline(data: MultiModalData):
      # image
      images_size = data["data_source_img"].features.shape[1:4]
      ds_image = PipelineNode("data_source_img")
      image_node = PipelineNode("cnn", nodes_from=[ds_image])
      image_node.parameters = {
          "image_shape": images_size,
          "architecture": "simplified",
          "epochs": 15,
          "batch_size": 128,
      }
  
      # table
      ds_table = PipelineNode("data_source_table")
      scaling_node = PipelineNode("scaling", nodes_from=[ds_table])
      numeric_node = PipelineNode("rf", nodes_from=[scaling_node])
  
      # text
      ds_text = PipelineNode("data_source_text")
      node_text_clean = PipelineNode("text_clean", nodes_from=[ds_text])
      text_node = PipelineNode("tfidf", nodes_from=[node_text_clean])
  
      pipeline = Pipeline(
          PipelineNode(
              "logit", nodes_from=[numeric_node, image_node, text_node]
          )
      )
  
      return pipeline
  
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 1 for calling a global function with example usage: generate_multi_modal_pipeline(data) and returns: pipeline