code: def run_automl(
      data: MultiModalData,
      features_to_use,
      forecast_horizon: int = 10,
      history_size: int = 397,
      timeout: int = 1,
  ):
      """Launch AutoML FEDOT algorithm for time series forecasting task"""
  
      metocean_folder = fedot_project_root().joinpath(
          "cases", "data", "metocean"
      )
  
      connect_params = {}
      exec_params = {
          "container_input_path": metocean_folder,
          "container_output_path": metocean_folder.joinpath("remote"),
          "container_config_path": metocean_folder.joinpath(
              "metocean", "."
          ),
          "container_image": "test",
          "timeout": 1,
      }
      client = TestClient(
          connect_params,
          exec_params,
          output_path=metocean_folder.joinpath("remote"),
      )
  
      remote_task_params = RemoteTaskParams(
          mode="remote",
          dataset_name="metocean_data_train",
          max_parallel=20,
          var_names=features_to_use,
          target="sea_height",
      )
  
      # the following client and params can be used with DataMall system
      # connect_params = DEFAULT_CONNECT_PARAMS
      # exec_params = DEFAULT_EXEC_PARAMS
      # DataMallClient(connect_params, exec_params, output_path=os.path.join(folder, 'remote'))
  
      evaluator = RemoteEvaluator()
      evaluator.init(
          client=client, remote_task_params=remote_task_params
      )
  
      # Prepare parameters for algorithm launch
      composer_params = {
          "max_depth": 6,
          "max_arity": 3,
          "pop_size": 20,
          "num_of_generations": 100,
          "preset": "fast_train",
          "metric": "rmse",
          "cv_folds": None,
      }
  
      automl = Fedot(
          problem="ts_forecasting", timeout=timeout, **composer_params
      )
  
      obtained_pipeline = automl.fit(data)
      forecast = automl.forecast(data)
      return forecast, obtained_pipeline
  
file_path: FEDOT/examples/advanced/remote_execution/ts_composer_with_integration.py
imports: from fedot import Fedot
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.utils import fedot_project_root
  from fedot.core.utils import set_random_seed
  from fedot.remote.infrastructure.clients.test_client import TestClient
  from fedot.remote.remote_evaluator import RemoteEvaluator, RemoteTaskParams
label_desc: Use image node_id 2 for calling a global function with example usage: run_automl(data, features_to_use, forecast_horizon, history_size, timeout) and returns: forecast,  obtained_pipeline