code: def test_cgru_forecasting():
      horizon = 5
      window_size = 200
      train_data, test_data = get_ts_data("salaries", horizon)
  
      pipeline = (
          PipelineBuilder()
          .add_node("lagged", params={"window_size": window_size})
          .add_node("cgru")
          .build()
      )
      pipeline.fit(train_data)
      predicted = pipeline.predict(test_data).predict[0]
  
      assert len(predicted) == horizon
  
imports: import pytest
  from examples.simple.time_series_forecasting.api_forecasting import get_ts_data
  from examples.simple.time_series_forecasting.ts_pipelines import cgru_pipeline
  from fedot.core.pipelines.pipeline_builder import PipelineBuilder
label_desc: Use image node_id 1 for calling a global function with example usage: test_cgru_forecasting() without return types