code: def matrix_worker(data):
      
      matrix = data['matrix']
      Logger.get_logger(__name__ + '.worker').info(
          "Processing pipeline for matrix entry '%s'", matrix['name'])
  
      env = matrix['env'].copy()
      env.update({'PIPELINE_MATRIX': matrix['name']})
  
      pipeline = Pipeline(model=data['model'], env=env, options=data['options'])
      pipeline.hooks = data['hooks']
      return pipeline.process(data['pipeline'])
docs: Run pipelines in parallel.
  
      Args:
          data(dict): parameters for the pipeline (model, options, ...).
      Returns:
          dict: with two fields: success True/False and captured output (list of str).