content: #  Copyright (c) ZenML GmbH 2020. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
  #  or implied. See the License for the specific language governing
  #  permissions and limitations under the License.
  from steps import data_loader, predictor, trainer
  
  from zenml import pipeline
  from zenml.config import DockerSettings
  from zenml.integrations.constants import XGBOOST
  
  docker_settings = DockerSettings(required_integrations=[XGBOOST])
  
  
  @pipeline(enable_cache=True, settings={"docker": docker_settings})
  def xgboost_pipeline():
      """Links all the steps together in a pipeline."""
      mat_train, mat_test = data_loader()
      model = trainer(mat_train)
      predictor(model, mat_test)
  