content: #  Copyright (c) ZenML GmbH 2022. 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.dynamic_importer_step import dynamic_importer
  from steps.predict_preprocessor_step import predict_preprocessor
  from steps.prediction_service_loader_step import prediction_service_loader
  from steps.predictor_step import predictor
  
  from zenml import pipeline
  from zenml.config import DockerSettings
  from zenml.integrations.constants import MLFLOW, SKLEARN
  
  docker_settings = DockerSettings(
      required_integrations=[MLFLOW, SKLEARN], requirements=["scikit-image"]
  )
  
  
  @pipeline(enable_cache=False, settings={"docker": docker_settings})
  def mlflow_deployment_inference_pipeline(
      pipeline_name: str = "mlflow_train_deploy_pipeline",
      pipeline_step_name: str = "mlflow_model_deployer_step",
  ):
      # Link all the steps artifacts together
      batch_data = dynamic_importer()
      inference_data = predict_preprocessor(batch_data)
      model_deployment_service = prediction_service_loader(
          pipeline_name=pipeline_name,
          pipeline_step_name=pipeline_step_name,
      )
      predictor(model_deployment_service, inference_data)
  