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.bento_builder import bento_builder
  from steps.deployer import bentoml_model_deployer
  from steps.deployment_trigger_step import (
      deployment_trigger,
  )
  from steps.evaluators import evaluator
  from steps.importers import importer_mnist
  from steps.trainers import trainer
  
  from zenml import pipeline
  from zenml.config import DockerSettings
  from zenml.integrations.constants import BENTOML, PYTORCH
  
  docker_settings = DockerSettings(required_integrations=[PYTORCH, BENTOML])
  
  
  @pipeline(enable_cache=False, settings={"docker": docker_settings})
  def training_fashion_mnist():
      """Train a model and deploy it with BentoML."""
      train_dataloader, test_dataloader = importer_mnist()
      model = trainer(train_dataloader)
      accuracy = evaluator(test_dataloader=test_dataloader, model=model)
      decision = deployment_trigger(accuracy=accuracy, min_accuracy=0.80)
      bento = bento_builder(model=model)
      bentoml_model_deployer(bento=bento, deploy_decision=decision)
  