name: 'SageMaker - Batch Transformation'
description: |
  Batch Transformation Jobs in SageMaker
inputs:
  - {name: region,          description: 'The region where the cluster launches.'}
  - {name: model_name,      description: 'The name of the model that you want to use for the transform job.'}
  - {name: input_location,  description: 'The S3 location of the data source that is associated with a channel.'}
  - {name: output_location, description: 'The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job.'}
outputs:
  - {name: output_location,    description: 'S3 URI of the transform job results.'}
implementation:
  container:
    image: seedjeffwan/kubeflow-pipeline-aws-sm:20190501-05
    command: ['python']
    args: [
      batch_transform.py,
      --region, {inputValue: region},
      --model_name, {inputValue: model_name},
      --input_location, {inputValue: input_location},
      --output_location, {inputValue: output_location},
      --output_location_file, {outputPath: output_location},
    ]