name: SageMaker - Batch Transformation
description: Batch Transformation Jobs in SageMaker
inputs:
- {name: region, type: String, description: The region for the SageMaker resource.}
- {name: endpoint_url, type: String, description: The URL to use when communicating
    with the SageMaker service., default: ''}
- {name: assume_role, type: String, description: The ARN of an IAM role to assume
    when connecting to SageMaker., default: ''}
- {name: tags, type: JsonObject, description: 'An array of key-value pairs, to categorize
    AWS resources.', default: '{}'}
- {name: job_name, type: String, description: The name of the transform job., default: ''}
- {name: model_name, type: String, description: The name of the model that you want
    to use for the transform job.}
- {name: max_concurrent, type: Integer, description: The maximum number of parallel
    requests that can be sent to each instance in a transform job., default: '0'}
- {name: max_payload, type: Integer, description: 'The maximum allowed size of the
    payload, in MB.', default: '6'}
- {name: batch_strategy, type: String, description: The number of records to include
    in a mini-batch for an HTTP inference request., default: ''}
- {name: environment, type: JsonObject, description: The dictionary of the environment
    variables to set in the Docker container. Up to 16 key-value entries in the map.,
  default: '{}'}
- {name: input_location, type: String, description: The S3 location of the data source
    that is associated with a channel.}
- {name: data_type, type: String, description: 'Data type of the input. Can be ManifestFile,
    S3Prefix, or AugmentedManifestFile.', default: S3Prefix}
- {name: content_type, type: String, description: The multipurpose internet mail extension
    (MIME) type of the data., default: ''}
- {name: split_type, type: String, description: The method to use to split the transform
    job data files into smaller batches., default: None}
- {name: compression_type, type: String, description: 'If the transform data is compressed,
    the specification of the compression type.', default: None}
- {name: output_location, type: String, description: The Amazon S3 path where you
    want Amazon SageMaker to store the results of the transform job.}
- {name: accept, type: String, description: The MIME type used to specify the output
    data., default: ''}
- {name: assemble_with, type: String, description: Defines how to assemble the results
    of the transform job as a single S3 object. Either None or Line., default: ''}
- {name: output_encryption_key, type: String, description: The AWS KMS key that Amazon
    SageMaker uses to encrypt the model artifacts., default: ''}
- {name: input_filter, type: String, description: A JSONPath expression used to select
    a portion of the input data to pass to the algorithm., default: ''}
- {name: output_filter, type: String, description: A JSONPath expression used to select
    a portion of the joined dataset to save in the output file for a batch transform
    job., default: ''}
- {name: join_source, type: String, description: Specifies the source of the data
    to join with the transformed data., default: None}
- {name: instance_type, type: String, description: The ML compute instance type for
    the transform job., default: ml.m4.xlarge}
- {name: instance_count, type: Integer, description: The number of ML compute instances
    to use in the transform job., default: '1'}
- {name: resource_encryption_key, type: String, description: The AWS KMS key that
    Amazon SageMaker uses to encrypt data on the storage volume attached to the ML
    compute instance(s)., default: ''}
outputs:
- {name: output_location, description: S3 URI of the transform job results.}
implementation:
  container:
    image: public.ecr.aws/kubeflow-on-aws/aws-sagemaker-kfp-components:1.1.2
    command: [python3]
    args:
    - batch_transform/src/sagemaker_transform_component.py
    - --region
    - {inputValue: region}
    - --endpoint_url
    - {inputValue: endpoint_url}
    - --assume_role
    - {inputValue: assume_role}
    - --tags
    - {inputValue: tags}
    - --job_name
    - {inputValue: job_name}
    - --model_name
    - {inputValue: model_name}
    - --max_concurrent
    - {inputValue: max_concurrent}
    - --max_payload
    - {inputValue: max_payload}
    - --batch_strategy
    - {inputValue: batch_strategy}
    - --environment
    - {inputValue: environment}
    - --input_location
    - {inputValue: input_location}
    - --data_type
    - {inputValue: data_type}
    - --content_type
    - {inputValue: content_type}
    - --split_type
    - {inputValue: split_type}
    - --compression_type
    - {inputValue: compression_type}
    - --output_location
    - {inputValue: output_location}
    - --accept
    - {inputValue: accept}
    - --assemble_with
    - {inputValue: assemble_with}
    - --output_encryption_key
    - {inputValue: output_encryption_key}
    - --input_filter
    - {inputValue: input_filter}
    - --output_filter
    - {inputValue: output_filter}
    - --join_source
    - {inputValue: join_source}
    - --instance_type
    - {inputValue: instance_type}
    - --instance_count
    - {inputValue: instance_count}
    - --resource_encryption_key
    - {inputValue: resource_encryption_key}
    - --output_location_output_path
    - {outputPath: output_location}