class Aws::SageMaker::Types::CreateTransformJobRequest

@note When making an API call, you may pass CreateTransformJobRequest

data as a hash:

    {
      transform_job_name: "TransformJobName", # required
      model_name: "ModelName", # required
      max_concurrent_transforms: 1,
      model_client_config: {
        invocations_timeout_in_seconds: 1,
        invocations_max_retries: 1,
      },
      max_payload_in_mb: 1,
      batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord
      environment: {
        "TransformEnvironmentKey" => "TransformEnvironmentValue",
      },
      transform_input: { # required
        data_source: { # required
          s3_data_source: { # required
            s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile
            s3_uri: "S3Uri", # required
          },
        },
        content_type: "ContentType",
        compression_type: "None", # accepts None, Gzip
        split_type: "None", # accepts None, Line, RecordIO, TFRecord
      },
      transform_output: { # required
        s3_output_path: "S3Uri", # required
        accept: "Accept",
        assemble_with: "None", # accepts None, Line
        kms_key_id: "KmsKeyId",
      },
      transform_resources: { # required
        instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge
        instance_count: 1, # required
        volume_kms_key_id: "KmsKeyId",
      },
      data_processing: {
        input_filter: "JsonPath",
        output_filter: "JsonPath",
        join_source: "Input", # accepts Input, None
      },
      tags: [
        {
          key: "TagKey", # required
          value: "TagValue", # required
        },
      ],
      experiment_config: {
        experiment_name: "ExperimentEntityName",
        trial_name: "ExperimentEntityName",
        trial_component_display_name: "ExperimentEntityName",
      },
    }

@!attribute [rw] transform_job_name

The name of the transform job. The name must be unique within an
Amazon Web Services Region in an Amazon Web Services account.
@return [String]

@!attribute [rw] model_name

The name of the model that you want to use for the transform job.
`ModelName` must be the name of an existing Amazon SageMaker model
within an Amazon Web Services Region in an Amazon Web Services
account.
@return [String]

@!attribute [rw] max_concurrent_transforms

The maximum number of parallel requests that can be sent to each
instance in a transform job. If `MaxConcurrentTransforms` is set to
`0` or left unset, Amazon SageMaker checks the optional
execution-parameters to determine the settings for your chosen
algorithm. If the execution-parameters endpoint is not enabled, the
default value is `1`. For more information on execution-parameters,
see [How Containers Serve Requests][1]. For built-in algorithms, you
don't need to set a value for `MaxConcurrentTransforms`.

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests
@return [Integer]

@!attribute [rw] model_client_config

Configures the timeout and maximum number of retries for processing
a transform job invocation.
@return [Types::ModelClientConfig]

@!attribute [rw] max_payload_in_mb

The maximum allowed size of the payload, in MB. A *payload* is the
data portion of a record (without metadata). The value in
`MaxPayloadInMB` must be greater than, or equal to, the size of a
single record. To estimate the size of a record in MB, divide the
size of your dataset by the number of records. To ensure that the
records fit within the maximum payload size, we recommend using a
slightly larger value. The default value is `6` MB.

For cases where the payload might be arbitrarily large and is
transmitted using HTTP chunked encoding, set the value to `0`. This
feature works only in supported algorithms. Currently, Amazon
SageMaker built-in algorithms do not support HTTP chunked encoding.
@return [Integer]

@!attribute [rw] batch_strategy

Specifies the number of records to include in a mini-batch for an
HTTP inference request. A *record* ** is a single unit of input data
that inference can be made on. For example, a single line in a CSV
file is a record.

To enable the batch strategy, you must set the `SplitType` property
to `Line`, `RecordIO`, or `TFRecord`.

To use only one record when making an HTTP invocation request to a
container, set `BatchStrategy` to `SingleRecord` and `SplitType` to
`Line`.

To fit as many records in a mini-batch as can fit within the
`MaxPayloadInMB` limit, set `BatchStrategy` to `MultiRecord` and
`SplitType` to `Line`.
@return [String]

@!attribute [rw] environment

The environment variables to set in the Docker container. We support
up to 16 key and values entries in the map.
@return [Hash<String,String>]

@!attribute [rw] transform_input

Describes the input source and the way the transform job consumes
it.
@return [Types::TransformInput]

@!attribute [rw] transform_output

Describes the results of the transform job.
@return [Types::TransformOutput]

@!attribute [rw] transform_resources

Describes the resources, including ML instance types and ML instance
count, to use for the transform job.
@return [Types::TransformResources]

@!attribute [rw] data_processing

The data structure used to specify the data to be used for inference
in a batch transform job and to associate the data that is relevant
to the prediction results in the output. The input filter provided
allows you to exclude input data that is not needed for inference in
a batch transform job. The output filter provided allows you to
include input data relevant to interpreting the predictions in the
output from the job. For more information, see [Associate Prediction
Results with their Corresponding Input Records][1].

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html
@return [Types::DataProcessing]

@!attribute [rw] tags

(Optional) An array of key-value pairs. For more information, see
[Using Cost Allocation Tags][1] in the *Amazon Web Services Billing
and Cost Management User Guide*.

[1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what
@return [Array<Types::Tag>]

@!attribute [rw] experiment_config

Associates a SageMaker job as a trial component with an experiment
and trial. Specified when you call the following APIs:

* CreateProcessingJob

* CreateTrainingJob

* CreateTransformJob
@return [Types::ExperimentConfig]

@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTransformJobRequest AWS API Documentation

Constants

SENSITIVE