class Aws::SageMaker::Types::DescribeTransformJobResponse

@!attribute [rw] transform_job_name

The name of the transform job.
@return [String]

@!attribute [rw] transform_job_arn

The Amazon Resource Name (ARN) of the transform job.
@return [String]

@!attribute [rw] transform_job_status

The status of the transform job. If the transform job failed, the
reason is returned in the `FailureReason` field.
@return [String]

@!attribute [rw] failure_reason

If the transform job failed, `FailureReason` describes why it
failed. A transform job creates a log file, which includes error
messages, and stores it as an Amazon S3 object. For more
information, see [Log Amazon SageMaker Events with Amazon
CloudWatch][1].

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/logging-cloudwatch.html
@return [String]

@!attribute [rw] model_name

The name of the model used in the transform job.
@return [String]

@!attribute [rw] max_concurrent_transforms

The maximum number of parallel requests on each instance node that
can be launched in a transform job. The default value is 1.
@return [Integer]

@!attribute [rw] model_client_config

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

@!attribute [rw] max_payload_in_mb

The maximum payload size, in MB, used in the transform job.
@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 `SplitType` to `Line`,
`RecordIO`, or `TFRecord`.
@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 dataset to be transformed and the Amazon S3 location
where it is stored.
@return [Types::TransformInput]

@!attribute [rw] transform_output

Identifies the Amazon S3 location where you want Amazon SageMaker to
save the results from 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] creation_time

A timestamp that shows when the transform Job was created.
@return [Time]

@!attribute [rw] transform_start_time

Indicates when the transform job starts on ML instances. You are
billed for the time interval between this time and the value of
`TransformEndTime`.
@return [Time]

@!attribute [rw] transform_end_time

Indicates when the transform job has been completed, or has stopped
or failed. You are billed for the time interval between this time
and the value of `TransformStartTime`.
@return [Time]

@!attribute [rw] labeling_job_arn

The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth
labeling job that created the transform or training job.
@return [String]

@!attribute [rw] auto_ml_job_arn

The Amazon Resource Name (ARN) of the AutoML transform job.
@return [String]

@!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] 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/DescribeTransformJobResponse AWS API Documentation

Constants

SENSITIVE