package Paws::SageMaker::DescribeTransformJobResponse; use Moose; has AutoMLJobArn => (is => 'ro', isa => 'Str'); has BatchStrategy => (is => 'ro', isa => 'Str'); has CreationTime => (is => 'ro', isa => 'Str', required => 1); has DataProcessing => (is => 'ro', isa => 'Paws::SageMaker::DataProcessing'); has Environment => (is => 'ro', isa => 'Paws::SageMaker::TransformEnvironmentMap'); has ExperimentConfig => (is => 'ro', isa => 'Paws::SageMaker::ExperimentConfig'); has FailureReason => (is => 'ro', isa => 'Str'); has LabelingJobArn => (is => 'ro', isa => 'Str'); has MaxConcurrentTransforms => (is => 'ro', isa => 'Int'); has MaxPayloadInMB => (is => 'ro', isa => 'Int'); has ModelClientConfig => (is => 'ro', isa => 'Paws::SageMaker::ModelClientConfig'); has ModelName => (is => 'ro', isa => 'Str', required => 1); has TransformEndTime => (is => 'ro', isa => 'Str'); has TransformInput => (is => 'ro', isa => 'Paws::SageMaker::TransformInput', required => 1); has TransformJobArn => (is => 'ro', isa => 'Str', required => 1); has TransformJobName => (is => 'ro', isa => 'Str', required => 1); has TransformJobStatus => (is => 'ro', isa => 'Str', required => 1); has TransformOutput => (is => 'ro', isa => 'Paws::SageMaker::TransformOutput'); has TransformResources => (is => 'ro', isa => 'Paws::SageMaker::TransformResources', required => 1); has TransformStartTime => (is => 'ro', isa => 'Str'); has _request_id => (is => 'ro', isa => 'Str'); ### main pod documentation begin ### =head1 NAME Paws::SageMaker::DescribeTransformJobResponse =head1 ATTRIBUTES =head2 AutoMLJobArn => Str The Amazon Resource Name (ARN) of the AutoML transform job. =head2 BatchStrategy => Str Specifies the number of records to include in a mini-batch for an HTTP inference request. A I I< 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 C to C, C, or C. Valid values are: C<"MultiRecord">, C<"SingleRecord"> =head2 B CreationTime => Str A timestamp that shows when the transform Job was created. =head2 DataProcessing => L =head2 Environment => L The environment variables to set in the Docker container. We support up to 16 key and values entries in the map. =head2 ExperimentConfig => L =head2 FailureReason => Str If the transform job failed, C 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 (https://docs.aws.amazon.com/sagemaker/latest/dg/logging-cloudwatch.html). =head2 LabelingJobArn => Str The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job. =head2 MaxConcurrentTransforms => Int The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1. =head2 MaxPayloadInMB => Int The maximum payload size, in MB, used in the transform job. =head2 ModelClientConfig => L The timeout and maximum number of retries for processing a transform job invocation. =head2 B ModelName => Str The name of the model used in the transform job. =head2 TransformEndTime => Str 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 C. =head2 B TransformInput => L Describes the dataset to be transformed and the Amazon S3 location where it is stored. =head2 B TransformJobArn => Str The Amazon Resource Name (ARN) of the transform job. =head2 B TransformJobName => Str The name of the transform job. =head2 B TransformJobStatus => Str The status of the transform job. If the transform job failed, the reason is returned in the C field. Valid values are: C<"InProgress">, C<"Completed">, C<"Failed">, C<"Stopping">, C<"Stopped"> =head2 TransformOutput => L Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job. =head2 B TransformResources => L Describes the resources, including ML instance types and ML instance count, to use for the transform job. =head2 TransformStartTime => Str Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of C. =head2 _request_id => Str =cut 1;