DescribeTransformJobResponse

import type { DescribeTransformJobResponse } from "https://aws-api.deno.dev/v0.4/services/sagemaker.ts?docs=full";

interface DescribeTransformJobResponse {

AutoMLJobArn?: string | null;

BatchStrategy?: BatchStrategy | null;

CreationTime: Date | number;

DataCaptureConfig?: BatchDataCaptureConfig | null;

DataProcessing?: DataProcessing | null;

Environment?: {

[key: string]: string | null | undefined;

} | null;

ExperimentConfig?: ExperimentConfig | null;

FailureReason?: string | null;

LabelingJobArn?: string | null;

MaxConcurrentTransforms?: number | null;

MaxPayloadInMB?: number | null;

ModelClientConfig?: ModelClientConfig | null;

ModelName: string;

TransformEndTime?: Date | number | null;

TransformInput: TransformInput;

TransformJobArn: string;

TransformJobName: string;

TransformJobStatus: TransformJobStatus;

TransformOutput?: TransformOutput | null;

TransformResources: TransformResources;

TransformStartTime?: Date | number | null;

}

§Properties

AutoMLJobArn?: string | null

[src]

The Amazon Resource Name (ARN) of the AutoML transform job.

BatchStrategy?: BatchStrategy | null

[src]

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.

CreationTime: Date | number

[src]

A timestamp that shows when the transform Job was created.

DataCaptureConfig?: BatchDataCaptureConfig | null

[src]

Configuration to control how SageMaker captures inference data.

DataProcessing?: DataProcessing | null

[src]

Environment?: {

[key: string]: string | null | undefined;

} | null

[src]

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

ExperimentConfig?: ExperimentConfig | null

[src]

FailureReason?: string | null

[src]

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.

LabelingJobArn?: string | null

[src]

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

MaxConcurrentTransforms?: number | null

[src]

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

MaxPayloadInMB?: number | null

[src]

The maximum payload size, in MB, used in the transform job.

ModelClientConfig?: ModelClientConfig | null

[src]

The timeout and maximum number of retries for processing a transform job invocation.

ModelName: string

[src]

The name of the model used in the transform job.

TransformEndTime?: Date | number | null

[src]

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.

TransformInput: TransformInput

[src]

Describes the dataset to be transformed and the Amazon S3 location where it is stored.

TransformJobArn: string

[src]

The Amazon Resource Name (ARN) of the transform job.

TransformJobName: string

[src]

The name of the transform job.

TransformJobStatus: TransformJobStatus

[src]

The status of the transform job. If the transform job failed, the reason is returned in the FailureReason field.

TransformOutput?: TransformOutput | null

[src]

Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.

TransformResources: TransformResources

[src]

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

TransformStartTime?: Date | number | null

[src]

Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.