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[ aws . sagemaker ]

create-transform-job

Description

Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.

To perform batch transformations, you create a transform job and use the data that you have readily available.

In the request body, you provide the following:

  • TransformJobName - Identifies the transform job. The name must be unique within an AWS Region in an AWS account.
  • ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.
  • TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
  • TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
  • TransformResources - Identifies the ML compute instances for the transform job.

For more information about how batch transformation works Amazon SageMaker, see How It Works .

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  create-transform-job
--transform-job-name <value>
--model-name <value>
[--max-concurrent-transforms <value>]
[--max-payload-in-mb <value>]
[--batch-strategy <value>]
[--environment <value>]
--transform-input <value>
--transform-output <value>
--transform-resources <value>
[--tags <value>]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--transform-job-name (string)

The name of the transform job. The name must be unique within an AWS Region in an AWS account.

--model-name (string)

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 AWS Region in an AWS account.

--max-concurrent-transforms (integer)

The maximum number of parallel requests that can be sent to each instance in a transform job. This is good for algorithms that implement multiple workers on larger instances . The default value is 1 . To allow Amazon SageMaker to determine the appropriate number for MaxConcurrentTransforms , set the value to 0 .

--max-payload-in-mb (integer)

The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater or equal to the size of a single record. You can approximate the size of a record by dividing the size of your dataset by the number of records. Then multiply this value by the number of records you want in a mini-batch. It is recommended to enter a value slightly larger than this to ensure the records fit within the maximum payload size. The default value is 6 MB. For an unlimited payload size, set the value to 0 .

--batch-strategy (string)

Determines the number of records included in a single mini-batch. SingleRecord means only one record is used per mini-batch. MultiRecord means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB limit.

Possible values:

  • MultiRecord
  • SingleRecord

--environment (map)

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

Shorthand Syntax:

KeyName1=string,KeyName2=string

JSON Syntax:

{"string": "string"
  ...}

--transform-input (structure)

Describes the input source and the way the transform job consumes it.

Shorthand Syntax:

DataSource={S3DataSource={S3DataType=string,S3Uri=string}},ContentType=string,CompressionType=string,SplitType=string

JSON Syntax:

{
  "DataSource": {
    "S3DataSource": {
      "S3DataType": "ManifestFile"|"S3Prefix",
      "S3Uri": "string"
    }
  },
  "ContentType": "string",
  "CompressionType": "None"|"Gzip",
  "SplitType": "None"|"Line"|"RecordIO"
}

--transform-output (structure)

Describes the results of the transform job.

Shorthand Syntax:

S3OutputPath=string,Accept=string,AssembleWith=string,KmsKeyId=string

JSON Syntax:

{
  "S3OutputPath": "string",
  "Accept": "string",
  "AssembleWith": "None"|"Line",
  "KmsKeyId": "string"
}

--transform-resources (structure)

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

Shorthand Syntax:

InstanceType=string,InstanceCount=integer

JSON Syntax:

{
  "InstanceType": "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",
  "InstanceCount": integer
}

--tags (list)

An array of key-value pairs. Adding tags is optional. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide .

Shorthand Syntax:

Key=string,Value=string ...

JSON Syntax:

[
  {
    "Key": "string",
    "Value": "string"
  }
  ...
]

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

TransformJobArn -> (string)

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