SageMakerCreateTransformJobProps

class aws_cdk.aws_stepfunctions_tasks.SageMakerCreateTransformJobProps(*, comment=None, heartbeat=None, input_path=None, integration_pattern=None, output_path=None, result_path=None, result_selector=None, timeout=None, model_name, transform_input, transform_job_name, transform_output, batch_strategy=None, environment=None, max_concurrent_transforms=None, max_payload=None, model_client_options=None, role=None, tags=None, transform_resources=None)

Bases: aws_cdk.aws_stepfunctions.TaskStateBaseProps

Properties for creating an Amazon SageMaker transform job task.

Parameters

  • comment (Optional[str]) – An optional description for this state. Default: - No comment

  • heartbeat (Optional[Duration]) – Timeout for the heartbeat. Default: - None

  • input_path (Optional[str]) – JSONPath expression to select part of the state to be the input to this state. May also be the special value JsonPath.DISCARD, which will cause the effective input to be the empty object {}. Default: - The entire task input (JSON path ‘$’)

  • integration_pattern (Optional[IntegrationPattern]) – AWS Step Functions integrates with services directly in the Amazon States Language. You can control these AWS services using service integration patterns Default: IntegrationPattern.REQUEST_RESPONSE

  • output_path (Optional[str]) – JSONPath expression to select select a portion of the state output to pass to the next state. May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}. Default: - The entire JSON node determined by the state input, the task result, and resultPath is passed to the next state (JSON path ‘$’)

  • result_path (Optional[str]) – JSONPath expression to indicate where to inject the state’s output. May also be the special value JsonPath.DISCARD, which will cause the state’s input to become its output. Default: - Replaces the entire input with the result (JSON path ‘$’)

  • result_selector (Optional[Mapping[str, Any]]) – The JSON that will replace the state’s raw result and become the effective result before ResultPath is applied. You can use ResultSelector to create a payload with values that are static or selected from the state’s raw result. Default: - None

  • timeout (Optional[Duration]) – Timeout for the state machine. Default: - None

  • model_name (str) – Name of the model that you want to use for the transform job.

  • transform_input (TransformInput) – Dataset to be transformed and the Amazon S3 location where it is stored.

  • transform_job_name (str) – Transform Job Name.

  • transform_output (TransformOutput) – S3 location where you want Amazon SageMaker to save the results from the transform job.

  • batch_strategy (Optional[BatchStrategy]) – Number of records to include in a mini-batch for an HTTP inference request. Default: - No batch strategy

  • environment (Optional[Mapping[str, str]]) – Environment variables to set in the Docker container. Default: - No environment variables

  • max_concurrent_transforms (Union[int, float, None]) – Maximum number of parallel requests that can be sent to each instance in a transform job. Default: - 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.

  • max_payload (Optional[Size]) – Maximum allowed size of the payload, in MB. Default: 6

  • model_client_options (Optional[ModelClientOptions]) – Configures the timeout and maximum number of retries for processing a transform job invocation. Default: - 0 retries and 60 seconds of timeout

  • role (Optional[IRole]) – Role for the Transform Job. Default: - A role is created with AmazonSageMakerFullAccess managed policy

  • tags (Optional[Mapping[str, str]]) – Tags to be applied to the train job. Default: - No tags

  • transform_resources (Optional[TransformResources]) – ML compute instances for the transform job. Default: - 1 instance of type M4.XLarge

Attributes

batch_strategy

Number of records to include in a mini-batch for an HTTP inference request.

Default

  • No batch strategy

Return type

Optional[BatchStrategy]

comment

An optional description for this state.

Default

  • No comment

Return type

Optional[str]

environment

Environment variables to set in the Docker container.

Default

  • No environment variables

Return type

Optional[Mapping[str, str]]

heartbeat

Timeout for the heartbeat.

Default

  • None

Return type

Optional[Duration]

input_path

JSONPath expression to select part of the state to be the input to this state.

May also be the special value JsonPath.DISCARD, which will cause the effective input to be the empty object {}.

Default

  • The entire task input (JSON path ‘$’)

Return type

Optional[str]

integration_pattern

AWS Step Functions integrates with services directly in the Amazon States Language.

You can control these AWS services using service integration patterns

Default

IntegrationPattern.REQUEST_RESPONSE

See

https://docs.aws.amazon.com/step-functions/latest/dg/connect-to-resource.html#connect-wait-token

Return type

Optional[IntegrationPattern]

max_concurrent_transforms

Maximum number of parallel requests that can be sent to each instance in a transform job.

Default

  • 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.

Return type

Union[int, float, None]

max_payload

Maximum allowed size of the payload, in MB.

Default

6

Return type

Optional[Size]

model_client_options

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

Default

  • 0 retries and 60 seconds of timeout

Return type

Optional[ModelClientOptions]

model_name

Name of the model that you want to use for the transform job.

Return type

str

output_path

JSONPath expression to select select a portion of the state output to pass to the next state.

May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.

Default

  • The entire JSON node determined by the state input, the task result,

and resultPath is passed to the next state (JSON path ‘$’)

Return type

Optional[str]

result_path

JSONPath expression to indicate where to inject the state’s output.

May also be the special value JsonPath.DISCARD, which will cause the state’s input to become its output.

Default

  • Replaces the entire input with the result (JSON path ‘$’)

Return type

Optional[str]

result_selector

The JSON that will replace the state’s raw result and become the effective result before ResultPath is applied.

You can use ResultSelector to create a payload with values that are static or selected from the state’s raw result.

Default

  • None

See

https://docs.aws.amazon.com/step-functions/latest/dg/input-output-inputpath-params.html#input-output-resultselector

Return type

Optional[Mapping[str, Any]]

role

Role for the Transform Job.

Default

  • A role is created with AmazonSageMakerFullAccess managed policy

Return type

Optional[IRole]

tags

Tags to be applied to the train job.

Default

  • No tags

Return type

Optional[Mapping[str, str]]

timeout

Timeout for the state machine.

Default

  • None

Return type

Optional[Duration]

transform_input

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

Return type

TransformInput

transform_job_name

Transform Job Name.

Return type

str

transform_output

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

Return type

TransformOutput

transform_resources

ML compute instances for the transform job.

Default

  • 1 instance of type M4.XLarge

Return type

Optional[TransformResources]