EstimatorTransformer: Workflow EstimatorTransformer class

In DyfanJones/sagemaker-r-workflow: sagemaker pipeline and workflows

Workflow EstimatorTransformer class

Description

Creates a Transformer step collection for workflow.

Super class

sagemaker.workflow::StepCollection -> EstimatorTransformer

Methods

Public methods

• EstimatorTransformer$new()

• EstimatorTransformer$clone()

Inherited methods

• sagemaker.workflow::StepCollection$format()

• sagemaker.workflow::StepCollection$request_list()

---

Method new()

Construct steps required for a Transformer step collection: An estimator-centric step collection. It models what happens in workflows when invoking the 'transform()' method on an estimator instance: First, if custom model artifacts are required, a '_RepackModelStep' is included. Second, a 'CreateModelStep' with the model data passed in from a training step or other training job output. Finally, a 'TransformerStep'. If repacking the model artifacts is not necessary, only the CreateModelStep and TransformerStep are in the step collection.

Usage

EstimatorTransformer$new(
  name,
  estimator,
  model_data,
  model_inputs,
  instance_count,
  instance_type,
  transform_inputs,
  description = NULL,
  display_name = NULL,
  image_uri = NULL,
  predictor_cls = NULL,
  env = NULL,
  strategy = NULL,
  assemble_with = NULL,
  output_path = NULL,
  output_kms_key = NULL,
  accept = NULL,
  max_concurrent_transforms = NULL,
  max_payload = NULL,
  tags = NULL,
  volume_kms_key = NULL,
  depends_on = NULL,
  repack_model_step_retry_policies = NULL,
  model_step_retry_policies = NULL,
  transform_step_retry_policies = NULL,
  ...
)

Arguments

name

(str): The name of the Transform Step.

estimator

: The estimator instance.

model_data

(str): The S3 location of a SageMaker model data “.tar.gz“ file (default: None).

model_inputs

(CreateModelInput): A 'sagemaker.inputs.CreateModelInput' instance. Defaults to 'None'.

instance_count

(int): The number of EC2 instances to use.

instance_type

(str): The type of EC2 instance to use.

transform_inputs

(TransformInput): A 'sagemaker.inputs.TransformInput' instance.

description

(str): The description of the step.

display_name

(str): The display name of the step.

image_uri

(str): A Docker image URI.

predictor_cls

(callable[string, :Session]): A function to call to create a predictor (default: None). If not None, “deploy“ will return the result of invoking this function on the created endpoint name.

env

(dict): The Environment variables to be set for use during the transform job (default: None).

strategy

(str): The strategy used to decide how to batch records in a single request (default: None). Valid values: 'MultiRecord' and 'SingleRecord'.

assemble_with

(str): How the output is assembled (default: None). Valid values: 'Line' or 'None'.

output_path

(str): The S3 location for saving the transform result. If not specified, results are stored to a default bucket.

output_kms_key

(str): Optional. A KMS key ID for encrypting the transform output (default: None).

accept

(str): The accept header passed by the client to the inference endpoint. If it is supported by the endpoint, it will be the format of the batch transform output.

max_concurrent_transforms

(int): The maximum number of HTTP requests to be made to each individual transform container at one time.

max_payload

(int): Maximum size of the payload in a single HTTP

tags

(list[dict]): List of tags for labeling a training job. For more, see https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html.

volume_kms_key

(str): Optional. KMS key ID for encrypting the volume attached to the ML compute instance (default: None).

depends_on

(List[str] or List[Step]): The list of step names or step instances the first step in the collection depends on

repack_model_step_retry_policies

(List[RetryPolicy]): The list of retry policies for the repack model step

model_step_retry_policies

(List[RetryPolicy]): The list of retry policies for model step

transform_step_retry_policies

(List[RetryPolicy]): The list of retry policies for transform step

...

: pass onto model class.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

EstimatorTransformer$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/sagemaker-r-workflow documentation built on April 3, 2022, 11:28 p.m.