aws / aws/aws-step-functions-data-science-sdk-python

Unable set ModelClientConfig in TransformerStep

Open
#171 3 comments 0 reactions 0 assignees View on GitHub
enhancement
Dominant language
Python
Stars
299
Forks
84
PR merge metrics
No merged PRs in 30d

Description

Not sure if this qualifies as a bug or a feature request...

When creating a transform job one can pass a ModelClientConfig containing the invocation timeout and number of retries. See https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html#sagemaker-CreateTransformJob-request-ModelClientConfig

This is implemented in the sagemaker python sdk, you can set `model_client_config` when calling `Transformer.transform`.

There is currently no option to set this in the `TransformerStep`

It should be relatively easy to implement by adding `model_client_config` as a param to the `TransformerStep` and setting `parameters['ModelClientConfig']` to the value passed there.

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This is :bug: Bug Report

Contributor guide

Open the contributing guide

Research direction

Start at the TransformerStep implementation and compare its parameter handling with Transformer.transform, which already accepts model_client_config. Confirm how the step builds its transform-job parameters, then verify that the supplied configuration is forwarded as ModelClientConfig and that existing behavior remains unchanged.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws, python
Domain
cloud, machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
45/100

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