aws / aws/aws-step-functions-data-science-sdk-python
Unable set ModelClientConfig in TransformerStep
- 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
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