aws-step-functions-data-science-sdk-python
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aws
Unable set ModelClientConfig in TransformerStep
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.
This is :bug: Bug Report
Hi @ysgit
Thank you reporting this!
We are currently working on exposing the TransformStep parameters in the step constructor. With this change, any parameters documented in CreateTransformJob will be dynamically configurable.
Current PR for this change: #157
@ca-nguyen - PR #157 is currently classified as a feature. If it is a bug, let's make sure we add the template information captured for posterity (repro steps, expected behaviour, observed behaviour, etc).
The template information really helps in clarifying the problem and resolves ambiguity :)
