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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 Report
The text was updated successfully, but these errors were encountered:
We are currently working on exposing the TransformStepparameters in the step constructor. With this change, any parameters documented in CreateTransformJob will be dynamically configurable.
@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 :)
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 callingTransformer.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 theTransformerStep
and settingparameters['ModelClientConfig']
to the value passed there.This is 🐛 Bug Report
The text was updated successfully, but these errors were encountered: