aws / aws/amazon-sagemaker-examples

Sagemaker Processors base_job_name argument not working

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Dominant language
Jupyter Notebook
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Description

**Describe the bug**
Even though the base_job_name argument is set in the Processor definition, for instance sagemaker.sklearn.processing.SKLearnProcessor, the resulting processing job created has a totally different name.

**To reproduce**
To simplify, it's possible to use the abalone pipeline example and give a custom base_job_name to the SKLearnProcessor.
The result should be a ProcessingJob created with a name not compliant with the given job name, such as pipelines-kytlemm1lvpq-PreprocessingStep-cIpzShs3Qp

Contributor guide

Open the contributing guide

Research direction

Start with the abalone pipeline example and its SKLearnProcessor definition, then reproduce the processing job using a custom base_job_name. Trace how that argument reaches the created ProcessingJob and verify that the resulting job name complies with the requested base name.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
38/100

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