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fix(core): describe transform jobs through the session client in logs_for_transform_job - #6411
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…_for_transform_job
logs_for_transform_job described the job with
TransformJob.get(transform_job_name=..., session=sagemaker_session).__dict__.
TransformJob.get expects a boto3 Session, so passing the SageMaker Session
failed pydantic validation ('Input should be an instance of Session'), and the
resource's snake_case __dict__ does not have the PascalCase keys
(TransformResources, TransformJobStatus) that _logs_init and
_check_job_status read.
Describe the job through sagemaker_session.sagemaker_client, as
logs_for_processing_job does (aws#6369). aws#6509 already fixed the session used
by transform()/wait()/stop()/attach(); this covers the log tailing path.
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Issue #, if available: Relates to #6503
Description of changes:
Narrowed after #6509, which fixed the session used by
transform(),wait(),stop()andattach(). One path was still broken:logs_for_transform_jobdescribed the job with:TransformJob.getexpects a boto3Session, so passing the SageMakerSessionfails pydantic validation (Input should be an instance of Session).__dict__doesn't have the PascalCase keys (TransformResources,TransformJobStatus) that_logs_initand_check_job_statusread.This change describes the job through
sagemaker_session.sagemaker_client.describe_transform_job, aslogs_for_processing_jobdoes (#6369).Testing:
test_logs_for_transform_job_describes_with_session_client. It fails on master.test_transformer.pyandtest_transformer_session_propagation.py: 44 passed.By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.