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I just followed the blog post and I was able to run a notebook job successfully.
If you successfully run the job, you will see following files under the S3 bucket you specified.
$ aws s3 ls s3://sagemaker-automated-execution-123456789012-us-east-2 --recursive
2024-04-17 17:57:49 9480 notebookjobtestip-notebookjobtest-bf50211d-2024-04-18-00-57-47/input/notebook-job-test.ipynb
2024-04-17 18:00:14 13948 notebookjobtestip-notebookjobtest-bf50211d-2024-04-18-00-57-47/output/output.tar.gz
I am sharing my input configurations:
- Compute type : ml.m5.large
- Image : arn:aws:sagemaker:us-east-2:429704687514:image/sagemaker-base-python-38
- Kernel : python3
- Role ARN : arn:aws:iam::123456789012:role/SagemakerJupyterSchedulerRole
- Input Folder : s3://sagemaker-automated-execution-123456789012-us-east-2/
- Output Folder : s3://sagemaker-automated-execution-123456789012-us-east-2/
Please try similar configurations and check if it works.
respondido hace un mes
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Same question on the StackOverflow: https://stackoverflow.com/questions/78333128/empty-output-job-folder
I provided an answer there.
respondido hace 24 días
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