aws / aws/amazon-sagemaker-examples
0_cust_churn_overview_dw.ipynb failed CI
- Dominant language
- Jupyter Notebook
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Description
Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/use-cases/customer_churn/0_cust_churn_overview_dw.ipynb
Error:
---------------------------------------------------------------------------
Exception encountered at "In [3]":
---------------------------------------------------------------------------
UnknownServiceError Traceback (most recent call last)
in
----> 1 sagemaker_session = sagemaker.Session()
2 bucket = sagemaker_session.default_bucket() #replace with your own bucket name if you have one
3 s3 = sagemaker_session.boto_session.resource('s3')
4
5 region = boto3.Session().region_name
/opt/conda/lib/python3.7/site-packages/sagemaker/session.py in __init__(self, boto_session, sagemaker_client, sagemaker_runtime_client, sagemaker_featurestore_runtime_client, default_bucket)
124 sagemaker_client=sagemaker_client,
125 sagemaker_runtime_client=sagemaker_runtime_client,
--> 126 sagemaker_featurestore_runtime_client=sagemaker_featurestore_runtime_client,
127 )
128
/opt/conda
Contributor guide
Research direction
Open use-cases/customer_churn/0_cust_churn_overview_dw.ipynb and start with the failing In [3] cell, where sagemaker.Session() raises UnknownServiceError. Reproduce the CI failure and inspect the session initialization context. Done means the notebook completes its CI run without this error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, jupyter-notebook, python
- Domain
- machine-learning, testing-qa
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100