aws / aws/amazon-sagemaker-examples
callback_bottleneck.ipynb failed CI
- Dominant language
- Jupyter Notebook
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- Merged PRs (30d)
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Description
Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/sagemaker-debugger/tensorflow_profiling/callback_bottleneck.ipynb
Error:
---------------------------------------------------------------------------
Exception encountered at "In [11]":
---------------------------------------------------------------------------
ClientError Traceback (most recent call last)
in
5 region = 'us-east-1'
6
----> 7 tj = TrainingJob(training_job_name, region)
8
9 pf = PandasFrame(tj.profiler_s3_output_path)
/usr/local/lib/python3.7/site-packages/smdebug/profiler/analysis/notebook_utils/training_job.py in __init__(self, training_job_name, region)
22 self.sm_client = boto3.client("sagemaker", region_name=region)
23 self.profiler_config, self.profiler_s3_output_path = (
---> 24 self.get_config_and_profiler_s3_output_path()
25 )
26 self.system_metrics_reader
[...]
ClientError: An error occurred (ValidationException) when calling the DescribeTrainingJob operation: Requested resource not found.
Contributor guide
Research direction
Open sagemaker-debugger/tensorflow_profiling/callback_bottleneck.ipynb and inspect In [11], starting with TrainingJob(training_job_name, region) and the reported DescribeTrainingJob error. Reproduce the CI execution and determine why the requested training job is unavailable; done means the notebook completes that step without the resource-not-found failure.
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
- 30/100