aws / aws/amazon-sagemaker-examples
tensorflow2_smdataparallel_maskrcnn_demo.ipynb failed CI
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- Jupyter Notebook
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Description
Link to the notebook:
https://github.com/aws/amazon-sagemaker-examples/blob/master/training/distributed_training/tensorflow/data_parallel/maskrcnn/tensorflow2_smdataparallel_maskrcnn_demo.ipynb
Error:
---------------------------------------------------------------------------
Exception encountered at "In [12]":
---------------------------------------------------------------------------
ParamValidationError Traceback (most recent call last)
in
1 # Submit SageMaker training job
----> 2 estimator.fit(inputs=data_channels, job_name=job_name)
/usr/local/lib/python3.7/site-packages/sagemaker/estimator.py in fit(self, inputs, wait, logs, job_name, experiment_config)
667 self._prepare_for_training(job_name=job_name)
668
--> 669 self.latest_training_job = _TrainingJob.start_new(self, inputs, experiment_config)
670 self.jobs.append(self.latest_training_job)
671 if wait:
/usr/local/lib/python3.7/site-packages/sagemaker/estimator.py in start_new(cls, estimator, inputs,
[...]
Invalid length for parameter InputDataConfig[0].DataSource.FileSystemDataSource.FileSystemId, value: 8, valid min length: 11
Contributor guide
Research direction
Open training/distributed_training/tensorflow/data_parallel/maskrcnn/tensorflow2_smdataparallel_maskrcnn_demo.ipynb and start at In [12], where estimator.fit(inputs=data_channels, job_name=job_name) fails. Reproduce the CI run and inspect the filesystem input configuration. Done means the notebook completes CI without the FileSystemId validation error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, jupyter-notebook, tensorflow
- Domain
- cloud, machine-learning, testing
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100