Parallel run example fail when executing with deserialization error
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- azure, jupyter-notebook, python
- Domain
- cloud, machine-learning
Research direction
Start with the file-dataset-partition-per-folder.ipynb example linked in the issue and run the same batch-processing script on multiple inputs. Reproduce the RawDeserializer and image-build failures, then confirm the example completes successfully without those errors and exposes usable logs.
Written by the indexing model from the issue text.
Description
I am trying to run a python script on multiple data inputs parallel, for this i am using the batch processing examples provided in this repo. Specifically I am looking at this one: https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/machine-learning-pipelines/parallel-run/file-dataset-partition-per-folder.ipynb
Running the exact same script initially generates a lot of value error saying "This pipeline didn't have the RawDeserializer policy; can't deserialize" (screenshot 1) and finally raises the Image build failed error (screenshot 2). I cannot find anything at the logfile mentioned in the error code. I have tried using the same environment from my azureml vm but that also didn't help.
Can someone kindly help?
- Dominant language
- Jupyter Notebook
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