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I have a dask cluster active

from dask.distributed import Client, progress 

client = Client()
client

When I try to encode my data I get the error:

AttributeError: 'MaterializedLayer' object has no attribute 'pack_annotations'

I encoded the data with the cluster closed and then tried to fit the model and I get the same error.

Alejandro
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  • same problem when using AWS SageMaker. It was working okay till yesterday! – armiro Jun 23 '22 at 21:54
  • I am about to use a bigger instance and not go for a distributed approach, I don't see any other options on my end. – Alejandro Jun 26 '22 at 06:28
  • In my case, the largest possible instance was not sufficient. I ended up creating a crawler and connecting the data to an Athena database. – armiro Jun 27 '22 at 17:39
  • I was even deleting some columns, I managed to train the model, but It was not giving me any predictions, I will just go iddle... Do you mind telling me more about your approach?, I would like to give it a try but I have no idea – Alejandro Jun 27 '22 at 21:06
  • Actually, my intention was to load a very large dataset and perform some SQL queries to filter some rows and export results, so in this case, I don't think my approach helps you. I suggest you try AWS EMR and create a cluster, then connect it to a SageMaker notebook. Let me know if it helped you. – armiro Jun 27 '22 at 21:20

1 Answers1

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Solution: Sagemaker Kernel most be python V3.8 which is compatible with dask distributed, as soon as I update the kernel to python 3.8. Works just fine.

Alejandro
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