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Google Colab - error in dist_manager.py _refresh_resource(cls) #163
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Thanks for the feedback! Looks like the remote on Collab is not initialized correctly. I will take a look. |
related issue: #162 |
Looks like dask distributed issue: dask/distributed#3330 |
thanks a lot. |
Using AutoGluon 0.0.6, I am able to get it working in Colab through:
RESTART RUNTIME
One thing I noticed was that NN takes ~3x longer to train than on my mac laptop. Intel MKL is installed on Colab and should be uninstalled to speed-up AutoGluon. Uninstalling MKL gives at least 2x speedup. Link to Colab Notebook: https://colab.research.google.com/drive/1ULOytrRHcw4GLl0qWgGnxUpr9zVQVYlr I think this issue has to be fixed on Google Colab's end to avoid the pip install -U ipykernel requirement. They need to upgrade their default ipykernel version. Until then, this should be the simplest way to get things working on Colab. Marking this issue as resolved. |
Just adding a comment for future reference to whoever stumbles on the same error. The suggestion by @Innixma worked perfectly but I also had to update "dask" because stringify was not getting called. So after: pip install -U ipykernel You can also update -U dask: !pip install -U dask |
Google Colab notebook for reference:
https://drive.google.com/open?id=1DAVTtAD7zGbJzrkvRKRjWvIhKzCawNkH
Code:
detector = task.fit(dataset)
Error:
ValueError Traceback (most recent call last)
in ()
----> 1 detector = task.fit(dataset)
5 frames
/usr/local/lib/python3.6/dist-packages/autogluon/scheduler/resource/dist_manager.py in _refresh_resource(cls)
48 @classmethod
49 def _refresh_resource(cls):
---> 50 cls.MAX_CPU_COUNT = max([x.get_all_resources()[0] for x in cls.NODE_RESOURCE_MANAGER.values()])
51 cls.MAX_GPU_COUNT = max([x.get_all_resources()[1] for x in cls.NODE_RESOURCE_MANAGER.values()])
52
ValueError: max() arg is an empty sequence
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