pip install --upgrade azureml-sdk[automl] fails on python 3.8 at requirement onnxruntime==1.0.0
See original GitHub issue- Package Name: azureml-sdk[automl]
- Package Version: 1.13.0
- Operating System: macos Catalina 10.15.6
- Python Version: 3.8.5
Describe the bug
I run pip install --upgrade azureml-sdk[automl]
as per the docs.
Installation fails.
To Reproduce Steps to reproduce the behavior:
pip install --upgrade azureml-sdk[automl]
Screenshots
ERROR: Could not find a version that satisfies the requirement onnxruntime==1.0.0 (from azureml-train-automl-runtime~=1.13.0->azureml-train-automl~=1.13.0; extra == "automl"->azureml-sdk[automl]) (from versions: 1.2.0, 1.3.0, 1.4.0)
ERROR: No matching distribution found for onnxruntime==1.0.0 (from azureml-train-automl-runtime~=1.13.0->azureml-train-automl~=1.13.0; extra == "automl"->azureml-sdk[automl])
Additional context
azureml-sdk[explain]
succeedspip install onnxruntime==1.0.0
fails with the sameERROR: Could not find a version that satisfies the requirement onnxruntime==1.0.0 (from versions: 1.2.0, 1.3.0, 1.4.0)
pip install onnxruntime
succeeds and installs 1.4.0python -c 'import struct;print( 8 * struct.calcsize("P"))'
--> 64
Issue Analytics
- State:
- Created 3 years ago
- Comments:7 (1 by maintainers)
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@chrisfcarroll @githubkingchamp Unfortunately the full automl package does not currently support Python version 3.8.5 because of dependent packages.
However, you can use a client version of automl, which is in the
azureml-train-automl-client
package. This package is installed by default when you install theazureml-sdk
package. It allows you to submit automl remote runs and do remote inferencing. It does not support local training or inferencing.There is an experimental sample notebook that demonstrates remote inference at: https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy This notebook also requires pandas<1.0.0, numpy<1.19.0, azureml-widgets, matplotlib and sklearn.
Closing because there’s a workaround - drop to python 3.7 - and the issue is with dependent packages