CODEWITHSUNDEEP
azureazure-machine-learning-service
user235
user235

Reputation: 1

several dependency errors causing in Azure AutoML while running model

I am trying to work on different models on a small piece of ML project which needs to work on azure platform and get the score.py with all the values. It is getting not a single library issue, but getting multiple Module errors and Attribute errors. I am using latest SDK version only, but I am not sure, where I am going side path.

Any previous observations on this error?

Upvotes: 0

Views: 120

Answers (1)

Sairam Tadepalli
Sairam Tadepalli

Reputation: 1683

The compatibility break is there for the newer version of the packages based on the current version of SDK. If the current SDK version is 1.13.0 and above, previous versions of packages are not in working stage. The compatibility issue is raising because of support of packages from SDK for different versions. It differs from version-to-version package support from SDK.

Because of this we are getting Module not found, ImportError and AttributeError.

This solution depends on the AutoML SDK training version.

  • If you are using 1.13.0 above version of SDK, update the versions of pandas to 0.25.1 and scikit-learn to 0.22.1

Using the following command in BASH to upgrade the versions.

pip install –upgrade pandas==0.25.1

pip install –upgrade sickit-learn==0.22.1

The generic syntax for upgrading is:

pip install –upgrade package_name==version
  • If the error occurs in AutoML Configuration file, then need to upgrade that also.
  • But it is suggestable to uninstall and reinstall AutoMLConfig.
pip uninstall azureml-train automl

Then reinstall using the below code,

pip install azureml-train automl

If you are using windows operating system, then install Miniconda.

If you are a linux user, then using sudo or conda syntaxes for the same operation.

Some of the advanced libraries of computer vision supportive like TensorFlow will be installed by default. Then we need to install them from dependencies.

azureml.core.runconfig import RunConfiguration from
azureml.core.conda_dependencies import CondaDependencies run_config =
RunConfiguration() run_config.environment.python.conda_dependencies =
CondaDependencies.create(conda_packages=['tensorflow==1.12.0'])

Documentation credit to @Larry Franks.

Upvotes: 0

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