Enable Python 3.8 support #210
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Abandoning this for now because tensorflow won't support Python 3.8 until version 2.2 sometime later this year, and we're limiting to tensorflow 1.* for now anyway. |
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Tensorflow 2.2 will soon be out, so I'm reopening this so that we can support Python 3.8, which has been out for several months and is seeing increased use in practice. |
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kbattocchi
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Aug 10, 2020
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| # - job: 'AutoML' | ||
| # dependsOn: 'EvalChanges' | ||
| # condition: eq(dependencies.EvalChanges.outputs['output.testCode'], 'True') | ||
| # variables: | ||
| # python.version: '3.6' | ||
| # pool: | ||
| # vmImage: 'ubuntu-16.04' | ||
| # steps: | ||
| # - template: azure-pipelines-steps.yml | ||
| # parameters: | ||
| # body: | ||
| # - task: AzureCLI@2 | ||
| # displayName: 'AutoML tests' | ||
| # inputs: | ||
| # azureSubscription: 'automl' | ||
| # scriptLocation: 'inlineScript' | ||
| # scriptType: 'pscore' | ||
| # powerShellIgnoreLASTEXITCODE: '' # string for now due to https://github.com/microsoft/azure-pipelines-tasks/issues/12266 | ||
| # inlineScript: | | ||
| # $env:SUBSCRIPTION_ID = az account show --query id -o tsv | ||
| # python setup.py pytest | ||
| # env: | ||
| # WORKSPACE_NAME: 'testWorkspace' | ||
| # RESOURCE_GROUP: 'testingAutoMLEconML' | ||
| # PYTEST_ADDOPTS: '-m "automl" -n 0' | ||
| # COVERAGE_PROCESS_START: 'setup.cfg' | ||
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| # - task: PublishTestResults@2 | ||
| # displayName: 'Publish Test Results **/test-results.xml' | ||
| # inputs: | ||
| # testResultsFiles: '**/test-results.xml' | ||
| # testRunTitle: 'AutoML' | ||
| # condition: succeededOrFailed() | ||
| # package: '.[automl]' |
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Had to disable AutoML tests, because it seems like they were already broken by something changing server-side for AutoML and I couldn't figure out the necessary changes after a small amount of debugging. I've opened a new issue (#270) to fix this.
kbattocchi
commented
Aug 11, 2020
| lightning package implements such a class: | ||
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| .. testcode:: | ||
| lightning package implements such a class:: |
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Released versions of lightning are currently not compatible with sklearn 0.23 (though this problem has been fixed in the lightning GitHub repo - see scikit-learn-contrib/lightning#142). We can revert this small change if there is a new PyPI release.
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