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Add onnxruntime nightly build to CI (#284)
* update svm converter test case failures to account for versioning on nightly ort builds * 2 new nightly linux and win32 pipelines with onnxruntime nightly builds
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‎.azure-pipelines/linux-CI-nightly.yml‎

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# Python package
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# Create and test a Python package on multiple Python versions.
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# Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more:
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# https://docs.microsoft.com/azure/devops/pipelines/languages/python
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trigger:
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- master
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jobs:
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- job: 'Test'
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pool:
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vmImage: 'Ubuntu-16.04'
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strategy:
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matrix:
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Python36-nightly:
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python.version: '3.6'
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ONNX_PATH: onnx==1.4.1
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ORT_PATH: -i https://test.pypi.org/simple/ ort-nightly
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maxParallel: 3
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steps:
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- task: CondaEnvironment@1
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inputs:
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createCustomEnvironment: true
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environmentName: 'py$(python.version)'
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packageSpecs: 'python=$(python.version)'
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- script: |
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python -m pip install --upgrade pip
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conda config --set always_yes yes --set changeps1 no
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conda install -c conda-forge protobuf
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conda install -c conda-forge numpy
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conda install -c conda-forge cmake
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pip install $(ONNX_PATH)
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pip install -r requirements.txt
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cd onnxutils
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pip install -e .
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cd ..
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pip install -r requirements-dev.txt
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pip install $(ORT_PATH)
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pip install pytest
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git clone --recursive https://github.com/cjlin1/libsvm libsvm
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cd libsvm
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make lib
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displayName: 'Install dependencies'
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- script: |
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export PYTHONPATH=$PYTHONPATH:libsvm/python
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python -c "import svmutil"
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python -c "import onnxconverter_common"
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test '$(python.version)' != '2.7' && python -c "import onnxruntime"
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pytest tests --doctest-modules --junitxml=junit/test-results.xml
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displayName: 'pytest - onnxmltools'
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- script: |
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export PYTHONPATH=$PYTHONPATH:libsvm/python
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python -c "import onnxconverter_common"
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pytest onnxutils/tests --doctest-modules --junitxml=junit/test-results-onnxutils.xml
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displayName: 'pytest - onnxutils'
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- task: PublishTestResults@2
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inputs:
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testResultsFiles: '**/test-results.xml'
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testRunTitle: 'Python $(python.version)'
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condition: succeededOrFailed()

‎.azure-pipelines/win32-CI-nightly.yml‎

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# Python package
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# Create and test a Python package on multiple Python versions.
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# Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more:
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# https://docs.microsoft.com/azure/devops/pipelines/languages/python
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trigger:
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- master
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jobs:
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- job: 'Test'
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pool:
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vmImage: 'vs2017-win2016'
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strategy:
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matrix:
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Python36-nightly:
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python.version: '3.6'
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ONNX_PATH: onnx==1.4.1
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ONNXRT_PATH: -i https://test.pypi.org/simple/ ort-nightly
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COREML_PATH: git+https://github.com/apple/coremltools
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maxParallel: 3
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steps:
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- task: UsePythonVersion@0
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inputs:
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versionSpec: '$(python.version)'
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architecture: 'x64'
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- powershell: Write-Host "##vso[task.prependpath]$env:CONDA\Scripts"
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displayName: Add conda to PATH
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- script: conda create --yes --quiet --name py$(python.version) -c conda-forge python=$(python.version) numpy protobuf
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displayName: Create Anaconda environment
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- script: |
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call activate py$(python.version)
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python -m pip install --upgrade pip numpy
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echo Test numpy installation... && python -c "import numpy"
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pip install %COREML_PATH% %ONNX_PATH%
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cd onnxutils
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pip install -e .
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echo Test onnxconverter-common installation... && python -c "import onnxconverter_common"
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cd ..
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pip install -r requirements-dev.txt
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pip install %ONNXRT_PATH%
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echo Test onnxruntime installation... && python -c "import onnxruntime"
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REM install libsvm from github
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git clone --recursive https://github.com/cjlin1/libsvm libsvm
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copy libsvm\windows\*.dll libsvm\python
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set PYTHONPATH=libsvm\python;%PYTHONPATH%
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dir libsvm\python
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echo Test libsvm installation... && python -c "import svmutil"
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displayName: 'Install dependencies'
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- script: |
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call activate py$(python.version)
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set PYTHONPATH=libsvm\python;%PYTHONPATH%
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pip install -e .
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pytest tests --doctest-modules --junitxml=junit/test-results.xml
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displayName: 'pytest - onnxmltools'
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- script: |
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call activate py$(python.version)
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set PYTHONPATH=libsvm\python;%PYTHONPATH%
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pytest onnxutils/tests --doctest-modules --junitxml=junit/test-results-onnxutils.xml
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displayName: 'pytest - onnxutils'
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- task: PublishTestResults@2
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inputs:
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testResultsFiles: '**/test-results.xml'
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testRunTitle: 'Python $(python.version)'
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condition: succeededOrFailed()

‎tests/svmlib/test_SVMConverters.py‎

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# known svm runtime dimension error in ONNX Runtime 0.3.0
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dump_data_and_model(X[:5].astype(numpy.float32), SkAPICl(libsvm_model), node,
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basename="LibSvmSvmcLinearRaw-Dec3", verbose=False,
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allow_failure="StrictVersion(onnxruntime.__version__) <= StrictVersion('0.3.0')")
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allow_failure="StrictVersion(onnxruntime.__version__) < StrictVersion('0.4.0')")
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def test_convert_svmc_raw(self):
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iris = load_iris()
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self.assertTrue(node is not None)
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dump_data_and_model(X[:5].astype(numpy.float32), SkAPICl(libsvm_model), node,
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basename="LibSvmSvmcRaw",
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allow_failure="StrictVersion(onnxruntime.__version__) <= StrictVersion('0.3.0')")
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allow_failure="StrictVersion(onnxruntime.__version__) < StrictVersion('0.4.0')")
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@unittest.skip(reason="libsvm crashes.")
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def test_convert_nusvmc_linear_raw(self):

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