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

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

@@ -0,0 +1,66 @@
+# Python package
+# Create and test a Python package on multiple Python versions.
+# Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more:
+# https://docs.microsoft.com/azure/devops/pipelines/languages/python
+
+trigger:
+- master
+
+jobs:
+
+- job: 'Test'
+  pool:
+    vmImage: 'Ubuntu-16.04'
+  strategy:
+    matrix:
+      Python36-nightly:
+        python.version: '3.6'
+        ONNX_PATH: onnx==1.4.1
+        ORT_PATH: -i https://test.pypi.org/simple/ ort-nightly
+    maxParallel: 3
+
+  steps:
+  - task: CondaEnvironment@1
+    inputs:
+      createCustomEnvironment: true
+      environmentName: 'py$(python.version)'
+      packageSpecs: 'python=$(python.version)'
+
+  - script: |
+      python -m pip install --upgrade pip
+      conda config --set always_yes yes --set changeps1 no
+      conda install -c conda-forge protobuf
+      conda install -c conda-forge numpy
+      conda install -c conda-forge cmake
+      pip install $(ONNX_PATH)
+      pip install -r requirements.txt
+      cd onnxutils
+      pip install -e .
+      cd ..
+      pip install -r requirements-dev.txt
+      pip install $(ORT_PATH)
+      pip install pytest
+      git clone --recursive https://github.com/cjlin1/libsvm libsvm
+      cd libsvm
+      make lib
+    displayName: 'Install dependencies'
+
+  - script: |
+      export PYTHONPATH=$PYTHONPATH:libsvm/python
+      python -c "import svmutil"
+      python -c "import onnxconverter_common"
+      test '$(python.version)' != '2.7' && python -c "import onnxruntime"
+      pytest tests --doctest-modules --junitxml=junit/test-results.xml
+    displayName: 'pytest - onnxmltools'
+
+  - script: |
+      export PYTHONPATH=$PYTHONPATH:libsvm/python
+      python -c "import onnxconverter_common"
+      pytest onnxutils/tests --doctest-modules --junitxml=junit/test-results-onnxutils.xml
+    displayName: 'pytest - onnxutils'
+
+  - task: PublishTestResults@2
+    inputs:
+      testResultsFiles: '**/test-results.xml'
+      testRunTitle: 'Python $(python.version)'
+    condition: succeededOrFailed()

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

@@ -0,0 +1,72 @@
+# Python package
+# Create and test a Python package on multiple Python versions.
+# Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more:
+# https://docs.microsoft.com/azure/devops/pipelines/languages/python
+
+trigger:
+- master
+
+jobs:
+
+- job: 'Test'
+  pool:
+    vmImage: 'vs2017-win2016'
+  strategy:
+    matrix:
+      Python36-nightly:
+        python.version: '3.6'
+        ONNX_PATH: onnx==1.4.1
+        ONNXRT_PATH: -i https://test.pypi.org/simple/ ort-nightly
+        COREML_PATH: git+https://github.com/apple/coremltools
+    maxParallel: 3
+
+  steps:
+  - task: UsePythonVersion@0
+    inputs:
+      versionSpec: '$(python.version)'
+      architecture: 'x64'
+
+  - powershell: Write-Host "##vso[task.prependpath]$env:CONDA\Scripts"
+    displayName: Add conda to PATH
+
+  - script: conda create --yes --quiet --name py$(python.version) -c conda-forge python=$(python.version) numpy protobuf
+    displayName: Create Anaconda environment
+
+  - script: |
+      call activate py$(python.version)
+      python -m pip install --upgrade pip numpy
+      echo Test numpy installation... && python -c "import numpy"
+      pip install %COREML_PATH% %ONNX_PATH%
+      cd onnxutils
+      pip install -e .
+      echo Test onnxconverter-common installation... && python -c "import onnxconverter_common"
+      cd ..
+      pip install -r requirements-dev.txt
+      pip install %ONNXRT_PATH%
+      echo Test onnxruntime installation... && python -c "import onnxruntime"
+      REM install libsvm from github
+      git clone --recursive https://github.com/cjlin1/libsvm libsvm
+      copy libsvm\windows\*.dll libsvm\python
+      set PYTHONPATH=libsvm\python;%PYTHONPATH%
+      dir libsvm\python
+      echo Test libsvm installation... && python -c "import svmutil"
+    displayName: 'Install dependencies'
+
+  - script: |
+      call activate py$(python.version)
+      set PYTHONPATH=libsvm\python;%PYTHONPATH%
+      pip install -e .
+      pytest tests --doctest-modules --junitxml=junit/test-results.xml
+    displayName: 'pytest - onnxmltools'
+
+  - script: |
+      call activate py$(python.version)
+      set PYTHONPATH=libsvm\python;%PYTHONPATH%
+      pytest onnxutils/tests --doctest-modules --junitxml=junit/test-results-onnxutils.xml
+    displayName: 'pytest - onnxutils'
+
+  - task: PublishTestResults@2
+    inputs:
+      testResultsFiles: '**/test-results.xml'
+      testRunTitle: 'Python $(python.version)'
+    condition: succeededOrFailed()

tests/svmlib/test_SVMConverters.py

@@ -261,7 +261,7 @@ def test_convert_svmc_linear_raw(self):
         # known svm runtime dimension error in ONNX Runtime 0.3.0
         dump_data_and_model(X[:5].astype(numpy.float32), SkAPICl(libsvm_model), node,
                             basename="LibSvmSvmcLinearRaw-Dec3", verbose=False,
-                            allow_failure="StrictVersion(onnxruntime.__version__) <= StrictVersion('0.3.0')")
+                            allow_failure="StrictVersion(onnxruntime.__version__) < StrictVersion('0.4.0')")
 
     def test_convert_svmc_raw(self):
         iris = load_iris()
@@ -287,7 +287,7 @@ def test_convert_svmc_raw(self):
         self.assertTrue(node is not None)
         dump_data_and_model(X[:5].astype(numpy.float32), SkAPICl(libsvm_model), node,
                             basename="LibSvmSvmcRaw",
-                            allow_failure="StrictVersion(onnxruntime.__version__) <= StrictVersion('0.3.0')")
+                            allow_failure="StrictVersion(onnxruntime.__version__) < StrictVersion('0.4.0')")
 
     @unittest.skip(reason="libsvm crashes.")
     def test_convert_nusvmc_linear_raw(self):