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azure-pipelines-4.yml
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azure-pipelines-4.yml
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# Starter pipeline
# Start with a minimal pipeline that you can customize to build and deploy your code.
# Add steps that build, run tests, deploy, and more:
# https://aka.ms/yaml
trigger:
- main
pool: wenjiao-test
stages:
- stage: pylint
jobs:
- job: pylint_test
steps:
- task: Bash@3
inputs:
targetType: "inline"
script: |
pip install pylint==2.12.1
pip install intel-tensorflow
# python -m pylint -f json --disable=R,C,W,E1129 --enable=line-too-long --max-line-length=120 --extension-pkg-whitelist=numpy --ignored-classes=TensorProto,NodeProto --ignored-modules=tensorflow,torch,torch.quantization,torch.tensor,torchvision,mxnet,onnx,onnxruntime ./neural_compressor > ${WORKSPACE}/lpot-pylint.json
# exit_code=$?
# if [ ${exit_code} -ne 0 ] ; then
# echo "PyLint exited with non-zero exit code."; exit 1
# fi
# exit 0
- stage: bandit
jobs:
- job: bandit_test
steps:
- task: Bash@3
inputs:
targetType: "inline"
script: |
pip install bandit
# python -m bandit -r -lll -iii neural_compressor > ${WORKSPACE}/lpot-bandit.log
# exit_code=$?
# if [ ${exit_code} -ne 0 ] ; then
# echo "Bandit exited with non-zero exit code."; exit 1
# fi
# exit 0
- stage: pyspelling
jobs:
- job: pyspelling_test
steps:
- task: Bash@3
inputs:
targetType: "inline"
script: |
pip install pyspelling
# Update paths to validation and lpot repositories
VAL_REPO=${WORKSPACE}
sed -i "s|\${VAL_REPO}|$VAL_REPO|g" ${VAL_REPO}/pyspelling_conf.yaml
sed -i "s|\${LPOT_REPO}|$REPO_DIR|g" ${VAL_REPO}/pyspelling_conf.yaml
echo "Modified config:"
cat ${VAL_REPO}/pyspelling_conf.yaml
# pyspelling -c ${VAL_REPO}/pyspelling_conf.yaml > ${WORKSPACE}/pyspelling_output.log
# exit_code=$?
# if [ ${exit_code} -ne 0 ] ; then
# echo "Pyspelling exited with non-zero exit code."; exit 1
# fi
# exit 0