Azure CI: Enable nGaph ONNX check (#2631)
* GitHub CI: Add nGraph ONNX check
* Fix job name
* Fix commands
* Enable nGraph Docker
* Fix
* Fix
* Fix
* Remove Actions
* Decrease a number of workers for executing models tests
* Enable "Docker run tests"
* Unset parallel execution
* Add cloning models
* Update model_zoo_preprocess.sh cmd
* Fix model_zoo_preprocess.sh cmd
* Add share
* ls -alR /mnt/onnxtestdata
* Change path
* move clone models
* Update script
* Add wget
* Update
* Update to master
* Update
* Update
* clone into tmp
* Enable clone
* Fix
* Use model_zoo_preprocess
* Add copy to share
* Enable tests
* Get MSFT
* Run tests
* Try 16 cores
* rub tests
* list models
* run tests
* Run tests, no --model_zoo_xfail
* Run tests, -n 8
* Run tests, -n 1
* Run tests, -n 4
* Run tests, -n 2
* Run with -n 1
* Update info
* First try to run onnx ci:
* disable MSFT models for first try,
* try to align onnx_models
* Enable steps
* Update cmake
* Add destination for cmake build
* Try to fix cmake build
* set ninja and instal dependencies
* Revert changes from Blaczkowski, Rafal
* Add swapfile 15 GB, run on AMD CPU 16 cores, 64 GB RAM
* Enable model_zoo_preprocess.sh
* Add reference-if-able
* Update
* test_zoo_models.py -n 8
* Fix clone
* Set LIN_VMSS_VENV_EPHEMERAL_WU2, F8s_v2
* git clone --single-branch
* test_zoo_models.py -n 6, D16as_v4
* -n 4
* clean
* -n 2
* -n 4, swap 48 GB
* E16ds_v4 (16-128), -n 8
* -n 8
* Set LIN_VMSS_VENV_ONNX_WU2
* -n 4
* del -n 16 for ut
Co-authored-by: rblaczko <rafal.blaczkowski@intel.com>
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