1. Publish the image ACR, instead of building it every time for every PR
2. Make USE_MKLML and USE_OPENMP be able to co-exist. Currently both of them are enabled in our Linux CI build but indeed only one of them is taking effect.
3. Split nuphar and DNNL to separated pipelines.
4. Fix two warnings in onnxruntime/core/optimizer/matmul_scale_fusion.cc and onnxruntime/test/tvm/tvm_basic_test.cc.
5. Update the manylinux2010_x86_64 image to the latest.
1. Increase job timeout, while we are investigating why the tests take much longer
2. Upgrade the linux docker image to manylinux2010, by request from Tianlei. (We had an offline discussion with Pranav and Tracy)
3. Remove the installation of "devtoolset-7" in the CUDA image. It was added for CUDA 10.0, it is not needed for CUDA 10.1. We have moved to CUDA 10.1.
Use CUDA 10.1 for Linux build
(Windows change is already in)
Please note, cublas 10.2.1.243 is for CUDA SDK 10.1.243, not CUDA 10.2.x. CUDA 10.2.89 need cublas 10.2.2.89. They match on the last part of the digits.
libcublas10-10.1.0.105 won't work!!!
The cuda docker image by viswamy is already using 10.1, no need to change.
* Update cuda for python wheels
* Update cuda for python wheels
* Update cuda for python wheels
* Update azure-pipelines-py-packaging.yml
* Update to cuda 10
* Only test win gpu
* Update cuda for python wheels
* Use manylinux2010 image to build linux python wheels
Allow wheels built to truly be compliant with a manylinux policy
