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1. Fix training e2e pipeline. The failure was caused by my recent change #7632. The fix is adding "--cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=70" to the build parameters because the machines are with V100 GPUs. 2. Simplify Nuphar pipeline. It doesn't need to install a separated ONNX version(1.5.0) 3. Fix a problem that run_dockerbuild.sh ignored OS version parameter. Now because it starts to take effect, I also set python version to the system default one(3.8 for ubuntu 20.04) |
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| .. | ||
| build_scripts | ||
| scripts | ||
| cuda_manylinux2010.repo | ||
| cuda_manylinux2014.repo | ||
| Dockerfile.arm_yocto | ||
| Dockerfile.manylinux2014_cpu | ||
| Dockerfile.manylinux2014_cuda11 | ||
| Dockerfile.manylinux2014_cuda11_1_tensorrt7_2 | ||
| Dockerfile.manylinux2014_cuda11_tensorrt7_2 | ||
| Dockerfile.manylinux2014_rocm | ||
| Dockerfile.manylinux2014_training_cuda10_2 | ||
| Dockerfile.manylinux2014_training_cuda11_1 | ||
| Dockerfile.ubuntu | ||
| Dockerfile.ubuntu_for_android | ||
| Dockerfile.ubuntu_for_arm | ||
| Dockerfile.ubuntu_gpu_training | ||
| Dockerfile.ubuntu_openvino | ||
| Dockerfile.ubuntu_server | ||
| Dockerfile.ubuntu_tensorrt | ||
| manylinux-entrypoint | ||