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[Build] Cuda Execution Provider library is needed despite we only use TensoRT Execution provider #22960
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onnxruntime/cmake/CMakeLists.txt Line 90 in b930b4a
Add this to your build command line |
thank you ! (I could not find it in build.py) |
unfortunately this does not work , there is still cuda dependencies that caused compilation errors |
same for |
@gedoensmax is this expected? Not sure if there are other build settings required to use onnxruntime_CUDA_MINIMAL |
The cmake variable you mention Scott prunes all the dependencies from CUDA and makes the CUDA EP lib very small. Essentially it will only be able to execute memory copies and stresm management. This build scenario is also published at: https://github.com/NVIDIA/onnxruntime/releases |
This issue has been automatically marked as stale due to inactivity and will be closed in 30 days if no further activity occurs. If further support is needed, please provide an update and/or more details. |
tried again , but got onnxrt compilation failure using TRT 10.7.23 Cudnn 9.6.0.74, ONNXRT 1.20.1 with gcc11
-- ******** Summary ********
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Describe the issue
There must be a way to build onnxruntime with tensorRt without the cuda execution provider and its cuda unused dependencies.
libonnxruntime_providers_cuda.so is big (220MB) and is dragging other big dependencies like libcufft or libcublas that we don't use in inference (another 400MB).
Urgency
non blocking
Target platform
linux
Build script
build.py
Error / output
N/A
Visual Studio Version
N/A
GCC / Compiler Version
gcc11
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