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There are two ways to reproduce the error.
Both case shows the same error message.
## FIRST WAY ##
docker run -ti --shm-size 5g --rm nvcr.io/nvidia/tensorflow:22.09-tf1-py3 bash
git clone https://github.com/NVIDIA/FasterTransformer.git
mkdir -p FasterTransformer/build
cd FasterTransformer/build
git submodule init && git submodule update
pip install torch
cmake -DSM=80 -DCMAKE_BUILD_TYPE=Release -DBUILD_PYT=ON -DBUILD_MULTI_GPU=ON ..
make -j12
## SECOND WAY ##
docker run -it -d --name=test --privileged --gpus all --cap-add=ALL --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 --net=host --ipc=host -v ${HOME}:${HOME} -v /dev:/dev -v /lib/modules:/lib/modules -v /raid:/raid nvcr.io/nvidia/tensorflow:22.09-tf1-py3 bash
git clone https://github.com/NVIDIA/FasterTransformer.git
mkdir -p FasterTransformer/build
cd FasterTransformer/build
git submodule init && git submodule update
cmake -DSM=80 -DCMAKE_BUILD_TYPE=Release -DBUILD_PYT=ON -DBUILD_MULTI_GPU=ON ..
make -j12
Then you can get the below error.
error C++17 or later compatible compiler is required to use PyTorch.
The text was updated successfully, but these errors were encountered:
Branch/Tag/Commit
main
Docker Image Version
nvcr.io/nvidia/tensorflow:22.09-tf1-py3
GPU name
A100
CUDA Driver
510.47.03
Reproduced Steps
The text was updated successfully, but these errors were encountered: