Creating custom python backend environment

After creating a the triton custom environment using the steps listed below we get:

triton_python_backend_stub: ../nptl/pthread_mutex_lock.c:81: __pthread_mutex_lock: Assertion `mutex->__data.__owner == 0' failed.

Steps we took to create custom triton environment

1. First we installed conda and created and environment called python-3-8
2. We then installed numpy as required in the documentation along with our custom packages listed below:

apt-get update
apt-get -y install libgl1
apt-get install -yq libgtk2.0-dev
pip3 install torch==1.9.1+cpu torchvision==0.10.1+cpu torchaudio==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
pip install detectron2 -f https://dl.fbaipublicfiles.com/detectron2/wheels/cpu/torch1.9/index.html
pip install opencv-python==4.5.2.52

We also set the PYTHONNOUSERSITE environment variables as requested: export PYTHONNOUSERSITE=True

1. We installed CMAKE and cuda-toolkit-11

install cmake and cuda

apt-get update
apt-get install -y apt-transport-https ca-certificates gnupg software-properties-common wget
wget -O -https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | apt-key add -

apt-add-repository 'debhttps://apt.kitware.com/ubuntu/ bionic main'
apt-get update
apt-get install -y cmake
##install rapidjson and libarchive
apt-get install -y rapidjson-dev libarchive-dev

apt-key adv --fetch-keys  http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub

bash -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/cuda.list'

apt update
apt install cuda-toolkit-11-0

1. We set the CUDA directory on our environment to the correct path: cmake -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-11.0 ..

2. we make the directory and create the custom backend stub

git clone https://github.com/triton-inference-server/python_backend -b r21.09
cd r21.09
mkdir build && cd build
cmake -DTRITON_ENABLE_GPU=ON -DCMAKE_INSTALL_PREFIX:PATH=pwd/install ..
make triton-python-backend-stub

1. We then uploaded the triton_backend_stub file to the model directory on our GCS bucket.
2. after this we used conda-pack to pack out environment and then uploaded it to our detectron2 model directory on our GCS bucket

Triton Information Triton Version 21.09 Model: Detectron2

[arshiamalek]

@Tabrizian This is the complete steps we took to create out environment

[Tabrizian]

Closing due to in-activity. Feel free to re-open if the issue persists.