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export MODEL_PATH=/tmp/tensorrt-inference-server
/opt/tritonserver/bin/tritonserver --strict-model-config=false --model-store=$MODEL_PATH/docs/examples/model_repository 2>&1 | tee $MODEL_PATH/svrStatus.txt
the server fails with:
I1130 21:40:16.147155 3120 server.cc:267] Timeout 29: Found 0 live models and 0 in-flight non-inference requests
error: creating server: Internal - failed to load all models
The densenet_onnx model fails to load with:
| densenet_onnx | 1 | UNAVAILABLE: Internal: onnx runtime error 1: /workspace/onnxruntime/onnxruntime/core/platform/posix/env.cc:173 onnxruntime::{anonymous}::PosixThread::PosixThread(const char*, int, unsigned int (*)(int, Eigen::ThreadPoolInterface*), Eigen::ThreadPoolInterface*, const onnxruntime::ThreadOptions&) pthread_setaffinity_np failed, error code: 2 error msg: No such file or directory |
The container has has a restricted cpuset which likely contributes to the above failure:
cat /sys/fs/cgroup/cpuset/cpuset.cpus
9-12,49-52
The tritonserver works fine on another container whose cpuset looks like this:
cat /sys/fs/cgroup/cpuset/cpuset.cpus
0-255
Likely the onnxruntime threadoptions affinity setting has to match the cpuset.
Triton Information
What version of Triton are you using?
2.15.0
Are you using the Triton container or did you build it yourself?
using the nvidia ngc container tritonserver:21.10-py3
To Reproduce
Run the tritonserver container with a restricted cpuset.
Inside container:
MODEL_PATH=/tmp/tensorrt-inference-server
git clone https://github.com/NVIDIA/tensorrt-inference-server.git
cd ${MODEL_PATH}/docs/examples/
bash fetch_models.sh
/opt/tritonserver/bin/tritonserver --strict-model-config=false --model-store=$MODEL_PATH/docs/examples/model_repository 2>&1 | tee $MODEL_PATH/svrStatus.txt
Expected behavior
there should be no failure to load the densenet_onnx model.
The text was updated successfully, but these errors were encountered:
Description
I am testing tritonserver on the example models fetched using this script:
https://github.com/triton-inference-server/server/blob/main/docs/examples/fetch_models.sh
triton server is run as follows:
the server fails with:
The densenet_onnx model fails to load with:
The container has has a restricted cpuset which likely contributes to the above failure:
The tritonserver works fine on another container whose cpuset looks like this:
Likely the onnxruntime threadoptions affinity setting has to match the cpuset.
Triton Information
What version of Triton are you using?
2.15.0
Are you using the Triton container or did you build it yourself?
using the nvidia ngc container tritonserver:21.10-py3
To Reproduce
Run the tritonserver container with a restricted cpuset.
Inside container:
Expected behavior
there should be no failure to load the densenet_onnx model.
The text was updated successfully, but these errors were encountered: