sandeepb2013

Hi @wphicks, thanks for your quick response. sorry for the late reply... ------------------------- ### For model generation and saving. --------------------------- # Import required libraries import numpy from numpy import loadtxt...

For building the docker image : https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/customization_guide/build.html

Hi @wphicks, Using Build script (https://github.com/triton-inference-server/fil_backend/blob/main/docs/build.md) able to built 2 docker images ---------------------------------------- REPOSITORY TAG IMAGE ID CREATED SIZE localhost/triton_fil latest 8fdf060142f9 3 weeks ago 12.4 GB -------------------------------------------- after running...

Hi @wphicks , any further pointers would really help. thanks in advance..

when i looked into further other backend(pytorch) could be the reason for LLVM issue. However i'm more interested trying out the FI backend and i kept only FIL backend in...

Do we have any specific minimal memory requirement for FIl backend to start?.. Thanks

root@lees1:~/work/fil_backend# docker run --rm --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 -p 8000:8000 -p 8001:8001 -p 8002:8002 -v /root/work/fil_backend/models:/models --name tritonserver nvcr.io/nvidia/tritonserver:23.08-py3 tritonserver --model-repository=/models """ ============================= == Triton Inference Server == =============================...

=========config.pbtxt============ name: "fil" # Name of the model directory (fil in our case) backend: "fil" # Triton FIL backend for deploying forest models max_batch_size: 8192 input [ { name: "input__0"...

root@lees1:~/work/fil_backend# docker run --rm --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 -p 8000:8000 -p 8001:8001 -p 8002:8002 -v /root/work/fil_backend/models:/models --name tritonserver fil_23 tritonserver --model-repository=/models ============================= == Triton Inference Server == ============================= NVIDIA...