samgis-lisa-on-zero / scripts /entrypoint.sh
alessandro trinca tornidor
[feat] prepare entire docker build with nvidia GPU on hf space cloning https://huggingface.co/spaces/aletrn/samgis
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#!/usr/bin/env bash
WORKDIR="/var/task"
XDG_CACHE_HOME="/data"
MPLCONFIGDIR=${XDG_CACHE_HOME}/.cache/matplotlib
TRANSFORMERS_CACHE=${XDG_CACHE_HOME}/.cache/transformers
FASTAPI_STATIC=${XDG_CACHE_HOME}/static
ls -ld ${XDG_CACHE_HOME}/
ls -l ${XDG_CACHE_HOME}/
mkdir -p ${XDG_CACHE_HOME}/.cache
chmod 770 -R ${XDG_CACHE_HOME}/.cache
mkdir -p ${MPLCONFIGDIR}
mkdir -p ${TRANSFORMERS_CACHE}
mkdir -p ${FASTAPI_STATIC}
chmod 770 -R ${FASTAPI_STATIC}
ls -ld ${XDG_CACHE_HOME}/
ls -l ${XDG_CACHE_HOME}/
export WORKDIR
export XDG_CACHE_HOME
export MPLCONFIGDIR
export TRANSFORMERS_CACHE
export FASTAPI_STATIC
source ${WORKDIR}/venv/bin/activate
which python
python --version
free -m
which nvcc
nvcc -V
which nvidia-smi
nvidia-smi
pip list
which uvicorn
ls -l ${WORKDIR}/venv/bin/uvicorn
df -h / /data /home /var/task
echo "WORKDIR - /var/task"
ls -l ${WORKDIR}
echo "XDG_CACHE_HOME - /data"
find ${XDG_CACHE_HOME}
CUDA_VISIBLE_DEVICES=$(nvidia-smi --query-gpu=memory.free,index --format=csv,nounits,noheader | sort -nr | head -1 | awk '{ print $NF }')
echo "calculated CUDA_VISIBLE_DEVICES env variable: ${CUDA_VISIBLE_DEVICES}."
export CUDA_VISIBLE_DEVICES
echo "running command 'uvicorn wrappers.fastapi_wrapper:app --host 0.0.0.0 --port 7860'..."
uvicorn wrappers.fastapi_wrapper:app --host 0.0.0.0 --port 7860
exit 0