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run.sh
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run.sh
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#!/bin/bash
docker_gpu=0
docker_egs=
docker_folders=
docker_cuda=10.1
docker_env=
docker_cmd=
docker_os=u18
is_root=false
is_local=false
is_egs2=false
while test $# -gt 0
do
case "$1" in
-h) echo "Usage: `basename $0` [-h] docker_gpu docker_egs docker_folders options"
exit 0;;
--help) echo "Usage: `basename $0` [-h] ] docker_gpu docker_egs docker_folders options"
exit 0;;
--docker*) ext=${1#--}
ext=${ext//-/_}
frombreak=true
for i in _ {a..z} {A..Z}; do
for var in `eval echo "\\${!${i}@}"`; do
if [ "$var" == "$ext" ]; then
eval ${ext}=$2
frombreak=false
shift
break 2
fi
done
done
if ${frombreak} ; then
echo "bad option $1"
exit 1
fi
;;
--is*) ext=${1#--}
ext=${ext//-/_}
frombreak=true
for i in _ {a..z} {A..Z}; do
for var in `eval echo "\\${!${i}@}"`; do
if [ "$var" == "$ext" ]; then
eval ${ext}=true
frombreak=false
break 2
fi
done
done
if ${frombreak} ; then
echo "bad option $1"
exit 1
fi
;;
--*) break
;;
esac
shift
done
if [ -z "${docker_egs}" ]; then
echo "Select an example to work with from the egs folder by setting --docker-egs."
exit 1
fi
from_tag="cpu"
if [ ! "${docker_gpu}" == "-1" ]; then
if [ -z "${docker_cuda}" ]; then
# If the docker_cuda is not set, the program will automatically
# search the installed version with default configurations (apt)
docker_cuda=$( nvcc -V | grep release )
docker_cuda=${docker_cuda#*"release "}
docker_cuda=${docker_cuda%,*}
fi
# After search for your cuda version, if the variable docker_cuda is empty the program will raise an error
if [ -z "${docker_cuda}" ]; then
echo "CUDA was not found in your system. Use CPU image or install NVIDIA-DOCKER, CUDA and NVCC for GPU image."
exit 1
else
from_tag="gpu-cuda${docker_cuda}-cudnn7"
fi
fi
if [ ! -z "${docker_os}" ]; then
from_tag="${from_tag}-${docker_os}"
fi
if [ ${is_local} = true ]; then
from_tag="${from_tag}-local"
fi
# Check if image exists in the system and download if required
docker_image=$( docker images -q espnet/espnet:${from_tag} )
if ! [[ -n ${docker_image} ]]; then
if [ ${is_local} = true ]; then
echo "!!! Warning: You need first to build the container using ./build.sh local <cuda_ver>."
exit 1
else
docker pull espnet/espnet:${from_tag}
fi
fi
if [ ${UID} -eq 0 ] && [ ${is_root} = false ]; then
echo "Warning: Your user ID belongs to root users.
Using Docker container with root instead of User-built container."
is_root=true
fi
if [ ${is_root} = false ]; then
# Build a container with the user account
container_tag="${from_tag}-user-${HOME##*/}"
docker_image=$( docker images -q espnet/espnet:${container_tag} )
if ! [[ -n ${docker_image} ]]; then
echo "Building docker image..."
build_args="--build-arg FROM_TAG=${from_tag}"
build_args="${build_args} --build-arg THIS_USER=${HOME##*/}"
build_args="${build_args} --build-arg THIS_UID=${UID}"
echo "Now running docker build ${build_args} -f prebuilt/Dockerfile -t espnet/espnet:${container_tag} ."
(docker build ${build_args} -f prebuilt/Dockerfile -t espnet/espnet:${container_tag} .) || exit 1
fi
else
container_tag=${from_tag}
fi
echo "Using image espnet/espnet:${container_tag}."
this_time="$(date '+%Y%m%dT%H%M')"
if [ "${docker_gpu}" == "-1" ]; then
cmd0="docker run "
container_name="espnet_cpu_${this_time}"
else
# --rm erase the container when the training is finished.
if [ -z "$( which nvidia-docker )" ]; then
# we assume that you already installed nvidia-docker 2
cmd0="docker run --gpus '\"device=${docker_gpu}\"'"
else
cmd0="NV_GPU='${docker_gpu}' nvidia-docker run "
fi
container_name="espnet_gpu${docker_gpu//,/_}_${this_time}"
fi
cd ..
vols="-v ${PWD}/egs:/espnet/egs
-v ${PWD}/espnet:/espnet/espnet
-v ${PWD}/test:/espnet/test
-v ${PWD}/utils:/espnet/utils"
in_egs=egs
if [ ${is_egs2} = true ]; then
vols="${vols} -v ${PWD}/egs2:/espnet/egs2
-v ${PWD}/espnet2:/espnet/espnet2
-v /dev/shm:/dev/shm"
in_egs=egs2
fi
if [ ! -z "${docker_folders}" ]; then
docker_folders=$(echo ${docker_folders} | tr "," "\n")
for i in ${docker_folders[@]}
do
vols=${vols}" -v $i:$i";
done
fi
cmd1="cd /espnet/${in_egs}/${docker_egs}"
if [ ! -z "${docker_cmd}" ]; then
cmd2="./${docker_cmd} $@"
else
cmd2="./run.sh $@"
fi
if [ ${is_root} = true ]; then
# Required to access to the folder once the training if finished in root access
cmd2="${cmd2}; chmod -R 777 /espnet/${in_egs}/${docker_egs}"
fi
cmd="${cmd1}; ${cmd2}"
this_env=""
if [ ! -z "${docker_env}" ]; then
docker_env=$(echo ${docker_env} | tr "," "\n")
for i in ${docker_env[@]}
do
this_env="-e $i ${this_env}"
done
fi
if [ ! -z "${HTTP_PROXY}" ]; then
this_env="${this_env} -e 'HTTP_PROXY=${HTTP_PROXY}'"
fi
if [ ! -z "${http_proxy}" ]; then
this_env="${this_env} -e 'http_proxy=${http_proxy}'"
fi
cmd="${cmd0} -i --rm ${this_env} --name ${container_name} ${vols} espnet/espnet:${container_tag} /bin/bash -c '${cmd}'"
trap ctrl_c INT
function ctrl_c() {
echo "** Kill docker container ${container_name}"
docker rm -f ${container_name}
}
echo "Executing application in Docker"
echo ${cmd}
eval ${cmd} &
PROC_ID=$!
while kill -0 "$PROC_ID" 2> /dev/null; do
sleep 1
done
echo "`basename $0` done."