!13361 [MSLITE][TOD] ci tests for version 1.2
From: @yonibaehr_admin Reviewed-by: Signed-off-by:pull/13361/MERGE
mindspore-ci-bot
4 years ago
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Gitee
commit
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@ -1,22 +1,14 @@
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#
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mini_alexnet_r1.1
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mobilenetv1_r1.1
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mobilenetv2_r1.1
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lenet_r1.1
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effnet_r1.1
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effnet_tune_r1.1
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googlenet_r1.1
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# mini_alexnet
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# nin
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# lenet
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# mobilenetv1
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# mobilenetv2
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# mobilenetv3
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# effnet
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# resnet
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# effnet_tune
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# googlenet
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# densenet
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# shufflenetv2
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# xception
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mini_alexnet
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#nin
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lenet
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mobilenetv1
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mobilenetv2
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mobilenetv3
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effnet
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resnet
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effnet_tune
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googlenet
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densenet
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shufflenetv2
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#xception
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# LAST
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@ -1,91 +0,0 @@
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#!/bin/bash
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# Print start msg after run testcase
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function MS_PRINT_TESTCASE_END_MSG() {
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echo -e "-----------------------------------------------------------------------------------------------------------------------------------"
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}
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function Print_Result() {
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MS_PRINT_TESTCASE_END_MSG
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while read line; do
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arr=("${line}")
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printf "%-15s %-20s %-90s %-7s\n" ${arr[0]} ${arr[1]} ${arr[2]} ${arr[3]}
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done < $1
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MS_PRINT_TESTCASE_END_MSG
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}
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basepath=$(pwd)
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echo ${basepath}
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# Set models default config filepath
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models_mindspore_train_config=${basepath}/models_ms_train.cfg
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# Example:run_net_export.sh -m /home/emir/Work/TestingEnv/train_models
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epoch_num=1
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while getopts "c:m:t:" opt; do
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case ${opt} in
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c)
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models_mindspore_train_config=${OPTARG}
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echo "models_mindspore_train_config is ${models_mindspore_train_config}"
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;;
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m)
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models_path=${OPTARG}"/models_train"
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echo "models_path is ${OPTARG}"
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;;
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t)
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epoch_num=${OPTARG}
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echo "train epoch num is ${OPTARG}"
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;;
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?)
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echo "unknown para"
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exit 1;;
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esac
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done
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logs_path=${basepath}/logs_train
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rm -rf ${logs_path}
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mkdir -p ${logs_path}
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docker_image=mindspore_build:210311
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#docker_image=mindspore/mindspore-gpu:1.1.1
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# Export models
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echo "Start Exporting models ..."
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# Set log files
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export_log_file=${logs_path}/export_log.txt
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echo ' ' > ${export_log_file}
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export_result_file=${logs_path}/export_result.txt
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echo ' ' > ${export_result_file}
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# Run export according to config file
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cd $models_path || exit 1
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if [[ -z "${CLOUD_MODEL_ZOO}" ]]; then
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echo "CLOUD_MODEL_ZOO is not defined - exiting export models"
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exit 1
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fi
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# Export mindspore train models:
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fail=0
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while read line; do
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LFS=" " read -r -a line_array <<< ${line}
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model_name=${line_array[0]}
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if [[ $model_name == \#* ]]; then
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continue
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fi
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echo ${model_name}'_train_export.py' >> "${export_log_file}"
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rm -f ${models_path}/${model_name}_train.mindir
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echo 'exporting' ${model_name}
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echo 'docker run --user '"$(id -u):$(id -g)"' --env CLOUD_MODEL_ZOO=${CLOUD_MODEL_ZOO} -w $PWD --runtime=nvidia -v /home/$USER:/home/$USER -v /opt/share:/opt/share --privileged=true '${docker_image}' python '${models_path}'/'${model_name}'_train_export.py' >> "${export_log_file}"
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docker run --user "$(id -u):$(id -g)" --env CLOUD_MODEL_ZOO=${CLOUD_MODEL_ZOO} -w $PWD --runtime=nvidia -v /home/$USER:/home/$USER -v /opt/share:/opt/share --privileged=true "${docker_image}" python ${models_path}'/'${model_name}_train_export.py "${epoch_num}"
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if [ $? = 0 ]; then
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export_result='export mindspore '${model_name}'_train_export pass';echo ${export_result} >> ${export_result_file}
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else
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export_result='export mindspore '${model_name}'_train_export failed';echo ${export_result} >> ${export_result_file}
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fail=1
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fi
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done < ${models_mindspore_train_config}
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Print_Result ${export_result_file}
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exit $fail
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