# Archimedesでの実行手順
# /mnt/work/containers/ にSingularityコンテナがある
# /mnt/data2 が \\nlab-fs\data2 に接続している
# コマンドモード
$ ./runCmd.sh
# Jupiter起動
$ ./runJupyter.sh
# デフォルト条件で実行
$ python3 bus_movie_classify.py
# ヘルプ表示
$ python3 bus_movie_classify.py -h
# 結果のサマリー(2行目)を連結
$ awk 'FNR==2{print FILENAME,$0}' res*.csv
#!/bin/bash
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 200 -v 100 -b 16 -o res18fc_t200_b16.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 500 -v 100 -b 16 -o res18fc_t500_b16.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 1000 -v 100 -b 16 -o res18fc_t1000_b16.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 1300 -v 100 -b 16 -o res18fc_t1300_b16.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 200 -v 100 -b 32 -o res18fc_t200_b32.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 500 -v 100 -b 32 -o res18fc_t500_b32.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 1000 -v 100 -b 32 -o res18fc_t1000_b32.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 1300 -v 100 -b 32 -o res18fc_t1300_b32.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 200 -v 100 -b 64 -o res18fc_t200_b64.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 500 -v 100 -b 64 -o res18fc_t500_b64.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 1000 -v 100 -b 64 -o res18fc_t1000_b64.csv
python3 ebus_movie_classify.py -m ResNet18 -u FC -e 50 -t 1300 -v 100 -b 64 -o res18fc_t1300_b64.csv