use candle function to download & store in data dir

Author: hyoo

Pilot1/Uno/test.sh

@@ -3,12 +3,13 @@
 set -x
 
 # AUC prediction model
-if [ ! -f "top_21_auc_1fold.uno.h5" ]; then
-  curl -o top_21_auc_1fold.uno.h5 http://ftp.mcs.anl.gov/pub/candle/public/benchmarks/Pilot1/uno/top_21_auc_1fold.uno.h5
+if [ ! -f "../../Data/Pilot1/Uno/top_21_auc_1fold.uno.h5" ]; then
+  # download from http://ftp.mcs.anl.gov/pub/candle/public/benchmarks/Pilot1/uno/top_21_auc_1fold.uno.h5
+  python -c 'from candle import get_file;get_file(fname="top_21_auc_1fold.uno.h5", origin="https://ftp.mcs.anl.gov/pub/candle/public/benchmarks/Pilot1/uno/top_21_auc_1fold.uno.h5", cache_subdir="Pilot1/Uno", datadir="../../Data")'
 fi
 
-python uno_baseline_keras2.py --config_file uno_auc_model.txt --use_exported_data top_21_auc_1fold.uno.h5 -e 3 --save_weights save/saved.model.weights.h5
-python uno_infer.py --data top_21_auc_1fold.uno.h5 \
+python uno_baseline_keras2.py --config_file uno_auc_model.txt --use_exported_data ../../Data/Pilot1/Uno/top_21_auc_1fold.uno.h5 -e 3 --save_weights save/saved.model.weights.h5
+python uno_infer.py --data ../../Data/Pilot1/Uno/top_21_auc_1fold.uno.h5 \
   --model_file save/'uno.A=relu.B=32.E=3.O=adamax.LR=0.0001.CF=r.DF=d.DR=0.1.wu_lr.re_lr.L1000.D1=1000.D2=1000.D3=1000.D4=1000.D5=1000.FD1=1000.FD2=1000.FD3=1000.FD4=1000.FD5=1000.model.json' \
   --weights_file save/saved.model.weights.h5 \
   --partition val \
@@ -17,5 +18,5 @@ python uno_infer.py --data top_21_auc_1fold.uno.h5 \
   --agg_dose AUC
 
 # CLR model
-python uno_clr_keras2.py --config_file uno_auc_clr_model.txt --use_exported_data top_21_auc_1fold.uno.h5 -e 3
+python uno_clr_keras2.py --config_file uno_auc_clr_model.txt --use_exported_data ../../Data/Pilot1/Uno/top_21_auc_1fold.uno.h5 -e 3