diff --git a/fancy.sh b/fancy.sh
new file mode 100644
index 0000000..d604926
--- /dev/null
+++ b/fancy.sh
@@ -0,0 +1,23 @@
+#!/usr/bin/env bash
+
+RESDIR=$1
+DATADIR=$2
+
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/both_small_final --test ${DATADIR}/futureData.csv --model_output both
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/both_small_inter --test ${DATADIR}/futureData.csv --model_output both
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/client_small_final --test ${DATADIR}/futureData.csv --model_output client
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/client_small_inter --test ${DATADIR}/futureData.csv --model_output client
+
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/both_medium_final --test ${DATADIR}/futureData.csv --model_output both
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/both_medium_inter --test ${DATADIR}/futureData.csv --model_output both
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/client_medium_final --test ${DATADIR}/futureData.csv --model_output client
+python3 main.py --mode fancy --batch 1024 --model ${RESDIR}/client_medium_inter --test ${DATADIR}/futureData.csv --model_output client
+
+python3 main.py --mode all_fancy --batch 256 --test ${DATADIR}/futureData.csv \
+                --models ${RESDIR}/*_small_*/ --out-prefix ${RESDIR}/small
+
+python3 main.py --mode all_fancy --batch 256 --test ${DATADIR}/futureData.csv \
+                --models ${RESDIR}/*_medium_*/ --out-prefix ${RESDIR}/medium
+
+python3 main.py --mode all_fancy --batch 256 --test ${DATADIR}/futureData.csv \
+                --models ${RESDIR}/*/ --out-prefix ${RESDIR}/all
\ No newline at end of file
diff --git a/main.py b/main.py
index 43247c5..7bbe486 100644
--- a/main.py
+++ b/main.py
@@ -180,6 +180,7 @@ def main_train(param=None):
                   class_weight=custom_class_weights)
 
         model.get_layer("dense_server").trainable = False
+        model.get_layer("server").trainable = False
         model.compile(optimizer='adam',
                       loss='binary_crossentropy',
                       loss_weights={"client": 1.0, "server": 0.0},