optionally use specific temp bucket when running ml-engine jobs

eval.sh

@@ -41,11 +41,12 @@ if [ $USE_SEPARATE_CHANNELS == true ]; then
 fi
 
 if [ $USE_CLOUD == true ]; then
+  JOB_ID="eval_$JOB_ID"
   gcloud ml-engine jobs submit training "$JOB_ID" \
     --stream-logs \
     --module-name sciencebeam_gym.trainer.task \
     --package-path sciencebeam_gym \
-    --staging-bucket "$BUCKET" \
+    --staging-bucket "$TEMP_BUCKET" \
     --region us-central1 \
     --runtime-version=1.2 \
     -- \

predict.sh

@@ -55,7 +55,7 @@ if [ $USE_CLOUD == true ]; then
     --stream-logs \
     --module-name sciencebeam_gym.trainer.task \
     --package-path sciencebeam_gym \
-    --staging-bucket "$BUCKET" \
+    --staging-bucket "$TEMP_BUCKET" \
     --region us-central1 \
     --runtime-version=1.2 \
     -- \

prepare-shell.sh

@@ -11,6 +11,7 @@ TRAINING_ARGS=""
 PROJECT=$(gcloud config list project --format "value(core.project)")
 LOCAL_PATH_ROOT="./.models"
 BUCKET="gs://${PROJECT}-ml"
+TEMP_BUCKET=
 COLOR_MAP_FILENAME="color_map.conf"
 USE_SEPARATE_CHANNELS=true
 DATASET_SUFFIX=
@@ -61,6 +62,10 @@ if [ -z "$JOB_ID" ]; then
   JOB_ID="${DEFAULT_JOB_ID}"
 fi
 
+if [ -z "$TEMP_BUCKET" ]; then
+  TEMP_BUCKET="${BUCKET}"
+fi
+
 # cloud paths
 GCS_SUB_PROJECT_PATH="${BUCKET}/${SUB_PROJECT_NAME}"
 GCS_PATH="${GCS_SUB_PROJECT_PATH}/${MODEL_NAME}/${VERSION_NAME}"

save-model.sh

@@ -41,7 +41,7 @@ if [ $USE_CLOUD == true ]; then
     --stream-logs \
     --module-name sciencebeam_gym.trainer.task \
     --package-path sciencebeam_gym \
-    --staging-bucket "$BUCKET" \
+    --staging-bucket "$TEMP_BUCKET" \
     --region us-central1 \
     --runtime-version=1.2 \
     -- \

train.sh

@@ -39,7 +39,7 @@ if [ $USE_CLOUD == true ]; then
     --stream-logs \
     --module-name sciencebeam_gym.trainer.task \
     --package-path sciencebeam_gym \
-    --staging-bucket "$BUCKET" \
+    --staging-bucket "$TEMP_BUCKET" \
     --region us-central1 \
     --runtime-version=1.2 \
     --scale-tier=BASIC_GPU \