Reduce XShards tutorial test time (#5555)

.github/workflows/orca-tutorial-xshards.yml

@@ -82,7 +82,7 @@ jobs:
         pip install tensorflow==1.15.0
         pip install sklearn
         pip install pandas
-        pip install jep
+        pip install jep==3.9.0
         pip install cloudpickle
     - name: Run Test
       #run: python -m build

python/orca/dev/test/run-tutorial-xshards.sh

@@ -27,7 +27,6 @@ cd "`dirname $0`"
 cd ../../tutorial/xshards
 
 echo "#1 Running run-tabular_playground_series"
-
 #timer
 start=$(date "+%s")
 
@@ -44,7 +43,6 @@ now=$(date "+%s")
 time1=$((now - start))
 
 echo "#2 Running titanic"
-
 #timer
 start=$(date "+%s")
 
@@ -63,7 +61,6 @@ now=$(date "+%s")
 time2=$((now - start))
 
 echo "#3 Running diabetes"
-
 #timer
 start=$(date "+%s")
 
@@ -74,14 +71,14 @@ else
     wget -nv $FTP_URI/analytics-zoo-data/xshards/pima-indians-diabetes-test.csv -P ${BIGDL_ROOT}/python/orca/tutorial/xshards/
 fi
 
+sed -i "s/epochs=150/epochs=2/g" diabetes.py
 python diabetes.py
 
 now=$(date "+%s")
 time3=$((now - start))
 
 
 echo "#4 Running ionosphere"
-
 #timer
 start=$(date "+%s")
 
@@ -92,14 +89,14 @@ else
     wget -nv $FTP_URI/analytics-zoo-data/xshards/new_ionosphere.csv -P ${BIGDL_ROOT}/python/orca/tutorial/xshards/
 fi
 
+sed -i "s/epochs=100/epochs=2/g" ionosphere.py
 python ionosphere.py
 
 now=$(date "+%s")
 time4=$((now - start))
 
 
 echo "#5 Running auto_mpg"
-
 #timer
 start=$(date "+%s")
 
@@ -110,12 +107,12 @@ else
     wget -nv $FTP_URI/analytics-zoo-data/xshards/auto-mpg.csv -P ${BIGDL_ROOT}/python/orca/tutorial/xshards/
 fi
 
+sed -i "s/EPOCHS = 1000/EPOCHS = 2/g" auto_mpg.py
 python auto_mpg.py
 
 now=$(date "+%s")
 time5=$((now - start))
 
-
 echo "#1 Running run-tabular_playground_series time used: $time1 seconds"
 echo "#2 Running titanic time used: $time2 seconds"
 echo "#3 Running diabetes time used: $time3 seconds"

python/orca/tutorial/xshards/auto_mpg.py

@@ -21,7 +21,6 @@
 from bigdl.orca.data.transformer import *
 from bigdl.orca.learn.tf.estimator import Estimator
 
-import pandas as pd
 import tensorflow.compat.v1 as tf
 from tensorflow.keras.models import Sequential
 from tensorflow.keras.layers import Dense
@@ -81,3 +80,4 @@ def build_model():
 est.fit(data=shards_train,
         batch_size=16,
         epochs=EPOCHS, feature_cols=['scaled_vec'], label_cols=['MPG'])
+stop_orca_context()