diff --git a/1.9-gpu/example.py b/1.9-gpu/example.py
new file mode 100644
index 0000000..f0915c2
--- /dev/null
+++ b/1.9-gpu/example.py
@@ -0,0 +1,18 @@
+import tensorflow as tf
+mnist = tf.keras.datasets.mnist
+
+(x_train, y_train),(x_test, y_test) = mnist.load_data()
+x_train, x_test = x_train / 255.0, x_test / 255.0
+
+model = tf.keras.models.Sequential([
+  tf.keras.layers.Flatten(),
+  tf.keras.layers.Dense(512, activation=tf.nn.relu),
+  tf.keras.layers.Dropout(0.2),
+  tf.keras.layers.Dense(10, activation=tf.nn.softmax)
+])
+model.compile(optimizer='adam',
+              loss='sparse_categorical_crossentropy',
+              metrics=['accuracy'])
+
+model.fit(x_train, y_train, epochs=5)
+model.evaluate(x_test, y_test)
diff --git a/1.9-gpu/script.sh b/1.9-gpu/script.sh
index 6b8eb47..1044233 100644
--- a/1.9-gpu/script.sh
+++ b/1.9-gpu/script.sh
@@ -1,16 +1,15 @@
 #!/bin/bash
 
 #SBATCH --nodes=1
 #SBATCH --time=1:0:0
 #SBATCH --partition=gpu
 #SBATCH --gres=gpu:1
 #SBATCH --qos=gpu
 
 source /ssoft/spack/bin/slmodules.sh -s  x86_E5v2_Mellanox_GPU
-source /scratch/nvarini/tensorflow-1.9.0-pip3/bin/activate
+source /home/nvarini/tensorflow-pip-deneb/1.9-gpu/tensorflow-1.9/bin/activate
 
-module load gcc/6.4.0 cuda/9.1.85 openmpi/3.0.1-cuda python cudnn
-export LD_LIBRARY_PATH=/usr/lib64:$LD_LIBRARY_PATH
-srun python tf_cnn_benchmarks.py  --batch_size=64 --model=resnet50  --num_gpus=1 --data_format=NCHW --variable_update=replicated --local_parameter_device=gpu --num_batches=3000
+module load gcc/6.4.0 cuda/9.1.85  python cudnn
+srun python3 example.py 
 
 deactivate