Update app.py

app.py

@@ -9,9 +9,12 @@ import pennylane as qml
 cnn_model = tf.keras.models.load_model('noq_c_model.h5')
 qcnn_model = tf.keras.models.load_model('q_model.h5')
 
-# Define the quanvolutional layer as per CNN_QCNN.ipynb
+# Define the quanvolutional layer
 n_layers = 3  # Number of quantum layers
 dev = qml.device("default.qubit", wires=2)
+
+# Set random number seed
+np.random.seed(0)
 rand_params = np.random.uniform(high=2 * np.pi, size=(n_layers, 2, 2))
 
 @qml.qnode(dev)