Remove the keras requirement from the example

examples/cifar10.py

@@ -1,22 +1,13 @@
 """
 Example membership inference attack against a deep net classifier on the CIFAR10 dataset
 """
-
-try:
-    import keras
-except ImportError as e:
-    raise ImportError(
-        "You need to have keras installed for this example: pip install keras"
-    )
-
-
 import numpy as np
 
 from absl import app
 from absl import flags
 
-from keras import layers
-from keras.datasets import cifar10
+import tensorflow as tf
+from tensorflow.keras import layers
 
 from sklearn.model_selection import train_test_split
 
@@ -41,9 +32,9 @@
 
 def get_data():
     """Prepare CIFAR10 data."""
-    (X_train, y_train), (X_test, y_test) = cifar10.load_data()
-    y_train = keras.utils.to_categorical(y_train)
-    y_test = keras.utils.to_categorical(y_test)
+    (X_train, y_train), (X_test, y_test) = tf.keras.datasets.cifar10.load_data()
+    y_train = tf.keras.utils.to_categorical(y_train)
+    y_test = tf.keras.utils.to_categorical(y_test)
     X_train = X_train.astype("float32")
     X_test = X_test.astype("float32")
     y_train = y_train.astype("float32")
@@ -58,7 +49,7 @@ def target_model_fn():
 
     The attack is white-box, hence the attacker is assumed to know this architecture too."""
 
-    model = keras.models.Sequential()
+    model = tf.keras.models.Sequential()
 
     model.add(
         layers.Conv2D(
@@ -95,7 +86,7 @@ def attack_model_fn():
     Following the original paper, this attack model is specific to the class of the input.
     AttachModelBundle creates multiple instances of this model for each class.
     """
-    model = keras.models.Sequential()
+    model = tf.keras.models.Sequential()
 
     model.add(layers.Dense(128, activation="relu", input_shape=(NUM_CLASSES,)))