diff --git a/tensorflow/lite/experimental/examples/lstm/g3doc/README.md b/tensorflow/lite/experimental/examples/lstm/g3doc/README.md
index 63873fd9752..ef21a3e0301 100644
--- a/tensorflow/lite/experimental/examples/lstm/g3doc/README.md
+++ b/tensorflow/lite/experimental/examples/lstm/g3doc/README.md
@@ -71,7 +71,7 @@ tflite_model = converter.convert()  # You got a tflite model!
 +          tf.lite.experimental.nn.TFLiteLSTMCell(
                self.num_lstm_units, forget_bias=0))
      # Weights and biases for output softmax layer.
-     out_weights = tf.Variable(tf.random_normal([self.units, self.num_class]))
+     out_weights = tf.Variable(tf.random.normal([self.units, self.num_class]))
 @@ -67,7 +67,7 @@ class MnistLstmModel(object):
      lstm_cells = tf.nn.rnn_cell.MultiRNNCell(lstm_layers)
      # Note here, we use `tf.lite.experimental.nn.dynamic_rnn` and `time_major`
@@ -170,7 +170,7 @@ class MnistLstmModel(object):
           tf.lite.experimental.nn.TFLiteLSTMCell(
               self.num_lstm_units, forget_bias=0))
     # Weights and biases for output softmax layer.
-    out_weights = tf.Variable(tf.random_normal([self.units, self.num_class]))
+    out_weights = tf.Variable(tf.random.normal([self.units, self.num_class]))
     out_bias = tf.Variable(tf.zeros([self.num_class]))
 
     # Transpose input x to make it time major.