Documentation Fix - Ragged Tensor

site/en/guide/ragged_tensor.ipynb

@@ -674,7 +674,7 @@
       "source": [
         "### Keras\n",
         "\n",
-        "[tf.keras](https://www.tensorflow.org/guide/keras) is TensorFlow's high-level API for building and training deep learning models. Ragged tensors may be passed as inputs to a Keras model by setting `ragged=True` on `tf.keras.Input` or `tf.keras.layers.InputLayer`.  Ragged tensors may also be passed between Keras layers, and returned by Keras models.  The following example shows a toy LSTM model that is trained using ragged tensors."
+        "[tf.keras](https://www.tensorflow.org/guide/keras) is TensorFlow's high-level API for building and training deep learning models. Ragged tensors can be passed as inputs to a Keras model by using ragged tensors between Keras layers, and returning ragged tensors by Keras models. The following example shows a toy LSTM model that is trained using ragged tensors:"
       ]
     },
     {
@@ -700,17 +700,17 @@
         "\n",
         "# Build the Keras model.\n",
         "keras_model = tf.keras.Sequential([\n",
-        "    tf.keras.layers.Input(shape=[None], dtype=tf.int64, ragged=True),\n",
-        "    tf.keras.layers.Embedding(hash_buckets, 16),\n",
-        "    tf.keras.layers.LSTM(32, use_bias=False),\n",
+        "    tf.keras.layers.Embedding(hash_buckets, 16, input_length=hashed_words.shape[1]),\n",
+        "    tf.keras.layers.LSTM(32, return_sequences=True, use_bias=False),\n",
+        "    tf.keras.layers.Flatten(),\n",
         "    tf.keras.layers.Dense(32),\n",
         "    tf.keras.layers.Activation(tf.nn.relu),\n",
         "    tf.keras.layers.Dense(1)\n",
         "])\n",
         "\n",
         "keras_model.compile(loss='binary_crossentropy', optimizer='rmsprop')\n",
         "keras_model.fit(hashed_words, is_question, epochs=5)\n",
-        "print(keras_model.predict(hashed_words))"
+        "print(keras_model.predict(hashed_words))\n"
       ]
     },
     {