diff --git a/tensorflow/contrib/eager/python/examples/generative_examples/image_captioning_with_attention.ipynb b/tensorflow/contrib/eager/python/examples/generative_examples/image_captioning_with_attention.ipynb
index 1a5a186e7a3..315d7a48931 100644
--- a/tensorflow/contrib/eager/python/examples/generative_examples/image_captioning_with_attention.ipynb
+++ b/tensorflow/contrib/eager/python/examples/generative_examples/image_captioning_with_attention.ipynb
@@ -1056,7 +1056,7 @@
         "\n",
         "        attention_plot[i] = tf.reshape(attention_weights, (-1, )).numpy()\n",
         "\n",
-        "        predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].numpy()\n",
+        "        predicted_id = tf.multinomial(predictions, num_samples=1)[0][0].numpy()\n",
         "        result.append(index_word[predicted_id])\n",
         "\n",
         "        if index_word[predicted_id] == '<end>':\n",
diff --git a/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb b/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb
index 027097908f2..40bc0987248 100644
--- a/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb
+++ b/tensorflow/contrib/eager/python/examples/generative_examples/text_generation.ipynb
@@ -610,7 +610,7 @@
         "\n",
         "    # using a multinomial distribution to predict the word returned by the model\n",
         "    predictions = predictions / temperature\n",
-        "    predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].numpy()\n",
+        "    predicted_id = tf.multinomial(predictions, num_samples=1)[0][0].numpy()\n",
         "    \n",
         "    # We pass the predicted word as the next input to the model\n",
         "    # along with the previous hidden state\n",
diff --git a/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb b/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb
index 08d8364978f..f1e1f99c57a 100644
--- a/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb
+++ b/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb
@@ -466,10 +466,10 @@
         "        # passing the concatenated vector to the GRU\n",
         "        output, state = self.gru(x)\n",
         "        \n",
-        "        # output shape == (batch_size * max_length, hidden_size)\n",
+        "        # output shape == (batch_size * 1, hidden_size)\n",
         "        output = tf.reshape(output, (-1, output.shape[2]))\n",
         "        \n",
-        "        # output shape == (batch_size * max_length, vocab)\n",
+        "        # output shape == (batch_size * 1, vocab)\n",
         "        x = self.fc(output)\n",
         "        \n",
         "        return x, state, attention_weights\n",
@@ -677,7 +677,7 @@
         "        attention_weights = tf.reshape(attention_weights, (-1, ))\n",
         "        attention_plot[t] = attention_weights.numpy()\n",
         "\n",
-        "        predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].numpy()\n",
+        "        predicted_id = tf.multinomial(predictions, num_samples=1)[0][0].numpy()\n",
         "\n",
         "        result += targ_lang.idx2word[predicted_id] + ' '\n",
         "\n",