add TF docstring example

static/index.html

@@ -134,9 +134,11 @@ label {
             <span class="softspan">Infill Examples:</span>
             <br>
             <span class="softspan"><a href='javascript:select_example("type-pred");'>Type prediction</a></span>
-            <span class="softspan"><a href='javascript:select_example("multi-region");'>Multi-region</a></span>
-            <span class="softspan"><a href='javascript:select_example("docstring");'>Function to docstring</a></span>
+            <span class="softspan"><a href='javascript:select_example("multi-region");'>Docstring to function</a></span>
+            <span class="softspan"><a href='javascript:select_example("docstring-2");'>Function to docstring</a></span>
+            <!--
             <span class="softspan"><a href='javascript:select_example("python-infill2");'>Docstring to function</a></span>
+            -->
             <span class="softspan"><a href='javascript:select_example("class");'>Class generation</a></span>
         </div>
         <div id="examples-extend">
@@ -282,6 +284,30 @@ def <infill>
         "temperature": 0.2,
         "mode": "python"
     },
+    "docstring-2": {
+        "prompt":
+`def _minimize_in_graph(build_loss_fn, num_steps=200, optimizer=None):
+  """
+  <infill>
+  """
+  optimizer = tf.compat.v1.train.AdamOptimizer(
+      0.1) if optimizer is None else optimizer
+
+  def train_loop_body(step):
+    train_op = optimizer.minimize(
+        build_loss_fn if tf.executing_eagerly() else build_loss_fn())
+    return tf.tuple(tensors=[tf.add(step, 1)], control_inputs=[train_op])
+
+  minimize_op = tf.compat.v1.while_loop(
+      cond=lambda step: step < num_steps,
+      body=train_loop_body,
+      loop_vars=[tf.constant(0)],
+      return_same_structure=True)[0] 
+  return minimize_op`,
+  "length": 64,
+  "temperature": 0.3,
+  "mode": "python",
+    },
     "docstring": {
         "prompt": 
 `<| file ext=.py |>