diff --git a/tensorflow/lite/python/op_hint.py b/tensorflow/lite/python/op_hint.py
index 159fcaa2bf3..9d62c1b8a97 100644
--- a/tensorflow/lite/python/op_hint.py
+++ b/tensorflow/lite/python/op_hint.py
@@ -435,6 +435,7 @@ class OpHint(object):
     Args:
       *args: List of inputs to be converted (should be Tf.Tensor).
       **kwargs: This allows 'names' which should be a list of names.
+
     Returns:
       Wrapped inputs (identity standins that have additional metadata). These
       are also are also tf.Tensor's.
@@ -453,6 +454,7 @@ class OpHint(object):
     Args:
       *args: List of outputs to be converted (should be tf.Tensor).
       **kwargs: See
+
     Returns:
       Wrapped outputs (identity standins that have additional metadata). These
       are also tf.Tensor's.
@@ -574,8 +576,8 @@ class _LiteAggregateOperand(_LiteOperand):
       elif self.aggregation == OpHint.AGGREGATE_STACK:
         pass
       else:
-        raise ValueError(
-            "Invalid aggregation type %r specified" % self.aggregation)
+        raise ValueError("Invalid aggregation type %r specified" %
+                         self.aggregation)
     return self.flattened
 
   def flatten(self):
@@ -646,8 +648,8 @@ class _LiteAggregateOperand(_LiteOperand):
       stack_node.attr["num"].i = len(flattened)
       output_type = flattened[0].attr["T"].type
       stack_node.attr["T"].type = output_type
-      stack_node.input.append(_tensorflow_output_name(
-          fused_op_name, output_index))
+      stack_node.input.append(
+          _tensorflow_output_name(fused_op_name, output_index))
       out_graphdef.node.extend([stack_node])
 
       for idx, discrete in enumerate(flattened):
@@ -675,11 +677,10 @@ class _LiteFuncCall(object):
     inputs: inputs to the op (hash from index # to argument)
     outputs: outputs to the op (hash from index # to argument)
     function_name: the tflite custom op name to use
-    uuid: a unique call id for this particular call  (i.e.
-      multiple function calls would have the same function_name but different
-      uuids.
-    params: A param name to key value for op constant data. I.e. for
-      axis on a reduction, strides on a convolution, etc.
+    uuid: a unique call id for this particular call  (i.e. multiple function
+      calls would have the same function_name but different uuids.
+    params: A param name to key value for op constant data. I.e. for axis on a
+      reduction, strides on a convolution, etc.
     level: Level of the OpHint.
     children_inputs_mappings: If the Ophint has children, children inputs
       mappings indicate how their inputs & outputs are mapped.
@@ -700,6 +701,7 @@ class _LiteFuncCall(object):
     Returns:
       Tuple of (inputs, outputs). where input and output i a list of names.
     """
+
     def _flatten(input_or_output_dict):
       flattened_items = []
       for item in input_or_output_dict.values():
@@ -709,6 +711,7 @@ class _LiteFuncCall(object):
     return _flatten(self.inputs), _flatten(self.outputs)
 
   def __str__(self):
+
     def format_args(items):
       s = ""
       for idx, item in items.iteritems():
@@ -739,8 +742,8 @@ def _find_all_hints_in_nodes(nodes):
   for node in nodes:
     attr = node.attr
     # This is an op hint if it has a FUNCTION_UUID_ATTR, otherwise skip
-    if (OpHint.FUNCTION_UUID_ATTR not in attr
-        or not attr[OpHint.FUNCTION_UUID_ATTR].s):
+    if (OpHint.FUNCTION_UUID_ATTR not in attr or
+        not attr[OpHint.FUNCTION_UUID_ATTR].s):
       continue
     uuid = attr[OpHint.FUNCTION_UUID_ATTR].s
 
@@ -751,9 +754,11 @@ def _find_all_hints_in_nodes(nodes):
     call_def.level = attr[OpHint.FUNCTION_LEVEL_ATTR].i
     # Get sorting and aggregation information
 
-    sort = (attr[OpHint.FUNCTION_SORT_INDEX_ATTR].i
-            if OpHint.FUNCTION_SORT_INDEX_ATTR in attr else None)
-    if sort == -1: sort = None
+    sort = (
+        attr[OpHint.FUNCTION_SORT_INDEX_ATTR].i
+        if OpHint.FUNCTION_SORT_INDEX_ATTR in attr else None)
+    if sort == -1:
+      sort = None
     aggregation = None
     if OpHint.FUNCTION_AGGREGATE_ATTR in attr:
       aggregation = _compat.as_text(attr[OpHint.FUNCTION_AGGREGATE_ATTR].s)
@@ -887,6 +892,7 @@ def _tensor_name_base(full_tensor_name):
   Args:
     full_tensor_name: A tensor name that is annotated with a device placement
       (this is what tensor flow introspection gives).
+
   Returns:
     A name without any device assignment.
   """
@@ -919,10 +925,10 @@ def _check_subgraph_closed(n, reachable_by_input, input_nodes_set,
   while next_to_visit:
     current_node = next_to_visit.pop()
     visited.add(current_node)
-    if (current_node in reachable_by_input
-        and current_node not in input_nodes_set):
-      raise TypeError(
-          "Node %s uses input %s not in input_nodes." % (n, current_node))
+    if (current_node in reachable_by_input and
+        current_node not in input_nodes_set):
+      raise TypeError("Node %s uses input %s not in input_nodes." %
+                      (n, current_node))
     if current_node not in input_nodes_set:
       next_to_visit += [
           input_node for input_node in name_to_input_name[current_node]
@@ -1066,6 +1072,7 @@ def _remove_one_redundant_stack_unstack(in_graph_def):
 
   Args:
     in_graph_def: Graph def to use as input.
+
   Returns:
     Simplified tuple (graph_def, changed_something) where changed_something
     is true if anything was done.
@@ -1101,15 +1108,15 @@ def _remove_one_redundant_stack_unstack(in_graph_def):
       node = name_to_node[current_node_name]
       is_op_hint_stack = node.name.startswith("OpHintStack")
       is_op_hint_unstack = node.name.startswith("OpHintUnstack")
-      if (node.op == "Identity" or is_op_hint_stack
-          or (do_generic_pack_unpack and node.op == "Pack")):
+      if (node.op == "Identity" or is_op_hint_stack or
+          (do_generic_pack_unpack and node.op == "Pack")):
         is_hint_created_stack |= is_op_hint_stack
         next_to_visit += [
             input_node for input_node in name_to_input_name[current_node_name]
             if input_node not in visited
         ]
-      elif (is_op_hint_unstack
-            or (do_generic_pack_unpack and node.op == "Unpack")):
+      elif (is_op_hint_unstack or
+            (do_generic_pack_unpack and node.op == "Unpack")):
         unpack_nodes.add(node.name)
         is_hint_created_stack &= is_op_hint_unstack
       else:
@@ -1124,7 +1131,8 @@ def _remove_one_redundant_stack_unstack(in_graph_def):
       # Unstacked form
       no_external_dependency = True
       for other_n in in_graph_def.node:
-        if other_n.name in visited: continue
+        if other_n.name in visited:
+          continue
         for input_tensor in name_to_input_name[other_n.name]:
           input_op = _tensor_name_base(input_tensor)
           if input_op in visited and input_op != pack_node:
@@ -1141,9 +1149,9 @@ def _remove_one_redundant_stack_unstack(in_graph_def):
           if node_name not in visited:
             new_node = _copy.deepcopy(other_n)
             new_node.input[:] = [
-                (end_input if stripped == pack_node else
-                 non_stripped) for stripped, non_stripped in zip(
-                     name_to_input_name[node_name], new_node.input[:])
+                (end_input if stripped == pack_node else non_stripped)
+                for stripped, non_stripped in zip(name_to_input_name[node_name],
+                                                  new_node.input[:])
             ]
             out.node.extend([new_node])
         return out, True
@@ -1177,6 +1185,7 @@ def _convert_op_hints_to_stubs_helper(
     graph_def: A graph def that we should convert.
     write_callback: A function pointer that can be used to write intermediate
       steps of graph transformation (optional).
+
   Returns:
     A new stubbed graph_def.
   """
@@ -1306,6 +1315,7 @@ def convert_op_hints_to_stubs(session=None,
     graph_def: A graph def that we should convert.
     write_callback: A function pointer that can be used to write intermediate
       steps of graph transformation (optional).
+
   Returns:
     A new graphdef with all ops contained in OpHints being replaced by
     a single op call with the right parameters.