Fix formatting

tensorflow_addons/image/dense_image_warp.py

@@ -57,35 +57,41 @@ def _interpolate_bilinear_with_checks(
 ) -> tf.Tensor:
     """Perform checks on inputs without tf.function decorator to avoid flakiness."""
     if indexing != "ij" and indexing != "xy":
-    raise ValueError("Indexing mode must be 'ij' or 'xy'")
+        raise ValueError("Indexing mode must be 'ij' or 'xy'")
 
     grid = tf.convert_to_tensor(grid)
     query_points = tf.convert_to_tensor(query_points)
     grid_shape = tf.shape(grid)
     query_shape = tf.shape(query_points)
 
-    with tf.control_dependencies([
-      tf.Assert(tf.equal(tf.rank(grid), 4), ["Grid must be 4D Tensor"]),
-      tf.Assert(
-          tf.greater_equal(grid_shape[1], 2),
-          ["Grid height must be at least 2."]),
-      tf.Assert(
-          tf.greater_equal(grid_shape[2], 2),
-          ["Grid width must be at least 2."]),
-      tf.Assert(
-          tf.equal(tf.rank(query_points), 3),
-          ["Query points must be 3 dimensional."]),
-      tf.Assert(
-          tf.equal(query_shape[2], 2),
-          ["Query points last dimension must be 2."])
-    ]):
+    with tf.control_dependencies(
+        [
+            tf.Assert(tf.equal(tf.rank(grid), 4), ["Grid must be 4D Tensor"]),
+            tf.Assert(
+                tf.greater_equal(grid_shape[1], 2), ["Grid height must be at least 2."]
+            ),
+            tf.Assert(
+                tf.greater_equal(grid_shape[2], 2), ["Grid width must be at least 2."]
+            ),
+            tf.Assert(
+                tf.equal(tf.rank(query_points), 3),
+                ["Query points must be 3 dimensional."],
+            ),
+            tf.Assert(
+                tf.equal(query_shape[2], 2), ["Query points last dimension must be 2."]
+            ),
+        ]
+    ):
         return _interpolate_bilinear_impl(grid, query_points, indexing, name)
 
 
 @tf.function
-def _interpolate_bilinear_impl(grid: types.TensorLike,
-                               query_points: types.TensorLike, indexing: str,
-                               name: Optional[str]) -> tf.Tensor:
+def _interpolate_bilinear_impl(
+    grid: types.TensorLike,
+    query_points: types.TensorLike,
+    indexing: str,
+    name: Optional[str],
+) -> tf.Tensor:
     """tf.function implementation of interpolate_bilinear."""
     with tf.name_scope(name or "interpolate_bilinear"):
         grid_shape = tf.shape(grid)