Lint Python files with Yapf (#1872)

python/ray/tune/trainable.py

@@ -114,8 +114,8 @@ class Trainable(object):
             time_this_iter = time.time() - start
 
         if result.timesteps_this_iter is None:
-            raise TuneError(
-                "Must specify timesteps_this_iter in result", result)
+            raise TuneError("Must specify timesteps_this_iter in result",
+                            result)
 
         self._time_total += time_this_iter
         self._timesteps_total += result.timesteps_this_iter
@@ -159,10 +159,10 @@ class Trainable(object):
         """
 
         checkpoint_path = self._save(checkpoint_dir or self.logdir)
-        pickle.dump(
-            [self._experiment_id, self._iteration, self._timesteps_total,
-             self._time_total],
-            open(checkpoint_path + ".tune_metadata", "wb"))
+        pickle.dump([
+            self._experiment_id, self._iteration, self._timesteps_total,
+            self._time_total
+        ], open(checkpoint_path + ".tune_metadata", "wb"))
         return checkpoint_path
 
     def save_to_object(self):
@@ -186,8 +186,10 @@ class Trainable(object):
         out = io.BytesIO()
         with gzip.GzipFile(fileobj=out, mode="wb") as f:
             compressed = pickle.dumps({
-                "checkpoint_name": os.path.basename(checkpoint_prefix),
-                "data": data,
+                "checkpoint_name":
+                os.path.basename(checkpoint_prefix),
+                "data":
+                data,
             })
             if len(compressed) > 10e6:  # getting pretty large
                 print("Checkpoint size is {} bytes".format(len(compressed)))