add yapf style and apply yapf to format all Python files

This recreates pull request #2192

examples/pybullet/gym/pybullet_envs/agents/utility.py

@@ -11,7 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
 """Utilities for using reinforcement learning algorithms."""
 
 from __future__ import absolute_import
@@ -46,8 +45,7 @@ def define_simulation_graph(batch_env, algo_cls, config):
   do_report = tf.placeholder(tf.bool, name='do_report')
   force_reset = tf.placeholder(tf.bool, name='force_reset')
   algo = algo_cls(batch_env, step, is_training, should_log, config)
-  done, score, summary = tools.simulate(
-      batch_env, algo, should_log, force_reset)
+  done, score, summary = tools.simulate(batch_env, algo, should_log, force_reset)
   message = 'Graph contains {} trainable variables.'
   tf.logging.info(message.format(tools.count_weights()))
   # pylint: enable=unused-variable
@@ -67,9 +65,7 @@ def define_batch_env(constructor, num_agents, env_processes):
   """
   with tf.variable_scope('environments'):
     if env_processes:
-      envs = [
-          tools.wrappers.ExternalProcess(constructor)
-          for _ in range(num_agents)]
+      envs = [tools.wrappers.ExternalProcess(constructor) for _ in range(num_agents)]
     else:
       envs = [constructor() for _ in range(num_agents)]
     batch_env = tools.BatchEnv(envs, blocking=not env_processes)
@@ -111,9 +107,7 @@ def initialize_variables(sess, saver, logdir, checkpoint=None, resume=None):
     ValueError: If resume expected but no log directory specified.
     RuntimeError: If no resume expected but a checkpoint was found.
   """
-  sess.run(tf.group(
-      tf.local_variables_initializer(),
-      tf.global_variables_initializer()))
+  sess.run(tf.group(tf.local_variables_initializer(), tf.global_variables_initializer()))
   if resume and not (logdir or checkpoint):
     raise ValueError('Need to specify logdir to resume a checkpoint.')
   if logdir:
@@ -152,9 +146,8 @@ def save_config(config, logdir=None):
     with tf.gfile.GFile(config_path, 'w') as file_:
       yaml.dump(config, file_, default_flow_style=False)
   else:
-    message = (
-        'Start a new run without storing summaries and checkpoints since no '
-        'logging directory was specified.')
+    message = ('Start a new run without storing summaries and checkpoints since no '
+               'logging directory was specified.')
     tf.logging.info(message)
   return config
 
@@ -173,9 +166,8 @@ def load_config(logdir):
   """
   config_path = logdir and os.path.join(logdir, 'config.yaml')
   if not config_path or not tf.gfile.Exists(config_path):
-    message = (
-        'Cannot resume an existing run since the logging directory does not '
-        'contain a configuration file.')
+    message = ('Cannot resume an existing run since the logging directory does not '
+               'contain a configuration file.')
     raise IOError(message)
   with tf.gfile.FastGFile(config_path, 'r') as file_:
     config = yaml.load(file_, Loader=yaml.Loader)