add yapf style and apply yapf to format all Python files

This recreates pull request #2192

examples/pybullet/gym/pybullet_envs/agents/train_ppo.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.
-
 r"""Script to train a batch reinforcement learning algorithm.
 
 Command line:
@@ -67,21 +66,25 @@ def _define_loop(graph, logdir, train_steps, eval_steps):
   Returns:
     Loop object.
   """
-  loop = tools.Loop(
-      logdir, graph.step, graph.should_log, graph.do_report,
-      graph.force_reset)
-  loop.add_phase(
-      'train', graph.done, graph.score, graph.summary, train_steps,
-      report_every=train_steps,
-      log_every=train_steps // 2,
-      checkpoint_every=None,
-      feed={graph.is_training: True})
-  loop.add_phase(
-      'eval', graph.done, graph.score, graph.summary, eval_steps,
-      report_every=eval_steps,
-      log_every=eval_steps // 2,
-      checkpoint_every=10 * eval_steps,
-      feed={graph.is_training: False})
+  loop = tools.Loop(logdir, graph.step, graph.should_log, graph.do_report, graph.force_reset)
+  loop.add_phase('train',
+                 graph.done,
+                 graph.score,
+                 graph.summary,
+                 train_steps,
+                 report_every=train_steps,
+                 log_every=train_steps // 2,
+                 checkpoint_every=None,
+                 feed={graph.is_training: True})
+  loop.add_phase('eval',
+                 graph.done,
+                 graph.score,
+                 graph.summary,
+                 eval_steps,
+                 report_every=eval_steps,
+                 log_every=eval_steps // 2,
+                 checkpoint_every=10 * eval_steps,
+                 feed={graph.is_training: False})
   return loop
 
 
@@ -102,18 +105,13 @@ def train(config, env_processes):
   if config.update_every % config.num_agents:
     tf.logging.warn('Number of agents should divide episodes per update.')
   with tf.device('/cpu:0'):
-    batch_env = utility.define_batch_env(
-        lambda: _create_environment(config),
-        config.num_agents, env_processes)
-    graph = utility.define_simulation_graph(
-        batch_env, config.algorithm, config)
-    loop = _define_loop(
-        graph, config.logdir,
-        config.update_every * config.max_length,
-        config.eval_episodes * config.max_length)
-    total_steps = int(
-        config.steps / config.update_every *
-        (config.update_every + config.eval_episodes))
+    batch_env = utility.define_batch_env(lambda: _create_environment(config), config.num_agents,
+                                         env_processes)
+    graph = utility.define_simulation_graph(batch_env, config.algorithm, config)
+    loop = _define_loop(graph, config.logdir, config.update_every * config.max_length,
+                        config.eval_episodes * config.max_length)
+    total_steps = int(config.steps / config.update_every *
+                      (config.update_every + config.eval_episodes))
   # Exclude episode related variables since the Python state of environments is
   # not checkpointed and thus new episodes start after resuming.
   saver = utility.define_saver(exclude=(r'.*_temporary/.*',))
@@ -131,8 +129,8 @@ def main(_):
   utility.set_up_logging()
   if not FLAGS.config:
     raise KeyError('You must specify a configuration.')
-  logdir = FLAGS.logdir and os.path.expanduser(os.path.join(
-      FLAGS.logdir, '{}-{}'.format(FLAGS.timestamp, FLAGS.config)))
+  logdir = FLAGS.logdir and os.path.expanduser(
+      os.path.join(FLAGS.logdir, '{}-{}'.format(FLAGS.timestamp, FLAGS.config)))
   try:
     config = utility.load_config(logdir)
   except IOError:
@@ -144,16 +142,11 @@ def main(_):
 
 if __name__ == '__main__':
   FLAGS = tf.app.flags.FLAGS
-  tf.app.flags.DEFINE_string(
-      'logdir', None,
-      'Base directory to store logs.')
-  tf.app.flags.DEFINE_string(
-      'timestamp', datetime.datetime.now().strftime('%Y%m%dT%H%M%S'),
-      'Sub directory to store logs.')
-  tf.app.flags.DEFINE_string(
-      'config', None,
-      'Configuration to execute.')
-  tf.app.flags.DEFINE_boolean(
-      'env_processes', True,
-      'Step environments in separate processes to circumvent the GIL.')
+  tf.app.flags.DEFINE_string('logdir', None, 'Base directory to store logs.')
+  tf.app.flags.DEFINE_string('timestamp',
+                             datetime.datetime.now().strftime('%Y%m%dT%H%M%S'),
+                             'Sub directory to store logs.')
+  tf.app.flags.DEFINE_string('config', None, 'Configuration to execute.')
+  tf.app.flags.DEFINE_boolean('env_processes', True,
+                              'Step environments in separate processes to circumvent the GIL.')
   tf.app.run()