diff --git a/baselines/ppo2/model.py b/baselines/ppo2/model.py
index 7437043..45629c8 100644
--- a/baselines/ppo2/model.py
+++ b/baselines/ppo2/model.py
@@ -129,8 +129,13 @@ class Model(object):
             if MPI is not None:
                 sync_from_root(sess, global_variables)  # pylint: disable=E1101
 
-    def step(self, *args, **kwargs):
-        return self.act_model.step(*args, **kwargs)
+    def step_as_dict(self, **kwargs):
+        return self.act_model.step(**kwargs)
+
+    def step(self, observations, **kwargs):
+        kwargs.update({'observations': observations})
+        transition = self.act_model.step(**kwargs)
+        return transition['actions'], transition['values'], transition['states'], transition['neglogpacs']
 
     def train(self,
               lr,
diff --git a/baselines/ppo2/runner.py b/baselines/ppo2/runner.py
index 9a3c770..c87a85c 100644
--- a/baselines/ppo2/runner.py
+++ b/baselines/ppo2/runner.py
@@ -54,7 +54,7 @@ class Runner(AbstractEnvRunner):
             transition = {}
             transition['obs'] = self.obs.copy()
             transition['dones'] = dones
-            transition.update(self.model.step(observations=self.obs, **prev_state))
+            transition.update(self.model.step_as_dict(observations=self.obs, **prev_state))
             transition['values'] = transition['values']
 
             # Take actions in env and look the results
@@ -84,7 +84,7 @@ class Runner(AbstractEnvRunner):
             dtype = data_type[key] if key in data_type else np.float
             minibatch[key] = np.asarray(minibatch[key], dtype=dtype)
 
-        last_values = self.model.step(observations=self.obs, **self.states)['values']
+        last_values = self.model.step_as_dict(observations=self.obs, **self.states)['values']
 
         # Calculate returns and advantages.
         minibatch['advs'], minibatch['returns'] = \