Refactor around @AbstractMethod

Author: kngwyu

rlpy/agents/agent.py

@@ -97,7 +97,7 @@ def learn(self, s, p_actions, a, r, ns, np_actions, na, terminal):
         :param na: action taken in the next state
         :param terminal: boolean indicating whether next state (ns) is terminal
         """
-        return NotImplementedError
+        pass
 
     def episode_terminated(self):
         """

rlpy/domains/cartpole_base.py

@@ -251,13 +251,15 @@ def _getReward(self, a, s=None):
         (e.g. for swinging the pendulum up vs. balancing).
 
         """
-        raise NotImplementedError
+        raise NotImplementedError("_getReward should be implemented in child classes")
 
+    @abstractmethod
     def show_domain(self, a=0):
-        raise NotImplementedError
+        pass
 
+    @abstractmethod
     def show_learning(self, representation):
-        raise NotImplementedError
+        pass
 
     def possible_actions(self, s=None):
         """
@@ -266,9 +268,11 @@ def possible_actions(self, s=None):
         """
         return np.arange(self.actions_num)
 
+    @abstractmethod
     def step(self):
-        errMsg = "Implemented in child classes which call _stepFourState()"
-        raise NotImplementedError(errMsg)
+        """Implemented in child classes which call _stepFourState()
+        """
+        pass
 
     def _stepFourState(self, s, a):
         """
@@ -656,7 +660,7 @@ def euler_int(self, df, x0, times):
         return [ns]
 
 
-class StateIndex(object):
+class StateIndex:
 
     """
     Flexible way to index states in the CartPole Domain.

rlpy/domains/domain.py

@@ -164,6 +164,7 @@ def show_learning(self, representation):
         """
         pass
 
+    @abstractmethod
     def s0(self):
         """
         Begins a new episode and returns the initial observed state of the Domain.
@@ -172,7 +173,7 @@ def s0(self):
         :return: A numpy array that defines the initial domain state.
 
         """
-        raise NotImplementedError("Children need to implement this method")
+        pass
 
     def possible_actions(self, s=None):
         """

rlpy/policies/policy.py

@@ -66,7 +66,7 @@ def pi(self, s, terminal, p_actions):
         :param terminal: boolean, whether or not the *s* is a terminal state.
         :param p_actions: a list / array of all possible actions in *s*.
         """
-        raise NotImplementedError
+        pass
 
     def turnOffExploration(self):
         """
@@ -105,7 +105,7 @@ def pi(self, s, terminal, p_actions):
     @abstractmethod
     def dlogpi(self, s, a):
         """derivative of the log probabilities of the policy"""
-        return NotImplementedError
+        pass
 
     def prob(self, s, a):
         """
@@ -128,4 +128,4 @@ def probabilities(self, s, terminal):
         returns a vector of num_actions length containing the normalized
         probabilities for taking each action given the state s
         """
-        return NotImplementedError
+        pass