small bugfix when using sgd for mle since sgd has no booked information and...

small bugfix when using sgd for mle since sgd has no booked information and not the full belief state is given in the dataset

convlab/policy/mle/loader.py

@@ -105,6 +105,7 @@ class PolicyDataVectorizer:
                 state['terminated'] = data_point['terminated']
                 if self.dst is not None and state['terminated']:
                     self.dst.init_session()
+                if "booked" in data_point:
                     state['booked'] = data_point['booked']
                 dialogue_act = flatten_acts(data_point['dialogue_acts'])
 

convlab/policy/vector/vector_binary.py

@@ -47,8 +47,15 @@ class VectorBinary(VectorBase):
         opp_act_vec = self.vectorize_user_act(state)
         last_act_vec = self.vectorize_system_act(state)
         belief_state, domain_active_dict = self.vectorize_belief_state(state, domain_active_dict)
+        if "booked" in state:
             book = self.vectorize_booked(state)
+        else:
+            book = []
+        if self.db is not None:
             degree, number_entities_dict = self.pointer()
+        else:
+            degree = []
+            number_entities_dict = {}
         final = 1. if state['terminated'] else 0.
 
         state_vec = np.r_[opp_act_vec, last_act_vec,
@@ -82,6 +89,7 @@ class VectorBinary(VectorBase):
         belief_state = np.zeros(self.belief_state_dim)
         i = 0
         for domain in self.belief_domains:
+            if domain in state['belief_state']:
                 for slot, value in state['belief_state'][domain].items():
                     if value:
                         belief_state[i] = 1.