support paddle 1.8.2 (#317)

examples/DQN_variant/train.py

@@ -93,7 +93,7 @@ def main():
     act_dim = env.action_space.n
 
     model = AtariModel(act_dim, args.algo)
-    if args.algo == 'Double':
+    if args.algo == 'DDQN':
         algorithm = parl.algorithms.DDQN(model, act_dim=act_dim, gamma=GAMMA)
     elif args.algo in ['DQN', 'Dueling']:
         algorithm = parl.algorithms.DQN(model, act_dim=act_dim, gamma=GAMMA)

parl/algorithms/fluid/ddqn.py

@@ -75,7 +75,7 @@ class DDQN(Algorithm):
         greedy_action = layers.argmax(next_action_value, axis=-1)
 
         # calculate the target q value with target network
-        batch_size = layers.cast(layers.shape(greedy_action)[0], dtype='int')
+        batch_size = layers.cast(layers.shape(greedy_action)[0], dtype='int32')
         range_tmp = layers.range(
             start=0, end=batch_size, step=1, dtype='int64') * self.act_dim
         a_indices = range_tmp + greedy_action