From 2e56337efd8b23ed3bc2eeddea5260a591c12d0a Mon Sep 17 00:00:00 2001
From: Bo Zhou <2466956298@qq.com>
Date: Wed, 24 Jun 2020 05:36:43 -0500
Subject: [PATCH] support paddle 1.8.2 (#317)

---
 examples/DQN_variant/train.py | 2 +-
 parl/algorithms/fluid/ddqn.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/DQN_variant/train.py b/examples/DQN_variant/train.py
index 5ca16df..e2ef720 100644
--- a/examples/DQN_variant/train.py
+++ b/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)
diff --git a/parl/algorithms/fluid/ddqn.py b/parl/algorithms/fluid/ddqn.py
index 03c0ced..e2fa7dc 100644
--- a/parl/algorithms/fluid/ddqn.py
+++ b/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
-- 
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