fix a bug in re-index replay buffer (fix #82)

test/base/test_buffer.py

@@ -1,5 +1,5 @@
 import numpy as np
-from tianshou.data import ReplayBuffer, PrioritizedReplayBuffer
+from tianshou.data import Batch, ReplayBuffer, PrioritizedReplayBuffer
 
 if __name__ == '__main__':
     from env import MyTestEnv
@@ -29,6 +29,26 @@ def test_replaybuffer(size=10, bufsize=20):
     assert buf2[-1].obs == buf[4].obs
 
 
+def test_ignore_obs_next(size=10):
+    # Issue 82
+    buf = ReplayBuffer(size, ignore_obs_net=True)
+    for i in range(size):
+        buf.add(obs={'mask1': np.array([i, 1, 1, 0, 0]),
+                     'mask2': np.array([i + 4, 0, 1, 0, 0])},
+                act={'act_id': i,
+                     'position_id': i + 3},
+                rew=i,
+                done=i % 3 == 0,
+                info={'if': i})
+    indice = np.arange(len(buf))
+    orig = np.arange(len(buf))
+    data = buf[indice]
+    data2 = buf[indice]
+    assert isinstance(data, Batch)
+    assert isinstance(data2, Batch)
+    assert np.allclose(indice, orig)
+
+
 def test_stack(size=5, bufsize=9, stack_num=4):
     env = MyTestEnv(size)
     buf = ReplayBuffer(bufsize, stack_num)
@@ -74,5 +94,6 @@ def test_priortized_replaybuffer(size=32, bufsize=15):
 
 if __name__ == '__main__':
     test_replaybuffer()
+    test_ignore_obs_next()
     test_stack()
     test_priortized_replaybuffer(233333, 200000)

test/discrete/test_pg.py

@@ -42,21 +42,21 @@ def test_fn(size=2560):
     )
     batch = fn(batch, buf, 0)
     ans = np.array([0, 1.23, 2.3, 3, 4.5, 5, 6.7, 7])
-    assert abs(batch.returns - ans).sum() <= 1e-5
+    assert np.allclose(batch.returns, ans)
     batch = Batch(
         done=np.array([0, 1, 0, 1, 0, 1, 0.]),
         rew=np.array([7, 6, 1, 2, 3, 4, 5.]),
     )
     batch = fn(batch, buf, 0)
     ans = np.array([7.6, 6, 1.2, 2, 3.4, 4, 5])
-    assert abs(batch.returns - ans).sum() <= 1e-5
+    assert np.allclose(batch.returns, ans)
     batch = Batch(
         done=np.array([0, 1, 0, 1, 0, 0, 1.]),
         rew=np.array([7, 6, 1, 2, 3, 4, 5.]),
     )
     batch = fn(batch, buf, 0)
     ans = np.array([7.6, 6, 1.2, 2, 3.45, 4.5, 5])
-    assert abs(batch.returns - ans).sum() <= 1e-5
+    assert np.allclose(batch.returns, ans)
     batch = Batch(
         done=np.array([0, 0, 0, 1., 0, 0, 0, 1, 0, 0, 0, 1]),
         rew=np.array([
@@ -68,7 +68,7 @@ def test_fn(size=2560):
         454.8344, 376.1143, 291.298, 200.,
         464.5610, 383.1085, 295.387, 201.,
         474.2876, 390.1027, 299.476, 202.])
-    assert abs(ret.returns - returns).sum() <= 1e-3
+    assert np.allclose(ret.returns, returns)
     if __name__ == '__main__':
         batch = Batch(
             done=np.random.randint(100, size=size) == 0,

tianshou/data/buffer.py

@@ -250,6 +250,8 @@ class ReplayBuffer(object):
                     else self._size - indice.stop if indice.stop < 0
                     else indice.stop,
                     1 if indice.step is None else indice.step)
+        else:
+            indice = np.array(indice)
         # set last frame done to True
         last_index = (self._index - 1 + self._size) % self._size
         last_done, self.done[last_index] = self.done[last_index], True