Fix episode buffer memory mapping on windows

Eclectic-Sheep · Jul 25, 2023 · 3c6f4af · 3c6f4af
1 parent ece0bbd
commit 3c6f4af
Show file tree

Hide file tree

Showing 3 changed files with 18 additions and 8 deletions.
diff --git a/sheeprl/data/buffers.py b/sheeprl/data/buffers.py
@@ -454,13 +454,17 @@ def add(self, episode: TensorDictBase) -> None:
             self._cum_lengths = cum_lengths.tolist()
         self._cum_lengths.append(len(self) + ep_len)
         if self._memmap:
+            episode_dir = None
+            if self._memmap_dir is not None:
+                episode_dir = self._memmap_dir / f"episode_{len(self._buf)}"
+                episode_dir.mkdir(parents=True, exist_ok=True)
             for k, v in episode.items():
                 episode[k] = MemmapTensor.from_tensor(
                     v,
-                    filename=None if self._memmap_dir is None else self._memmap_dir / f"{k}.memmap",
+                    filename=None if episode_dir is None else episode_dir / f"{k}.memmap",
                     transfer_ownership=False,
                 )
-            episode.memmap_(prefix=self._memmap_dir)
+            episode.memmap_(prefix=episode_dir)
         episode.to(self.device)
         self._buf.append(episode)
 

diff --git a/tests/test_data/test_buffers.py b/tests/test_data/test_buffers.py
@@ -189,4 +189,6 @@ def test_memmap_to_file_replay_buffer():
     fabric.save(ckpt_file, {"rb": rb})
     ckpt = fabric.load(ckpt_file)
     assert (ckpt["rb"]["observations"][:10] == rb["observations"][:10]).all()
+    del rb
+    del ckpt
     shutil.rmtree(root_dir)
diff --git a/tests/test_data/test_episode_buffer.py b/tests/test_data/test_episode_buffer.py
@@ -190,18 +190,22 @@ def test_memmap_to_file_episode_buffer():
     root_dir = os.path.join("pytest_" + str(int(time.time())))
     memmap_dir = os.path.join(root_dir, "memmap_buffer")
     rb = EpisodeBuffer(buf_size, sl, memmap=True, memmap_dir=memmap_dir)
-    for _ in range(buf_size // bs):
+    for i in range(buf_size // bs):
         td = TensorDict(
             {"observations": torch.randint(0, 256, (bs, 3, 64, 64), dtype=torch.uint8), "dones": torch.zeros(bs)},
             batch_size=[bs],
         )
         td["dones"][-1] = 1
         rb.add(td)
+        del td
         assert rb[-1].is_memmap()
+        assert os.path.exists(os.path.join(memmap_dir, f"episode_{i}", "meta.pt"))
+        assert os.path.exists(os.path.join(memmap_dir, f"episode_{i}", "dones.meta.pt"))
+        assert os.path.exists(os.path.join(memmap_dir, f"episode_{i}", "dones.memmap"))
+        assert os.path.exists(os.path.join(memmap_dir, f"episode_{i}", "observations.meta.pt"))
+        assert os.path.exists(os.path.join(memmap_dir, f"episode_{i}", "observations.memmap"))
     assert rb.is_memmap
-    assert os.path.exists(os.path.join(memmap_dir, "meta.pt"))
-    assert os.path.exists(os.path.join(memmap_dir, "dones.meta.pt"))
-    assert os.path.exists(os.path.join(memmap_dir, "dones.memmap"))
-    assert os.path.exists(os.path.join(memmap_dir, "observations.meta.pt"))
-    assert os.path.exists(os.path.join(memmap_dir, "observations.memmap"))
+    for ep in rb.buffer:
+        del ep
+    del rb
     shutil.rmtree(root_dir)