diff --git a/test/base/test_batch.py b/test/base/test_batch.py
index d169085..eafd7b3 100644
--- a/test/base/test_batch.py
+++ b/test/base/test_batch.py
@@ -1,4 +1,5 @@
 import pytest
+import pickle
 import torch
 import numpy as np
 
@@ -30,6 +31,15 @@ def test_batch_over_batch():
     assert batch2[-1].b.b == 0
 
 
+def test_batch_pickle():
+    batch = Batch(obs=Batch(a=0.0, c=torch.Tensor([1.0, 2.0])),
+                  np=np.zeros([3, 4]))
+    batch_pk = pickle.loads(pickle.dumps(batch))
+    assert batch.obs.a == batch_pk.obs.a
+    assert torch.all(batch.obs.c == batch_pk.obs.c)
+    assert np.all(batch.np == batch_pk.np)
+
+
 def test_batch_from_to_numpy_without_copy():
     batch = Batch(a=np.ones((1,)), b=Batch(c=np.ones((1,))))
     a_mem_addr_orig = batch["a"].__array_interface__['data'][0]
diff --git a/tianshou/data/batch.py b/tianshou/data/batch.py
index 526cea0..e0129f7 100644
--- a/tianshou/data/batch.py
+++ b/tianshou/data/batch.py
@@ -1,8 +1,15 @@
 import torch
+import warnings
 import pprint
 import numpy as np
 from typing import Any, List, Union, Iterator, Optional
 
+# Disable pickle warning related to torch, since it has been removed
+# on torch master branch. See Pull Request #39003 for details:
+# https://github.com/pytorch/pytorch/pull/39003
+warnings.filterwarnings(
+    "ignore", message="pickle support for Storage will be removed in 1.5.")
+
 
 class Batch:
     """Tianshou provides :class:`~tianshou.data.Batch` as the internal data
@@ -66,9 +73,13 @@ class Batch:
         [11 22] [6 6]
     """
 
+    def __new__(cls, **kwargs) -> None:
+        self = super().__new__(cls)
+        self._meta = {}
+        return self
+
     def __init__(self, **kwargs) -> None:
         super().__init__()
-        self._meta = {}
         for k, v in kwargs.items():
             if isinstance(v, (list, np.ndarray)) \
                     and len(v) > 0 and isinstance(v[0], dict) and k != 'info':
@@ -86,6 +97,25 @@ class Batch:
             else:
                 self.__dict__[k] = kwargs[k]
 
+    def __getstate__(self):
+        """Pickling interface. Only the actual data are serialized
+        for both efficiency and simplicity.
+        """
+        state = {}
+        for k in self.keys():
+            v = self[k]
+            if isinstance(v, Batch):
+                v = v.__getstate__()
+            state[k] = v
+        return state
+
+    def __setstate__(self, state):
+        """Unpickling interface. At this point, self is an empty Batch
+        instance that has not been initialized, so it can safely be
+        initialized by the pickle state.
+        """
+        self.__init__(**state)
+
     def __getitem__(self, index: Union[str, slice]) -> Union['Batch', dict]:
         """Return self[index]."""
         if isinstance(index, str):
diff --git a/tianshou/env/vecenv.py b/tianshou/env/vecenv.py
index 6145cc7..f2ea4b7 100644
--- a/tianshou/env/vecenv.py
+++ b/tianshou/env/vecenv.py
@@ -12,7 +12,7 @@ except ImportError:
 from tianshou.env.utils import CloudpickleWrapper
 
 
-class BaseVectorEnv(ABC, gym.Wrapper):
+class BaseVectorEnv(ABC, gym.Env):
     """Base class for vectorized environments wrapper. Usage:
     ::
 
@@ -79,8 +79,14 @@ class BaseVectorEnv(ABC, gym.Wrapper):
 
     @abstractmethod
     def seed(self, seed: Optional[Union[int, List[int]]] = None) -> None:
-        """Set the seed for all environments. Accept ``None``, an int (which
-        will extend ``i`` to ``[i, i + 1, i + 2, ...]``) or a list.
+        """Set the seed for all environments.
+
+        Accept ``None``, an int (which will extend ``i`` to
+        ``[i, i + 1, i + 2, ...]``) or a list.
+
+        :return: The list of seeds used in this env's random number generators.
+        The first value in the list should be the "main" seed, or the value
+        which a reproducer should pass to 'seed'.
         """
         pass
 
@@ -91,7 +97,11 @@ class BaseVectorEnv(ABC, gym.Wrapper):
 
     @abstractmethod
     def close(self) -> None:
-        """Close all of the environments."""
+        """Close all of the environments.
+
+        Environments will automatically close() themselves when garbage
+        collected or when the program exits.
+        """
         pass