diff --git a/test/mocking_classes.py b/test/mocking_classes.py
index 5f92e0da52c..757f12a98c7 100644
--- a/test/mocking_classes.py
+++ b/test/mocking_classes.py
@@ -7,6 +7,7 @@
 import torch
 import torch.nn as nn
 from tensordict.tensordict import TensorDict, TensorDictBase
+
 from torchrl.data.tensor_specs import (
     BinaryDiscreteTensorSpec,
     BoundedTensorSpec,
@@ -212,13 +213,16 @@ def _step(self, tensordict):
         self.counter += 1
         # We use tensordict.batch_size instead of self.batch_size since this method will also be used by MockBatchedUnLockedEnv
         n = (
-            torch.full(tensordict.batch_size, self.counter)
+            torch.full(
+                (*tensordict.batch_size, *self.observation_spec["observation"].shape),
+                self.counter,
+            )
             .to(self.device)
             .to(torch.get_default_dtype())
         )
         done = self.counter >= self.max_val
         done = torch.full(
-            tensordict.batch_size, done, dtype=torch.bool, device=self.device
+            (*tensordict.batch_size, 1), done, dtype=torch.bool, device=self.device
         )
 
         return TensorDict(
@@ -235,12 +239,14 @@ def _reset(self, tensordict: TensorDictBase, **kwargs) -> TensorDictBase:
             batch_size = tensordict.batch_size
 
         n = (
-            torch.full(batch_size, self.counter)
+            torch.full(
+                (*batch_size, *self.observation_spec["observation"].shape), self.counter
+            )
             .to(self.device)
             .to(torch.get_default_dtype())
         )
         done = self.counter >= self.max_val
-        done = torch.full(batch_size, done, dtype=torch.bool, device=self.device)
+        done = torch.full((*batch_size, 1), done, dtype=torch.bool, device=self.device)
 
         return TensorDict(
             {"reward": n, "done": done, "observation": n},
diff --git a/test/test_env.py b/test/test_env.py
index a1e6a725e34..a36c88b6282 100644
--- a/test/test_env.py
+++ b/test/test_env.py
@@ -367,6 +367,16 @@ def test_mb_env_batch_lock(self, device, seed=0):
 
 
 class TestParallel:
+    @pytest.mark.parametrize("num_parallel_env", [1, 10])
+    @pytest.mark.parametrize("env_batch_size", [[], (32,), (32, 1), (32, 0)])
+    def test_env_with_batch_size(self, num_parallel_env, env_batch_size):
+        env = MockBatchedLockedEnv(device="cpu", batch_size=torch.Size(env_batch_size))
+        env.set_seed(1)
+        parallel_env = ParallelEnv(num_parallel_env, lambda: env)
+        parallel_env.start()
+        assert parallel_env.batch_size == (num_parallel_env, *env_batch_size)
+        parallel_env.close()
+
     @pytest.mark.skipif(not _has_dmc, reason="no dm_control")
     @pytest.mark.parametrize("env_task", ["stand,stand,stand", "stand,walk,stand"])
     @pytest.mark.parametrize("share_individual_td", [True, False])
diff --git a/torchrl/envs/vec_env.py b/torchrl/envs/vec_env.py
index f119e9e2151..a74a70c3d86 100644
--- a/torchrl/envs/vec_env.py
+++ b/torchrl/envs/vec_env.py
@@ -209,9 +209,10 @@ def _get_metadata(
     ):
         if self._single_task:
             # if EnvCreator, the metadata are already there
-            self.meta_data = get_env_metadata(
-                create_env_fn[0], create_env_kwargs[0]
-            ).expand(self.num_workers)
+            meta_data = get_env_metadata(create_env_fn[0], create_env_kwargs[0])
+            self.meta_data = meta_data.expand(
+                *(self.num_workers, *meta_data.batch_size)
+            )
         else:
             n_tasks = len(create_env_fn)
             self.meta_data = []