diff --git a/torchrl/envs/transforms/__init__.py b/torchrl/envs/transforms/__init__.py
index 9a702c8d290..cdb4d35f4ce 100644
--- a/torchrl/envs/transforms/__init__.py
+++ b/torchrl/envs/transforms/__init__.py
@@ -28,5 +28,6 @@
     VecNorm,
     gSDENoise,
     TensorDictPrimer,
+    SqueezeTransform,
 )
-from .vip import VIPTransform
+from .vip import VIPTransform, VIPRewardTransform
diff --git a/torchrl/envs/transforms/transforms.py b/torchrl/envs/transforms/transforms.py
index 91ea7049a1f..6e0f612f511 100644
--- a/torchrl/envs/transforms/transforms.py
+++ b/torchrl/envs/transforms/transforms.py
@@ -1049,15 +1049,26 @@ def _apply_transform(self, observation: torch.Tensor) -> torch.Tensor:
 
     def set_parent(self, parent: Union[Transform, EnvBase]) -> None:
         out = super().set_parent(parent)
-        observation_spec = self.parent.observation_spec
-        for key in self.in_keys:
-            if key in observation_spec:
-                observation_spec = observation_spec[key]
-                if self.first_dim >= 0:
-                    self.first_dim = self.first_dim - len(observation_spec.shape)
-                if self.last_dim >= 0:
-                    self.last_dim = self.last_dim - len(observation_spec.shape)
-                break
+        try:
+            observation_spec = self.parent.observation_spec
+            for key in self.in_keys:
+                if key in observation_spec:
+                    observation_spec = observation_spec[key]
+                    if self.first_dim >= 0:
+                        self.first_dim = self.first_dim - len(observation_spec.shape)
+                    if self.last_dim >= 0:
+                        self.last_dim = self.last_dim - len(observation_spec.shape)
+                    break
+        except ValueError:
+            if self.first_dim >= 0 or self.last_dim >= 0:
+                raise ValueError(
+                    f"FlattenObservation got first and last dim {self.first_dim} amd {self.last_dim}. "
+                    f"Those values assume that the observation spec is known, which requires the "
+                    f"parent environment to be set. "
+                    f"Consider setting the parent environment beforehand (ie passing the transform "
+                    f"to `TransformedEnv.append_transform()`) or setting strictly negative "
+                    f"flatten dimensions to the transform."
+                )
         return out
 
     @_apply_to_composite
@@ -1119,7 +1130,15 @@ def set_parent(self, parent: Union[Transform, EnvBase]) -> None:
             self._unsqueeze_dim = self._unsqueeze_dim_orig
         else:
             parent = self.parent
-            batch_size = parent.batch_size
+            try:
+                batch_size = parent.batch_size
+            except AttributeError:
+                raise ValueError(
+                    f"Got the unsqueeze dimension {self._unsqueeze_dim_orig} which is greater or equal to zero. "
+                    f"However this requires to know what the parent environment is, but it has not been provided. "
+                    f"Consider providing a negative dimension or setting the transform using the "
+                    f"`TransformedEnv.append_transform()` method."
+                )
             self._unsqueeze_dim = self._unsqueeze_dim_orig + len(batch_size)
         return super().set_parent(parent)