[BugFix] patch rand_action in TransformedEnv to read the base_env method

ghstack-source-id: f4d4769ddbbd0a61a097c1ab2f7cb9a2647156bc
Pull Request resolved: #2699

Author: vmoens

torchrl/envs/transforms/transforms.py

@@ -795,6 +795,17 @@ def input_spec(self) -> TensorSpec:
             input_spec = self.__dict__.get("_input_spec", None)
         return input_spec
 
+    def rand_action(self, tensordict: Optional[TensorDictBase] = None) -> TensorDict:
+        if self.base_env.rand_action is not EnvBase.rand_action:
+            # TODO: this will fail if the transform modifies the input.
+            #  For instance, if PendulumEnv overrides rand_action and we build a
+            #  env = PendulumEnv().append_transform(ActionDiscretizer(num_intervals=4))
+            #  env.rand_action will NOT have a discrete action!
+            #  Getting a discrete action would require coding the inverse transform of an action within
+            #  ActionDiscretizer (ie, float->int, not int->float).
+            return self.base_env.rand_action(tensordict)
+        return super().rand_action(tensordict)
+
     def _step(self, tensordict: TensorDictBase) -> TensorDictBase:
         # No need to clone here because inv does it already
         # tensordict = tensordict.clone(False)