[Feature] single_<attr>_spec

ghstack-source-id: 27e247ea1775e455999a114dd6d95fac748376c4
Pull Request resolved: #2549

test/test_env.py

@@ -3510,6 +3510,22 @@ def test_serial_partial_step_and_maybe_reset(self, use_buffers, device, env_devi
             assert (td[3].get("next") != 0).any()
 
 
+def test_single_env_spec():
+    env = NestedCountingEnv(batch_size=[3, 1, 7])
+    assert not env.single_full_action_spec.shape
+    assert not env.single_full_done_spec.shape
+    assert not env.single_input_spec.shape
+    assert not env.single_full_observation_spec.shape
+    assert not env.single_output_spec.shape
+    assert not env.single_full_reward_spec.shape
+
+    assert env.single_action_spec.shape
+    assert env.single_reward_spec.shape
+
+    assert env.output_spec.is_in(env.single_output_spec.zeros(env.shape))
+    assert env.input_spec.is_in(env.single_input_spec.zeros(env.shape))
+
+
 if __name__ == "__main__":
     args, unknown = argparse.ArgumentParser().parse_known_args()
     pytest.main([__file__, "--capture", "no", "--exitfirst"] + unknown)

torchrl/envs/common.py

@@ -1480,6 +1480,77 @@ def full_state_spec(self) -> Composite:
     def full_state_spec(self, spec: Composite) -> None:
         self.state_spec = spec
 
+    # Single-env specs can be used to remove the batch size from the spec
+    @property
+    def batch_dims(self):
+        return len(self.batch_size)
+
+    def _make_single_env_spec(self, spec: TensorSpec) -> TensorSpec:
+        if not self.batch_dims:
+            return spec
+        idx = tuple(0 for _ in range(self.batch_dims))
+        return spec[idx]
+
+    @property
+    def single_full_action_spec(self) -> Composite:
+        """Returns the action spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.full_action_spec)
+
+    @property
+    def single_action_spec(self) -> TensorSpec:
+        """Returns the action spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.action_spec)
+
+    @property
+    def single_full_observation_spec(self) -> Composite:
+        """Returns the observation spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.full_action_spec)
+
+    @property
+    def single_observation_spec(self) -> Composite:
+        """Returns the observation spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.observation_spec)
+
+    @property
+    def single_full_reward_spec(self) -> Composite:
+        """Returns the reward spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.full_action_spec)
+
+    @property
+    def single_reward_spec(self) -> TensorSpec:
+        """Returns the reward spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.reward_spec)
+
+    @property
+    def single_full_done_spec(self) -> Composite:
+        """Returns the done spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.full_action_spec)
+
+    @property
+    def single_done_spec(self) -> TensorSpec:
+        """Returns the done spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.done_spec)
+
+    @property
+    def single_output_spec(self) -> Composite:
+        """Returns the output spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.output_spec)
+
+    @property
+    def single_input_spec(self) -> Composite:
+        """Returns the input spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.input_spec)
+
+    @property
+    def single_full_state_spec(self) -> Composite:
+        """Returns the state spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.full_state_spec)
+
+    @property
+    def single_state_spec(self) -> TensorSpec:
+        """Returns the state spec of the env as if it had no batch dimensions."""
+        return self._make_single_env_spec(self.state_spec)
+
     def step(self, tensordict: TensorDictBase) -> TensorDictBase:
         """Makes a step in the environment.