Fix name collisions between core env and gym envs. Improve benchmarking

benchmarks/main.py

@@ -5,12 +5,12 @@
 from sim import time_multi_drone_reset, time_multi_drone_step, time_sim_reset, time_sim_step
 
 
-def print_benchmark_results(name: str, timings: list[float]):
-    print(f"\nResults for {name}:")
+def print_benchmark_results(name: str, timings: list[float], n_envs: int, device: str):
+    print(f"\nResults for {name} ({n_envs} envs, {device}):")
     print(f"Mean/std: {np.mean(timings):.2e}s +- {np.std(timings):.2e}s")
     print(f"Min time: {np.min(timings):.2e}s")
     print(f"Max time: {np.max(timings):.2e}s")
-    print(f"FPS: {1 / np.mean(timings):.2f}")
+    print(f"FPS: {n_envs / np.mean(timings):.2f}")
 
 
 def main(
@@ -19,18 +19,31 @@ def main(
     multi_drone: bool = False,
     reset: bool = True,
     step: bool = True,
+    vec_size: int = 1,
+    device: str = "cpu",
 ):
     reset_fn, step_fn = time_sim_reset, time_sim_step
     if multi_drone:
         reset_fn, step_fn = time_multi_drone_reset, time_multi_drone_step
     if reset:
-        timings = reset_fn(n_tests=n_tests, number=number)
-        print_benchmark_results(name="Racing env reset", timings=timings / number)
+        timings = reset_fn(n_tests=n_tests, number=number, n_envs=vec_size, device=device)
+        print_benchmark_results(
+            name="Racing env reset", timings=timings / number, n_envs=vec_size, device=device
+        )
     if step:
-        timings = step_fn(n_tests=n_tests, number=number)
-        print_benchmark_results(name="Racing env steps", timings=timings / number)
-        timings = step_fn(n_tests=n_tests, number=number, physics_mode="sys_id")
-        print_benchmark_results(name="Racing env steps (sys_id backend)", timings=timings / number)
+        timings = step_fn(n_tests=n_tests, number=number, n_envs=vec_size, device=device)
+        print_benchmark_results(
+            name="Racing env steps", timings=timings / number, n_envs=vec_size, device=device
+        )
+        timings = step_fn(
+            n_tests=n_tests, number=number, physics_mode="sys_id", n_envs=vec_size, device=device
+        )
+        print_benchmark_results(
+            name="Racing env steps (sys_id backend)",
+            timings=timings / number,
+            n_envs=vec_size,
+            device=device,
+        )
         # timings = step_fn(n_tests=n_tests, number=number, physics_mode="mujoco")
         # print_benchmark_results(name="Sim steps (mujoco backend)", timings=timings / number)
 

benchmarks/sim.py

@@ -19,11 +19,13 @@
 
 env_setup_code = """
 import gymnasium
+import jax
 
 import lsy_drone_racing
 
-env = gymnasium.make(
+env = gymnasium.make_vec(
     config.env.id,
+    num_envs={num_envs},
     freq=config.env.freq,
     sim_config=config.sim,
     sensor_range=config.env.sensor_range,
@@ -32,21 +34,29 @@
     randomizations=config.env.get("randomizations"),
     random_resets=config.env.random_resets,
     seed=config.env.seed,
+    device='{device}',
 )
+
+# JIT compile the reset and step functions
 env.reset()
-env.step(env.action_space.sample())  # JIT compile
-env.reset()
-env.action_space.seed(42)
-action = env.action_space.sample()
+env.step(env.action_space.sample())
+jax.block_until_ready(env.unwrapped.data)
+# JIT masked reset (used in autoreset)
+mask = env.unwrapped.data.marked_for_reset
+mask = mask.at[0].set(True)
+env.unwrapped._reset(mask=mask)  # enforce masked reset compile
+jax.block_until_ready(env.unwrapped.data)
+env.action_space.seed(2)
 """
 
 attitude_env_setup_code = """
 import gymnasium
+import jax
 
 import lsy_drone_racing
 
-env = gymnasium.make('DroneRacingAttitude-v0',
-    config.env.id,
+env = gymnasium.make_vec('DroneRacingAttitude-v0',
+    num_envs={num_envs},
     freq=config.env.freq,
     sim_config=config.sim,
     sensor_range=config.env.sensor_range,
@@ -55,12 +65,19 @@
     randomizations=config.env.get("randomizations"),
     random_resets=config.env.random_resets,
     seed=config.env.seed,
+    device='{device}',
 )
+
+# JIT compile the reset and step functions
 env.reset()
-env.step(env.action_space.sample())  # JIT compile
-env.reset()
-env.action_space.seed(42)
-action = env.action_space.sample()
+env.step(env.action_space.sample())
+jax.block_until_ready(env.unwrapped.data)
+# JIT masked reset (used in autoreset)
+mask = env.unwrapped.data.marked_for_reset
+mask = mask.at[0].set(True)
+env.unwrapped._reset(mask=mask)  # enforce masked reset compile
+jax.block_until_ready(env.unwrapped.data)
+env.action_space.seed(2)
 """
 
 load_multi_drone_config_code = f"""
@@ -76,9 +93,11 @@
 import jax
 
 import lsy_drone_racing
-from lsy_drone_racing.envs.multi_drone_race import MultiDroneRaceEnv
+from lsy_drone_racing.envs.multi_drone_race import VecMultiDroneRaceEnv
 
-env = gymnasium.make('MultiDroneRacing-v0',
+
+env = gymnasium.make_vec('MultiDroneRacing-v0',
+    num_envs={num_envs},
     n_drones=config.env.n_drones,
     freq=config.env.freq,
     sim_config=config.sim,
@@ -88,58 +107,72 @@
     randomizations=config.env.get("randomizations"),
     random_resets=config.env.random_resets,
     seed=config.env.seed,
-    device='cpu',
+    device='{device}',
 )
 
+# JIT compile the reset and step functions
 env.reset()
-# JIT step
 env.step(env.action_space.sample())
 jax.block_until_ready(env.unwrapped.data)
 # JIT masked reset (used in autoreset)
 mask = env.unwrapped.data.marked_for_reset
 mask = mask.at[0].set(True)
-super(MultiDroneRaceEnv, env.unwrapped).reset(mask=mask)  # enforce masked reset compile
+env.unwrapped._reset(mask=mask)  # enforce masked reset compile
 jax.block_until_ready(env.unwrapped.data)
 env.action_space.seed(2)
 """
 
 
-def time_sim_reset(n_tests: int = 10, number: int = 1) -> NDArray[np.floating]:
-    setup = load_config_code + env_setup_code
+def time_sim_reset(
+    n_tests: int = 10, number: int = 1, n_envs: int = 1, device: str = "cpu"
+) -> NDArray[np.floating]:
+    setup = load_config_code + env_setup_code.format(num_envs=n_envs, device=device)
     stmt = """env.reset()"""
     return np.array(timeit.repeat(stmt=stmt, setup=setup, number=number, repeat=n_tests))
 
 
 def time_sim_step(
-    n_tests: int = 10, number: int = 1, physics_mode: str = "analytical"
+    n_tests: int = 10,
+    number: int = 1,
+    physics_mode: str = "analytical",
+    n_envs: int = 1,
+    device: str = "cpu",
 ) -> NDArray[np.floating]:
     modify_config_code = f"""config.sim.physics = '{physics_mode}'\n"""
-    setup = load_config_code + modify_config_code + env_setup_code + "\nenv.reset()"
-    stmt = """env.step(action)"""
+    _env_setup_code = env_setup_code.format(num_envs=n_envs, device=device)
+    setup = load_config_code + modify_config_code + _env_setup_code + "\nenv.reset()"
+    stmt = """env.step(env.action_space.sample())"""
     return np.array(timeit.repeat(stmt=stmt, setup=setup, number=number, repeat=n_tests))
 
 
-def time_sim_attitude_step(n_tests: int = 10, number: int = 1) -> NDArray[np.floating]:
-    setup = load_config_code + attitude_env_setup_code + "\nenv.reset()"
-    stmt = """env.step(action)"""
+def time_sim_attitude_step(
+    n_tests: int = 10, number: int = 1, n_envs: int = 1, device: str = "cpu"
+) -> NDArray[np.floating]:
+    env_setup_code = attitude_env_setup_code.format(num_envs=n_envs, device=device)
+    setup = load_config_code + env_setup_code + "\nenv.reset()"
+    stmt = """env.step(env.action_space.sample())"""
     return np.array(timeit.repeat(stmt=stmt, setup=setup, number=number, repeat=n_tests))
 
 
-def time_multi_drone_reset(n_tests: int = 10, number: int = 1) -> NDArray[np.floating]:
-    setup = load_multi_drone_config_code + multi_drone_env_setup_code + "\nenv.reset()"
+def time_multi_drone_reset(
+    n_tests: int = 10, number: int = 1, n_envs: int = 1, device: str = "cpu"
+) -> NDArray[np.floating]:
+    env_setup_code = multi_drone_env_setup_code.format(num_envs=n_envs, device=device)
+    setup = load_multi_drone_config_code + env_setup_code + "\nenv.reset()"
     stmt = """env.reset()"""
     return np.array(timeit.repeat(stmt=stmt, setup=setup, number=number, repeat=n_tests))
 
 
 def time_multi_drone_step(
-    n_tests: int = 10, number: int = 100, physics_mode: str = "analytical"
+    n_tests: int = 10,
+    number: int = 100,
+    physics_mode: str = "analytical",
+    n_envs: int = 1,
+    device: str = "cpu",
 ) -> NDArray[np.floating]:
     modify_config_code = f"""config.sim.physics = '{physics_mode}'\n"""
-    setup = (
-        load_multi_drone_config_code
-        + modify_config_code
-        + multi_drone_env_setup_code
-        + "\nenv.reset()"
-    )
+    env_setup_code = multi_drone_env_setup_code.format(num_envs=n_envs, device=device)
+
+    setup = load_multi_drone_config_code + modify_config_code + env_setup_code + "\nenv.reset()"
     stmt = """env.step(env.action_space.sample())"""
     return np.array(timeit.repeat(stmt=stmt, setup=setup, number=number, repeat=n_tests))

lsy_drone_racing/envs/drone_race.py

@@ -78,7 +78,7 @@ def reset(self, seed: int | None = None, options: dict | None = None) -> tuple[d
         Returns:
             The initial observation and info.
         """
-        obs, info = super().reset(seed=seed, options=options)
+        obs, info = self._reset(seed=seed, options=options)
         obs = {k: v[0, 0] for k, v in obs.items()}
         info = {k: v[0, 0] for k, v in info.items()}
         return obs, info
@@ -92,7 +92,7 @@ def step(self, action: NDArray[np.floating]) -> tuple[dict, float, bool, bool, d
         Returns:
             Observation, reward, terminated, truncated, and info.
         """
-        obs, reward, terminated, truncated, info = super().step(action)
+        obs, reward, terminated, truncated, info = self._step(action)
         obs = {k: v[0, 0] for k, v in obs.items()}
         info = {k: v[0, 0] for k, v in info.items()}
         return obs, float(reward[0, 0]), bool(terminated[0, 0]), bool(truncated[0, 0]), info
@@ -163,7 +163,7 @@ def reset(self, seed: int | None = None, options: dict | None = None) -> tuple[d
         Returns:
             The initial observation and info.
         """
-        obs, info = super().reset(seed=seed, options=options)
+        obs, info = self._reset(seed=seed, options=options)
         obs = {k: v[:, 0] for k, v in obs.items()}
         info = {k: v[:, 0] for k, v in info.items()}
         return obs, info
@@ -179,7 +179,7 @@ def step(
         Returns:
             Observation, reward, terminated, truncated, and info.
         """
-        obs, reward, terminated, truncated, info = super().step(action)
+        obs, reward, terminated, truncated, info = self._step(action)
         obs = {k: v[:, 0] for k, v in obs.items()}
         info = {k: v[:, 0] for k, v in info.items()}
         return obs, reward[:, 0], terminated[:, 0], truncated[:, 0], info

lsy_drone_racing/envs/multi_drone_race.py

@@ -82,7 +82,7 @@ def reset(self, seed: int | None = None, options: dict | None = None) -> tuple[d
         Returns:
             Observation and info for all drones.
         """
-        obs, info = super().reset(seed=seed, options=options)
+        obs, info = self._reset(seed=seed, options=options)
         obs = {k: v[0] for k, v in obs.items()}
         info = {k: v[0] for k, v in info.items()}
         return obs, info
@@ -98,7 +98,7 @@ def step(
         Returns:
             Observation, reward, terminated, truncated, and info for all drones.
         """
-        obs, reward, terminated, truncated, info = super().step(action)
+        obs, reward, terminated, truncated, info = self._step(action)
         obs = {k: v[0] for k, v in obs.items()}
         info = {k: v[0] for k, v in info.items()}
         return obs, reward[0], terminated[0], truncated[0], info
@@ -165,3 +165,25 @@ def __init__(
             build_observation_space(n_gates, n_obstacles), n_drones
         )
         self.observation_space = batch_space(batch_space(self.single_observation_space), num_envs)
+
+    def reset(self, seed: int | None = None, options: dict | None = None) -> tuple[dict, dict]:
+        """Reset the environment for all drones.
+
+        Args:
+            seed: Random seed.
+            options: Additional reset options. Not used.
+
+        Returns:
+            Observation and info for all drones.
+        """
+        return self._reset(seed=seed, options=options)
+
+    def step(
+        self, action: NDArray[np.floating]
+    ) -> tuple[dict, NDArray[np.floating], NDArray[np.bool_], NDArray[np.bool_], dict]:
+        """Step the environment for all drones.
+
+        Args:
+            action: Action for all drones, i.e., a batch of (n_drones, action_dim) arrays.
+        """
+        return self._step(action)

lsy_drone_racing/envs/race_core.py

@@ -270,7 +270,7 @@ def __init__(
             self.device,
         )
 
-    def reset(
+    def _reset(
         self, *, seed: int | None = None, options: dict | None = None, mask: Array | None = None
     ) -> tuple[dict[str, NDArray[np.floating]], dict]:
         """Reset the environment.
@@ -292,10 +292,10 @@ def reset(
         # Randomization of gates, obstacles and drones is compiled into the sim reset function with
         # the sim.reset_hook function, so we don't need to explicitly do it here
         self.sim.reset(mask=mask)
-        self.data = self._reset(self.data, self.sim.data.states.pos, mask)
+        self.data = self._reset_env_data(self.data, self.sim.data.states.pos, mask)
         return self.obs(), self.info()
 
-    def step(
+    def _step(
         self, action: NDArray[np.floating]
     ) -> tuple[dict[str, NDArray[np.floating]], float, bool, bool, dict]:
         """Step the firmware_wrapper class and its environment.
@@ -321,10 +321,12 @@ def step(
         # previous flags, not the ones from the current step
         marked_for_reset = self.data.marked_for_reset
         # Apply the environment logic with updated simulation data.
-        self.data = self._step(self.data, drone_pos, drone_quat, mocap_pos, mocap_quat, contacts)
+        self.data = self._step_env(
+            self.data, drone_pos, drone_quat, mocap_pos, mocap_quat, contacts
+        )
         # Auto-reset envs. Add configuration option to disable for single-world envs
         if self.autoreset and marked_for_reset.any():
-            self.reset(mask=marked_for_reset)
+            self._reset(mask=marked_for_reset)
         return self.obs(), self.reward(), self.terminated(), self.truncated(), self.info()
 
     def apply_action(self, action: NDArray[np.floating]):
@@ -422,7 +424,7 @@ def symbolic_model(self) -> SymbolicModel:
 
     @staticmethod
     @jax.jit
-    def _reset(data: EnvData, drone_pos: Array, mask: Array | None = None) -> EnvData:
+    def _reset_env_data(data: EnvData, drone_pos: Array, mask: Array | None = None) -> EnvData:
         """Reset auxiliary variables of the environment data."""
         mask = jp.ones(data.steps.shape, dtype=bool) if mask is None else mask
         target_gate = jp.where(mask[..., None], 0, data.target_gate)
@@ -443,7 +445,7 @@ def _reset(data: EnvData, drone_pos: Array, mask: Array | None = None) -> EnvDat
 
     @staticmethod
     @jax.jit
-    def _step(
+    def _step_env(
         data: EnvData,
         drone_pos: Array,
         drone_quat: Array,