style: apply ruff import formatting across scripts, tests, and envs

Author: TATP-233

benchmark/benchmark_postprocess.py

@@ -14,6 +14,7 @@
 import mlx.core as mx
 import numpy as np
 import torch
+
 from unilab.base import registry
 
 try:

scripts/train_appo.py

@@ -48,6 +48,7 @@ def play_appo(args, rl_cfg):
     import numpy as np
     from rsl_rl.utils import resolve_callable
     from tensordict import TensorDict
+
     from unilab.base import registry
     from unilab.utils import render_many
     from unilab.utils.rsl_rl_compat import convert_config_v3_to_v4, is_rsl_rl_v4, is_rsl_rl_v5

scripts/train_mlx_ppo.py

@@ -159,6 +159,7 @@ def play_mlx_ppo(args, cfg, dtype, use_fp16, resolved_sim_backend, task_log_root
     """Play mode for MLX PPO."""
     import mlx.core as mx
     import numpy as np
+
     from unilab.base import registry
 
     play_model_dtype = mx.float32 if use_fp16 else dtype

scripts/train_offpolicy.py

@@ -212,6 +212,7 @@ def play_offpolicy(algo_name: str, args, cfg) -> None:
     import mediapy as media
     import numpy as np
     import torch
+
     from unilab.base import registry
     from unilab.utils import render_many
     from unilab.utils.algo_utils import build_actor

scripts/train_rsl_rl.py

@@ -201,6 +201,7 @@ def step(self, actions):
 def play_rsl_rl(args, cfg, device):
     """Play mode for RSL-RL."""
     import torch
+
     from unilab.base import registry
 
     env = registry.make(args.task, num_envs=args.play_env_num, sim_backend=args.sim_backend)
@@ -291,6 +292,7 @@ def play_rsl_rl(args, cfg, device):
     else:
         # MuJoCo backend: render to video
         import mediapy as media
+
         from unilab.utils import render_many
 
         output_video = Path(load_path_dir) / "play_video.mp4"

scripts/visualization_env.py

@@ -7,6 +7,7 @@
 import time
 
 import numpy as np
+
 from unilab.base import registry
 
 parser = argparse.ArgumentParser(description="Visualize robot tasks")

src/unilab/envs/manipulation/inhand_rot_allegro/base.py

@@ -5,6 +5,7 @@
 import gymnasium as gym
 import mujoco
 import numpy as np
+
 from unilab.base.backend import SimBackend
 from unilab.base.base import EnvCfg
 from unilab.base.dtype_config import get_global_dtype

src/unilab/envs/manipulation/inhand_rot_allegro/rotation_sac.py

@@ -52,11 +52,12 @@ def _quat_to_axis_angle(q: np.ndarray) -> np.ndarray:
     return np.asarray(xyz / sin_half_over_angle)  # (N, 3)
 
 
-from unilab.base import registry
 from unilab.envs.backend import create_backend
-from unilab.envs.manipulation.inhand_rot_allegro.base import AllegroBaseCfg, AllegroBaseMjEnv
 from unilab.envs.np_env import NpEnvState
 
+from unilab.base import registry
+from unilab.envs.manipulation.inhand_rot_allegro.base import AllegroBaseCfg, AllegroBaseMjEnv
+
 # ─────────────────────────── Configuration ────────────────────────────
 
 

tests/algos/test_mlx_ppo.py

@@ -20,6 +20,7 @@
 
 import mlx.core as mx
 import numpy as np
+
 from unilab.algos.mlx.common import RolloutBuffer
 from unilab.algos.mlx.ppo import MLPActorCritic, PPOConfig, PPOTrainer
 

tests/base/test_registry.py

@@ -8,6 +8,7 @@
 import gymnasium as gym
 import numpy as np
 import pytest
+
 import unilab.base.registry as registry_mod
 from unilab.base.base import ABEnv, EnvCfg