make rl envs lazy import

src/tensorneat/problem/rl/brax.py

@@ -1,6 +1,4 @@
 import jax.numpy as jnp
-from brax import envs
-
 from .rl_jit import RLEnv, norm_obs
 
 
@@ -8,6 +6,7 @@ class BraxEnv(RLEnv):
     def __init__(
         self, env_name: str = "ant", backend: str = "generalized", *args, **kwargs
     ):
+        from brax import envs
         super().__init__(*args, **kwargs)
         self.env_name = env_name
         self.env = envs.create(env_name=env_name, backend=backend)

src/tensorneat/problem/rl/gymnax.py

@@ -1,10 +1,9 @@
-import gymnax
-
 from .rl_jit import RLEnv
 
 
 class GymNaxEnv(RLEnv):
     def __init__(self, env_name, *args, **kwargs):
+        import gymnax
         super().__init__(*args, **kwargs)
         assert env_name in gymnax.registered_envs, f"Env {env_name} not registered in gymnax."
         self.env, self.env_params = gymnax.make(env_name)

src/tensorneat/problem/rl/mujoco_playground.py

@@ -1,7 +1,5 @@
 import jax.numpy as jnp
 from jax import Array
-from mujoco_playground import registry
-
 from .rl_jit import RLEnv, norm_obs
 
 
@@ -9,6 +7,7 @@ class MujocoEnv(RLEnv):
     def __init__(
         self, env_name: str = "SwimmerSwimmer6", *args, **kwargs
     ):
+        from mujoco_playground import registry
         super().__init__(*args, **kwargs)
         self.env_name = env_name
         self.env = registry.load(env_name=env_name)