Fix 6 critical bugs in REPPO repository preventing execution

- Fix missing MUON optimizer by replacing with optax.adam
- Fix Hydra configuration parameter paths (env.name instead of env_name)
- Fix BraxGymnaxWrapper method signatures to accept params argument
- Fix training loop division by zero with proper total_time_steps
- Fix incorrect algorithm name in wandb (reppo instead of sac)
- Fix JAX key batching error in BraxGymnaxWrapper reset method
- Add comprehensive HoReKa SLURM integration with wandb logging
- Update README with detailed bug documentation and fixes

reppo_alg/env_utils/jax_wrappers.py

@@ -218,7 +218,11 @@ class BraxGymnaxWrapper:
         self.reward_scaling = reward_scaling
 
     def reset(self, key):
-        state = self.env.reset(key)
+        # Handle both single key and batched keys
+        if key.ndim > 1:  # Batched keys
+            state = jax.vmap(self.env.reset)(key)
+        else:  # Single key
+            state = self.env.reset(key)
         return state.obs, state
 
     def step(self, key, state, action):
@@ -232,7 +236,7 @@ class BraxGymnaxWrapper:
             {},
         )
 
-    def observation_space(self):
+    def observation_space(self, params=None):
         return spaces.Box(
             low=-jnp.inf,
             high=jnp.inf,
@@ -243,7 +247,7 @@ class BraxGymnaxWrapper:
             shape=(self.env.observation_size,),
         )
 
-    def action_space(self):
+    def action_space(self, params=None):
         return spaces.Box(
             low=-1.0,
             high=1.0,