diff --git a/brax/training/agents/sac/networks.py b/brax/training/agents/sac/networks.py
index 7e8d58e9..dc50106a 100644
--- a/brax/training/agents/sac/networks.py
+++ b/brax/training/agents/sac/networks.py
@@ -56,7 +56,9 @@ def make_sac_networks(
     preprocess_observations_fn: types.PreprocessObservationFn = types
     .identity_observation_preprocessor,
     hidden_layer_sizes: Sequence[int] = (256, 256),
-    activation: networks.ActivationFn = linen.relu) -> SACNetworks:
+    activation: networks.ActivationFn = linen.relu,
+    policy_network_layer_norm: bool = False,
+    q_network_layer_norm: bool = False) -> SACNetworks:
   """Make SAC networks."""
   parametric_action_distribution = distribution.NormalTanhDistribution(
       event_size=action_size)
@@ -65,13 +67,15 @@ def make_sac_networks(
       observation_size,
       preprocess_observations_fn=preprocess_observations_fn,
       hidden_layer_sizes=hidden_layer_sizes,
-      activation=activation)
+      activation=activation,
+      layer_norm=policy_network_layer_norm)
   q_network = networks.make_q_network(
       observation_size,
       action_size,
       preprocess_observations_fn=preprocess_observations_fn,
       hidden_layer_sizes=hidden_layer_sizes,
-      activation=activation)
+      activation=activation,
+      layer_norm=q_network_layer_norm)
   return SACNetworks(
       policy_network=policy_network,
       q_network=q_network,
diff --git a/brax/training/networks.py b/brax/training/networks.py
index 76e9c12f..23e041aa 100644
--- a/brax/training/networks.py
+++ b/brax/training/networks.py
@@ -136,7 +136,8 @@ def make_q_network(
     .identity_observation_preprocessor,
     hidden_layer_sizes: Sequence[int] = (256, 256),
     activation: ActivationFn = linen.relu,
-    n_critics: int = 2) -> FeedForwardNetwork:
+    n_critics: int = 2,
+    layer_norm: bool = False) -> FeedForwardNetwork:
   """Creates a value network."""
 
   class QModule(linen.Module):
@@ -151,7 +152,8 @@ def __call__(self, obs: jnp.ndarray, actions: jnp.ndarray):
         q = MLP(
             layer_sizes=list(hidden_layer_sizes) + [1],
             activation=activation,
-            kernel_init=jax.nn.initializers.lecun_uniform())(
+            kernel_init=jax.nn.initializers.lecun_uniform(),
+            layer_norm=layer_norm)(
                 hidden)
         res.append(q)
       return jnp.concatenate(res, axis=-1)
diff --git a/brax/v1/jumpy.py b/brax/v1/jumpy.py
index 168d9c10..2c65ef23 100644
--- a/brax/v1/jumpy.py
+++ b/brax/v1/jumpy.py
@@ -43,7 +43,7 @@ def _in_jit() -> bool:
 
   if jax.__version_info__ <= (0, 4, 33):
     return 'DynamicJaxprTrace' in str(
-        jax.core.thread_local_state.trace_state.trace_stack
+        jax.core.thread_local_state.trace_state.trace_stack  # type: ignore
     )
 
   return jax.core.unsafe_am_i_under_a_jit_DO_NOT_USE()
diff --git a/docs/release-notes/next-release.md b/docs/release-notes/next-release.md
index 7e5c6680..46b3124c 100644
--- a/docs/release-notes/next-release.md
+++ b/docs/release-notes/next-release.md
@@ -1,4 +1,5 @@
 # Brax Release Notes
 
 * Add boolean `wrap_env` to all brax `train` functions, which optionally wraps the env for training, or uses the env as is.
-* Fix bug in PPO train to return loaded checkpoint when `num_timesteps` is 0.
\ No newline at end of file
+* Fix bug in PPO train to return loaded checkpoint when `num_timesteps` is 0.
+* Add `layer_norm` to `make_q_network` and set `layer_norm` to `True` in `make_sace_networks` Q Network.