    """Train for a single step."""
    def loss_fn(model):
      logits = model(batch['image'])
-@@ -119,8 +119,12 @@ def train_step(optimizer, batch):
+@@ -92,8 +92,12 @@ def train_step(optimizer, batch):
    grad_fn = jax.value_and_grad(loss_fn, has_aux=True)
    (_, logits), grad = grad_fn(optimizer.target)
    optimizer = optimizer.apply_gradient(grad)

diff --git a/examples/mnist/train.py b/examples/mnist/train.py
index 9c21985..4306d09 100644
--- a/examples/mnist/mnist_lib.py
+++ b/examples/mnist/mnist_lib.py
@@ -110,7 +110,7 @@ def compute_metrics(logits, labels):
 
 
 @jax.jit

 
 
 @jax.jit
@@ -102,7 +106,7 @@ def eval_step(model, batch):
   return compute_metrics(logits, batch['label'])
 
 
