diff --git a/algorithmic_efficiency/workloads/fastmri/fastmri_jax/workload.py b/algorithmic_efficiency/workloads/fastmri/fastmri_jax/workload.py
index 155b2dff1..f34c854e9 100644
--- a/algorithmic_efficiency/workloads/fastmri/fastmri_jax/workload.py
+++ b/algorithmic_efficiency/workloads/fastmri/fastmri_jax/workload.py
@@ -36,14 +36,6 @@ def init_model_fn(
         dropout_rate=dropout_rate)
     variables = jax.jit(self._model.init)({'params': rng}, fake_batch)
     params = variables['params']
-    tabulate_fn = nn.tabulate(
-      self._model,
-      jax.random.PRNGKey(0),
-      console_kwargs={
-        'force_terminal': False, 'force_jupyter':False, 'width':240
-      }
-    )
-    print(tabulate_fn(fake_batch, train=False))
     self._param_shapes = param_utils.jax_param_shapes(params)
     self._param_types = param_utils.jax_param_types(self._param_shapes)
     params = jax_utils.replicate(params)
diff --git a/tests/modeldiffs/fastmri_layernorm/compare.py b/tests/modeldiffs/fastmri_layernorm/compare.py
index 30939b7d4..f8e073d8b 100644
--- a/tests/modeldiffs/fastmri_layernorm/compare.py
+++ b/tests/modeldiffs/fastmri_layernorm/compare.py
@@ -28,9 +28,9 @@ def sort_key(k):
 
   keys = sorted(sd.keys(), key=sort_key)
   c = 0
-  jax_weights_name = 'kernel'
   for idx, k in enumerate(keys):
     new_key = []
+    jax_weights_name = 'kernel'
     for idx2, i in enumerate(k):
       if 'ModuleList' in i or 'Sequential' in i:
         continue
@@ -44,6 +44,7 @@ def sort_key(k):
         i = i.replace('ConvTranspose2d', 'ConvTranspose')
       if 'LayerNorm' in i:
         jax_weights_name = 'scale'
+        continue
       if 'weight' in i:
         i = i.replace('weight', jax_weights_name)
       new_key.append(i)