diff --git a/src/data.py b/src/data.py
index e9561af..01e92a1 100644
--- a/src/data.py
+++ b/src/data.py
@@ -131,7 +131,7 @@ def process_data(
 
                 # Convert to Data object
                 data_obj = Data(
-                    x=feat_dict["node_tensor"],
+                    x=feat_dict["node_tensor"].to(torch.float32),
                     edge_index=feat_dict["edge_indices"],
                     edge_attr=feat_dict["edge_tensor"],
                     y=torch.Tensor([self.map_name_prop[name]]),
@@ -245,7 +245,7 @@ def process_data(
 
                 # Convert to Data object
                 data_obj = Data(
-                    x=feat_dict["node_tensor"],
+                    x=feat_dict["node_tensor"].to(torch.float32),
                     edge_index=feat_dict["edge_indices"],
                     edge_attr=feat_dict["edge_tensor"],
                 )
diff --git a/src/models.py b/src/models.py
index 615ddc8..8ff3fd6 100644
--- a/src/models.py
+++ b/src/models.py
@@ -95,7 +95,9 @@ def __init__(self, partition_configs):
 
         # Final linear layer
         # TODO: replace 1 with multiple outputs
-        self.final_lin_transform = nn.Linear(self.n_partitions, 1)
+        self.final_lin_transform = nn.Linear(self.n_partitions, 1, bias=False)
+        with torch.no_grad():
+            self.final_lin_transform.weight.copy_(torch.ones(self.n_partitions))
 
     def init_conv_layers(self):
         """Initialize convolutional layers."""
@@ -230,3 +232,4 @@ def forward(self, data_objects):
     ]
     net = MultiGCN(partition_configs)
     result_dict = net(data_objects)
+    print(result_dict)