diff --git a/requirements.txt b/requirements.txt
index 41f1999..45ad673 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
-zigzag-dse==3.6.1
+zigzag-dse==3.6.2
 rtree
 deap
 matplotlib
diff --git a/stream/classes/io/onnx/softmax.py b/stream/classes/io/onnx/softmax.py
index f8a43b9..af14e04 100644
--- a/stream/classes/io/onnx/softmax.py
+++ b/stream/classes/io/onnx/softmax.py
@@ -52,7 +52,6 @@ def get_nodes(self):
         self.set_nodes_name_and_type()
         # Override dependencies
         self.correct_nodes_operand_source()
-        # self.correct_nodes_inputs_outputs()
 
         return self.nodes
 
@@ -78,21 +77,6 @@ def correct_nodes_operand_source(self):
         node_div.input_operand_source = {op_I: id_exp, op_W: id_sum}
         node_div.constant_operands = []
 
-    # def correct_nodes_inputs_outputs(self):
-    #     """Correct the `node_inputs` and `node_outputs` of all Computation Nodes that stem from the base
-    #     ONNX node"""
-    #     node_max, node_exp, node_sum, node_div = self.nodes
-    #     prev_node_name = node_max.input_names[0]  # Node before Softmax
-    #     next_node_name = node_max.output_names[0]  # Node after Softmax
-
-    #     node_max.output_names = [node_exp.name]
-    #     node_exp.input_names = [node_max.name, prev_node_name]
-    #     node_exp.output_names = [node_div.name, node_sum.name]
-    #     node_sum.input_names = [node_exp.name]
-    #     node_sum.output_names = [node_div.name]
-    #     node_div.input_names = [node_exp.name, node_sum.name]
-    #     node_div.output_names = [next_node_name]
-
 
 class SoftmaxExpParser(OnnxComputeOperatorParser):
     """Parses a softmax node into a ComputationNode for the element-wise operation exp(row-m) where m is the max value
diff --git a/stream/classes/opt/splitting/splitting.py b/stream/classes/opt/splitting/splitting.py
index 4a931c6..334ac71 100644
--- a/stream/classes/opt/splitting/splitting.py
+++ b/stream/classes/opt/splitting/splitting.py
@@ -104,7 +104,7 @@ def convert_outer_cn_loops(outer_cn_loops: list[tuple[str, int | str]], layer: C
                         new_layer_dim_size += 1
                     # Set the new loop size of the layer
                     logger.warn(
-                        f"Layer {layer}: {layer_dim} {layer.layer_dim_sizes[layer_dim]} -> {new_layer_dim_size}"
+                        f"Rounding {layer}: {layer_dim} {layer.layer_dim_sizes[layer_dim]} -> {new_layer_dim_size}"
                     )
                     layer.layer_dim_sizes[layer_dim] = new_layer_dim_size
                     outer_loops.append(TemporalLoop(layer_dim, loop_size))