diff --git a/aidge_core/export_utils/scheduler_export.py b/aidge_core/export_utils/scheduler_export.py
index 5b50f803f0b0a6073ccec7d9d049ba8482f2d2b4..33869ea5ada0839e328d5f9edc43dcb84defbe6f 100644
--- a/aidge_core/export_utils/scheduler_export.py
+++ b/aidge_core/export_utils/scheduler_export.py
@@ -50,9 +50,19 @@ def scheduler_export(scheduler, export_folder_path: str, export_lib: ExportLib =
             if not isinstance(op_impl, ExportLib):
                 raise RuntimeError(f"Operator {node.name()}[{node.type()}] doesn't have an exportable backend ({op_impl}).")
 
-            is_input = node in graphview.get_input_nodes()
-            is_output = node in graphview.get_output_nodes()
+            is_input:bool  = node in graphview.get_input_nodes()
+            is_output:bool = node in graphview.get_output_nodes()
 
+            if is_input:
+                # GraphView.get_inputs_nodes() returns the nodes that have an Input set to None or not in the graph
+                # However, some inputs are Optional and thus the node may not be an input of the graph!
+                # So we need ot check that all the inputs of the nodes or in the graph or not optional
+                # This is what the following code block is checking.
+                for idx, node_in in enumerate(node.inputs()):
+                    optional:bool = node.get_operator().input_category(idx) == aidge_core.InputCategory.OptionalData
+                    # Note: node_in is a Tuple(Node, out_idx)
+                    in_graph:bool = node_in[0] in graphview.get_nodes()
+                    is_input &= (in_graph or not optional)
 
             required_specs = op_impl.get_required_spec()
             specs = op_impl.get_best_match(required_specs)
@@ -76,7 +86,8 @@ def scheduler_export(scheduler, export_folder_path: str, export_lib: ExportLib =
                 for idx in range(len(node.outputs())):
                     outputs_name.append(op.attributes["out_name"][idx])
                     outputs_dtype.append(
-                        op.attributes["out_cdtype"][idx])
+                        op.attributes["out_cdtype"][idx]
+                    )
                     outputs_size.append(op.attributes["out_size"][idx])
 
         func_name = "model_forward"