diff --git a/ethosu/vela/live_range.py b/ethosu/vela/live_range.py
index 0b94b19..5aec0df 100644
--- a/ethosu/vela/live_range.py
+++ b/ethosu/vela/live_range.py
@@ -112,7 +112,6 @@
     def __init__(self):
         self.lrs: List[LiveRange] = []  # List of all created ranges
         self.ranges = {}  # tens -> range
-        self.ignore_tensors = set()
         self.processed_subgraphs = set()
         self.current_time = 0
         self.end_time = None
@@ -151,17 +150,17 @@
         return usage
 
 
-def tensor_should_be_ignored(lr_graph, tens, target_mem_area, target_mem_type_set):
+def tensor_should_be_ignored(tens, target_mem_area, target_mem_type_set):
     if tens.mem_area != target_mem_area or tens.mem_type not in target_mem_type_set:
         return True
-    if tens in lr_graph.ignore_tensors:
-        return True
     return False
 
 
-def merge_elementwise_op_ranges(sched_op, lr_graph, target_mem_area, target_mem_type_set):
+def merge_elementwise_op_ranges(sg, sched_op, lr_graph, target_mem_area, target_mem_type_set):
     def _tensor_should_be_ignored(tens):
-        return tensor_should_be_ignored(lr_graph, tens, target_mem_area, target_mem_type_set)
+        if tens in sg.input_tensors + sg.output_tensors:
+            return True
+        return tensor_should_be_ignored(tens, target_mem_area, target_mem_type_set)
 
     # Tries to merge ifm/ofm live ranges of elementwise op
     if sched_op.op_type.is_elementwise_op():
@@ -198,12 +197,7 @@
 
 
 def extract_live_ranges_from_cascaded_passes(
-    sg,
-    target_mem_area,
-    target_mem_type_set,
-    ignore_subgraph_input_output_tensors=False,
-    lr_graph=None,
-    cpu_tensor_alignment=Tensor.AllocationQuantum,
+    sg, target_mem_area, target_mem_type_set, lr_graph=None, cpu_tensor_alignment=Tensor.AllocationQuantum,
 ):
     if lr_graph is None:
         lr_graph = LiveRangeGraph()
@@ -212,17 +206,13 @@
         # if subgraph has been processed already, return the lr_graph as is
         return lr_graph
 
-    if ignore_subgraph_input_output_tensors:
-        lr_graph.ignore_tensors.update(sg.input_tensors)
-        lr_graph.ignore_tensors.update(sg.output_tensors)
-
     for cps in sg.cascaded_passes:
         cps.time = lr_graph.current_time
 
         time_for_pass = cps.time
 
         for tens in cps.inputs:
-            if tensor_should_be_ignored(lr_graph, tens, target_mem_area, target_mem_type_set):
+            if tensor_should_be_ignored(tens, target_mem_area, target_mem_type_set):
                 continue
             rng = lr_graph.get_or_create_range(tens, cpu_tensor_alignment)
             rng.mark_usage(time_for_pass)
@@ -244,7 +234,7 @@
             cps.time = time_for_pass
 
         for tens in cps.intermediates + cps.outputs:
-            if tensor_should_be_ignored(lr_graph, tens, target_mem_area, target_mem_type_set):
+            if tensor_should_be_ignored(tens, target_mem_area, target_mem_type_set):
                 continue
             rng = lr_graph.get_or_create_range(tens, cpu_tensor_alignment)
             rng.mark_usage(time_for_pass)
@@ -257,7 +247,7 @@
         end_time = max(end_time, rng.end_time)
 
     for tens in sg.output_tensors:
-        if tensor_should_be_ignored(lr_graph, tens, target_mem_area, target_mem_type_set):
+        if tensor_should_be_ignored(tens, target_mem_area, target_mem_type_set):
             continue
         rng = lr_graph.get_or_create_range(tens, cpu_tensor_alignment)
         rng.mark_usage(end_time)
@@ -273,7 +263,7 @@
     for ps in sg.passes:
         for tens in ps.inputs + ps.outputs + ps.intermediates:
             if tens.purpose == TensorPurpose.Weights or tensor_should_be_ignored(
-                lr_graph, tens, target_mem_area, target_mem_type_set
+                tens, target_mem_area, target_mem_type_set
             ):
                 continue
             rng = lr_graph.get_or_create_range(tens)
@@ -281,7 +271,7 @@
 
     for _, op_info in sg.schedule.cost_map.items():
         for tensor in [op_info.npu_weights_tensor, op_info.npu_scales_tensor]:
-            if tensor and not (tensor_should_be_ignored(lr_graph, tensor, target_mem_area, target_mem_type_set)):
+            if tensor and not (tensor_should_be_ignored(tensor, target_mem_area, target_mem_type_set)):
                 rng = lr_graph.get_or_create_range(tensor)
                 rng.mark_usage(sg_time)
 
@@ -292,7 +282,7 @@
 def _extract_live_ranges_from_schedule(sg, target_mem_area, target_mem_type_set, lr_graph):
     time_for_cascade = {}
     for sched_op in sg.sched_ops:
-        merge_elementwise_op_ranges(sched_op, lr_graph, target_mem_area, target_mem_type_set)
+        merge_elementwise_op_ranges(sg, sched_op, lr_graph, target_mem_area, target_mem_type_set)
 
         op_info = sg.schedule.cost_map[sched_op]
         cascade = op_info.cascade