diff --git a/ethosu/vela/scheduler.py b/ethosu/vela/scheduler.py
index 5c2ddab..41e1529 100644
--- a/ethosu/vela/scheduler.py
+++ b/ethosu/vela/scheduler.py
@@ -37,6 +37,7 @@
 from .npu_performance import PassCycles
 from .numeric_util import full_shape
 from .operation import NpuBlockType
+from .operation import Op
 from .shared_buffer_allocation import find_block_configs_suitable_for_pass_and_shared_buffer
 from .shared_buffer_allocation import shared_buffer_allocation_for_pass_and_block_config
 from .tensor import MemArea
@@ -254,11 +255,7 @@
         self.pareto_max_candidates = 16
 
         self.ifm_stream_npu_blocks = set(
-            (
-                NpuBlockType.ConvolutionMxN,
-                NpuBlockType.ConvolutionDepthWise,
-                NpuBlockType.Pooling,
-            )
+            (NpuBlockType.ConvolutionMxN, NpuBlockType.ConvolutionDepthWise, NpuBlockType.Pooling,)
         )
 
     num_pareto_metrics = 4
@@ -652,7 +649,7 @@
     def avoid_for_cascading(self, pred_candidate):
         for op in pred_candidate.ops:
             if (
-                op.type == "ConcatSliceWrite"
+                op.type == Op.ConcatSliceWrite
                 and self.arch.feature_map_storage_mem_area != self.arch.fast_storage_mem_area
             ):
                 # For SRAM spilling, concat op is avoided as predecessor
@@ -981,9 +978,9 @@
                             use_NHCWB16 = False
                             use_fast_storage = False
                             continue
-                        if op.type == "ReduceSum" and output.dtype == DataType.int32:
+                        if op.type == Op.ReduceSum and output.dtype == DataType.int32:
                             use_NHCWB16 = False
-                        elif op.type == "Reshape":
+                        elif op.type == Op.Reshape:
                             # Detect no-op reshapes by comparing their full input and output tensor shapes.
                             inshape = full_shape(4, op.inputs[0].shape, 1)
                             outshape = full_shape(4, op.outputs[0].shape, 1)
@@ -995,7 +992,7 @@
                             incompatible_consumers = [
                                 (
                                     not consumer.run_on_npu
-                                    or consumer.type == "Reshape"
+                                    or consumer.type == Op.Reshape
                                     or (consumer is last_op_in_subgraph)
                                 )
                                 for consumer in op.outputs[0].consumer_list