diff --git a/ethosu/vela/test/test_supported_operators.py b/ethosu/vela/test/test_supported_operators.py
index 53c2092..20d448d 100644
--- a/ethosu/vela/test/test_supported_operators.py
+++ b/ethosu/vela/test/test_supported_operators.py
@@ -19,6 +19,7 @@
 import numpy as np
 
 from ethosu.vela.data_type import DataType
+from ethosu.vela.operation import Op
 from ethosu.vela.supported_operators import SupportedOperators
 from ethosu.vela.tensor import create_const_tensor
 from ethosu.vela.tensor import QuantizationParameters
@@ -35,7 +36,7 @@
     in3 = create_const_tensor("strides", [len(end_offsets)], DataType.uint8, len(end_offsets) * [1])
     out = Tensor(out_shape, DataType.uint8, "out")
     attrs = {"ellipsis_mask": 0, "new_axis_mask": 0, "shrink_axis_mask": 0, "begin_mask": 0, "end_mask": 0}
-    return testutil.create_op("StridedSlice", [in0, in1, in2, in3], out, attrs=attrs)
+    return testutil.create_op(Op.StridedSlice, [in0, in1, in2, in3], out, attrs=attrs)
 
 
 def create_strided_slice():
@@ -93,21 +94,21 @@
     # Tensors cannot have None in them
     inp = Tensor([1, 8, None, 8], DataType.uint8, "in")
     out = Tensor([1, 8, 8, 8], DataType.uint8, "out")
-    op = testutil.create_op("Relu", [inp], out)
+    op = testutil.create_op(Op.Relu, [inp], out)
     assert not support.is_operator_supported(op)
 
 
 def test_constraint_tens_shapeless():
     # Shapeless input is allowed if its of a certain type:
-    op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8])
+    op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8])
     assert support.is_operator_supported(op)
     # Shapeless output is not allowed at all:
-    op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [1, 8, 8, 8], [])
+    op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [1, 8, 8, 8], [])
     assert not support.is_operator_supported(op)
     # Invalid shapeless input due to op type:
     inp = Tensor([], DataType.uint8, "in")
     out = Tensor([1, 8, 8, 8], DataType.uint8, "out")
-    op = testutil.create_op("Relu", [inp], out)
+    op = testutil.create_op(Op.Relu, [inp], out)
     assert not support.is_operator_supported(op)
 
 
@@ -115,7 +116,7 @@
     # Tensors cannot be > 4D
     inp = Tensor([1, 1, 8, 8, 8], DataType.uint8, "in")
     out = Tensor([1, 1, 8, 8, 8], DataType.uint8, "out")
-    op = testutil.create_op("Relu", [inp], out)
+    op = testutil.create_op(Op.Relu, [inp], out)
     assert not support.is_operator_supported(op)
 
 
@@ -123,14 +124,14 @@
     # Tensors can only be of type uint8, int8, int16 (and int32)
     inp = Tensor([1, 8, 8, 8], DataType.float32, "in")
     out = Tensor([1, 8, 8, 8], DataType.float32, "out")
-    op = testutil.create_op("Relu", [inp], out)
+    op = testutil.create_op(Op.Relu, [inp], out)
     assert not support.is_operator_supported(op)
     # For int32, only select op types are allowed:
-    op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8], DataType.int32)
+    op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8], DataType.int32)
     assert support.is_operator_supported(op)
     inp = Tensor([1, 8, 8, 8], DataType.int32, "in")
     out = Tensor([1, 8, 8, 8], DataType.int32, "out")
-    op = testutil.create_op("Relu", [inp], out)
+    op = testutil.create_op(Op.Relu, [inp], out)
     assert not support.is_operator_supported(op)
 
 
@@ -138,11 +139,11 @@
     # Tensors can only have values in the inclusive range of 1-65535
     inp = Tensor([1, 8, 8, 0], DataType.uint8, "in")
     out = Tensor([1, 8, 8, 0], DataType.uint8, "out")
-    op = testutil.create_op("Relu", [inp], out)
+    op = testutil.create_op(Op.Relu, [inp], out)
     assert not support.is_operator_supported(op)
     inp = Tensor([1, 8, 8, 65536], DataType.uint8, "in")
     out = Tensor([1, 8, 8, 65536], DataType.uint8, "out")
-    op = testutil.create_op("Relu", [inp], out)
+    op = testutil.create_op(Op.Relu, [inp], out)
     assert not support.is_operator_supported(op)
 
 
@@ -150,13 +151,14 @@
     # Fused activation functions, if set, must be a valid op type
     inp = Tensor([1, 8, 8, 8], DataType.uint8, "in")
     out = Tensor([1, 8, 8, 8], DataType.uint8, "out")
-    op = testutil.create_op("Relu", [inp], out, attrs={"fused_activation_function": "Conv2D"})
+    op = testutil.create_op(Op.Relu, [inp], out)
+    op.activation = Op.Conv2D
     assert not support.is_operator_supported(op)
 
 
 def test_constraint_tens_quant_scale():
     # Quantization scale cannot be infinit
-    op = testutil.create_elemwise_op("Mul", "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8])
+    op = testutil.create_elemwise_op(Op.Mul, "scalar_mul", [1, 8, 8, 8], [], [1, 8, 8, 8])
     op.inputs[0].quantization = QuantizationParameters()
     op.inputs[0].quantization.scale_f32 = np.inf
     assert not support.is_operator_supported(op)