diff --git a/aidge_core/unit_tests/test_forward_dims_constant_shape.py b/aidge_core/unit_tests/test_forward_dims_constant_shape.py
index 5490ffdd234ab4c90b095f8086c7e2cd5d078b8a..ecab2664a25023d2919324898fc6d84d63d8853d 100644
--- a/aidge_core/unit_tests/test_forward_dims_constant_shape.py
+++ b/aidge_core/unit_tests/test_forward_dims_constant_shape.py
@@ -11,24 +11,22 @@ SPDX-License-Identifier: EPL-2.0
 import unittest
 import aidge_core
 import numpy as np
-import aidge_backend_cpu
-
-# class DivImpl(aidge_core.OperatorImpl):
-#     """Div operator implementation to avoid dependency to backend_cpu"""
-
-#     def __init__(self, op: aidge_core.Operator):
-#         aidge_core.OperatorImpl.__init__(self, op, "div")
-#         self.op = op
-#         print("Creating divImpl")
-#     def forward(self):
-#         data_input_0 = np.array(self.op.get_input(0))
-#         data_input_1 = np.array(self.op.get_input(1))
-#         output =  (data_input_0 / data_input_1)
-#         print(output, " = ",  data_input_0, "/", data_input_1)
-#         self.op.set_output(0, aidge_core.Tensor(output)) # setting operator output
-
-# # Note: In this test, except Div, every operator are backend independent
-# aidge_core.register_DivOp("cpu", DivImpl)
+
+class DivImpl(aidge_core.OperatorImpl):
+    """Div operator implementation to avoid dependency to backend_cpu"""
+
+    def __init__(self, op: aidge_core.Operator):
+        aidge_core.OperatorImpl.__init__(self, op, "div")
+        self.op = op
+        print("Creating divImpl")
+    def forward(self):
+        data_input_0 = np.array(self.op.get_input(0))
+        data_input_1 = np.array(self.op.get_input(1))
+        output =  (data_input_0 / data_input_1)
+        self.op.set_output(0, aidge_core.Tensor(output)) # setting operator output
+
+# Note: In this test, except Div, every operator are backend independent
+aidge_core.register_DivOp("cpu", DivImpl)
 
 class test_forward_dims_constant_shape(unittest.TestCase):
     """Test forwardDims with shapeAsConstant=True