Refactor test_local_zero_div

tests/tensor/test_math_opt.py

@@ -3885,28 +3885,32 @@ class TestIntDivByOne:
         assert len(divs) == 0
 
 
-def test_local_zero_div():
-    # Tests 0/x -> 0
-
-    for t in (scalar, ivector, ftensor4):
-        x = t("x")
-        for op in (int_div, true_div):
-            y = op(0, x)
-            g = optimize(FunctionGraph([x], [y]))
-            # the division should be gone
-            divs = [
-                node
-                for node in g.toposort()
-                if isinstance(node.op, Elemwise)
-                and isinstance(node.op.scalar_op, type(op.scalar_op))
-            ]
-            assert len(divs) == 0
-            # the output type should match the unoptimized one
-            output = g.outputs[0]
-            assert output.ndim == y.ndim
-            assert output.type == y.type
-            # and the output should be zero
-            assert aet.get_scalar_constant_value(output) == 0
+@pytest.mark.parametrize("t", [scalar, ivector, ftensor4])
+@pytest.mark.parametrize("op", [int_div, true_div])
+def test_local_zero_div(t, op):
+    """Test the canonicalization ``0/x -> 0``."""
+    x = t("x")
+    y = op(0, x)
+    g = optimize(FunctionGraph([x], [y]))
+    # the division should be gone
+    divs = [
+        node
+        for node in g.toposort()
+        if isinstance(node.op, Elemwise)
+        and isinstance(node.op.scalar_op, type(op.scalar_op))
+    ]
+    assert len(divs) == 0
+    # the output type should match the unoptimized one
+    output = g.outputs[0]
+    assert output.ndim == y.ndim
+    assert output.type == y.type
+    # and the output should be zero
+    if output.owner and isinstance(output.owner.op, Alloc):
+        out_var = output.owner.inputs[0]
+    else:
+        out_var = output
+
+    assert out_var.data == 0
 
 
 def test_local_sumsqr2dot():