Add benchmark test for CAReduce

tests/tensor/test_elemwise.py

@@ -985,3 +985,29 @@ class TestVectorize:
         assert isinstance(vect_node.op, Any)
         assert vect_node.op.axis == (1,)
         assert vect_node.inputs[0] is bool_tns
+
+
+@pytest.mark.parametrize(
+    "axis",
+    (0, 1, 2, (0, 1), (0, 2), (1, 2), None),
+    ids=lambda x: f"axis={x}",
+)
+@pytest.mark.parametrize(
+    "c_contiguous",
+    (True, False),
+    ids=lambda x: f"c_contiguous={x}",
+)
+def test_careduce_benchmark(axis, c_contiguous, benchmark):
+    N = 256
+    x_test = np.random.uniform(size=(N, N, N))
+    transpose_axis = (0, 1, 2) if c_contiguous else (2, 0, 1)
+
+    x = pytensor.shared(x_test, name="x", shape=x_test.shape)
+    out = x.transpose(transpose_axis).sum(axis=axis)
+    fn = pytensor.function([], out)
+
+    np.testing.assert_allclose(
+        fn(),
+        x_test.transpose(transpose_axis).sum(axis=axis),
+    )
+    benchmark(fn)