diff --git a/tests/python/unittest/test_operator.py b/tests/python/unittest/test_operator.py
index 78285b64543a..f246689e34e6 100644
--- a/tests/python/unittest/test_operator.py
+++ b/tests/python/unittest/test_operator.py
@@ -1616,7 +1616,6 @@ def test_convolution_grouping():
             np.testing.assert_allclose(arr1.asnumpy(), arr2.asnumpy(), rtol=1e-3, atol=1e-3)
 
 
-@unittest.skip("Flaky test https://github.com/apache/incubator-mxnet/issues/12203")
 @with_seed()
 def test_depthwise_convolution():
     for dim in [1,2]:
@@ -1650,7 +1649,7 @@ def test_depthwise_convolution():
                             exe2 = y2.simple_bind(mx.cpu(), x=shape, w=(num_filter, shape[1]//num_group)+kernel,
                                     b=(num_filter,))
                             for arr1, arr2 in zip(exe1.arg_arrays, exe2.arg_arrays):
-                                arr1[:] = np.random.normal(size=arr1.shape)
+                                arr1[:] = np.float32(np.random.normal(size=arr1.shape))
                                 arr2[:] = arr1
                             exe1.forward(is_train=True)
                             exe1.backward(exe1.outputs[0])
@@ -1658,7 +1657,7 @@ def test_depthwise_convolution():
                             exe2.backward(exe2.outputs[0])
 
                             for arr1, arr2 in zip(exe1.outputs + exe1.grad_arrays, exe2.outputs + exe2.grad_arrays):
-                                np.testing.assert_allclose(arr1.asnumpy(), arr2.asnumpy(), rtol=1e-3, atol=1e-3)
+                                np.testing.assert_allclose(arr1.asnumpy(), arr2.asnumpy(), rtol=1e-2, atol=1e-3)
 
 def gen_broadcast_data(idx):
     # Manually set test cases