fixed flaky test issue for test_operator_gpu.test_convolution_grouping (

#12385)

* fixed flaky test issue for test_operator_gpu.test_convolution_grouping

* Changed implicit cast to explicit cast

tests/python/unittest/test_operator.py

@@ -1583,7 +1583,6 @@ def check_batchnorm_training(stype):
     check_batchnorm_training('default')
 
 
-@unittest.skip("Flaky test https://github.com/apache/incubator-mxnet/issues/12219")
 @with_seed()
 def test_convolution_grouping():
     for dim in [1, 2, 3]:
@@ -1606,15 +1605,15 @@ def test_convolution_grouping():
         exe1 = y1.simple_bind(default_context(), x=shape)
         exe2 = y2.simple_bind(default_context(), 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])
         exe2.forward(is_train=True)
         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-4)
+            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")