Align round op to support round half to even

oneflow/core/ep/common/primitive/unary_functor.h

@@ -456,7 +456,7 @@ template<DeviceType device, typename Dst, typename Src>
 struct UnaryFunctor<device, UnaryOp::kRound, Dst, Src> {
   OF_DEVICE_FUNC UnaryFunctor(Scalar attr0, Scalar attr1) {}
 
-  OF_DEVICE_FUNC Dst operator()(Src src) const { return static_cast<Dst>(round(src)); }
+  OF_DEVICE_FUNC Dst operator()(Src src) const { return static_cast<Dst>(nearbyint(src)); }
 };
 
 template<DeviceType device, typename Dst, typename Src>

python/oneflow/framework/docstr/math_ops.py

@@ -1373,6 +1373,10 @@
 add_docstr(
     oneflow.round,
     r"""This operator rounds the value of Blob to the nearest integer.
+
+    .. note::
+        This function implements the "round half to even" to break ties when a number is equidistant from two integers (e.g. `round(2.5)` is 2).
+
     Args:
         input (oneflow.Tensor): A Tensor
     Returns:

python/oneflow/test/modules/test_global_round.py

@@ -31,9 +31,6 @@ def _test_round_impl(test_case, ndim, placement, sbp):
     return z
 
 
-@unittest.skip(
-    "TODO: special input is not align with pytorch: https://github.com/Oneflow-Inc/oneflow/issues/9074"
-)
 class TestRoundGlobal(flow.unittest.TestCase):
     @globaltest
     def test_round(test_case):

python/oneflow/test/modules/test_round.py

@@ -40,6 +40,18 @@ def test_flow_round_with_0dim_data(test_case):
         y = torch.round(x)
         return y
 
+    @autotest(check_graph=True)
+    def test_flow_round_half_to_even(test_case):
+        device = random_device()
+        random_shape = [random(1, 10).to(int).value() for _ in range(4)]
+        random_tenosr = np.random.randint(-99999, 99999, size=random_shape)
+        x = torch.tensor(random_tenosr).to(device)
+        y = torch.full(x.shape, 0.5).to(device)
+        y += x
+        y = y.requires_grad_()
+        z = torch.round(y)
+        return z
+
 
 if __name__ == "__main__":
     unittest.main()