diff --git a/onnxscript/function_libs/torch_lib/ops/core.py b/onnxscript/function_libs/torch_lib/ops/core.py
index b2138d4e6..a955583e9 100644
--- a/onnxscript/function_libs/torch_lib/ops/core.py
+++ b/onnxscript/function_libs/torch_lib/ops/core.py
@@ -8022,53 +8022,35 @@ def aten_sub_complex(self: TReal, other: TReal, alpha: float = 1.0) -> TReal:
     return aten_sub(self, other, alpha=alpha)
 
 
-@torch_op(("aten::sum", "aten::sum.dim_IntList"), trace_only=True)
-def aten_sum_dim_IntList(
-    self: TReal, dim: Optional[INT64] = None, keepdim: bool = False, dtype: int = -1
-) -> TReal:
-    """sum(Tensor self, SymInt dim, bool keepdim, *, ScalarType? dtype=None) -> Tensor"""
-
-    # NOTE: trace_only because both if branches need to be the same type, but we have
-    # a cast in the if branch.
-
-    # TODO: Combine the overloads when OptionalHasElement() works
-    if dim is None:
-        result = _aten_sum_dim_none(self, keepdim=keepdim)
+@torch_op("aten::sum", trace_only=True)
+def aten_sum(self: TReal, dtype: int = -1) -> TReal:
+    """sum(Tensor self, *, ScalarType? dtype=None) -> Tensor"""
+    if len(self.shape) == 0:
+        result = op.Identity(self)
     else:
-        result = _aten_sum_dim_onnx(self, dim, keepdim=keepdim)
-
-    if dtype != -1:
+        result = op.ReduceSum(self, keepdims=False)
+    if dtype != -1 and dtype is not None:
         result = op.Cast(result, to=dtype)
-
     return result
 
 
-@torch_op("aten::sum", private=True, traceable=True)
-def _aten_sum_dim_onnx(self: TReal, dim: INT64, keepdim: bool = False) -> TReal:
-    self_is_scalar = IsScalar(self)
-    if self_is_scalar:
-        self = op.Reshape(self, op.Constant(value_ints=[-1]))
-
-    if IsScalar(dim):
+@torch_op("aten::sum.dim_IntList", trace_only=True)
+def aten_sum_dim_IntList(
+    self: TReal, dim: Optional[INT64] = None, keepdim: bool = False, dtype: int = -1
+) -> TReal:
+    """sum.dim_IntList(Tensor self, int[1]? dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor"""
+    if len(self.shape) == 0:
+        result = op.Identity(self)
+    elif dim is None:
+        result = op.ReduceSum(self, keepdims=keepdim)
+    else:
         dim = op.Reshape(dim, op.Constant(value_ints=[-1]))
         dim = op.Cast(dim, to=INT64.dtype)
-    result = op.ReduceSum(self, dim, keepdims=keepdim)
-
-    if self_is_scalar:
-        result = op.Squeeze(result)
-    return result
+        result = op.ReduceSum(self, dim, keepdims=keepdim)
 
+    if dtype != -1 and dtype is not None:
+        result = op.Cast(result, to=dtype)
 
-@torch_op("aten::sum", private=True)
-def _aten_sum_dim_none(self: TReal, keepdim: bool = False) -> TReal:
-    self_is_scalar = IsScalar(self)
-    if self_is_scalar:
-        self = op.Reshape(self, op.Constant(value_ints=[-1]))
-
-    result = op.ReduceSum(self, keepdims=keepdim)
-
-    if self_is_scalar:
-        result = op.Squeeze(result)
     return result