diff --git a/onnxscript/function_libs/torch_lib/ops/core.py b/onnxscript/function_libs/torch_lib/ops/core.py
index f980465bc4..c3892c6cd3 100644
--- a/onnxscript/function_libs/torch_lib/ops/core.py
+++ b/onnxscript/function_libs/torch_lib/ops/core.py
@@ -6682,11 +6682,21 @@ def aten_prelu_backward(
     raise NotImplementedError()
 
 
-@torch_op("aten::prod.dim_int", trace_only=True)
-def aten_prod(self: TReal, dim: int, keepdim: bool = False) -> TReal:
+@torch_op("aten::prod", trace_only=True)
+def aten_prod(self: TReal, dtype: int = -1) -> TReal:
     """prod(Tensor self, *, ScalarType? dtype=None) -> Tensor"""
 
-    # Todo: add test for this function later
+    if dtype != -1 and dtype is not None:
+        self = op.Cast(self, to=dtype)
+    return op.ReduceProd(self)
+
+
+@torch_op("aten::prod.dim_int", trace_only=True)
+def aten_prod_dim_int(self: TReal, dim: int, keepdim: bool = False, dtype: int = -1) -> TReal:
+    """prod.dim_int(Tensor self, int dim, bool keepdim=False, *, ScalarType? dtype=None) -> Tensor"""
+
+    if dtype != -1 and dtype is not None:
+        self = op.Cast(self, to=dtype)
     return op.ReduceProd(self, axes=[dim], keepdims=keepdim)
 
 
diff --git a/tests/function_libs/torch_lib/ops_test_data.py b/tests/function_libs/torch_lib/ops_test_data.py
index 35e1778ca2..1399264546 100644
--- a/tests/function_libs/torch_lib/ops_test_data.py
+++ b/tests/function_libs/torch_lib/ops_test_data.py
@@ -1271,6 +1271,19 @@ def _where_input_wrangler(
     ),
     TorchLibOpInfo("polar", core_ops.aten_polar),
     TorchLibOpInfo("pow", core_ops.aten_pow),
+    TorchLibOpInfo("prod", core_ops.aten_prod).skip(
+        matcher=lambda sample: sample.kwargs.get("dim") is not None
+        or sample.kwargs.get("keepdim") is not None
+        or sample.kwargs.get("dtype") != -1,
+        reason="this Aten overload only accept 1 inputs: self",
+    ),
+    TorchLibOpInfo("prod_dim_int", core_ops.aten_prod_dim_int).skip(
+        matcher=lambda sample: (
+            sample.kwargs.get("dim") is None and sample.kwargs.get("keepdim") is None
+        )
+        or sample.kwargs.get("dtype") != -1,
+        reason="this Aten overload can accept 3 inputs:(self, dim, keepdim)",
+    ),
     TorchLibOpInfo("nn.functional.prelu", core_ops.aten_prelu),
     TorchLibOpInfo("ops.aten.rand", core_ops.aten_rand, nondeterministic=True),
     TorchLibOpInfo("ops.aten.rand_like", core_ops.aten_rand_like, nondeterministic=True),
@@ -2203,6 +2216,7 @@ def _where_input_wrangler(
     OPS_DB, "ops.aten._log_softmax", ("ops.aten._log_softmax_half",)
 )
 ops_test_common.duplicate_opinfo(OPS_DB, "ops.aten._softmax", ("ops.aten._softmax_half",))
+ops_test_common.duplicate_opinfo(OPS_DB, "prod", ("prod_dim_int",))
 ops_test_common.duplicate_opinfo(OPS_DB, "round", ("round_decimals",))
 ops_test_common.duplicate_opinfo(OPS_DB, "squeeze", ("squeeze_dim",))
 ops_test_common.duplicate_opinfo(OPS_DB, "view_as_complex", ("view_as_complex_copy",))