diff --git a/onnxscript/function_libs/torch_lib/ops/nn.py b/onnxscript/function_libs/torch_lib/ops/nn.py
index 37298f3a9..62edd7caa 100644
--- a/onnxscript/function_libs/torch_lib/ops/nn.py
+++ b/onnxscript/function_libs/torch_lib/ops/nn.py
@@ -1769,8 +1769,9 @@ def aten_scaled_dot_product_attention(
     dropout_p: float = 0.0,
     is_causal: bool = False,
     scale: Optional[float] = None,
+    enable_gqa: bool = False,
 ) -> TFloat:
-    """scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None) -> Tensor
+    """scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None, bool enable_gqa=False) -> Tensor
 
     Reference: https://pytorch.org/docs/stable/generated/torch.nn.functional.scaled_dot_product_attention.html
 
@@ -1790,6 +1791,10 @@ def aten_scaled_dot_product_attention(
         is_causal and attn_mask is None
     ), "is_causal and attn_mask cannot be set at the same time"
 
+    assert (
+        not enable_gqa
+    ), "conversion of scaled_dot_product_attention not implemented if enable_gqa is True"
+
     # Reference: https://pytorch.org/docs/stable/generated/torch.nn.functional.scaled_dot_product_attention.html
     if scale is None:
         scale = _attention_scale(query)
@@ -1982,8 +1987,9 @@ def aten_scaled_dot_product_attention_bool_mask(
     dropout_p: float = 0.0,
     is_causal: bool = False,
     scale: Optional[float] = None,
+    enable_gqa: bool = False,
 ) -> TFloat:
-    """scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None) -> Tensor
+    """scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, *, float? scale=None, bool enable_gqa=False) -> Tensor
 
     Reference: https://pytorch.org/docs/stable/generated/torch.nn.functional.scaled_dot_product_attention.html
 
@@ -2003,6 +2009,10 @@ def aten_scaled_dot_product_attention_bool_mask(
         is_causal and attn_mask is None
     ), "is_causal and attn_mask cannot be set at the same time"
 
+    assert (
+        not enable_gqa
+    ), "conversion of scaled_dot_product_attention not implemented if enable_gqa is True"
+
     if scale is None:
         scale = _attention_scale(query)
     scale = op.CastLike(scale, query)