diff --git a/onnxscript/backend/onnx_export_test.py b/onnxscript/backend/onnx_export_test.py
index ab97c5f98..c1a2afbfb 100644
--- a/onnxscript/backend/onnx_export_test.py
+++ b/onnxscript/backend/onnx_export_test.py
@@ -100,6 +100,10 @@ def skip(pattern: str | Pattern, reason: str, *, condition: bool = True):
             "cannot import module, import_module does not work",
         ),
         skip("^test_bitwise_not_3d", "cannot import module, import_module does not work"),
+        skip(
+            "^test_resize_upsample_scales_linear_half_pixel_symmetric",
+            "cannot import module, import_module does not work",
+        ),
     )
 
 
diff --git a/onnxscript/function_libs/torch_lib/ops/quantized_decomposed.py b/onnxscript/function_libs/torch_lib/ops/quantized_decomposed.py
index fa2df9751..92962a9ea 100644
--- a/onnxscript/function_libs/torch_lib/ops/quantized_decomposed.py
+++ b/onnxscript/function_libs/torch_lib/ops/quantized_decomposed.py
@@ -56,6 +56,8 @@ def quantized_decomposed_dequantize_per_tensor(
 ) -> TensorType:
     # TODO(justinchuby): Use dtype when we use opset 21
     dequantized = op.DequantizeLinear(input, scale, common.constant(zero_point, dtype=dtype))
-    if out_dtype == -1:
+    if out_dtype in (-1, None):
+        # out_dtype can be None as well
         return dequantized
+    assert out_dtype > 0, f"out_dtype must be -1 or > 0 not {out_dtype}"
     return op.Cast(dequantized, to=out_dtype)