add fake_quantize_per_channel_affine expected failure case for non-integer zero_point

Author: ruro

tests/function_libs/torch_lib/ops_test_data.py

@@ -698,7 +698,10 @@ def _where_input_wrangler(
     TorchLibOpInfo("special.erfcx", special_ops.aten_special_erfcx).xfail(
         reason="fixme: The implementation is numerically unstable: https://github.com/microsoft/onnxscript/issues/1223"
     ),
-    TorchLibOpInfo("fake_quantize_per_channel_affine", core_ops.aten_fake_quantize_per_channel_affine),
+    TorchLibOpInfo("fake_quantize_per_channel_affine", core_ops.aten_fake_quantize_per_channel_affine).xfail(
+        reason="fixme: ONNX (De)QuantizeLinear only supports integer zero_point values",
+        matcher=lambda sample: sample.args[1].dtype != torch.int32,
+    ),
     TorchLibOpInfo("fake_quantize_per_tensor_affine", core_ops.aten_fake_quantize_per_tensor_affine),
     TorchLibOpInfo("fill", core_ops.aten_fill),
     TorchLibOpInfo("flip", core_ops.aten_flip).skip(