[ONNX] Drop 'aten_graph' arg for 'DynamoExporter'

ghstack-source-id: b15d9612edec3ebd2917ad381e5c52de79416d1b
Pull Request resolved: #99667

test/onnx/test_fx_to_onnx_with_onnxruntime.py

@@ -468,13 +468,17 @@ def forward(self, x):
 
         _run_test_with_fx_to_onnx_exporter_and_onnx_runtime(self, SigmoidModel(), (x,))
 
-    @pytorch_test_common.xfail(
-        "RuntimeError: false INTERNAL ASSERT FAILED at "
-        "'/home/titaiwang/pytorch/build/aten/src/ATen/RegisterFunctionalization_0.cpp':3725,"
-        " please report a bug to PyTorch. mutating a non-functional tensor with a "
-        "functional tensor is not allowed. Please ensure that all of your inputs are "
-        "wrapped inside of a functionalize() call."
-    )
+    @skip_if_no_torchvision
+    def test_resnet18(self):
+        model = torchvision.models.resnet18(pretrained=False)
+        dummy_input = torch.randn(1, 3, 224, 224)
+
+        _run_test_with_fx_to_onnx_exporter_and_onnx_runtime(
+            self,
+            model,
+            (dummy_input,),
+        )
+
     @skip_if_no_torchvision
     def test_shufflenet_v2(self):
         model = torchvision.models.shufflenet_v2_x0_5(pretrained=False)

torch/onnx/_internal/fx/dynamo_exporter.py

@@ -164,10 +164,7 @@ def export(self) -> torch.onnx.ExportOutput:
         # TODO(wechi): There are several symbolic tracing mechanisms to convert
         # nn.Module to FX graph. We should choose the right one after they are
         # matured.
-        # TODO(titaiwang): Set `tracing_mode` according to `self.options.dynamic_shapes`
-        graph_module, graph_guard = torch._dynamo.export(
-            wrapped_model, *args, aten_graph=True, **kwargs
-        )
+        graph_module, graph_guard = torch._dynamo.export(wrapped_model, *args, **kwargs)
         del graph_guard  # Unused
         torch._dynamo.reset()