xfail for FX backend conformance test

openvinotoolkit · Feb 14, 2025 · 960e12f · 960e12f
1 parent 49d6251
commit 960e12f
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Showing 3 changed files with 10 additions and 5 deletions.
diff --git a/tests/post_training/data/ptq_reference_data.yaml b/tests/post_training/data/ptq_reference_data.yaml
@@ -39,6 +39,7 @@ torchvision/resnet18_backend_CUDA_TORCH:
   metric_value: 0.69152
 torchvision/resnet18_backend_FX_TORCH:
   metric_value: 0.6946
+  xfail_reason: "Issue-CVS-162009"
 torchvision/resnet18_backend_CUDA_FX_TORCH:
   metric_value: 0.6946
 torchvision/mobilenet_v3_small_BC_backend_FP32:
@@ -49,6 +50,7 @@ torchvision/mobilenet_v3_small_BC_backend_ONNX:
   metric_value: 0.6679
 torchvision/mobilenet_v3_small_BC_backend_FX_TORCH:
   metric_value: 0.6679
+  xfail_reason: "Issue-CVS-162009"
 torchvision/mobilenet_v3_small_BC_backend_CUDA_FX_TORCH:
   metric_value: 0.6664
 torchvision/vit_b_16_backend_FP32:
@@ -57,6 +59,7 @@ torchvision/vit_b_16_backend_OV:
   metric_value: 0.80948
 torchvision/vit_b_16_backend_FX_TORCH:
   metric_value: 0.80922
+  xfail_reason: "Issue-CVS-162009"
 torchvision/vit_b_16_backend_CUDA_FX_TORCH:
   metric_value: 0.80922
 torchvision/swin_v2_s_backend_FP32:
@@ -65,6 +68,7 @@ torchvision/swin_v2_s_backend_OV:
   metric_value: 0.83638
 torchvision/swin_v2_s_backend_FX_TORCH:
   metric_value: 0.8360
+  xfail_reason: "Issue-CVS-162009"
 torchvision/swin_v2_s_backend_CUDA_FX_TORCH:
   metric_value: 0.8360
 timm/crossvit_9_240_backend_CUDA_TORCH:

diff --git a/tests/post_training/pipelines/base.py b/tests/post_training/pipelines/base.py
@@ -441,7 +441,7 @@ def save_compressed_model(self) -> None:
             self.path_compressed_ir = self.output_model_dir / "model.xml"
             ov.serialize(ov_model, self.path_compressed_ir)
         elif self.backend in FX_BACKENDS:
-            exported_model = torch.export.export_for_inference(self.compressed_model.cpu(), (self.dummy_tensor.cpu(),))
+            exported_model = torch.export.export(self.compressed_model.cpu(), (self.dummy_tensor.cpu(),))
             ov_model = ov.convert_model(exported_model, example_input=self.dummy_tensor.cpu(), input=self.input_size)
             ov_model.reshape(self.input_size)
             self.path_compressed_ir = self.output_model_dir / "model.xml"
@@ -468,7 +468,8 @@ def get_num_compressed(self) -> None:
         """
         Get number of the FakeQuantize nodes in the compressed IR.
         """
-
+        if self.backend in FX_BACKENDS:
+            return
         ie = ov.Core()
         model = ie.read_model(model=self.path_compressed_ir)
 

diff --git a/tests/post_training/pipelines/image_classification_torchvision.py b/tests/post_training/pipelines/image_classification_torchvision.py
@@ -30,7 +30,7 @@ def _torch_export_for_training(model: torch.nn.Module, args: Tuple[Any, ...]) ->
 
 
 def _torch_export(model: torch.nn.Module, args: Tuple[Any, ...]) -> torch.fx.GraphModule:
-    return torch.export.export_for_inference(model, args).module()
+    return torch.export.export(model, args).module()
 
 
 @dataclass
@@ -118,14 +118,14 @@ def _dump_model_fp32(self) -> None:
         if self.backend in PT_BACKENDS:
             with disable_patching():
                 ov_model = ov.convert_model(
-                    torch.export.export_for_inference(self.model, args=(self.dummy_tensor,)),
+                    self.model,
                     example_input=self.dummy_tensor,
                     input=self.input_size,
                 )
             ov.serialize(ov_model, self.fp32_model_dir / "model_fp32.xml")
 
         if self.backend in FX_BACKENDS:
-            exported_model = torch.export.export_for_inference(self.model.cpu(), (self.dummy_tensor.cpu(),))
+            exported_model = torch.export.export(self.model.cpu(), (self.dummy_tensor.cpu(),))
             ov_model = ov.convert_model(exported_model, example_input=self.dummy_tensor, input=self.input_size)
             ov.serialize(ov_model, self.fp32_model_dir / "fx_model_fp32.xml")