Fixes torch jit tracing for LayoutLMv2 model (re-open) (#18313)

* Fixes torch jit tracing for LayoutLMv2 model.
Pytorch seems to reuse memory for input_shape which caused a mismatch in shapes later in the forward pass.

* Fixed code quality

* avoid unneeded allocation of vector for shape

tests/models/layoutlmv2/test_modeling_layoutlmv2.py

@@ -260,7 +260,7 @@ class LayoutLMv2ModelTester:
 class LayoutLMv2ModelTest(ModelTesterMixin, unittest.TestCase):
 
     test_pruning = False
-    test_torchscript = False
+    test_torchscript = True
     test_mismatched_shapes = False
 
     all_model_classes = (

tests/test_modeling_common.py

@@ -648,6 +648,13 @@ class ModelTesterMixin:
                     traced_model = torch.jit.trace(
                         model, (main_input, attention_mask, decoder_input_ids, decoder_attention_mask)
                     )
+                elif "bbox" in inputs and "image" in inputs:  # LayoutLMv2 requires additional inputs
+                    input_ids = inputs["input_ids"]
+                    bbox = inputs["bbox"]
+                    image = inputs["image"].tensor
+                    traced_model = torch.jit.trace(
+                        model, (input_ids, bbox, image), check_trace=False
+                    )  # when traced model is checked, an error is produced due to name mangling
                 else:
                     main_input = inputs[main_input_name]
                     traced_model = torch.jit.trace(model, main_input)