Fix failing tests, remove integration test

src/transformers/utils/fx.py

@@ -103,7 +103,7 @@ def _generate_supported_model_class_names(
     "deberta",
     "deberta-v2",
     "distilbert",
-    "donut",
+    "donut-swin",
     "electra",
     "gpt2",
     "gpt_neo",

tests/models/donut/test_feature_extraction_donut.py

@@ -72,7 +72,7 @@ def prepare_feat_extract_dict(self):
             "do_pad": self.do_pad,
             "do_normalize": self.do_normalize,
             "image_mean": self.image_mean,
-            "image_std": self.image_std, 
+            "image_std": self.image_std,
         }
 
 
@@ -196,4 +196,4 @@ def test_call_pytorch(self):
                 self.feature_extract_tester.size[1],
                 self.feature_extract_tester.size[0],
             ),
-        )
+        )

tests/models/donut/test_modeling_donut_swin.py

@@ -22,8 +22,8 @@
 import unittest
 
 from transformers import DonutSwinConfig
-from transformers.testing_utils import require_torch, require_vision, slow, torch_device
-from transformers.utils import cached_property, is_torch_available, is_torch_fx_available, is_vision_available
+from transformers.testing_utils import require_torch, slow, torch_device
+from transformers.utils import is_torch_available, is_torch_fx_available
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
@@ -36,9 +36,6 @@
     from transformers import DonutSwinModel
     from transformers.models.donut.modeling_donut_swin import DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST
 
-if is_vision_available():
-    from transformers import AutoFeatureExtractor
-
 if is_torch_fx_available():
     from transformers.utils.fx import symbolic_trace
 
@@ -465,15 +462,3 @@ def flatten_output(output):
                         torch.allclose(model_output[i], loaded_output[i]),
                         f"serialized model {i}th output doesn't match model {i}th output for {model_class}",
                     )
-
-
-@require_vision
-@require_torch
-class DonutSwinModelIntegrationTest(unittest.TestCase):
-    @cached_property
-    def default_feature_extractor(self):
-        return AutoFeatureExtractor.from_pretrained("naver-clova-ix/donut-base") if is_vision_available() else None
-
-    @slow
-    def test_inference_image_classification_head(self):
-        raise NotImplementedError("To do")