Fix CI failures

Author: raghavanone

src/transformers/__init__.py

@@ -822,10 +822,7 @@
         "TapasConfig",
         "TapasTokenizer",
     ],
-    "models.textnet": [
-        "TEXTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
-        "TextNetConfig"
-    ],
+    "models.textnet": ["TEXTNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "TextNetConfig"],
     "models.time_series_transformer": [
         "TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
         "TimeSeriesTransformerConfig",

src/transformers/models/auto/modeling_auto.py

@@ -95,10 +95,7 @@
         ("ernie_m", "ErnieMModel"),
         ("esm", "EsmModel"),
         ("falcon", "FalconModel"),
-<<<<<<< HEAD
         ("fastspeech2_conformer", "FastSpeech2ConformerModel"),
-=======
->>>>>>> ae576e088 (Remove all the references of fast model)
         ("flaubert", "FlaubertModel"),
         ("flava", "FlavaModel"),
         ("fnet", "FNetModel"),

tests/models/textnet/test_modeling_textnet.py

@@ -197,7 +197,7 @@ def prepare_config_and_inputs_for_common(self):
         return config, inputs_dict
 
 
-# Copied from tests.test_modeling_bit.BitBackboneTest with Bit -> TextNet
+# Copied from tests.models.bit.test_modeling_bit.BitBackboneTest with Bit -> TextNet
 @require_torch
 class TextNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     all_model_classes = (TextNetModel, TextNetForImageClassification, TextNetBackbone) if is_torch_available() else ()
@@ -327,7 +327,7 @@ def test_inference_textnet_image_classification(self):
         self.assertEqual(output.logits.shape, torch.Size([1, 2]))
 
 
-# Copied from tests.test_modeling_bit.BitBackboneTest with Bit -> TextNet
+# Copied from tests.models.bit.test_modeling_bit.BitBackboneTest with Bit -> TextNet
 @require_torch
 class TextNetBackboneTest(BackboneTesterMixin, unittest.TestCase):
     all_model_classes = (TextNetBackbone,) if is_torch_available() else ()