Add DeiT (PyTorch) (#11056)

* First draft of deit

* More improvements

* Remove DeiTTokenizerFast from init

* Conversion script works

* Add DeiT to ViT conversion script

* Add tests, add head model, add support for deit in vit conversion script

* Update model checkpoint names

* Update image_mean and image_std, set resample to bicubic

* Improve docs

* Docs improvements

* Add DeiTForImageClassificationWithTeacher to init

* Address comments by @sgugger

* Improve feature extractors

* Make fix-copies

* Minor fixes

* Address comments by @patil-suraj

* All models uploaded

* Fix tests

* Remove labels argument from DeiTForImageClassificationWithTeacher

* Fix-copies, style and quality

* Fix tests

* Fix typo

* Multiple docs improvements

* More docs fixes

tests/test_feature_extraction_vit.py

@@ -42,11 +42,11 @@ class ViTFeatureExtractionTester(unittest.TestCase):
         image_size=18,
         min_resolution=30,
         max_resolution=400,
-        image_mean=[0.5, 0.5, 0.5],
-        image_std=[0.5, 0.5, 0.5],
-        do_normalize=True,
         do_resize=True,
         size=18,
+        do_normalize=True,
+        image_mean=[0.5, 0.5, 0.5],
+        image_std=[0.5, 0.5, 0.5],
     ):
         self.parent = parent
         self.batch_size = batch_size
@@ -54,11 +54,11 @@ class ViTFeatureExtractionTester(unittest.TestCase):
         self.image_size = image_size
         self.min_resolution = min_resolution
         self.max_resolution = max_resolution
-        self.image_mean = image_mean
-        self.image_std = image_std
-        self.do_normalize = do_normalize
         self.do_resize = do_resize
         self.size = size
+        self.do_normalize = do_normalize
+        self.image_mean = image_mean
+        self.image_std = image_std
 
     def prepare_feat_extract_dict(self):
         return {