Remove script datasets in tests (#38940)

* remove trust_remote_code

* again

* Revert "Skip some tests for now (#38931)"

This reverts commit 31d30b7224.

* again

* style

* again

* again

* style

* fix integration test

* fix tests

* style

* fix

* fix

* fix the last ones

* style

* last one

* fix last

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/models/mobilevit/test_image_processing_mobilevit.py

@@ -27,8 +27,6 @@ if is_torch_available():
     import torch
 
 if is_vision_available():
-    from PIL import Image
-
     from transformers import MobileViTImageProcessor
 
 
@@ -86,23 +84,14 @@ class MobileViTImageProcessingTester:
 
 
 def prepare_semantic_single_inputs():
-    dataset = load_dataset("hf-internal-testing/fixtures_ade20k", split="test", trust_remote_code=True)
-
-    image = Image.open(dataset[0]["file"])
-    map = Image.open(dataset[1]["file"])
-
-    return image, map
+    ds = load_dataset("hf-internal-testing/fixtures_ade20k", split="test")
+    example = ds[0]
+    return example["image"], example["map"]
 
 
 def prepare_semantic_batch_inputs():
-    dataset = load_dataset("hf-internal-testing/fixtures_ade20k", split="test", trust_remote_code=True)
-
-    image1 = Image.open(dataset[0]["file"])
-    map1 = Image.open(dataset[1]["file"])
-    image2 = Image.open(dataset[2]["file"])
-    map2 = Image.open(dataset[3]["file"])
-
-    return [image1, image2], [map1, map2]
+    ds = load_dataset("hf-internal-testing/fixtures_ade20k", split="test")
+    return list(ds["image"][:2]), list(ds["map"][:2])
 
 
 @require_torch
@@ -135,7 +124,6 @@ class MobileViTImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
         self.assertEqual(image_processor.size, {"shortest_edge": 42})
         self.assertEqual(image_processor.crop_size, {"height": 84, "width": 84})
 
-    @unittest.skip("temporary to avoid failing on circleci")
     def test_call_segmentation_maps(self):
         # Initialize image_processing
         image_processing = self.image_processing_class(**self.image_processor_dict)