[Styling] stylify using ruff (#27144)

* try to stylify using ruff

* might need to remove these changes?

* use ruf format andruff check

* use isinstance instead of type comparision

* use # fmt: skip

* use # fmt: skip

* nits

* soem styling changes

* update ci job

* nits isinstance

* more files update

* nits

* more nits

* small nits

* check and format

* revert wrong changes

* actually use formatter instead of checker

* nits

* well docbuilder is overwriting this commit

* revert notebook changes

* try to nuke docbuilder

* style

* fix feature exrtaction test

* remve `indent-width = 4`

* fixup

* more nits

* update the ruff version that we use

* style

* nuke docbuilder styling

* leve the print for detected changes

* nits

* Remove file I/O

Co-authored-by: charliermarsh
 <charlie.r.marsh@gmail.com>

* style

* nits

* revert notebook changes

* Add # fmt skip when possible

* Add # fmt skip when possible

* Fix

* More `  # fmt: skip` usage

* More `  # fmt: skip` usage

* More `  # fmt: skip` usage

* NIts

* more fixes

* fix tapas

* Another way to skip

* Recommended way

* Fix two more fiels

* Remove asynch
Remove asynch

---------

Co-authored-by: charliermarsh <charlie.r.marsh@gmail.com>

tests/models/xglm/test_modeling_tf_xglm.py

@@ -177,9 +177,7 @@ class TFXGLMModelLanguageGenerationTest(unittest.TestCase):
         model = TFXGLMForCausalLM.from_pretrained("facebook/xglm-564M")
         input_ids = tf.convert_to_tensor([[2, 268, 9865]], dtype=tf.int32)  # The dog
         # </s> The dog is a very friendly dog. He is very affectionate and loves to play with other
-        # fmt: off
-        expected_output_ids = [2, 268, 9865, 67, 11, 1988, 57252, 9865, 5, 984, 67, 1988, 213838, 1658, 53, 70446, 33, 6657, 278, 1581]
-        # fmt: on
+        expected_output_ids = [2, 268, 9865, 67, 11, 1988, 57252, 9865, 5, 984, 67, 1988, 213838, 1658, 53, 70446, 33, 6657, 278, 1581]  # fmt: skip
         output_ids = model.generate(input_ids, do_sample=False, num_beams=1)
         if verify_outputs:
             self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)

tests/models/xglm/test_modeling_xglm.py

@@ -383,9 +383,7 @@ class XGLMModelLanguageGenerationTest(unittest.TestCase):
         model.to(torch_device)
         input_ids = torch.tensor([[2, 268, 9865]], dtype=torch.long, device=torch_device)  # The dog
         # </s> The dog is a very friendly dog. He is very affectionate and loves to play with other
-        # fmt: off
-        expected_output_ids = [2, 268, 9865, 67, 11, 1988, 57252, 9865, 5, 984, 67, 1988, 213838, 1658, 53, 70446, 33, 6657, 278, 1581]
-        # fmt: on
+        expected_output_ids = [2, 268, 9865, 67, 11, 1988, 57252, 9865, 5, 984, 67, 1988, 213838, 1658, 53, 70446, 33, 6657, 278, 1581]  # fmt: skip
         output_ids = model.generate(input_ids, do_sample=False, num_beams=1)
         if verify_outputs:
             self.assertListEqual(output_ids[0].tolist(), expected_output_ids)

tests/models/xglm/test_tokenization_xglm.py

@@ -182,9 +182,7 @@ class XGLMTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
             'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
             " add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth"
         )
-        # fmt: off
-        original_tokenizer_encodings = [2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 71630, 28085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 13675, 377, 652, 7580, 10341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 202277, 17892, 33, 60, 87, 4, 3234, 157, 61, 2667, 52376, 19, 88, 23, 735]
-        # fmt: on
+        original_tokenizer_encodings = [2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 71630, 28085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 13675, 377, 652, 7580, 10341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 202277, 17892, 33, 60, 87, 4, 3234, 157, 61, 2667, 52376, 19, 88, 23, 735]  # fmt: skip
 
         self.assertListEqual(original_tokenizer_encodings, self.big_tokenizer.encode(symbols))