[`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

...

pyproject.toml

-[tool.black]
-line-length = 119
-target-version = ['py37']
-
 [tool.ruff]
 # Never enforce `E501` (line length violations).
-ignore = ["C901", "E501", "E741"]
+ignore = ["C901", "E501", "E741", "F402", "F823" ]
 select = ["C", "E", "F", "I", "W"]
 line-length = 119
 
@@ -18,6 +14,19 @@ line-length = 119
 lines-after-imports = 2
 known-first-party = ["transformers"]
 
+[tool.ruff.format]
+# Like Black, use double quotes for strings.
+quote-style = "double"
+
+# Like Black, indent with spaces, rather than tabs.
+indent-style = "space"
+
+# Like Black, respect magic trailing commas.
+skip-magic-trailing-comma = false
+
+# Like Black, automatically detect the appropriate line ending.
+line-ending = "auto"
+
 [tool.pytest.ini_options]
 doctest_optionflags="NUMBER NORMALIZE_WHITESPACE ELLIPSIS"
 doctest_glob="**/*.md"

scripts/check_tokenizers.py

 from collections import Counter
+
 import datasets
+
 import transformers
 from transformers.convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
-
 from transformers.utils import logging
 
+
 logging.set_verbosity_info()
 
 TOKENIZER_CLASSES = {
@@ -101,8 +103,8 @@ def check_details(line, spm_ids, tok_ids, slow, fast):
     except Exception:
         pass
 
-    ok_start = fast.decode(spm_ids[:first])
-    ok_end = fast.decode(spm_ids[last:])
+    fast.decode(spm_ids[:first])
+    fast.decode(spm_ids[last:])
     wrong = fast.decode(spm_ids[first:last])
     print()
     print(wrong)

scripts/fsmt/fsmt-make-super-tiny-model.py

@@ -24,18 +24,19 @@
 #
 # It will be used then as "stas/tiny-wmt19-en-ru"
 
-from pathlib import Path
 import json
 import tempfile
+from pathlib import Path
 
-from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
+from transformers import FSMTConfig, FSMTForConditionalGeneration, FSMTTokenizer
 from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES
 
+
 mname_tiny = "tiny-wmt19-en-ru"
 
 # Build
 
-# borrowed from a test 
+# borrowed from a test
 vocab = [ "l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "w</w>", "r</w>", "t</w>", "lo", "low", "er</w>", "low</w>", "lowest</w>", "newer</w>", "wider</w>", "<unk>", ]
 vocab_tokens = dict(zip(vocab, range(len(vocab))))
 merges = ["l o 123", "lo w 1456", "e r</w> 1789", ""]
@@ -57,7 +58,7 @@ with tempfile.TemporaryDirectory() as tmpdirname:
         tgt_vocab_file=tgt_vocab_file,
         merges_file=merges_file,
     )
-    
+
 config = FSMTConfig(
     langs=['ru', 'en'],
     src_vocab_size=1000, tgt_vocab_size=1000,

scripts/fsmt/fsmt-make-tiny-model.py

@@ -27,16 +27,18 @@
 # It will be used then as "stas/tiny-wmt19-en-de"
 
 # Build
-from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
+from transformers import FSMTConfig, FSMTForConditionalGeneration, FSMTTokenizer
+
+
 mname = "facebook/wmt19-en-de"
 tokenizer = FSMTTokenizer.from_pretrained(mname)
 # get the correct vocab sizes, etc. from the master model
 config = FSMTConfig.from_pretrained(mname)
-config.update(dict(
-    d_model=4,
-    encoder_layers=1, decoder_layers=1,
-    encoder_ffn_dim=4, decoder_ffn_dim=4,
-    encoder_attention_heads=1, decoder_attention_heads=1))
+config.update({
+    "d_model": 4,
+    "encoder_layers": 1, "decoder_layers": 1,
+    "encoder_ffn_dim": 4, "decoder_ffn_dim": 4,
+    "encoder_attention_heads": 1, "decoder_attention_heads": 1})
 
 tiny_model = FSMTForConditionalGeneration(config)
 print(f"num of params {tiny_model.num_parameters()}")

scripts/fsmt/gen-card-allenai-wmt16.py

@@ -19,6 +19,7 @@
 import os
 from pathlib import Path
 
+
 def write_model_card(model_card_dir, src_lang, tgt_lang, model_name):
 
     texts = {

scripts/fsmt/gen-card-allenai-wmt19.py

@@ -19,6 +19,7 @@
 import os
 from pathlib import Path
 
+
 def write_model_card(model_card_dir, src_lang, tgt_lang, model_name):
 
     texts = {

scripts/fsmt/gen-card-facebook-wmt19.py

@@ -19,6 +19,7 @@
 import os
 from pathlib import Path
 
+
 def write_model_card(model_card_dir, src_lang, tgt_lang):
 
     texts = {
@@ -39,7 +40,7 @@ def write_model_card(model_card_dir, src_lang, tgt_lang):
 
     readme = f"""
 ---
-language: 
+language:
 - {src_lang}
 - {tgt_lang}
 thumbnail:

scripts/pegasus/build_test_sample_spm_no_bos.py

@@ -13,15 +13,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus 
+# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus
 
 # 1. pip install sentencepiece
-# 
+#
 # 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt
 
 # 3. build
 import sentencepiece as spm
 
+
 # pegasus:
 # 1. no bos
 # 2. eos_id is 1

scripts/stale.py

@@ -15,8 +15,8 @@
 Script to close stale issue. Taken in part from the AllenNLP repository.
 https://github.com/allenai/allennlp.
 """
-from datetime import datetime as dt
 import os
+from datetime import datetime as dt
 
 import github.GithubException
 from github import Github
@@ -39,7 +39,7 @@ def main():
 
     for i, issue in enumerate(open_issues):
         print(i, issue)
-        comments = sorted([comment for comment in issue.get_comments()], key=lambda i: i.created_at, reverse=True)
+        comments = sorted(list(issue.get_comments()), key=lambda i: i.created_at, reverse=True)
         last_comment = comments[0] if len(comments) > 0 else None
         if (
             last_comment is not None and last_comment.user.login == "github-actions[bot]"

setup.py

@@ -99,7 +99,6 @@ _deps = [
     "accelerate>=0.20.3",
     "av==9.2.0",  # Latest version of PyAV (10.0.0) has issues with audio stream.
     "beautifulsoup4",
-    "black~=23.1",
     "codecarbon==1.2.0",
     "cookiecutter==1.7.3",
     "dataclasses",
@@ -156,7 +155,7 @@ _deps = [
     "rhoknp>=1.1.0,<1.3.1",
     "rjieba",
     "rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1",
-    "ruff>=0.0.241,<=0.0.259",
+    "ruff>=0.1.5,<=0.2",
     "sacrebleu>=1.4.12,<2.0.0",
     "sacremoses",
     "safetensors>=0.3.1",
@@ -310,7 +309,7 @@ extras["testing"] = (
         "dill",
         "evaluate",
         "pytest-timeout",
-        "black",
+        "ruff",
         "sacrebleu",
         "rouge-score",
         "nltk",
@@ -329,7 +328,7 @@ extras["testing"] = (
 
 extras["deepspeed-testing"] = extras["deepspeed"] + extras["testing"] + extras["optuna"] + extras["sentencepiece"]
 
-extras["quality"] = deps_list("black", "datasets", "isort", "ruff", "GitPython", "hf-doc-builder", "urllib3")
+extras["quality"] = deps_list("datasets", "isort", "ruff", "GitPython", "hf-doc-builder", "urllib3")
 
 extras["all"] = (
     extras["tf"]

src/transformers/configuration_utils.py

@@ -246,6 +246,7 @@ class PretrainedConfig(PushToHubMixin):
             not be XLA-compatible. This option is here for backward compatibility and will be removed in Transformers
             v5.
     """
+
     model_type: str = ""
     is_composition: bool = False
     attribute_map: Dict[str, str] = {}

src/transformers/convert_slow_tokenizer.py

@@ -724,9 +724,7 @@ class MBart50Converter(SpmConverter):
             ("<unk>", 0.0),
         ]
         vocab += [(piece.piece, piece.score) for piece in proto.pieces[3:]]
-        # fmt: off
-        vocab += [("ar_AR", 0.0), ("cs_CZ", 0.0), ("de_DE", 0.0), ("en_XX", 0.0), ("es_XX", 0.0), ("et_EE", 0.0), ("fi_FI", 0.0), ("fr_XX", 0.0), ("gu_IN", 0.0), ("hi_IN", 0.0), ("it_IT", 0.0), ("ja_XX", 0.0), ("kk_KZ", 0.0), ("ko_KR", 0.0), ("lt_LT", 0.0), ("lv_LV", 0.0), ("my_MM", 0.0), ("ne_NP", 0.0), ("nl_XX", 0.0), ("ro_RO", 0.0), ("ru_RU", 0.0), ("si_LK", 0.0), ("tr_TR", 0.0), ("vi_VN", 0.0), ("zh_CN", 0.0), ("af_ZA", 0.0), ("az_AZ", 0.0), ("bn_IN", 0.0), ("fa_IR", 0.0), ("he_IL", 0.0), ("hr_HR", 0.0), ("id_ID", 0.0), ("ka_GE", 0.0), ("km_KH", 0.0), ("mk_MK", 0.0), ("ml_IN", 0.0), ("mn_MN", 0.0), ("mr_IN", 0.0), ("pl_PL", 0.0), ("ps_AF", 0.0), ("pt_XX", 0.0), ("sv_SE", 0.0), ("sw_KE", 0.0), ("ta_IN", 0.0), ("te_IN", 0.0), ("th_TH", 0.0), ("tl_XX", 0.0), ("uk_UA", 0.0), ("ur_PK", 0.0), ("xh_ZA", 0.0), ("gl_ES", 0.0), ("sl_SI", 0.0)]
-        # fmt: on
+        vocab += [("ar_AR", 0.0), ("cs_CZ", 0.0), ("de_DE", 0.0), ("en_XX", 0.0), ("es_XX", 0.0), ("et_EE", 0.0), ("fi_FI", 0.0), ("fr_XX", 0.0), ("gu_IN", 0.0), ("hi_IN", 0.0), ("it_IT", 0.0), ("ja_XX", 0.0), ("kk_KZ", 0.0), ("ko_KR", 0.0), ("lt_LT", 0.0), ("lv_LV", 0.0), ("my_MM", 0.0), ("ne_NP", 0.0), ("nl_XX", 0.0), ("ro_RO", 0.0), ("ru_RU", 0.0), ("si_LK", 0.0), ("tr_TR", 0.0), ("vi_VN", 0.0), ("zh_CN", 0.0), ("af_ZA", 0.0), ("az_AZ", 0.0), ("bn_IN", 0.0), ("fa_IR", 0.0), ("he_IL", 0.0), ("hr_HR", 0.0), ("id_ID", 0.0), ("ka_GE", 0.0), ("km_KH", 0.0), ("mk_MK", 0.0), ("ml_IN", 0.0), ("mn_MN", 0.0), ("mr_IN", 0.0), ("pl_PL", 0.0), ("ps_AF", 0.0), ("pt_XX", 0.0), ("sv_SE", 0.0), ("sw_KE", 0.0), ("ta_IN", 0.0), ("te_IN", 0.0), ("th_TH", 0.0), ("tl_XX", 0.0), ("uk_UA", 0.0), ("ur_PK", 0.0), ("xh_ZA", 0.0), ("gl_ES", 0.0), ("sl_SI", 0.0)]  # fmt: skip
         vocab += [("<mask>", 0.0)]
         return vocab
 
@@ -753,11 +751,7 @@ class NllbConverter(SpmConverter):
             ("<unk>", 0.0),
         ]
         vocab += [(piece.piece, piece.score) for piece in proto.pieces[3:]]
-        vocab += [
-            # fmt: off
-            ('ace_Arab', 0.0), ('ace_Latn', 0.0), ('acm_Arab', 0.0), ('acq_Arab', 0.0), ('aeb_Arab', 0.0), ('afr_Latn', 0.0), ('ajp_Arab', 0.0), ('aka_Latn', 0.0), ('amh_Ethi', 0.0), ('apc_Arab', 0.0), ('arb_Arab', 0.0), ('ars_Arab', 0.0), ('ary_Arab', 0.0), ('arz_Arab', 0.0), ('asm_Beng', 0.0), ('ast_Latn', 0.0), ('awa_Deva', 0.0), ('ayr_Latn', 0.0), ('azb_Arab', 0.0), ('azj_Latn', 0.0), ('bak_Cyrl', 0.0), ('bam_Latn', 0.0), ('ban_Latn', 0.0), ('bel_Cyrl', 0.0), ('bem_Latn', 0.0), ('ben_Beng', 0.0), ('bho_Deva', 0.0), ('bjn_Arab', 0.0), ('bjn_Latn', 0.0), ('bod_Tibt', 0.0), ('bos_Latn', 0.0), ('bug_Latn', 0.0), ('bul_Cyrl', 0.0), ('cat_Latn', 0.0), ('ceb_Latn', 0.0), ('ces_Latn', 0.0), ('cjk_Latn', 0.0), ('ckb_Arab', 0.0), ('crh_Latn', 0.0), ('cym_Latn', 0.0), ('dan_Latn', 0.0), ('deu_Latn', 0.0), ('dik_Latn', 0.0), ('dyu_Latn', 0.0), ('dzo_Tibt', 0.0), ('ell_Grek', 0.0), ('eng_Latn', 0.0), ('epo_Latn', 0.0), ('est_Latn', 0.0), ('eus_Latn', 0.0), ('ewe_Latn', 0.0), ('fao_Latn', 0.0), ('pes_Arab', 0.0), ('fij_Latn', 0.0), ('fin_Latn', 0.0), ('fon_Latn', 0.0), ('fra_Latn', 0.0), ('fur_Latn', 0.0), ('fuv_Latn', 0.0), ('gla_Latn', 0.0), ('gle_Latn', 0.0), ('glg_Latn', 0.0), ('grn_Latn', 0.0), ('guj_Gujr', 0.0), ('hat_Latn', 0.0), ('hau_Latn', 0.0), ('heb_Hebr', 0.0), ('hin_Deva', 0.0), ('hne_Deva', 0.0), ('hrv_Latn', 0.0), ('hun_Latn', 0.0), ('hye_Armn', 0.0), ('ibo_Latn', 0.0), ('ilo_Latn', 0.0), ('ind_Latn', 0.0), ('isl_Latn', 0.0), ('ita_Latn', 0.0), ('jav_Latn', 0.0), ('jpn_Jpan', 0.0), ('kab_Latn', 0.0), ('kac_Latn', 0.0), ('kam_Latn', 0.0), ('kan_Knda', 0.0), ('kas_Arab', 0.0), ('kas_Deva', 0.0), ('kat_Geor', 0.0), ('knc_Arab', 0.0), ('knc_Latn', 0.0), ('kaz_Cyrl', 0.0), ('kbp_Latn', 0.0), ('kea_Latn', 0.0), ('khm_Khmr', 0.0), ('kik_Latn', 0.0), ('kin_Latn', 0.0), ('kir_Cyrl', 0.0), ('kmb_Latn', 0.0), ('kon_Latn', 0.0), ('kor_Hang', 0.0), ('kmr_Latn', 0.0), ('lao_Laoo', 0.0), ('lvs_Latn', 0.0), ('lij_Latn', 0.0), ('lim_Latn', 0.0), ('lin_Latn', 0.0), ('lit_Latn', 0.0), ('lmo_Latn', 0.0), ('ltg_Latn', 0.0), ('ltz_Latn', 0.0), ('lua_Latn', 0.0), ('lug_Latn', 0.0), ('luo_Latn', 0.0), ('lus_Latn', 0.0), ('mag_Deva', 0.0), ('mai_Deva', 0.0), ('mal_Mlym', 0.0), ('mar_Deva', 0.0), ('min_Latn', 0.0), ('mkd_Cyrl', 0.0), ('plt_Latn', 0.0), ('mlt_Latn', 0.0), ('mni_Beng', 0.0), ('khk_Cyrl', 0.0), ('mos_Latn', 0.0), ('mri_Latn', 0.0), ('zsm_Latn', 0.0), ('mya_Mymr', 0.0), ('nld_Latn', 0.0), ('nno_Latn', 0.0), ('nob_Latn', 0.0), ('npi_Deva', 0.0), ('nso_Latn', 0.0), ('nus_Latn', 0.0), ('nya_Latn', 0.0), ('oci_Latn', 0.0), ('gaz_Latn', 0.0), ('ory_Orya', 0.0), ('pag_Latn', 0.0), ('pan_Guru', 0.0), ('pap_Latn', 0.0), ('pol_Latn', 0.0), ('por_Latn', 0.0), ('prs_Arab', 0.0), ('pbt_Arab', 0.0), ('quy_Latn', 0.0), ('ron_Latn', 0.0), ('run_Latn', 0.0), ('rus_Cyrl', 0.0), ('sag_Latn', 0.0), ('san_Deva', 0.0), ('sat_Beng', 0.0), ('scn_Latn', 0.0), ('shn_Mymr', 0.0), ('sin_Sinh', 0.0), ('slk_Latn', 0.0), ('slv_Latn', 0.0), ('smo_Latn', 0.0), ('sna_Latn', 0.0), ('snd_Arab', 0.0), ('som_Latn', 0.0), ('sot_Latn', 0.0), ('spa_Latn', 0.0), ('als_Latn', 0.0), ('srd_Latn', 0.0), ('srp_Cyrl', 0.0), ('ssw_Latn', 0.0), ('sun_Latn', 0.0), ('swe_Latn', 0.0), ('swh_Latn', 0.0), ('szl_Latn', 0.0), ('tam_Taml', 0.0), ('tat_Cyrl', 0.0), ('tel_Telu', 0.0), ('tgk_Cyrl', 0.0), ('tgl_Latn', 0.0), ('tha_Thai', 0.0), ('tir_Ethi', 0.0), ('taq_Latn', 0.0), ('taq_Tfng', 0.0), ('tpi_Latn', 0.0), ('tsn_Latn', 0.0), ('tso_Latn', 0.0), ('tuk_Latn', 0.0), ('tum_Latn', 0.0), ('tur_Latn', 0.0), ('twi_Latn', 0.0), ('tzm_Tfng', 0.0), ('uig_Arab', 0.0), ('ukr_Cyrl', 0.0), ('umb_Latn', 0.0), ('urd_Arab', 0.0), ('uzn_Latn', 0.0), ('vec_Latn', 0.0), ('vie_Latn', 0.0), ('war_Latn', 0.0), ('wol_Latn', 0.0), ('xho_Latn', 0.0), ('ydd_Hebr', 0.0), ('yor_Latn', 0.0), ('yue_Hant', 0.0), ('zho_Hans', 0.0), ('zho_Hant', 0.0), ('zul_Latn', 0.0)
-            # fmt: on
-        ]
+        vocab += [('ace_Arab', 0.0), ('ace_Latn', 0.0), ('acm_Arab', 0.0), ('acq_Arab', 0.0), ('aeb_Arab', 0.0), ('afr_Latn', 0.0), ('ajp_Arab', 0.0), ('aka_Latn', 0.0), ('amh_Ethi', 0.0), ('apc_Arab', 0.0), ('arb_Arab', 0.0), ('ars_Arab', 0.0), ('ary_Arab', 0.0), ('arz_Arab', 0.0), ('asm_Beng', 0.0), ('ast_Latn', 0.0), ('awa_Deva', 0.0), ('ayr_Latn', 0.0), ('azb_Arab', 0.0), ('azj_Latn', 0.0), ('bak_Cyrl', 0.0), ('bam_Latn', 0.0), ('ban_Latn', 0.0), ('bel_Cyrl', 0.0), ('bem_Latn', 0.0), ('ben_Beng', 0.0), ('bho_Deva', 0.0), ('bjn_Arab', 0.0), ('bjn_Latn', 0.0), ('bod_Tibt', 0.0), ('bos_Latn', 0.0), ('bug_Latn', 0.0), ('bul_Cyrl', 0.0), ('cat_Latn', 0.0), ('ceb_Latn', 0.0), ('ces_Latn', 0.0), ('cjk_Latn', 0.0), ('ckb_Arab', 0.0), ('crh_Latn', 0.0), ('cym_Latn', 0.0), ('dan_Latn', 0.0), ('deu_Latn', 0.0), ('dik_Latn', 0.0), ('dyu_Latn', 0.0), ('dzo_Tibt', 0.0), ('ell_Grek', 0.0), ('eng_Latn', 0.0), ('epo_Latn', 0.0), ('est_Latn', 0.0), ('eus_Latn', 0.0), ('ewe_Latn', 0.0), ('fao_Latn', 0.0), ('pes_Arab', 0.0), ('fij_Latn', 0.0), ('fin_Latn', 0.0), ('fon_Latn', 0.0), ('fra_Latn', 0.0), ('fur_Latn', 0.0), ('fuv_Latn', 0.0), ('gla_Latn', 0.0), ('gle_Latn', 0.0), ('glg_Latn', 0.0), ('grn_Latn', 0.0), ('guj_Gujr', 0.0), ('hat_Latn', 0.0), ('hau_Latn', 0.0), ('heb_Hebr', 0.0), ('hin_Deva', 0.0), ('hne_Deva', 0.0), ('hrv_Latn', 0.0), ('hun_Latn', 0.0), ('hye_Armn', 0.0), ('ibo_Latn', 0.0), ('ilo_Latn', 0.0), ('ind_Latn', 0.0), ('isl_Latn', 0.0), ('ita_Latn', 0.0), ('jav_Latn', 0.0), ('jpn_Jpan', 0.0), ('kab_Latn', 0.0), ('kac_Latn', 0.0), ('kam_Latn', 0.0), ('kan_Knda', 0.0), ('kas_Arab', 0.0), ('kas_Deva', 0.0), ('kat_Geor', 0.0), ('knc_Arab', 0.0), ('knc_Latn', 0.0), ('kaz_Cyrl', 0.0), ('kbp_Latn', 0.0), ('kea_Latn', 0.0), ('khm_Khmr', 0.0), ('kik_Latn', 0.0), ('kin_Latn', 0.0), ('kir_Cyrl', 0.0), ('kmb_Latn', 0.0), ('kon_Latn', 0.0), ('kor_Hang', 0.0), ('kmr_Latn', 0.0), ('lao_Laoo', 0.0), ('lvs_Latn', 0.0), ('lij_Latn', 0.0), ('lim_Latn', 0.0), ('lin_Latn', 0.0), ('lit_Latn', 0.0), ('lmo_Latn', 0.0), ('ltg_Latn', 0.0), ('ltz_Latn', 0.0), ('lua_Latn', 0.0), ('lug_Latn', 0.0), ('luo_Latn', 0.0), ('lus_Latn', 0.0), ('mag_Deva', 0.0), ('mai_Deva', 0.0), ('mal_Mlym', 0.0), ('mar_Deva', 0.0), ('min_Latn', 0.0), ('mkd_Cyrl', 0.0), ('plt_Latn', 0.0), ('mlt_Latn', 0.0), ('mni_Beng', 0.0), ('khk_Cyrl', 0.0), ('mos_Latn', 0.0), ('mri_Latn', 0.0), ('zsm_Latn', 0.0), ('mya_Mymr', 0.0), ('nld_Latn', 0.0), ('nno_Latn', 0.0), ('nob_Latn', 0.0), ('npi_Deva', 0.0), ('nso_Latn', 0.0), ('nus_Latn', 0.0), ('nya_Latn', 0.0), ('oci_Latn', 0.0), ('gaz_Latn', 0.0), ('ory_Orya', 0.0), ('pag_Latn', 0.0), ('pan_Guru', 0.0), ('pap_Latn', 0.0), ('pol_Latn', 0.0), ('por_Latn', 0.0), ('prs_Arab', 0.0), ('pbt_Arab', 0.0), ('quy_Latn', 0.0), ('ron_Latn', 0.0), ('run_Latn', 0.0), ('rus_Cyrl', 0.0), ('sag_Latn', 0.0), ('san_Deva', 0.0), ('sat_Beng', 0.0), ('scn_Latn', 0.0), ('shn_Mymr', 0.0), ('sin_Sinh', 0.0), ('slk_Latn', 0.0), ('slv_Latn', 0.0), ('smo_Latn', 0.0), ('sna_Latn', 0.0), ('snd_Arab', 0.0), ('som_Latn', 0.0), ('sot_Latn', 0.0), ('spa_Latn', 0.0), ('als_Latn', 0.0), ('srd_Latn', 0.0), ('srp_Cyrl', 0.0), ('ssw_Latn', 0.0), ('sun_Latn', 0.0), ('swe_Latn', 0.0), ('swh_Latn', 0.0), ('szl_Latn', 0.0), ('tam_Taml', 0.0), ('tat_Cyrl', 0.0), ('tel_Telu', 0.0), ('tgk_Cyrl', 0.0), ('tgl_Latn', 0.0), ('tha_Thai', 0.0), ('tir_Ethi', 0.0), ('taq_Latn', 0.0), ('taq_Tfng', 0.0), ('tpi_Latn', 0.0), ('tsn_Latn', 0.0), ('tso_Latn', 0.0), ('tuk_Latn', 0.0), ('tum_Latn', 0.0), ('tur_Latn', 0.0), ('twi_Latn', 0.0), ('tzm_Tfng', 0.0), ('uig_Arab', 0.0), ('ukr_Cyrl', 0.0), ('umb_Latn', 0.0), ('urd_Arab', 0.0), ('uzn_Latn', 0.0), ('vec_Latn', 0.0), ('vie_Latn', 0.0), ('war_Latn', 0.0), ('wol_Latn', 0.0), ('xho_Latn', 0.0), ('ydd_Hebr', 0.0), ('yor_Latn', 0.0), ('yue_Hant', 0.0), ('zho_Hans', 0.0), ('zho_Hant', 0.0), ('zul_Latn', 0.0)]  # fmt: skip
         vocab += [("<mask>", 0.0)]
         return vocab
 
@@ -1128,9 +1122,7 @@ class XGLMConverter(SpmConverter):
             ("<unk>", 0.0),
         ]
         vocab += [(piece.piece, piece.score) for piece in proto.pieces[3:]]
-        # fmt: off
-        vocab += [("<madeupword0>", 0.0), ("<madeupword1>", 0.0), ("<madeupword2>", 0.0), ("<madeupword3>", 0.0), ("<madeupword4>", 0.0), ("<madeupword5>", 0.0), ("<madeupword6>", 0.0)]
-        # fmt: on
+        vocab += [("<madeupword0>", 0.0), ("<madeupword1>", 0.0), ("<madeupword2>", 0.0), ("<madeupword3>", 0.0), ("<madeupword4>", 0.0), ("<madeupword5>", 0.0), ("<madeupword6>", 0.0)]  # fmt: skip
         return vocab
 
     def unk_id(self, proto):

src/transformers/data/data_collator.py

@@ -121,7 +121,7 @@ def torch_default_data_collator(features: List[InputDataClass]) -> Dict[str, Any
         if isinstance(first["label_ids"], torch.Tensor):
             batch["labels"] = torch.stack([f["label_ids"] for f in features])
         else:
-            dtype = torch.long if type(first["label_ids"][0]) is int else torch.float
+            dtype = torch.long if isinstance(first["label_ids"][0], int) else torch.float
             batch["labels"] = torch.tensor([f["label_ids"] for f in features], dtype=dtype)
 
     # Handling of all other possible keys.
@@ -196,7 +196,7 @@ def numpy_default_data_collator(features: List[InputDataClass]) -> Dict[str, Any
         if isinstance(first["label_ids"], np.ndarray):
             batch["labels"] = np.stack([f["label_ids"] for f in features])
         else:
-            dtype = np.int64 if type(first["label_ids"][0]) is int else np.float32
+            dtype = np.int64 if isinstance(first["label_ids"][0], int) else np.float32
             batch["labels"] = np.array([f["label_ids"] for f in features], dtype=dtype)
 
     # Handling of all other possible keys.

src/transformers/dependency_versions_table.py

@@ -6,7 +6,6 @@ deps = {
     "accelerate": "accelerate>=0.20.3",
     "av": "av==9.2.0",
     "beautifulsoup4": "beautifulsoup4",
-    "black": "black~=23.1",
     "codecarbon": "codecarbon==1.2.0",
     "cookiecutter": "cookiecutter==1.7.3",
     "dataclasses": "dataclasses",
@@ -62,7 +61,7 @@ deps = {
     "rhoknp": "rhoknp>=1.1.0,<1.3.1",
     "rjieba": "rjieba",
     "rouge-score": "rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1",
-    "ruff": "ruff>=0.0.241,<=0.0.259",
+    "ruff": "ruff>=0.1.5,<=0.2",
     "sacrebleu": "sacrebleu>=1.4.12,<2.0.0",
     "sacremoses": "sacremoses",
     "safetensors": "safetensors>=0.3.1",

src/transformers/image_utils.py

@@ -245,8 +245,7 @@ def is_valid_annotation_coco_detection(annotation: Dict[str, Union[List, Tuple]]
         and isinstance(annotation["annotations"], (list, tuple))
         and (
             # an image can have no annotations
-            len(annotation["annotations"]) == 0
-            or isinstance(annotation["annotations"][0], dict)
+            len(annotation["annotations"]) == 0 or isinstance(annotation["annotations"][0], dict)
         )
     ):
         return True
@@ -262,8 +261,7 @@ def is_valid_annotation_coco_panoptic(annotation: Dict[str, Union[List, Tuple]])
         and isinstance(annotation["segments_info"], (list, tuple))
         and (
             # an image can have no segments
-            len(annotation["segments_info"]) == 0
-            or isinstance(annotation["segments_info"][0], dict)
+            len(annotation["segments_info"]) == 0 or isinstance(annotation["segments_info"][0], dict)
         )
     ):
         return True

src/transformers/modeling_flax_utils.py

@@ -179,6 +179,7 @@ class FlaxPreTrainedModel(PushToHubMixin, FlaxGenerationMixin):
         - **main_input_name** (`str`) -- The name of the principal input to the model (often `input_ids` for NLP
           models, `pixel_values` for vision models and `input_values` for speech models).
     """
+
     config_class = None
     base_model_prefix = ""
     main_input_name = "input_ids"

src/transformers/modeling_tf_utils.py

@@ -1075,6 +1075,7 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
         - **main_input_name** (`str`) -- The name of the principal input to the model (often `input_ids` for NLP
           models, `pixel_values` for vision models and `input_values` for speech models).
     """
+
     config_class = None
     base_model_prefix = ""
     main_input_name = "input_ids"
@@ -3242,6 +3243,7 @@ class TFSharedEmbeddings(tf.keras.layers.Layer):
         kwargs (`Dict[str, Any]`, *optional*):
             Additional keyword arguments passed along to the `__init__` of `tf.keras.layers.Layer`.
     """
+
     # TODO (joao): flagged for delection due to embeddings refactor
 
     def __init__(self, vocab_size: int, hidden_size: int, initializer_range: Optional[float] = None, **kwargs):

src/transformers/modeling_utils.py

@@ -1095,6 +1095,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
         - **main_input_name** (`str`) -- The name of the principal input to the model (often `input_ids` for NLP
           models, `pixel_values` for vision models and `input_values` for speech models).
     """
+
     config_class = None
     base_model_prefix = ""
     main_input_name = "input_ids"

src/transformers/models/align/configuration_align.py

@@ -97,6 +97,7 @@ class AlignTextConfig(PretrainedConfig):
     >>> # Accessing the model configuration
     >>> configuration = model.config
     ```"""
+
     model_type = "align_text_model"
 
     def __init__(

src/transformers/models/altclip/configuration_altclip.py

@@ -100,6 +100,7 @@ class AltCLIPTextConfig(PretrainedConfig):
     >>> # Accessing the model configuration
     >>> configuration = model.config
     ```"""
+
     model_type = "altclip_text_model"
 
     def __init__(