Format code style

tests/models/encoder_decoder/test_modeling_encoder_decoder.py

@@ -179,7 +179,10 @@ def check_encoder_decoder_model_from_pretrained_using_model_paths(
         **kwargs,
     ):
         encoder_model, decoder_model = self.get_encoder_decoder_model(config, decoder_config)
-        with tempfile.TemporaryDirectory() as encoder_tmp_dirname, tempfile.TemporaryDirectory() as decoder_tmp_dirname:
+        with (
+            tempfile.TemporaryDirectory() as encoder_tmp_dirname,
+            tempfile.TemporaryDirectory() as decoder_tmp_dirname,
+        ):
             encoder_model.save_pretrained(encoder_tmp_dirname)
             decoder_model.save_pretrained(decoder_tmp_dirname)
             model_kwargs = {"encoder_hidden_dropout_prob": 0.0}
@@ -306,7 +309,10 @@ def check_save_and_load_encoder_decoder_model(
             out_2 = outputs[0].cpu().numpy()
             out_2[np.isnan(out_2)] = 0
 
-            with tempfile.TemporaryDirectory() as encoder_tmp_dirname, tempfile.TemporaryDirectory() as decoder_tmp_dirname:
+            with (
+                tempfile.TemporaryDirectory() as encoder_tmp_dirname,
+                tempfile.TemporaryDirectory() as decoder_tmp_dirname,
+            ):
                 enc_dec_model.encoder.save_pretrained(encoder_tmp_dirname)
                 enc_dec_model.decoder.save_pretrained(decoder_tmp_dirname)
                 enc_dec_model = EncoderDecoderModel.from_encoder_decoder_pretrained(

tests/models/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py

@@ -266,7 +266,10 @@ def check_save_and_load_encoder_decoder_model(
             out_2 = outputs[0].cpu().numpy()
             out_2[np.isnan(out_2)] = 0
 
-            with tempfile.TemporaryDirectory() as encoder_tmp_dirname, tempfile.TemporaryDirectory() as decoder_tmp_dirname:
+            with (
+                tempfile.TemporaryDirectory() as encoder_tmp_dirname,
+                tempfile.TemporaryDirectory() as decoder_tmp_dirname,
+            ):
                 enc_dec_model.encoder.save_pretrained(encoder_tmp_dirname)
                 enc_dec_model.decoder.save_pretrained(decoder_tmp_dirname)
                 SpeechEncoderDecoderModel.from_encoder_decoder_pretrained(

tests/models/vision_encoder_decoder/test_modeling_vision_encoder_decoder.py

@@ -216,7 +216,10 @@ def check_save_and_load_encoder_decoder_model(
             out_2 = outputs[0].cpu().numpy()
             out_2[np.isnan(out_2)] = 0
 
-            with tempfile.TemporaryDirectory() as encoder_tmp_dirname, tempfile.TemporaryDirectory() as decoder_tmp_dirname:
+            with (
+                tempfile.TemporaryDirectory() as encoder_tmp_dirname,
+                tempfile.TemporaryDirectory() as decoder_tmp_dirname,
+            ):
                 enc_dec_model.encoder.save_pretrained(encoder_tmp_dirname)
                 enc_dec_model.decoder.save_pretrained(decoder_tmp_dirname)
                 VisionEncoderDecoderModel.from_encoder_decoder_pretrained(

tests/models/wav2vec2/test_modeling_flax_wav2vec2.py

@@ -623,9 +623,10 @@ def test_wav2vec2_with_lm_pool(self):
         self.assertEqual(transcription[0], "bien y qué regalo vas a abrir primero")
 
         # user-managed pool + num_processes should trigger a warning
-        with CaptureLogger(processing_wav2vec2_with_lm.logger) as cl, multiprocessing.get_context("fork").Pool(
-            2
-        ) as pool:
+        with (
+            CaptureLogger(processing_wav2vec2_with_lm.logger) as cl,
+            multiprocessing.get_context("fork").Pool(2) as pool,
+        ):
             transcription = processor.batch_decode(np.array(logits), pool, num_processes=2).text
 
         self.assertIn("num_process", cl.out)

tests/models/wav2vec2/test_modeling_tf_wav2vec2.py

@@ -827,9 +827,10 @@ def test_wav2vec2_with_lm_pool(self):
         self.assertEqual(transcription[0], "el libro ha sido escrito por cervantes")
 
         # user-managed pool + num_processes should trigger a warning
-        with CaptureLogger(processing_wav2vec2_with_lm.logger) as cl, multiprocessing.get_context("fork").Pool(
-            2
-        ) as pool:
+        with (
+            CaptureLogger(processing_wav2vec2_with_lm.logger) as cl,
+            multiprocessing.get_context("fork").Pool(2) as pool,
+        ):
             transcription = processor.batch_decode(logits.numpy(), pool, num_processes=2).text
 
         self.assertIn("num_process", cl.out)

tests/models/wav2vec2/test_modeling_wav2vec2.py

@@ -1889,9 +1889,10 @@ def test_wav2vec2_with_lm_pool(self):
         self.assertEqual(transcription[0], "habitan aguas poco profundas y rocosas")
 
         # user-managed pool + num_processes should trigger a warning
-        with CaptureLogger(processing_wav2vec2_with_lm.logger) as cl, multiprocessing.get_context("fork").Pool(
-            2
-        ) as pool:
+        with (
+            CaptureLogger(processing_wav2vec2_with_lm.logger) as cl,
+            multiprocessing.get_context("fork").Pool(2) as pool,
+        ):
             transcription = processor.batch_decode(logits.cpu().numpy(), pool, num_processes=2).text
 
         self.assertIn("num_process", cl.out)

utils/download_glue_data.py

@@ -79,9 +79,11 @@ def format_mrpc(data_dir, path_to_data):
         for row in ids_fh:
             dev_ids.append(row.strip().split("\t"))
 
-    with open(mrpc_train_file, encoding="utf8") as data_fh, open(
-        os.path.join(mrpc_dir, "train.tsv"), "w", encoding="utf8"
-    ) as train_fh, open(os.path.join(mrpc_dir, "dev.tsv"), "w", encoding="utf8") as dev_fh:
+    with (
+        open(mrpc_train_file, encoding="utf8") as data_fh,
+        open(os.path.join(mrpc_dir, "train.tsv"), "w", encoding="utf8") as train_fh,
+        open(os.path.join(mrpc_dir, "dev.tsv"), "w", encoding="utf8") as dev_fh,
+    ):
         header = data_fh.readline()
         train_fh.write(header)
         dev_fh.write(header)
@@ -92,9 +94,10 @@ def format_mrpc(data_dir, path_to_data):
             else:
                 train_fh.write("%s\t%s\t%s\t%s\t%s\n" % (label, id1, id2, s1, s2))
 
-    with open(mrpc_test_file, encoding="utf8") as data_fh, open(
-        os.path.join(mrpc_dir, "test.tsv"), "w", encoding="utf8"
-    ) as test_fh:
+    with (
+        open(mrpc_test_file, encoding="utf8") as data_fh,
+        open(os.path.join(mrpc_dir, "test.tsv"), "w", encoding="utf8") as test_fh,
+    ):
         header = data_fh.readline()
         test_fh.write("index\t#1 ID\t#2 ID\t#1 String\t#2 String\n")
         for idx, row in enumerate(data_fh):