[AutoAccept][Codemod][FBSourceBlackLinter] Daily `arc lint --take BLACK`

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drop-conflicts

Reviewed By: adamjernst

Differential Revision: D37375235

fbshipit-source-id: 3d7eb39e5c0539a78d1412f37562dec90b0fc759

test/torchaudio_unittest/datasets/speechcommands_test.py

@@ -2,13 +2,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets import speechcommands
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    normalize_wav,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin, TorchaudioTestCase
 
 _LABELS = [
     "bed",

test/torchaudio_unittest/datasets/tedlium_test.py

@@ -3,13 +3,7 @@ import platform
 from pathlib import Path
 
 from torchaudio.datasets import tedlium
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    save_wav,
-    skipIfNoSox,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, save_wav, skipIfNoSox, TempDirMixin, TorchaudioTestCase
 
 # Used to generate a unique utterance for each dummy audio file
 _UTTERANCES = [

test/torchaudio_unittest/datasets/vctk_test.py

@@ -2,13 +2,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets import vctk
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    normalize_wav,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin, TorchaudioTestCase
 
 # Used to generate a unique transcript for each dummy audio file
 _TRANSCRIPT = [

test/torchaudio_unittest/datasets/yesno_test.py

@@ -2,13 +2,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets import yesno
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    normalize_wav,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin, TorchaudioTestCase
 
 
 def get_mock_data(root_dir, labels):

test/torchaudio_unittest/example/souce_sepration/wsj0mix_test.py

 import os
 
 from source_separation.utils.dataset import wsj0mix
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    normalize_wav,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin, TorchaudioTestCase
 
 
 _FILENAMES = [

test/torchaudio_unittest/example/tacotron2/tacotron2_loss_cpu_test.py

 import torch
 from torchaudio_unittest.common_utils import PytorchTestCase
 
-from .tacotron2_loss_impl import (
-    Tacotron2LossGradcheckTests,
-    Tacotron2LossShapeTests,
-    Tacotron2LossTorchscriptTests,
-)
+from .tacotron2_loss_impl import Tacotron2LossGradcheckTests, Tacotron2LossShapeTests, Tacotron2LossTorchscriptTests
 
 
 class TestTacotron2LossShapeFloat32CPU(Tacotron2LossShapeTests, PytorchTestCase):

test/torchaudio_unittest/example/tacotron2/tacotron2_loss_gpu_test.py

 import torch
 from torchaudio_unittest.common_utils import PytorchTestCase, skipIfNoCuda
 
-from .tacotron2_loss_impl import (
-    Tacotron2LossGradcheckTests,
-    Tacotron2LossShapeTests,
-    Tacotron2LossTorchscriptTests,
-)
+from .tacotron2_loss_impl import Tacotron2LossGradcheckTests, Tacotron2LossShapeTests, Tacotron2LossTorchscriptTests
 
 
 @skipIfNoCuda

test/torchaudio_unittest/functional/autograd_impl.py

@@ -6,12 +6,7 @@ import torchaudio.functional as F
 from parameterized import parameterized
 from torch import Tensor
 from torch.autograd import gradcheck, gradgradcheck
-from torchaudio_unittest.common_utils import (
-    get_spectrogram,
-    get_whitenoise,
-    rnnt_utils,
-    TestBaseMixin,
-)
+from torchaudio_unittest.common_utils import get_spectrogram, get_whitenoise, rnnt_utils, TestBaseMixin
 
 
 class Autograd(TestBaseMixin):

test/torchaudio_unittest/functional/functional_cpu_test.py

@@ -3,11 +3,7 @@ import unittest
 import torch
 import torchaudio.functional as F
 from parameterized import parameterized
-from torchaudio_unittest.common_utils import (
-    PytorchTestCase,
-    skipIfNoSox,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import PytorchTestCase, skipIfNoSox, TorchaudioTestCase
 
 from .functional_impl import Functional, FunctionalCPUOnly
 

test/torchaudio_unittest/functional/librosa_compatibility_test_impl.py

@@ -13,12 +13,7 @@ if LIBROSA_AVAILABLE:
     import numpy as np
 
 
-from torchaudio_unittest.common_utils import (
-    get_spectrogram,
-    get_whitenoise,
-    nested_params,
-    TestBaseMixin,
-)
+from torchaudio_unittest.common_utils import get_spectrogram, get_whitenoise, nested_params, TestBaseMixin
 
 
 @unittest.skipIf(not LIBROSA_AVAILABLE, "Librosa not available")

test/torchaudio_unittest/functional/torchscript_consistency_impl.py

@@ -5,12 +5,7 @@ import torch
 import torchaudio.functional as F
 from parameterized import parameterized
 from torchaudio_unittest import common_utils
-from torchaudio_unittest.common_utils import (
-    skipIfRocm,
-    TempDirMixin,
-    TestBaseMixin,
-    torch_script,
-)
+from torchaudio_unittest.common_utils import skipIfRocm, TempDirMixin, TestBaseMixin, torch_script
 
 
 class Functional(TempDirMixin, TestBaseMixin):

test/torchaudio_unittest/models/ctc_decoder_test.py

@@ -2,12 +2,7 @@ import itertools
 
 import torch
 from parameterized import parameterized
-from torchaudio_unittest.common_utils import (
-    get_asset_path,
-    skipIfNoCtcDecoder,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_asset_path, skipIfNoCtcDecoder, TempDirMixin, TorchaudioTestCase
 
 NUM_TOKENS = 8
 

test/torchaudio_unittest/models/rnnt_decoder/rnnt_decoder_cpu_test.py

 import torch
 from torchaudio_unittest.common_utils import PytorchTestCase
-from torchaudio_unittest.models.rnnt_decoder.rnnt_decoder_test_impl import (
-    RNNTBeamSearchTestImpl,
-)
+from torchaudio_unittest.models.rnnt_decoder.rnnt_decoder_test_impl import RNNTBeamSearchTestImpl
 
 
 class RNNTBeamSearchFloat32CPUTest(RNNTBeamSearchTestImpl, PytorchTestCase):

test/torchaudio_unittest/models/rnnt_decoder/rnnt_decoder_gpu_test.py

 import torch
 from torchaudio_unittest.common_utils import PytorchTestCase, skipIfNoCuda
-from torchaudio_unittest.models.rnnt_decoder.rnnt_decoder_test_impl import (
-    RNNTBeamSearchTestImpl,
-)
+from torchaudio_unittest.models.rnnt_decoder.rnnt_decoder_test_impl import RNNTBeamSearchTestImpl
 
 
 @skipIfNoCuda

test/torchaudio_unittest/models/tacotron2/model_test_cpu_test.py

 import torch
 from torchaudio_unittest.common_utils import PytorchTestCase
 
-from .model_test_impl import (
-    Tacotron2DecoderTests,
-    Tacotron2EncoderTests,
-    Tacotron2Tests,
-)
+from .model_test_impl import Tacotron2DecoderTests, Tacotron2EncoderTests, Tacotron2Tests
 
 
 class TestTacotron2EncoderFloat32CPU(Tacotron2EncoderTests, PytorchTestCase):

test/torchaudio_unittest/models/tacotron2/model_test_gpu_test.py

 import torch
 from torchaudio_unittest.common_utils import PytorchTestCase, skipIfNoCuda
 
-from .model_test_impl import (
-    Tacotron2DecoderTests,
-    Tacotron2EncoderTests,
-    Tacotron2Tests,
-)
+from .model_test_impl import Tacotron2DecoderTests, Tacotron2EncoderTests, Tacotron2Tests
 
 
 @skipIfNoCuda

test/torchaudio_unittest/models/wav2vec2/fairseq_integration_test.py

@@ -11,11 +11,7 @@ from torchaudio.models.wav2vec2 import (
     wav2vec2_large_lv60k,
 )
 from torchaudio.models.wav2vec2.utils import import_fairseq_model
-from torchaudio_unittest.common_utils import (
-    get_asset_path,
-    skipIfNoModule,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_asset_path, skipIfNoModule, TorchaudioTestCase
 
 
 def _load_config(*paths):
@@ -102,10 +98,7 @@ class TestFairseqIntegration(TorchaudioTestCase):
         from fairseq.models.hubert.hubert import HubertConfig, HubertModel
         from fairseq.models.hubert.hubert_asr import HubertCtcConfig, HubertEncoder
         from fairseq.models.wav2vec.wav2vec2 import Wav2Vec2Config, Wav2Vec2Model
-        from fairseq.models.wav2vec.wav2vec2_asr import (
-            Wav2Vec2CtcConfig,
-            Wav2VecEncoder,
-        )
+        from fairseq.models.wav2vec.wav2vec2_asr import Wav2Vec2CtcConfig, Wav2VecEncoder
         from fairseq.tasks.hubert_pretraining import HubertPretrainingConfig
         from omegaconf import OmegaConf
 

test/torchaudio_unittest/models/wav2vec2/huggingface_intergration_test.py

@@ -2,17 +2,9 @@ import json
 
 import torch
 from parameterized import parameterized
-from torchaudio.models.wav2vec2 import (
-    wav2vec2_base,
-    wav2vec2_large,
-    wav2vec2_large_lv60k,
-)
+from torchaudio.models.wav2vec2 import wav2vec2_base, wav2vec2_large, wav2vec2_large_lv60k
 from torchaudio.models.wav2vec2.utils import import_huggingface_model
-from torchaudio_unittest.common_utils import (
-    get_asset_path,
-    skipIfNoModule,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_asset_path, skipIfNoModule, TorchaudioTestCase
 
 
 def _load_config(*paths):
@@ -76,11 +68,7 @@ class TestHFIntegration(TorchaudioTestCase):
         # However, somehow, once "transformers" is imported, `is_module_available`
         # starts to fail. Therefore, we defer importing "transformers" until
         # the actual tests are started.
-        from transformers.models.wav2vec2 import (
-            Wav2Vec2Config,
-            Wav2Vec2ForCTC,
-            Wav2Vec2Model,
-        )
+        from transformers.models.wav2vec2 import Wav2Vec2Config, Wav2Vec2ForCTC, Wav2Vec2Model
 
         if config["architectures"] == ["Wav2Vec2Model"]:
             return Wav2Vec2Model(Wav2Vec2Config(**config))

test/torchaudio_unittest/models/wav2vec2/model_test.py

@@ -12,12 +12,7 @@ from torchaudio.models.wav2vec2 import (
     wav2vec2_large,
     wav2vec2_large_lv60k,
 )
-from torchaudio_unittest.common_utils import (
-    skipIfNoCuda,
-    skipIfNoQengine,
-    torch_script,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import skipIfNoCuda, skipIfNoQengine, torch_script, TorchaudioTestCase
 
 TORCH_VERSION: Tuple[int, ...] = tuple(int(x) for x in torch.__version__.split(".")[:2])
 if TORCH_VERSION >= (1, 10):

test/torchaudio_unittest/sox_effect/dataset_test.py

@@ -8,13 +8,7 @@ from unittest import skipIf
 import numpy as np
 import torch
 import torchaudio
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    PytorchTestCase,
-    save_wav,
-    skipIfNoSox,
-    TempDirMixin,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, PytorchTestCase, save_wav, skipIfNoSox, TempDirMixin
 
 
 class RandomPerturbationFile(torch.utils.data.Dataset):