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

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drop-conflicts

Reviewed By: adamjernst

Differential Revision: D37375235

fbshipit-source-id: 3d7eb39e5c0539a78d1412f37562dec90b0fc759

examples/asr/emformer_rnnt/pipeline_demo.py

@@ -16,10 +16,7 @@ import torchaudio
 from common import MODEL_TYPE_LIBRISPEECH, MODEL_TYPE_MUSTC, MODEL_TYPE_TEDLIUM3
 from mustc.dataset import MUSTC
 from torchaudio.pipelines import EMFORMER_RNNT_BASE_LIBRISPEECH, RNNTBundle
-from torchaudio.prototype.pipelines import (
-    EMFORMER_RNNT_BASE_MUSTC,
-    EMFORMER_RNNT_BASE_TEDLIUM3,
-)
+from torchaudio.prototype.pipelines import EMFORMER_RNNT_BASE_MUSTC, EMFORMER_RNNT_BASE_TEDLIUM3
 
 logger = logging.getLogger(__name__)
 

examples/hubert/finetune.py

@@ -9,11 +9,7 @@ python finetune.py --dataset-path ./root/datasets/ --exp-dir ./exp_finetune \
 
 import logging
 import pathlib
-from argparse import (
-    ArgumentDefaultsHelpFormatter,
-    ArgumentParser,
-    RawDescriptionHelpFormatter,
-)
+from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, RawDescriptionHelpFormatter
 from typing import Tuple
 
 from lightning import HuBERTFineTuneModule

examples/hubert/train.py

@@ -6,11 +6,7 @@ python train.py --dataset-path ./exp/data/mfcc/ --feature-type mfcc --num-classe
 
 import logging
 import pathlib
-from argparse import (
-    ArgumentDefaultsHelpFormatter,
-    ArgumentParser,
-    RawDescriptionHelpFormatter,
-)
+from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, RawDescriptionHelpFormatter
 from typing import Optional, Tuple
 
 from lightning import HuBERTPreTrainModule

examples/interactive_asr/asr.py

@@ -13,12 +13,7 @@ import datetime as dt
 import logging
 
 from fairseq import options
-from interactive_asr.utils import (
-    add_asr_eval_argument,
-    get_microphone_transcription,
-    setup_asr,
-    transcribe_file,
-)
+from interactive_asr.utils import add_asr_eval_argument, get_microphone_transcription, setup_asr, transcribe_file
 
 
 def main(args):

examples/pipeline_tacotron2/inference.py

@@ -12,12 +12,7 @@ import numpy as np
 import torch
 import torchaudio
 from datasets import InverseSpectralNormalization
-from text.text_preprocessing import (
-    available_phonemizers,
-    available_symbol_set,
-    get_symbol_list,
-    text_to_sequence,
-)
+from text.text_preprocessing import available_phonemizers, available_symbol_set, get_symbol_list, text_to_sequence
 from torchaudio.models import Tacotron2, tacotron2 as pretrained_tacotron2
 from utils import prepare_input_sequence
 
@@ -26,12 +21,8 @@ def parse_args():
     r"""
     Parse commandline arguments.
     """
-    from torchaudio.models.tacotron2 import (
-        _MODEL_CONFIG_AND_URLS as tacotron2_config_and_urls,
-    )
-    from torchaudio.models.wavernn import (
-        _MODEL_CONFIG_AND_URLS as wavernn_config_and_urls,
-    )
+    from torchaudio.models.tacotron2 import _MODEL_CONFIG_AND_URLS as tacotron2_config_and_urls
+    from torchaudio.models.wavernn import _MODEL_CONFIG_AND_URLS as wavernn_config_and_urls
 
     parser = argparse.ArgumentParser(description=__doc__)
     parser.add_argument(

examples/pipeline_tacotron2/train.py

@@ -52,12 +52,7 @@ plt.switch_backend("agg")
 
 from datasets import SpectralNormalization, split_process_dataset, text_mel_collate_fn
 from loss import Tacotron2Loss
-from text.text_preprocessing import (
-    available_phonemizers,
-    available_symbol_set,
-    get_symbol_list,
-    text_to_sequence,
-)
+from text.text_preprocessing import available_phonemizers, available_symbol_set, get_symbol_list, text_to_sequence
 from utils import save_checkpoint
 
 

test/torchaudio_unittest/backend/sox_io/roundtrip_test.py

@@ -2,13 +2,7 @@ import itertools
 
 from parameterized import parameterized
 from torchaudio.backend import sox_io_backend
-from torchaudio_unittest.common_utils import (
-    get_wav_data,
-    PytorchTestCase,
-    skipIfNoExec,
-    skipIfNoSox,
-    TempDirMixin,
-)
+from torchaudio_unittest.common_utils import get_wav_data, PytorchTestCase, skipIfNoExec, skipIfNoSox, TempDirMixin
 
 from .common import get_enc_params, name_func
 

test/torchaudio_unittest/backend/sox_io/smoke_test.py

@@ -3,12 +3,7 @@ import itertools
 
 from parameterized import parameterized
 from torchaudio.backend import sox_io_backend
-from torchaudio_unittest.common_utils import (
-    get_wav_data,
-    skipIfNoSox,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_wav_data, skipIfNoSox, TempDirMixin, TorchaudioTestCase
 
 from .common import name_func
 

test/torchaudio_unittest/common_utils/case_utils.py

@@ -10,11 +10,7 @@ import unittest
 import torch
 import torchaudio
 from torch.testing._internal.common_utils import TestCase as PytorchTestCase
-from torchaudio._internal.module_utils import (
-    is_kaldi_available,
-    is_module_available,
-    is_sox_available,
-)
+from torchaudio._internal.module_utils import is_kaldi_available, is_module_available, is_sox_available
 
 from .backend_utils import set_audio_backend
 

test/torchaudio_unittest/datasets/cmuarctic_test.py

@@ -2,13 +2,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets import cmuarctic
-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_dataset(root_dir):

test/torchaudio_unittest/datasets/commonvoice_test.py

@@ -5,13 +5,7 @@ from typing import Dict, Tuple
 
 from torch import Tensor
 from torchaudio.datasets import COMMONVOICE
-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
 
 _ORIGINAL_EXT_AUDIO = COMMONVOICE._ext_audio
 _SAMPLE_RATE = 48000

test/torchaudio_unittest/datasets/dr_vctk_test.py

@@ -2,12 +2,7 @@ from pathlib import Path
 
 import pytest
 from torchaudio.datasets import dr_vctk
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, save_wav, TempDirMixin, TorchaudioTestCase
 
 
 _SUBSETS = ["train", "test"]

test/torchaudio_unittest/datasets/fluentcommands_test.py

@@ -5,12 +5,7 @@ import string
 from pathlib import Path
 
 from torchaudio.datasets import fluentcommands
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, save_wav, TempDirMixin, TorchaudioTestCase
 
 HEADER = ["", "path", "speakerId", "transcription", "action", "object", "location"]
 SLOTS = ["action", "object", "location"]

test/torchaudio_unittest/datasets/gtzan_test.py

@@ -2,13 +2,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets import gtzan
-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_dataset(root_dir):

test/torchaudio_unittest/datasets/librilightlimited_test.py

 import os
 
 from torchaudio.datasets import librilight_limited
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, save_wav, TempDirMixin, TorchaudioTestCase
 
 
 # Used to generate a unique transcript for each dummy audio file

test/torchaudio_unittest/datasets/librispeech_test_impl.py

@@ -2,12 +2,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets import librispeech
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    normalize_wav,
-    save_wav,
-    TempDirMixin,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin
 
 # Used to generate a unique transcript for each dummy audio file
 _NUMBERS = ["ZERO", "ONE", "TWO", "THREE", "FOUR", "FIVE", "SIX", "SEVEN", "EIGHT", "NINE"]

test/torchaudio_unittest/datasets/libritts_test.py

@@ -2,13 +2,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets.libritts import LIBRITTS
-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
 
 _UTTERANCE_IDS = [
     [19, 198, "000000", "000000"],

test/torchaudio_unittest/datasets/ljspeech_test.py

@@ -3,13 +3,7 @@ import os
 from pathlib import Path
 
 from torchaudio.datasets import ljspeech
-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
 
 _TRANSCRIPTS = [
     "Test transcript 1",

test/torchaudio_unittest/datasets/musdb_hq_test.py

@@ -4,12 +4,7 @@ import torch
 from parameterized import parameterized
 from torchaudio.datasets import musdb_hq
 from torchaudio.datasets.musdb_hq import _VALIDATION_SET
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, save_wav, TempDirMixin, TorchaudioTestCase
 
 _SOURCE_SETS = [
     (None,),

test/torchaudio_unittest/datasets/quesst14_test.py

@@ -4,12 +4,7 @@ from pathlib import Path
 
 from parameterized import parameterized
 from torchaudio.datasets import quesst14
-from torchaudio_unittest.common_utils import (
-    get_whitenoise,
-    save_wav,
-    TempDirMixin,
-    TorchaudioTestCase,
-)
+from torchaudio_unittest.common_utils import get_whitenoise, save_wav, TempDirMixin, TorchaudioTestCase
 
 
 def _get_filename(folder, index):