[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/transforms/autograd_test_impl.py

@@ -5,13 +5,7 @@ import torch
 import torchaudio.transforms as T
 from parameterized import parameterized
 from torch.autograd import gradcheck, gradgradcheck
-from torchaudio_unittest.common_utils import (
-    get_spectrogram,
-    get_whitenoise,
-    nested_params,
-    rnnt_utils,
-    TestBaseMixin,
-)
+from torchaudio_unittest.common_utils import get_spectrogram, get_whitenoise, nested_params, rnnt_utils, TestBaseMixin
 
 
 class _DeterministicWrapper(torch.nn.Module):

test/torchaudio_unittest/transforms/librosa_compatibility_test_impl.py

@@ -4,13 +4,7 @@ import torch
 import torchaudio.transforms as T
 from parameterized import param, parameterized
 from torchaudio._internal.module_utils import is_module_available
-from torchaudio_unittest.common_utils import (
-    get_sinusoid,
-    get_spectrogram,
-    get_whitenoise,
-    nested_params,
-    TestBaseMixin,
-)
+from torchaudio_unittest.common_utils import get_sinusoid, get_spectrogram, get_whitenoise, nested_params, TestBaseMixin
 
 LIBROSA_AVAILABLE = is_module_available("librosa")
 

test/torchaudio_unittest/transforms/transforms_test_impl.py

@@ -2,12 +2,7 @@ import torch
 import torchaudio.transforms as T
 from parameterized import param, parameterized
 from torchaudio.functional.functional import _get_sinc_resample_kernel
-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
 from torchaudio_unittest.common_utils.psd_utils import psd_numpy
 
 

tools/convert_voxpopuli_models.py

@@ -93,9 +93,7 @@ def _main(args):
 
     import torch
     import torchaudio
-    from torchaudio.models.wav2vec2.utils.import_fairseq import (
-        _convert_state_dict as _convert,
-    )
+    from torchaudio.models.wav2vec2.utils.import_fairseq import _convert_state_dict as _convert
 
     cfg, state_dict = _load(args.input_file)
     params = _parse_model_param(cfg, state_dict)

torchaudio/prototype/models/conv_emformer.py

@@ -2,11 +2,7 @@ import math
 from typing import List, Optional, Tuple
 
 import torch
-from torchaudio.models.emformer import (
-    _EmformerAttention,
-    _EmformerImpl,
-    _get_weight_init_gains,
-)
+from torchaudio.models.emformer import _EmformerAttention, _EmformerImpl, _get_weight_init_gains
 
 
 def _get_activation_module(activation: str) -> torch.nn.Module:

torchaudio/sox_effects/__init__.py

 from torchaudio._internal import module_utils as _mod_utils
 
-from .sox_effects import (
-    apply_effects_file,
-    apply_effects_tensor,
-    effect_names,
-    init_sox_effects,
-    shutdown_sox_effects,
-)
+from .sox_effects import apply_effects_file, apply_effects_tensor, effect_names, init_sox_effects, shutdown_sox_effects
 
 
 if _mod_utils.is_sox_available():