format and fix pre-commit (#1120)

dataset/aidatatang_200zh/aidatatang_200zh.py

@@ -25,6 +25,7 @@
 from pathlib import Path
 
 import soundfile
+
 from utils.utility import download
 from utils.utility import unpack
 

dataset/aishell/aishell.py

@@ -25,6 +25,7 @@
 from pathlib import Path
 
 import soundfile
+
 from utils.utility import download
 from utils.utility import unpack
 

dataset/librispeech/librispeech.py

@@ -27,6 +27,7 @@
 from multiprocessing.pool import Pool
 
 import soundfile
+
 from utils.utility import download
 from utils.utility import unpack
 

dataset/mini_librispeech/mini_librispeech.py

@@ -26,6 +26,7 @@
 from multiprocessing.pool import Pool
 
 import soundfile
+
 from utils.utility import download
 from utils.utility import unpack
 

dataset/musan/musan.py

@@ -28,6 +28,7 @@
 import os
 
 import soundfile
+
 from utils.utility import download
 from utils.utility import unpack
 

dataset/rir_noise/rir_noise.py

@@ -28,6 +28,7 @@
 import os
 
 import soundfile
+
 from utils.utility import download
 from utils.utility import unzip
 

dataset/thchs30/thchs30.py

@@ -26,6 +26,7 @@
 from pathlib import Path
 
 import soundfile
+
 from utils.utility import download
 from utils.utility import unpack
 

dataset/timit/timit.py

@@ -27,6 +27,7 @@
 from pathlib import Path
 
 import soundfile
+
 from utils.utility import unzip
 
 URL_ROOT = ""

dataset/voxforge/voxforge.py

@@ -27,6 +27,7 @@
 import subprocess
 
 import soundfile
+
 from utils.utility import download_multi
 from utils.utility import getfile_insensitive
 from utils.utility import unpack

docs/source/released_model.md

@@ -75,4 +75,3 @@ PANN | ESC-50 |[pann-esc50]("./examples/esc50/cls0")|[panns_cnn6.tar.gz](https:/
 | [Ds2 Offline Aishell model](https://deepspeech.bj.bcebos.com/mandarin_models/aishell_model_v1.8_to_v2.x.tar.gz) | Aishell Dataset | Char-based | 234 MB | 2 Conv + 3 bidirectional GRU layers | 0.0804 | - | 151 h |
 | [Ds2 Offline Librispeech model](https://deepspeech.bj.bcebos.com/eng_models/librispeech_v1.8_to_v2.x.tar.gz) | Librispeech Dataset | Word-based | 307 MB | 2 Conv + 3 bidirectional sharing weight RNN layers | - | 0.0685 | 960 h |
 | [Ds2 Offline Baidu en8k model](https://deepspeech.bj.bcebos.com/eng_models/baidu_en8k_v1.8_to_v2.x.tar.gz) | Baidu Internal English Dataset | Word-based | 273 MB | 2 Conv + 3 bidirectional GRU layers | - | 0.0541 | 8628 h |
-

paddlespeech/cli/__init__.py

@@ -11,8 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
 import _locale
+
 from .asr import ASRExecutor
 from .base_commands import BaseCommand
 from .base_commands import HelpCommand

paddlespeech/cls/exps/panns/deploy/predict.py

@@ -16,10 +16,11 @@
 
 import numpy as np
 from paddle import inference
+from scipy.special import softmax
+
 from paddleaudio.backends import load as load_audio
 from paddleaudio.datasets import ESC50
 from paddleaudio.features import melspectrogram
-from scipy.special import softmax
 
 # yapf: disable
 parser = argparse.ArgumentParser()

paddlespeech/cls/exps/panns/export_model.py

@@ -15,8 +15,8 @@
 import os
 
 import paddle
-from paddleaudio.datasets import ESC50
 
+from paddleaudio.datasets import ESC50
 from paddlespeech.cls.models import cnn14
 from paddlespeech.cls.models import SoundClassifier
 

paddlespeech/cls/exps/panns/predict.py

@@ -16,11 +16,11 @@
 import numpy as np
 import paddle
 import paddle.nn.functional as F
+
 from paddleaudio.backends import load as load_audio
 from paddleaudio.datasets import ESC50
 from paddleaudio.features import LogMelSpectrogram
 from paddleaudio.features import melspectrogram
-
 from paddlespeech.cls.models import cnn14
 from paddlespeech.cls.models import SoundClassifier
 

paddlespeech/cls/exps/panns/train.py

@@ -15,11 +15,11 @@
 import os
 
 import paddle
+
 from paddleaudio.datasets import ESC50
 from paddleaudio.features import LogMelSpectrogram
 from paddleaudio.utils import logger
 from paddleaudio.utils import Timer
-
 from paddlespeech.cls.models import cnn14
 from paddlespeech.cls.models import SoundClassifier
 

paddlespeech/cls/models/panns/panns.py

@@ -15,6 +15,7 @@
 
 import paddle.nn as nn
 import paddle.nn.functional as F
+
 from paddleaudio.utils.download import load_state_dict_from_url
 from paddleaudio.utils.env import MODEL_HOME
 

paddlespeech/s2t/frontend/audio.py

@@ -356,16 +356,17 @@ def change_speed(self, speed_rate):
  # sox, slow
  try:
  import soxbindings as sox
- except:
+ except ImportError:
  try:
  from paddlespeech.s2t.utils import dynamic_pip_install
  package = "sox"
  dynamic_pip_install.install(package)
  package = "soxbindings"
  dynamic_pip_install.install(package)
  import soxbindings as sox
- except:
- raise RuntimeError("Can not install soxbindings on your system." )
+ except Exception:
+ raise RuntimeError(
+ "Can not install soxbindings on your system.")
 
  tfm = sox.Transformer()
  tfm.set_globals(multithread=False)

paddlespeech/s2t/frontend/utility.py

@@ -102,9 +102,11 @@ def read_manifest(
  with jsonlines.open(manifest_path, 'r') as reader:
  for json_data in reader:
  feat_len = json_data["input"][0]["shape"][
- 0] if "input" in json_data and "shape" in json_data["input"][0] else 1.0
+ 0] if "input" in json_data and "shape" in json_data["input"][
+ 0] else 1.0
  token_len = json_data["output"][0]["shape"][
- 0] if "output" in json_data and "shape" in json_data["output"][0] else 1.0
+ 0] if "output" in json_data and "shape" in json_data["output"][
+ 0] else 1.0
  conditions = [
  feat_len >= min_input_len,
  feat_len <= max_input_len,

paddlespeech/s2t/io/sampler.py

@@ -20,13 +20,13 @@
 
 from paddlespeech.s2t.utils.log import Log
 
+logger = Log(__name__).getlog()
+
 __all__ = [
  "SortagradDistributedBatchSampler",
  "SortagradBatchSampler",
 ]
 
-logger = Log(__name__).getlog()
-
 
 def _batch_shuffle(indices, batch_size, epoch, clipped=False):
  """Put similarly-sized instances into minibatches for better efficiency

paddlespeech/s2t/models/ds2/__init__.py

@@ -17,11 +17,11 @@
 
 try:
  import swig_decoders
-except:
+except ImportError:
  try:
  package_name = 'paddlespeech_ctcdecoders'
  dynamic_pip_install.install(package_name)
- except:
+ except Exception:
  raise RuntimeError(
  "Can not install package paddlespeech_ctcdecoders on your system. \
  The DeepSpeech2 model is not supported for your system")

paddlespeech/s2t/models/ds2/deepspeech2.py

@@ -129,7 +129,7 @@ def params(cls, config: Optional[CfgNode]=None) -> CfgNode:
  rnn_layer_size=1024, #RNN layer size (number of RNN cells).
  use_gru=True, #Use gru if set True. Use simple rnn if set False.
  share_rnn_weights=True, #Whether to share input-hidden weights between forward and backward directional RNNs.Notice that for GRU, weight sharing is not supported.
- ctc_grad_norm_type=None,))
+ ctc_grad_norm_type=None, ))
  if config is not None:
  config.merge_from_other_cfg(default)
  return default

paddlespeech/s2t/models/ds2_online/__init__.py

@@ -17,11 +17,11 @@
 
 try:
  import swig_decoders
-except:
+except ImportError:
  try:
  package_name = 'paddlespeech_ctcdecoders'
  dynamic_pip_install.install(package_name)
- except:
+ except Exception:
  raise RuntimeError(
  "Can not install package paddlespeech_ctcdecoders on your system. \
  The DeepSpeech2 model is not supported for your system")

paddlespeech/s2t/modules/ctc.py

@@ -28,7 +28,7 @@
  from paddlespeech.s2t.decoders.ctcdecoder.swig_wrapper import ctc_beam_search_decoder_batch # noqa: F401
  from paddlespeech.s2t.decoders.ctcdecoder.swig_wrapper import ctc_greedy_decoder # noqa: F401
  from paddlespeech.s2t.decoders.ctcdecoder.swig_wrapper import Scorer # noqa: F401
-except:
+except ImportError:
  try:
  from paddlespeech.s2t.utils import dynamic_pip_install
  package_name = 'paddlespeech_ctcdecoders'

paddlespeech/s2t/training/trainer.py

@@ -221,6 +221,8 @@ def maybe_batch_sampler_step(self):
  if hasattr(self.train_loader, "batch_sampler"):
  batch_sampler = self.train_loader.batch_sampler
  if isinstance(batch_sampler, paddle.io.DistributedBatchSampler):
+ logger.debug(
+ f"train_loader.batch_sample set epoch: {self.epoch}")
  batch_sampler.set_epoch(self.epoch)
 
  def before_train(self):

paddlespeech/s2t/transform/perturb.py

@@ -147,16 +147,18 @@ def __init__(
 
  try:
  import soxbindings as sox
- except:
+ except ImportError:
  try:
  from paddlespeech.s2t.utils import dynamic_pip_install
  package = "sox"
  dynamic_pip_install.install(package)
  package = "soxbindings"
  dynamic_pip_install.install(package)
  import soxbindings as sox
- except:
- raise RuntimeError("Can not install soxbindings on your system." )
+ except Exception:
+ raise RuntimeError(
+ "Can not install soxbindings on your system.")
+ self.sox = sox
 
  if utt2ratio is not None:
  self.utt2ratio = {}
@@ -200,7 +202,7 @@ def __call__(self, x, uttid=None, train=True):
  else:
  ratio = self.state.uniform(self.lower, self.upper)
 
- tfm = sox.Transformer()
+ tfm = self.sox.Transformer()
  tfm.set_globals(multithread=False)
  tfm.speed(ratio)
  y = tfm.build_array(input_array=x, sample_rate_in=self.sr)

utils/manifest_key_value.py

@@ -5,6 +5,7 @@
 from pathlib import Path
 
 import jsonlines
+
 from utils.utility import add_arguments
 from utils.utility import print_arguments