format code

examples/aishell/asr1/READEME.md

@@ -339,6 +339,3 @@ You need to prepare an audio file, please confirm the sample rate of the audio i
 ```bash
 CUDA_VISIBLE_DEVICES= ./local/test_hub.sh conf/transformer.yaml exp/transformer/checkpoints/avg_20 data/test_audio.wav
 ```
-
-
-

paddlespeech/s2t/exps/u2/model.py

@@ -129,8 +129,8 @@ def train_batch(self, batch_index, batch_data, msg):
  losses_np_v = losses_np.copy()
  losses_np_v.update({"lr": self.lr_scheduler()})
  for key, val in losses_np_v.items():
- self.visualizer.add_scalar(tag='train/'+key, value=val, step=self.iteration-1)
-
+ self.visualizer.add_scalar(
+ tag='train/' + key, value=val, step=self.iteration - 1)
 
  @paddle.no_grad()
  def valid(self):
@@ -238,8 +238,10 @@ def do_train(self):
  logger.info(
  'Epoch {} Val info val_loss {}'.format(self.epoch, cv_loss))
  if self.visualizer:
- self.visualizer.add_scalar(tag='eval/cv_loss', value=cv_loss, step=self.epoch)
- self.visualizer.add_scalar(tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/cv_loss', value=cv_loss, step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
 
  self.save(tag=self.epoch, infos={'val_loss': cv_loss})
  self.new_epoch()

paddlespeech/s2t/exps/u2_kaldi/model.py

@@ -132,7 +132,8 @@ def train_batch(self, batch_index, batch_data, msg):
  losses_np_v = losses_np.copy()
  losses_np_v.update({"lr": self.lr_scheduler()})
  for key, val in losses_np_v.items():
- self.visualizer.add_scalar(tag="train/"+key, value=val, step=self.iteration - 1)
+ self.visualizer.add_scalar(
+ tag="train/" + key, value=val, step=self.iteration - 1)
 
  @paddle.no_grad()
  def valid(self):
@@ -222,9 +223,11 @@ def do_train(self):
  logger.info(
  'Epoch {} Val info val_loss {}'.format(self.epoch, cv_loss))
  if self.visualizer:
- self.visualizer.add_scalar(tag='eval/cv_loss', value=cv_loss, step=self.epoch)
- self.visualizer.add_scalar(tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
-
+ self.visualizer.add_scalar(
+ tag='eval/cv_loss', value=cv_loss, step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
+
  self.save(tag=self.epoch, infos={'val_loss': cv_loss})
  self.new_epoch()
 

paddlespeech/s2t/exps/u2_st/model.py

@@ -139,7 +139,8 @@ def train_batch(self, batch_index, batch_data, msg):
  losses_np_v = losses_np.copy()
  losses_np_v.update({"lr": self.lr_scheduler()})
  for key, val in losses_np_v.items():
- self.visualizer.add_scalar(tag="train/"+key, value=val, step=self.iteration - 1)
+ self.visualizer.add_scalar(
+ tag="train/" + key, value=val, step=self.iteration - 1)
 
  @paddle.no_grad()
  def valid(self):
@@ -235,9 +236,11 @@ def do_train(self):
  logger.info(
  'Epoch {} Val info val_loss {}'.format(self.epoch, cv_loss))
  if self.visualizer:
- self.visualizer.add_scalar(tag='eval/cv_loss', value=cv_loss, step=self.epoch)
- self.visualizer.add_scalar(tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
-
+ self.visualizer.add_scalar(
+ tag='eval/cv_loss', value=cv_loss, step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
+
  self.save(tag=self.epoch, infos={'val_loss': cv_loss})
  self.new_epoch()
 

paddlespeech/s2t/frontend/augmentor/impulse_response.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 """Contains the impulse response augmentation model."""
 import jsonlines
+
 from paddlespeech.s2t.frontend.audio import AudioSegment
 from paddlespeech.s2t.frontend.augmentor.base import AugmentorBase
 

paddlespeech/s2t/frontend/augmentor/noise_perturb.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 """Contains the noise perturb augmentation model."""
 import jsonlines
+
 from paddlespeech.s2t.frontend.audio import AudioSegment
 from paddlespeech.s2t.frontend.augmentor.base import AugmentorBase
 

paddlespeech/s2t/frontend/normalizer.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 """Contains feature normalizers."""
 import json
+
 import jsonlines
 import numpy as np
 import paddle
@@ -26,7 +27,8 @@
 __all__ = ["FeatureNormalizer"]
 
 logger = Log(__name__).getlog()
-
+
+
 # https://github.com/PaddlePaddle/Paddle/pull/31481
 class CollateFunc(object):
  def __init__(self, feature_func):
@@ -62,7 +64,7 @@ def __init__(self, manifest_path, num_samples=-1, rng=None, random_seed=0):
 
  with jsonlines.open(manifest_path, 'r') as reader:
  manifest = list(reader)
- 
+
  if num_samples == -1:
  sampled_manifest = manifest
  else:

paddlespeech/s2t/frontend/utility.py

@@ -64,7 +64,7 @@ def load_dict(dict_path: Optional[Text], maskctc=False) -> Optional[List[Text]]:
  char_list.append(MASKCTC)
  return char_list
 
- 
+
 def read_manifest(
  manifest_path,
  max_input_len=float('inf'),

paddlespeech/s2t/io/dataloader.py

@@ -15,8 +15,8 @@
 from typing import Dict
 from typing import List
 from typing import Text
-import jsonlines
 
+import jsonlines
 import numpy as np
 from paddle.io import DataLoader
 
@@ -93,7 +93,7 @@ def __init__(self,
  # read json data
  with jsonlines.open(json_file, 'r') as reader:
  self.data_json = list(reader)
- 
+
  self.feat_dim, self.vocab_size = feat_dim_and_vocab_size(
  self.data_json, mode='asr')
 

paddlespeech/s2t/io/dataset.py

@@ -14,6 +14,7 @@
 # Modified from espnet(https://github.com/espnet/espnet)
 # Modified from wenet(https://github.com/wenet-e2e/wenet)
 from typing import Optional
+
 import jsonlines
 from paddle.io import Dataset
 from yacs.config import CfgNode

paddlespeech/s2t/io/sampler.py

@@ -51,7 +51,7 @@ def _batch_shuffle(indices, batch_size, epoch, clipped=False):
  """
  rng = np.random.RandomState(epoch)
  shift_len = rng.randint(0, batch_size - 1)
- batch_indices = list(zip(*[iter(indices[shift_len:])] * batch_size))
+ batch_indices = list(zip(* [iter(indices[shift_len:])] * batch_size))
  rng.shuffle(batch_indices)
  batch_indices = [item for batch in batch_indices for item in batch]
  assert clipped is False

paddlespeech/s2t/training/trainer.py

@@ -309,8 +309,10 @@ def do_train(self):
  logger.info(
  'Epoch {} Val info val_loss {}'.format(self.epoch, cv_loss))
  if self.visualizer:
- self.visualizer.add_scalar(tag='eval/cv_loss', value=cv_loss, step=self.epoch)
- self.visualizer.add_scalar(tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/cv_loss', value=cv_loss, step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
 
  # after epoch
  self.save(tag=self.epoch, infos={'val_loss': cv_loss})

paddlespeech/s2t/utils/socket_server.py

@@ -20,6 +20,7 @@
 import wave
 from time import gmtime
 from time import strftime
+
 import jsonlines
 
 __all__ = ["socket_send", "warm_up_test", "AsrTCPServer", "AsrRequestHandler"]

paddlespeech/text/speechtask/punctuation_restoration/training/trainer.py

@@ -252,8 +252,10 @@ def train(self):
  self.logger.info("Epoch {} Val info val_loss {}, F1_score {}".
  format(self.epoch, total_loss, F1_score))
  if self.visualizer:
- self.visualizer.add_scalar(tag='eval/cv_loss', value=cv_loss, step=self.epoch)
- self.visualizer.add_scalar(tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/cv_loss', value=cv_loss, step=self.epoch)
+ self.visualizer.add_scalar(
+ tag='eval/lr', value=self.lr_scheduler(), step=self.epoch)
 
  self.save(
  tag=self.epoch, infos={"val_loss": total_loss,

utils/build_vocab.py

@@ -19,9 +19,10 @@
 import functools
 import os
 import tempfile
-import jsonlines
 from collections import Counter
 
+import jsonlines
+
 from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
 from paddlespeech.s2t.frontend.utility import BLANK
 from paddlespeech.s2t.frontend.utility import SOS
@@ -63,7 +64,7 @@ def count_manifest(counter, text_feature, manifest_path):
  with jsonlines.open(manifest_path, 'r') as reader:
  for json_data in reader:
  manifest_jsons.append(json_data)
- 
+
  for line_json in manifest_jsons:
  line = text_feature.tokenize(line_json['text'], replace_space=False)
  counter.update(line)
@@ -73,7 +74,7 @@ def dump_text_manifest(fileobj, manifest_path, key='text'):
  with jsonlines.open(manifest_path, 'r') as reader:
  for json_data in reader:
  manifest_jsons.append(json_data)
- 
+
  for line_json in manifest_jsons:
  fileobj.write(line_json[key] + "\n")
 

utils/dump_manifest.py

@@ -16,6 +16,7 @@
 import argparse
 from pathlib import Path
 from typing import Union
+
 import jsonlines
 
 key_whitelist = set(['feat', 'text', 'syllable', 'phone'])
@@ -34,7 +35,7 @@ def dump_manifest(manifest_path, output_dir: Union[str, Path]):
 
  with jsonlines.open(str(manifest_path), 'r') as reader:
  manifest_jsons = list(reader)
- 
+
  first_line = manifest_jsons[0]
  file_map = {}
 

utils/format_data.py

@@ -15,9 +15,10 @@
 """format manifest with more metadata."""
 import argparse
 import functools
-import jsonlines
 import json
 
+import jsonlines
+
 from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
 from paddlespeech.s2t.frontend.utility import load_cmvn
 from paddlespeech.s2t.io.utility import feat_type
@@ -73,7 +74,7 @@ def main():
  for manifest_path in args.manifest_paths:
  with jsonlines.open(str(manifest_path), 'r') as reader:
  manifest_jsons = list(reader)
- 
+
  for line_json in manifest_jsons:
  output_json = {
  "input": [],

utils/format_triplet_data.py

@@ -16,6 +16,7 @@
 import argparse
 import functools
 import json
+
 import jsonlines
 
 from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer

utils/manifest_key_value.py

@@ -3,6 +3,7 @@
 import argparse
 import functools
 from pathlib import Path
+
 import jsonlines
 
 from utils.utility import add_arguments

utils/utility.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import hashlib
-import json
 import os
 import sys
 import tarfile