[s2t] DataLoader with BatchSampler or DistributeBatchSampler (#1242)

* batchsampler or distributebatchsampler

* format

paddlespeech/s2t/exps/u2_st/model.py

@@ -292,7 +292,8 @@ def setup_dataloader(self):
  n_iter_processes=config.collator.num_workers,
  subsampling_factor=1,
  load_aux_output=load_transcript,
- num_encs=1)
+ num_encs=1,
+ dist_sampler=True)
 
  self.valid_loader = BatchDataLoader(
  json_file=config.data.dev_manifest,
@@ -313,7 +314,8 @@ def setup_dataloader(self):
  n_iter_processes=config.collator.num_workers,
  subsampling_factor=1,
  load_aux_output=load_transcript,
- num_encs=1)
+ num_encs=1,
+ dist_sampler=True)
  logger.info("Setup train/valid Dataloader!")
  else:
  # test dataset, return raw text
@@ -335,7 +337,8 @@ def setup_dataloader(self):
  augmentation_config, # aug will be off when train_mode=False
  n_iter_processes=config.collator.num_workers,
  subsampling_factor=1,
- num_encs=1)
+ num_encs=1,
+ dist_sampler=False)
 
  logger.info("Setup test Dataloader!")
 
@@ -542,7 +545,8 @@ def test(self):
  len_refs += metrics['len_refs']
  num_ins += metrics['num_ins']
  rtf = num_time / (num_frames * stride_ms)
- logger.info("RTF: %f, instance (%d), batch BELU = %f" % (rtf, num_ins, bleu))
+ logger.info("RTF: %f, instance (%d), batch BELU = %f" %
+ (rtf, num_ins, bleu))
 
  rtf = num_time / (num_frames * stride_ms)
  msg = "Test: "

paddlespeech/s2t/io/converter.py

@@ -65,8 +65,9 @@ def __call__(self, batch):
  # text data (output): (text_len, )
  ys_data.append(ud)
 
- assert xs_data[0][0] is not None, "please check Reader and Augmentation impl."
-
+ assert xs_data[0][
+ 0] is not None, "please check Reader and Augmentation impl."
+
  xs_pad, ilens = [], []
  for xs in xs_data:
  # perform subsampling
@@ -79,22 +80,26 @@ def __call__(self, batch):
  # perform padding and convert to tensor
  # currently only support real number
  xs_pad.append(pad_list(xs, 0).astype(self.dtype))
- 
+
  if not self.load_aux_input:
  xs_pad, ilens = xs_pad[0], ilens[0]
  break
- 
+
  # NOTE: this is for multi-output (e.g., speech translation)
  ys_pad, olens = [], []
- 
+
  for ys in ys_data:
- ys_pad.append(pad_list(
- [np.array(y[0][:]) if isinstance(y, tuple) else y for y in ys],
- self.ignore_id))
+ ys_pad.append(
+ pad_list([
+ np.array(y[0][:]) if isinstance(y, tuple) else y for y in ys
+ ], self.ignore_id))
+
+ olens.append(
+ np.array([
+ y[0].shape[0] if isinstance(y, tuple) else y.shape[0]
+ for y in ys
+ ]))
 
- olens.append(np.array(
- [y[0].shape[0] if isinstance(y, tuple) else y.shape[0] for y in ys]))
-
  if not self.load_aux_output:
  ys_pad, olens = ys_pad[0], olens[0]
  break

paddlespeech/s2t/io/dataloader.py

@@ -18,6 +18,7 @@
 
 import jsonlines
 import numpy as np
+from paddle.io import BatchSampler
 from paddle.io import DataLoader
 from paddle.io import DistributedBatchSampler
 
@@ -76,7 +77,8 @@ def __init__(self,
  subsampling_factor: int=1,
  load_aux_input: bool=False,
  load_aux_output: bool=False,
- num_encs: int=1):
+ num_encs: int=1,
+ dist_sampler: bool=False):
  self.json_file = json_file
  self.train_mode = train_mode
  self.use_sortagrad = sortagrad == -1 or sortagrad > 0
@@ -94,6 +96,7 @@ def __init__(self,
  self.n_iter_processes = n_iter_processes
  self.load_aux_input = load_aux_input
  self.load_aux_output = load_aux_output
+ self.dist_sampler = dist_sampler
 
  # read json data
  with jsonlines.open(json_file, 'r') as reader:
@@ -145,11 +148,18 @@ def __init__(self,
  self.dataset = TransformDataset(self.minibaches, self.converter,
  self.reader)
 
- self.sampler = DistributedBatchSampler(
- dataset=self.dataset,
- batch_size=1,
- shuffle=not self.use_sortagrad if self.train_mode else False,
- )
+ if self.dist_sampler:
+ self.sampler = DistributedBatchSampler(
+ dataset=self.dataset,
+ batch_size=1,
+ shuffle=not self.use_sortagrad if self.train_mode else False,
+ drop_last=False, )
+ else:
+ self.sampler = BatchSampler(
+ dataset=self.dataset,
+ batch_size=1,
+ shuffle=not self.use_sortagrad if self.train_mode else False,
+ drop_last=False, )
 
  self.dataloader = DataLoader(
  dataset=self.dataset,
@@ -181,5 +191,8 @@ def __repr__(self):
  echo += f"subsampling_factor: {self.subsampling_factor}, "
  echo += f"num_encs: {self.num_encs}, "
  echo += f"num_workers: {self.n_iter_processes}, "
+ echo += f"load_aux_input: {self.load_aux_input}, "
+ echo += f"load_aux_output: {self.load_aux_output}, "
+ echo += f"dist_sampler: {self.dist_sampler}, "
  echo += f"file: {self.json_file}"
  return echo

paddlespeech/t2s/exps/synthesize_e2e.py

@@ -203,12 +203,15 @@ def evaluate(args):
  get_tone_ids = True
  if args.lang == 'zh':
  input_ids = frontend.get_input_ids(
- sentence, merge_sentences=merge_sentences, get_tone_ids=get_tone_ids)
+ sentence,
+ merge_sentences=merge_sentences,
+ get_tone_ids=get_tone_ids)
  phone_ids = input_ids["phone_ids"]
  if get_tone_ids:
  tone_ids = input_ids["tone_ids"]
  elif args.lang == 'en':
- input_ids = frontend.get_input_ids(sentence, merge_sentences=merge_sentences)
+ input_ids = frontend.get_input_ids(
+ sentence, merge_sentences=merge_sentences)
  phone_ids = input_ids["phone_ids"]
  else:
  print("lang should in {'zh', 'en'}!")