minor fixes

This commit is contained in:
jinzr 2024-03-08 02:10:57 +08:00
parent 4e90233785
commit ff53cb0458
3 changed files with 18 additions and 12 deletions

View File

@ -381,9 +381,11 @@ class CommonVoiceAsrDataModule:
def test_dataloaders(self, cuts: CutSet) -> DataLoader:
logging.debug("About to create test dataset")
test = K2SpeechRecognitionDataset(
input_strategy=OnTheFlyFeatures(Fbank(FbankConfig(num_mel_bins=80)))
input_strategy=(
OnTheFlyFeatures(Fbank(FbankConfig(num_mel_bins=80)))
if self.args.on_the_fly_feats
else eval(self.args.input_strategy)(),
else eval(self.args.input_strategy)()
),
return_cuts=self.args.return_cuts,
)
sampler = DynamicBucketingSampler(

View File

@ -31,7 +31,7 @@ from lhotse.dataset import ( # noqa F401 for PrecomputedFeatures
DynamicBucketingSampler,
K2SpeechRecognitionDataset,
PrecomputedFeatures,
SingleCutSampler,
SimpleCutSampler,
SpecAugment,
)
from lhotse.dataset.input_strategies import ( # noqa F401 For AudioSamples
@ -315,8 +315,8 @@ class CommonVoiceAsrDataModule:
drop_last=self.args.drop_last,
)
else:
logging.info("Using SingleCutSampler.")
train_sampler = SingleCutSampler(
logging.info("Using SimpleCutSampler.")
train_sampler = SimpleCutSampler(
cuts_train,
max_duration=self.args.max_duration,
shuffle=self.args.shuffle,
@ -383,9 +383,11 @@ class CommonVoiceAsrDataModule:
def test_dataloaders(self, cuts: CutSet) -> DataLoader:
logging.debug("About to create test dataset")
test = K2SpeechRecognitionDataset(
input_strategy=OnTheFlyFeatures(Fbank(FbankConfig(num_mel_bins=80)))
input_strategy=(
OnTheFlyFeatures(Fbank(FbankConfig(num_mel_bins=80)))
if self.args.on_the_fly_feats
else eval(self.args.input_strategy)(),
else eval(self.args.input_strategy)()
),
return_cuts=self.args.return_cuts,
)
sampler = DynamicBucketingSampler(

View File

@ -425,9 +425,11 @@ class LibriHeavyAsrDataModule:
def test_dataloaders(self, cuts: CutSet) -> DataLoader:
logging.debug("About to create test dataset")
test = K2SpeechRecognitionDataset(
input_strategy=OnTheFlyFeatures(Fbank(FbankConfig(num_mel_bins=80)))
input_strategy=(
OnTheFlyFeatures(Fbank(FbankConfig(num_mel_bins=80)))
if self.args.on_the_fly_feats
else PrecomputedFeatures(),
else PrecomputedFeatures()
),
return_cuts=self.args.return_cuts,
)
sampler = DynamicBucketingSampler(