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isort and black formatting

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This commit is contained in:
Bailey Hirota 2025-07-18 17:14:51 +09:00
parent 73b30aeda5
commit 57633e1eb0
3 changed files with 11 additions and 7 deletions
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4
egs/reazonspeech/ASR/local/compute_fbank_musan.py
View File

@ -55,7 +55,9 @@ def is_cut_long(c: MonoCut) -> bool:
def compute_fbank_musan( def compute_fbank_musan(
num_mel_bins: int = 80, whisper_fbank: bool = False, output_dir: str = "data/manifests" num_mel_bins: int = 80,
whisper_fbank: bool = False,
output_dir: str = "data/manifests",
): ):
src_dir = Path("data/manifests") src_dir = Path("data/manifests")
output_dir = Path(output_dir) output_dir = Path(output_dir)

4
egs/reazonspeech/ASR/local/utils/asr_datamodule.py
View File

@ -180,8 +180,8 @@ class ReazonSpeechAsrDataModule:
) )
def train_dataloaders( def train_dataloaders(
self, self,
cuts_train: CutSet, cuts_train: CutSet,
sampler_state_dict: Optional[Dict[str, Any]] = None, sampler_state_dict: Optional[Dict[str, Any]] = None,
cuts_musan: Optional[CutSet] = None, cuts_musan: Optional[CutSet] = None,
) -> DataLoader: ) -> DataLoader:

10
egs/reazonspeech/ASR/zipformer/train.py
View File

@ -65,10 +65,10 @@ import torch.nn as nn
from asr_datamodule import ReazonSpeechAsrDataModule from asr_datamodule import ReazonSpeechAsrDataModule
from decoder import Decoder from decoder import Decoder
from joiner import Joiner from joiner import Joiner
from lhotse import load_manifest
from lhotse.cut import Cut from lhotse.cut import Cut
from lhotse.dataset.sampling.base import CutSampler from lhotse.dataset.sampling.base import CutSampler
from lhotse.utils import fix_random_seed from lhotse.utils import fix_random_seed
from lhotse import load_manifest
from model import AsrModel from model import AsrModel
from optim import Eden, ScaledAdam from optim import Eden, ScaledAdam
from scaling import ScheduledFloat from scaling import ScheduledFloat
@ -1226,14 +1226,16 @@ def run(rank, world_size, args):
cuts_musan = load_manifest(musan_path) cuts_musan = load_manifest(musan_path)
logging.info(f"Loaded MUSAN manifest from {musan_path}") logging.info(f"Loaded MUSAN manifest from {musan_path}")
else: else:
logging.warning(f"MUSAN manifest not found at {musan_path}, disabling MUSAN augmentation") logging.warning(
f"MUSAN manifest not found at {musan_path}, disabling MUSAN augmentation"
)
cuts_musan = None cuts_musan = None
else: else:
cuts_musan = None cuts_musan = None
train_dl = reazonspeech_corpus.train_dataloaders( train_dl = reazonspeech_corpus.train_dataloaders(
train_cuts, train_cuts,
sampler_state_dict=sampler_state_dict, sampler_state_dict=sampler_state_dict,
cuts_musan=cuts_musan, cuts_musan=cuts_musan,
) )