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Merge branch 'k2-fsa:master' into dev/speechllm

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Yifan Yang 2025-05-24 13:13:42 +08:00 committed by GitHub
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3 changed files with 8 additions and 4 deletions
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4
README.md
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@ -383,3 +383,7 @@ Please see: [![Open In Colab](https://colab.research.google.com/assets/colab-bad
[vctk]: egs/vctk/TTS [vctk]: egs/vctk/TTS
[ljspeech]: egs/ljspeech/TTS [ljspeech]: egs/ljspeech/TTS
[libritts_tts]: egs/libritts/TTS [libritts_tts]: egs/libritts/TTS
## Acknowledgements
Some contributors to this project were supported by Xiaomi Corporation. Others were supported by National Science Foundation CCRI award 2120435. This is not an exhaustive list of sources of support.

6
egs/librispeech/ASR/zipformer/finetune.py
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@ -140,8 +140,8 @@ def add_finetune_arguments(parser: argparse.ArgumentParser):
type=str2bool, type=str2bool,
default=False, default=False,
help=""" help="""
Whether to adapt. If true, we will mix 5% of the new data Whether to adapt. If true, we will mix 5%% of the new data
with 95% of the original data to fine-tune. This is useful with 95%% of the original data to fine-tune. This is useful
if you want to maintain the performance on the original domain if you want to maintain the performance on the original domain
""", """,
) )
@ -1134,7 +1134,7 @@ def train_one_epoch(
f"Epoch {params.cur_epoch}, " f"Epoch {params.cur_epoch}, "
f"batch {batch_idx}, loss[{loss_info}], " f"batch {batch_idx}, loss[{loss_info}], "
f"tot_loss[{tot_loss}], batch size: {batch_size}, " f"tot_loss[{tot_loss}], batch size: {batch_size}, "
f"lr: {cur_lr:.2e}, " f"lr: {cur_lr: .2e}, "
+ (f"grad_scale: {scaler._scale.item()}" if params.use_fp16 else "") + (f"grad_scale: {scaler._scale.item()}" if params.use_fp16 else "")
) )

2
icefall/utils.py
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@ -186,7 +186,7 @@ class AttributeDict(dict):
tmp = {} tmp = {}
for k, v in self.items(): for k, v in self.items():
# PosixPath is ont JSON serializable # PosixPath is ont JSON serializable
if isinstance(v, pathlib.Path) or isinstance(v, torch.device): if isinstance(v, (pathlib.Path, torch.device, torch.dtype)):
v = str(v) v = str(v)
tmp[k] = v tmp[k] = v
return json.dumps(tmp, indent=indent, sort_keys=True) return json.dumps(tmp, indent=indent, sort_keys=True)