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https://github.com/modelscope/FunASR
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861147c730
* sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * sensevoice finetune * bugfix * update with main (#1631) * update seaco finetune * v1.0.24 --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com> * sensevoice * sensevoice * sensevoice * update with main (#1638) * update seaco finetune * v1.0.24 * update rwkv template --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com> * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sensevoice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * sense voice * whisper * whisper * update style * update style --------- Co-authored-by: 维石 <shixian.shi@alibaba-inc.com>
32 lines
876 B
Python
32 lines
876 B
Python
from funasr.register import tables
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from funasr.models.whisper_lid.eres2net.ResNet import (
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ERes2Net,
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BasicBlockERes2Net,
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BasicBlockERes2Net_diff_AFF,
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)
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@tables.register("lid_predictor_classes", "LidPredictor")
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class LidPredictor(ERes2Net):
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def __init__(
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self,
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block=BasicBlockERes2Net,
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block_fuse=BasicBlockERes2Net_diff_AFF,
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num_blocks=[3, 4, 6, 3],
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m_channels=32,
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feat_dim=80,
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embedding_size=192,
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pooling_func="TSTP",
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two_emb_layer=False,
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):
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super(LidPredictor, self).__init__(
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block=block,
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block_fuse=block_fuse,
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num_blocks=num_blocks,
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m_channels=m_channels,
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feat_dim=feat_dim,
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embedding_size=embedding_size,
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pooling_func=pooling_func,
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two_emb_layer=two_emb_layer,
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)
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