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[paraformer] fsdp fix submodule call #2431

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merged 2 commits into from
Mar 22, 2024
Merged

[paraformer] fsdp fix submodule call #2431

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5cf75ed
[paraformer] fsdp fix submodule call
Mddct Mar 22, 2024
5734825
fix blank_id
Mddct Mar 22, 2024
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2 changes: 2 additions & 0 deletions wenet/paraformer/convert_paraformer_to_wenet_config_and_ckpt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -186,6 +186,8 @@ def convert_to_wenet_state_dict(args, wenet_model_path):
wenet_name = wenet_name.replace('predictor.', 'predictor.tp_')
elif wenet_name.startswith('predictor.blstm'):
wenet_name = wenet_name.replace('predictor.', 'predictor.tp_')
elif wenet_name == 'decoder.embed.0.weight':
wenet_name = 'embed.weight'

wenet_state_dict[wenet_name] = checkpoint[name].float()

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6 changes: 1 addition & 5 deletions wenet/paraformer/layers.py
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Expand Up @@ -410,11 +410,7 @@ def __init__(
normalize_before,
src_attention,
gradient_checkpointing=gradient_checkpointing)
del self.embed
self.embed = torch.nn.Sequential(
torch.nn.Embedding(vocab_size, encoder_output_size))

del self.decoders
del self.embed, self.decoders
self.decoders = torch.nn.ModuleList([
SanmDecoderLayer(
encoder_output_size,
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4 changes: 1 addition & 3 deletions wenet/paraformer/paraformer.py
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Expand Up @@ -141,9 +141,7 @@ def __init__(self,
self.sampler = sampler
self.sampling_ratio = sampling_ratio
if sampler:
self.embed = self.decoder.embed
else:
del self.decoder.embed
self.embed = torch.nn.Embedding(vocab_size, encoder.output_size())
# NOTE(Mddct): add eos in tail of labels for predictor
# eg:
# gt: 你 好 we@@ net
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