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[cli/paraformer] ali-paraformer inference #2067

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merged 21 commits into from
Oct 30, 2023
Merged

[cli/paraformer] ali-paraformer inference #2067

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000c7af
[cli/paraformer] ali-paraformer load and infer work
Mddct Oct 16, 2023
6967ef5
fix lint
Mddct Oct 20, 2023
c8cccdc
export jit and load work
Mddct Oct 23, 2023
852165c
reuse init_model.py
Mddct Oct 23, 2023
e8fa013
mv the intermediate files to the assets directory
Mddct Oct 23, 2023
0a98847
merge main
Mddct Oct 23, 2023
e987b00
model.decodde work && recognize.py work
Mddct Oct 23, 2023
3d25e2e
rm positionwise_feed_forward.py/lfr.py
Mddct Oct 23, 2023
aedd43b
Merge branch 'main' into Mddct-cli-paraformer
Mddct Oct 24, 2023
d264297
refactor search
Mddct Oct 24, 2023
3f45af7
merge main
Mddct Oct 24, 2023
30b5677
merge main
Mddct Oct 24, 2023
20146f4
cli work
Mddct Oct 24, 2023
e3ec8e7
fix lint
Mddct Oct 24, 2023
b1b44df
fix att mask && batch infer
Mddct Oct 30, 2023
cd9c659
search confidence works
Mddct Oct 30, 2023
0b0eea7
merge main
Mddct Oct 30, 2023
c11aefe
merge main
Mddct Oct 30, 2023
daff617
fix linux dtype
Mddct Oct 30, 2023
9e810d1
fix label type
Mddct Oct 30, 2023
b765c12
revert init_model.py and add init_model in export_jit
Mddct Oct 30, 2023
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mv the intermediate files to the assets directory
  • Loading branch information
@Mddct
Mddct committed Oct 23, 2023
commit e8fa0132fc4957d3448c0a57fe94f2520c300652
2 changes: 2 additions & 0 deletions wenet/paraformer/ali_paraformer/config.yaml → ...aformer/ali_paraformer/assets/config.yaml
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Expand Up @@ -14,6 +14,8 @@ encoder_conf:
kernel_size: 11
sanm_shfit: 0

input_dim: 80
output_dim: 8404
paraformer: true
# decoder related
decoder: SanmDecoder
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0 wenet/paraformer/ali_paraformer/global_cmvn → ...aformer/ali_paraformer/assets/global_cmvn
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0 wenet/paraformer/ali_paraformer/units.txt → ...araformer/ali_paraformer/assets/units.txt
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16 changes: 0 additions & 16 deletions ...t/paraformer/ali_paraformer/export_jit.py → ...raformer/ali_paraformer/test_infer_jit.py
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Expand Up @@ -43,24 +43,8 @@ def main():
char_dict = {v: k for k, v in symbol_table.items()}
with open(args.config, 'r') as fin:
configs = yaml.load(fin, Loader=yaml.FullLoader)

# mean, istd = load_cmvn(args.cmvn, is_json=True)
# global_cmvn = GlobalCMVN(
# torch.from_numpy(mean).float(),
# torch.from_numpy(istd).float())
# configs['encoder_conf']['input_size'] = 80 * 7
# encoder = SanmEncoder(global_cmvn=global_cmvn, **configs['encoder_conf'])
# configs['decoder_conf']['vocab_size'] = len(char_dict)
# configs['decoder_conf']['encoder_output_size'] = encoder.output_size()
# decoder = SanmDecoer(**configs['decoder_conf'])

# # predictor = PredictorV3(**configs['predictor_conf'])
# predictor = Predictor(**configs['predictor_conf'])
# model = AliParaformer(encoder, decoder, predictor)
configs['cmvn_file'] = args.cmvn
configs['is_json_cmvn'] = True
configs['input_dim'] = 80
configs['output_dim'] = len(char_dict)
model = init_model(configs)
load_checkpoint(model, args.ali_paraformer)
model.eval()
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1 change: 0 additions & 1 deletion wenet/utils/init_model.py
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Expand Up @@ -131,7 +131,6 @@ def init_model(configs):
if isinstance(encoder, SanmEncoder):
assert isinstance(decoder, SanmDecoer)
# NOTE(Mddct): only support inference for now
print('hello world')
model = AliParaformer(encoder, decoder, predictor)
else:
model = Paraformer(vocab_size=vocab_size,
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