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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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revert init_model.py and add init_model in export_jit
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@Mddct
Mddct committed Oct 30, 2023
commit b765c1280351a46094a56bb5207ffad6191b8dc9
28 changes: 27 additions & 1 deletion wenet/paraformer/ali_paraformer/export_jit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,12 @@
import argparse
import torch
import yaml
from wenet.cif.predictor import Predictor
from wenet.paraformer.ali_paraformer.model import (AliParaformer, SanmDecoer,
SanmEncoder)
from wenet.transformer.cmvn import GlobalCMVN
from wenet.utils.checkpoint import load_checkpoint
from wenet.utils.init_model import init_model
from wenet.utils.cmvn import load_cmvn


def get_args():
Expand All @@ -23,6 +27,28 @@ def get_args():
return args


def init_model(configs):
mean, istd = load_cmvn(configs['cmvn_file'], configs['is_json_cmvn'])
global_cmvn = GlobalCMVN(
torch.from_numpy(mean).float(),
torch.from_numpy(istd).float())
input_dim = configs['input_dim']
vocab_size = configs['output_dim']
encoder = SanmEncoder(global_cmvn=global_cmvn,
input_size=configs['lfr_conf']['lfr_m'] * input_dim,
**configs['encoder_conf'])
decoder = decoder = SanmDecoer(vocab_size=vocab_size,
encoder_output_size=encoder.output_size(),
**configs['decoder_conf'])
predictor = Predictor(**configs['cif_predictor_conf'])
model = AliParaformer(
encoder=encoder,
decoder=decoder,
predictor=predictor,
)
return model


def main():

args = get_args()
Expand Down
35 changes: 6 additions & 29 deletions wenet/utils/init_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,7 @@

import torch

from wenet.paraformer.ali_paraformer.model import SanmDecoer, SanmEncoder
from wenet.k2.model import K2Model

from wenet.transducer.joint import TransducerJoint
from wenet.transducer.predictor import (ConvPredictor, EmbeddingPredictor,
RNNPredictor)
Expand All @@ -31,7 +29,6 @@
from wenet.squeezeformer.encoder import SqueezeformerEncoder
from wenet.efficient_conformer.encoder import EfficientConformerEncoder
from wenet.paraformer.paraformer import Paraformer
from wenet.paraformer.ali_paraformer.model import AliParaformer
from wenet.cif.predictor import Predictor
from wenet.utils.cmvn import load_cmvn

Expand Down Expand Up @@ -74,24 +71,13 @@ def init_model(configs):
encoder = EBranchformerEncoder(input_dim,
global_cmvn=global_cmvn,
**configs['encoder_conf'])
elif encoder_type == 'SanmEncoder':
assert 'lfr_conf' in configs
encoder = SanmEncoder(global_cmvn=global_cmvn,
input_size=configs['lfr_conf']['lfr_m'] *
input_dim,
**configs['encoder_conf'])
else:
encoder = TransformerEncoder(input_dim,
global_cmvn=global_cmvn,
**configs['encoder_conf'])
if decoder_type == 'transformer':
decoder = TransformerDecoder(vocab_size, encoder.output_size(),
**configs['decoder_conf'])
elif decoder_type == 'SanmDecoder':
assert isinstance(encoder, SanmEncoder)
decoder = SanmDecoer(vocab_size=vocab_size,
encoder_output_size=encoder.output_size(),
**configs['decoder_conf'])
else:
assert 0.0 < configs['model_conf']['reverse_weight'] < 1.0
assert configs['decoder_conf']['r_num_blocks'] > 0
Expand Down Expand Up @@ -131,21 +117,12 @@ def init_model(configs):
**configs['model_conf'])
elif 'paraformer' in configs:
predictor = Predictor(**configs['cif_predictor_conf'])
if isinstance(encoder, SanmEncoder):
assert isinstance(decoder, SanmDecoer)
# NOTE(Mddct): only support inference for now
model = AliParaformer(
encoder=encoder,
decoder=decoder,
predictor=predictor,
)
else:
model = Paraformer(vocab_size=vocab_size,
encoder=encoder,
decoder=decoder,
ctc=ctc,
predictor=predictor,
**configs['model_conf'])
model = Paraformer(vocab_size=vocab_size,
encoder=encoder,
decoder=decoder,
ctc=ctc,
predictor=predictor,
**configs['model_conf'])
else:
print(configs)
if configs.get('lfmmi_dir', '') != '':
Expand Down
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