mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
exoprt model
This commit is contained in:
游雁
parent
2edb3a1bf0
commit
8bf1a6adbb
@ -16,17 +16,13 @@ from funasr.export.export_model import ASRModelExportParaformer
|
||||
|
||||
output_dir = "../export" # onnx/torchscripts model save path
|
||||
export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=True)
|
||||
export_model.export_from_modelscope('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
export_model.export('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
```
|
||||
|
||||
|
||||
Export model from local path
|
||||
```python
|
||||
from funasr.export.export_model import ASRModelExportParaformer
|
||||
|
||||
output_dir = "../export" # onnx/torchscripts model save path
|
||||
export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=True)
|
||||
export_model.export_from_local('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
export_model.export('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
```
|
||||
|
||||
## Export torchscripts format model
|
||||
@ -36,15 +32,12 @@ from funasr.export.export_model import ASRModelExportParaformer
|
||||
|
||||
output_dir = "../export" # onnx/torchscripts model save path
|
||||
export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=False)
|
||||
export_model.export_from_modelscope('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
export_model.export('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
```
|
||||
|
||||
Export model from local path
|
||||
```python
|
||||
from funasr.export.export_model import ASRModelExportParaformer
|
||||
|
||||
output_dir = "../export" # onnx/torchscripts model save path
|
||||
export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=False)
|
||||
export_model.export_from_local('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
export_model.export('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
```
|
||||
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
import json
|
||||
from typing import Union, Dict
|
||||
from pathlib import Path
|
||||
from typeguard import check_argument_types
|
||||
@ -25,7 +26,7 @@ class ASRModelExportParaformer:
|
||||
logging.info("output dir: {}".format(self.cache_dir))
|
||||
self.onnx = onnx
|
||||
|
||||
def export(
|
||||
def _export(
|
||||
self,
|
||||
model: Speech2Text,
|
||||
tag_name: str = None,
|
||||
@ -60,38 +61,66 @@ class ASRModelExportParaformer:
|
||||
model_script = torch.jit.trace(model, dummy_input)
|
||||
model_script.save(os.path.join(path, f'{model.model_name}.torchscripts'))
|
||||
|
||||
def export_from_modelscope(
|
||||
self,
|
||||
tag_name: str = 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
|
||||
):
|
||||
def export(self,
|
||||
tag_name: str = 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
|
||||
mode: str = 'paraformer',
|
||||
):
|
||||
|
||||
from funasr.tasks.asr import ASRTaskParaformer as ASRTask
|
||||
from modelscope.hub.snapshot_download import snapshot_download
|
||||
|
||||
model_dir = snapshot_download(tag_name, cache_dir=self.cache_dir)
|
||||
asr_train_config = os.path.join(model_dir, 'config.yaml')
|
||||
asr_model_file = os.path.join(model_dir, 'model.pb')
|
||||
cmvn_file = os.path.join(model_dir, 'am.mvn')
|
||||
model, asr_train_args = ASRTask.build_model_from_file(
|
||||
asr_train_config, asr_model_file, cmvn_file, 'cpu'
|
||||
)
|
||||
self.export(model, tag_name)
|
||||
|
||||
def export_from_local(
|
||||
self,
|
||||
tag_name: str = '/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
|
||||
):
|
||||
|
||||
from funasr.tasks.asr import ASRTaskParaformer as ASRTask
|
||||
|
||||
model_dir = tag_name
|
||||
if model_dir.startswith('damo/'):
|
||||
from modelscope.hub.snapshot_download import snapshot_download
|
||||
model_dir = snapshot_download(tag_name, cache_dir=self.cache_dir)
|
||||
asr_train_config = os.path.join(model_dir, 'config.yaml')
|
||||
asr_model_file = os.path.join(model_dir, 'model.pb')
|
||||
cmvn_file = os.path.join(model_dir, 'am.mvn')
|
||||
json_file = os.path.join(model_dir, 'configuration.json')
|
||||
if mode is None:
|
||||
import json
|
||||
with open(json_file, 'r') as f:
|
||||
config_data = json.load(f)
|
||||
mode = config_data['model']['model_config']['mode']
|
||||
if mode == 'paraformer':
|
||||
from funasr.tasks.asr import ASRTaskParaformer as ASRTask
|
||||
elif mode == 'uniasr':
|
||||
from funasr.tasks.asr import ASRTaskUniASR as ASRTask
|
||||
|
||||
model, asr_train_args = ASRTask.build_model_from_file(
|
||||
asr_train_config, asr_model_file, cmvn_file, 'cpu'
|
||||
)
|
||||
self.export(model, tag_name)
|
||||
|
||||
# def export_from_modelscope(
|
||||
# self,
|
||||
# tag_name: str = 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
|
||||
# ):
|
||||
#
|
||||
# from funasr.tasks.asr import ASRTaskParaformer as ASRTask
|
||||
# from modelscope.hub.snapshot_download import snapshot_download
|
||||
#
|
||||
# model_dir = snapshot_download(tag_name, cache_dir=self.cache_dir)
|
||||
# asr_train_config = os.path.join(model_dir, 'config.yaml')
|
||||
# asr_model_file = os.path.join(model_dir, 'model.pb')
|
||||
# cmvn_file = os.path.join(model_dir, 'am.mvn')
|
||||
# model, asr_train_args = ASRTask.build_model_from_file(
|
||||
# asr_train_config, asr_model_file, cmvn_file, 'cpu'
|
||||
# )
|
||||
# self.export(model, tag_name)
|
||||
#
|
||||
# def export_from_local(
|
||||
# self,
|
||||
# tag_name: str = '/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
|
||||
# ):
|
||||
#
|
||||
# from funasr.tasks.asr import ASRTaskParaformer as ASRTask
|
||||
#
|
||||
# model_dir = tag_name
|
||||
# asr_train_config = os.path.join(model_dir, 'config.yaml')
|
||||
# asr_model_file = os.path.join(model_dir, 'model.pb')
|
||||
# cmvn_file = os.path.join(model_dir, 'am.mvn')
|
||||
# model, asr_train_args = ASRTask.build_model_from_file(
|
||||
# asr_train_config, asr_model_file, cmvn_file, 'cpu'
|
||||
# )
|
||||
# self.export(model, tag_name)
|
||||
|
||||
def _export_onnx(self, model, verbose, path, enc_size=None):
|
||||
if enc_size:
|
||||
@ -116,5 +145,5 @@ class ASRModelExportParaformer:
|
||||
if __name__ == '__main__':
|
||||
output_dir = "../export"
|
||||
export_model = ASRModelExportParaformer(cache_dir=output_dir, onnx=False)
|
||||
export_model.export_from_modelscope('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
# export_model.export_from_local('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
export_model.export('damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
# export_model.export('/root/cache/export/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
|
||||
@ -1,42 +1,3 @@
|
||||
# from .ctc import CTC
|
||||
# from .joint_network import JointNetwork
|
||||
#
|
||||
# # encoder
|
||||
# from espnet2.asr.encoder.rnn_encoder import RNNEncoder as espnetRNNEncoder
|
||||
# from espnet2.asr.encoder.vgg_rnn_encoder import VGGRNNEncoder as espnetVGGRNNEncoder
|
||||
# from espnet2.asr.encoder.contextual_block_transformer_encoder import ContextualBlockTransformerEncoder as espnetContextualTransformer
|
||||
# from espnet2.asr.encoder.contextual_block_conformer_encoder import ContextualBlockConformerEncoder as espnetContextualConformer
|
||||
# from espnet2.asr.encoder.transformer_encoder import TransformerEncoder as espnetTransformerEncoder
|
||||
# from espnet2.asr.encoder.conformer_encoder import ConformerEncoder as espnetConformerEncoder
|
||||
# from funasr.export.models.encoder.rnn import RNNEncoder
|
||||
# from funasr.export.models.encoders import TransformerEncoder
|
||||
# from funasr.export.models.encoders import ConformerEncoder
|
||||
# from funasr.export.models.encoder.contextual_block_xformer import ContextualBlockXformerEncoder
|
||||
#
|
||||
# # decoder
|
||||
# from espnet2.asr.decoder.rnn_decoder import RNNDecoder as espnetRNNDecoder
|
||||
# from espnet2.asr.transducer.transducer_decoder import TransducerDecoder as espnetTransducerDecoder
|
||||
# from funasr.export.models.decoder.rnn import (
|
||||
# RNNDecoder
|
||||
# )
|
||||
# from funasr.export.models.decoders import XformerDecoder
|
||||
# from funasr.export.models.decoders import TransducerDecoder
|
||||
#
|
||||
# # lm
|
||||
# from espnet2.lm.seq_rnn_lm import SequentialRNNLM as espnetSequentialRNNLM
|
||||
# from espnet2.lm.transformer_lm import TransformerLM as espnetTransformerLM
|
||||
# from .language_models.seq_rnn import SequentialRNNLM
|
||||
# from .language_models.transformer import TransformerLM
|
||||
#
|
||||
# # frontend
|
||||
# from espnet2.asr.frontend.s3prl import S3prlFrontend as espnetS3PRLModel
|
||||
# from .frontends.s3prl import S3PRLModel
|
||||
#
|
||||
# from espnet2.asr.encoder.sanm_encoder import SANMEncoder_tf, SANMEncoderChunkOpt_tf
|
||||
# from espnet_onnx.export.asr.models.encoders.transformer_sanm import TransformerEncoderSANM_tf
|
||||
# from espnet2.asr.decoder.transformer_decoder import FsmnDecoderSCAMAOpt_tf
|
||||
# from funasr.export.models.decoders import XformerDecoderSANM
|
||||
|
||||
from funasr.models.e2e_asr_paraformer import Paraformer
|
||||
from funasr.export.models.e2e_asr_paraformer import Paraformer as Paraformer_export
|
||||
|
||||
@ -45,47 +6,4 @@ def get_model(model, export_config=None):
|
||||
if isinstance(model, Paraformer):
|
||||
return Paraformer_export(model, **export_config)
|
||||
else:
|
||||
raise "The model is not exist!"
|
||||
|
||||
|
||||
# def get_encoder(model, frontend, preencoder, predictor=None, export_config=None):
|
||||
# if isinstance(model, espnetRNNEncoder) or isinstance(model, espnetVGGRNNEncoder):
|
||||
# return RNNEncoder(model, frontend, preencoder, **export_config)
|
||||
# elif isinstance(model, espnetContextualTransformer) or isinstance(model, espnetContextualConformer):
|
||||
# return ContextualBlockXformerEncoder(model, **export_config)
|
||||
# elif isinstance(model, espnetTransformerEncoder):
|
||||
# return TransformerEncoder(model, frontend, preencoder, **export_config)
|
||||
# elif isinstance(model, espnetConformerEncoder):
|
||||
# return ConformerEncoder(model, frontend, preencoder, **export_config)
|
||||
# elif isinstance(model, SANMEncoder_tf) or isinstance(model, SANMEncoderChunkOpt_tf):
|
||||
# return TransformerEncoderSANM_tf(model, frontend, preencoder, predictor, **export_config)
|
||||
# else:
|
||||
# raise "The model is not exist!"
|
||||
|
||||
|
||||
#
|
||||
# def get_decoder(model, export_config):
|
||||
# if isinstance(model, espnetRNNDecoder):
|
||||
# return RNNDecoder(model, **export_config)
|
||||
# elif isinstance(model, espnetTransducerDecoder):
|
||||
# return TransducerDecoder(model, **export_config)
|
||||
# elif isinstance(model, FsmnDecoderSCAMAOpt_tf):
|
||||
# return XformerDecoderSANM(model, **export_config)
|
||||
# else:
|
||||
# return XformerDecoder(model, **export_config)
|
||||
#
|
||||
#
|
||||
# def get_lm(model, export_config):
|
||||
# if isinstance(model, espnetSequentialRNNLM):
|
||||
# return SequentialRNNLM(model, **export_config)
|
||||
# elif isinstance(model, espnetTransformerLM):
|
||||
# return TransformerLM(model, **export_config)
|
||||
#
|
||||
#
|
||||
# def get_frontend_models(model, export_config):
|
||||
# if isinstance(model, espnetS3PRLModel):
|
||||
# return S3PRLModel(model, **export_config)
|
||||
# else:
|
||||
# return None
|
||||
#
|
||||
|
||||
raise "The model is not exist!"
|
||||
Loading…
Reference in New Issue
Block a user