export model

游雁

2023-02-10 db0dd1950f6d619411f8bb8779f59be411a3783e

export model

 funasr/export/export_model.py

@@ -9,14 +9,15 @@

from funasr.bin.asr_inference_paraformer import Speech2Text
from funasr.export.models import get_model


import numpy as np
import random

class ASRModelExportParaformer:
    def __init__(self, cache_dir: Union[Path, str] = None, onnx: bool = True):
        assert check_argument_types()
        self.set_all_random_seed(0)
        if cache_dir is None:
            cache_dir = Path.home() / "cache" / "export"
            cache_dir = Path.home() / ".cache" / "export"

        self.cache_dir = Path(cache_dir)
        self.export_config = dict(
@@ -25,6 +26,7 @@
        )
        logging.info("output dir: {}".format(self.cache_dir))
        self.onnx = onnx
        

    def _export(
        self,
@@ -61,6 +63,10 @@
        model_script = torch.jit.trace(model, dummy_input)
        model_script.save(os.path.join(path, f'{model.model_name}.torchscripts'))

    def set_all_random_seed(self, seed: int):
        random.seed(seed)
        np.random.seed(seed)
        torch.random.manual_seed(seed)
    def export(self,
               tag_name: str = 'damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
               mode: str = 'paraformer',
@@ -89,38 +95,6 @@
        )
        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: