hnluo
2023-06-29 c2dee5e3c29eba79e591d9e9caebaef15ea4e56b
funasr/runtime/python/onnxruntime/funasr_onnx/paraformer_bin.py
@@ -1,4 +1,6 @@
# -*- encoding: utf-8 -*-
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
#  MIT License  (https://opensource.org/licenses/MIT)
import os.path
from pathlib import Path
@@ -19,20 +21,41 @@
class Paraformer():
    """
    Author: Speech Lab of DAMO Academy, Alibaba Group
    Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition
    https://arxiv.org/abs/2206.08317
    """
    def __init__(self, model_dir: Union[str, Path] = None,
                 batch_size: int = 1,
                 device_id: Union[str, int] = "-1",
                 plot_timestamp_to: str = "",
                 quantize: bool = False,
                 intra_op_num_threads: int = 4,
                 cache_dir: str = None
                 ):
        if not Path(model_dir).exists():
            raise FileNotFoundError(f'{model_dir} does not exist.')
            from modelscope.hub.snapshot_download import snapshot_download
            try:
                model_dir = snapshot_download(model_dir, cache_dir=cache_dir)
            except:
                raise "model_dir must be model_name in modelscope or local path downloaded from modelscope, but is {}".format(model_dir)
        model_file = os.path.join(model_dir, 'model.onnx')
        if quantize:
            model_file = os.path.join(model_dir, 'model_quant.onnx')
        if not os.path.exists(model_file):
            print(".onnx is not exist, begin to export onnx")
            from funasr.export.export_model import ModelExport
            export_model = ModelExport(
                cache_dir=cache_dir,
                onnx=True,
                device="cpu",
                quant=quantize,
            )
            export_model.export(model_dir)
        config_file = os.path.join(model_dir, 'config.yaml')
        cmvn_file = os.path.join(model_dir, 'am.mvn')
        config = read_yaml(config_file)