jmwang66
2023-06-20 2ff405b2f4ab899eff9bece232969fbb0c8f0555
funasr/bin/vad_infer.py
@@ -1,42 +1,23 @@
# -*- encoding: utf-8 -*-
#!/usr/bin/env python3
# -*- encoding: utf-8 -*-
# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
#  MIT License  (https://opensource.org/licenses/MIT)
import argparse
import logging
import os
import sys
import json
import math
from pathlib import Path
from typing import Any
from typing import Dict
from typing import List
from typing import Optional
from typing import Sequence
from typing import Tuple
from typing import Union
from typing import Dict
import math
import numpy as np
import torch
from typeguard import check_argument_types
from typeguard import check_return_type
from funasr.fileio.datadir_writer import DatadirWriter
from funasr.modules.scorers.scorer_interface import BatchScorerInterface
from funasr.modules.subsampling import TooShortUttError
from funasr.tasks.vad import VADTask
from funasr.torch_utils.device_funcs import to_device
from funasr.torch_utils.set_all_random_seed import set_all_random_seed
from funasr.utils import config_argparse
from funasr.utils.cli_utils import get_commandline_args
from funasr.utils.types import str2bool
from funasr.utils.types import str2triple_str
from funasr.utils.types import str_or_none
from funasr.utils import asr_utils, wav_utils, postprocess_utils
from funasr.build_utils.build_model_from_file import build_model_from_file
from funasr.models.frontend.wav_frontend import WavFrontend, WavFrontendOnline
from funasr.torch_utils.device_funcs import to_device
class Speech2VadSegment:
@@ -64,8 +45,8 @@
        assert check_argument_types()
        # 1. Build vad model
        vad_model, vad_infer_args = VADTask.build_model_from_file(
            vad_infer_config, vad_model_file, device
        vad_model, vad_infer_args = build_model_from_file(
            vad_infer_config, vad_model_file, None, device, task_name="vad"
        )
        frontend = None
        if vad_infer_args.frontend is not None:
@@ -128,12 +109,13 @@
                "in_cache": in_cache
            }
            # a. To device
            #batch = to_device(batch, device=self.device)
            # batch = to_device(batch, device=self.device)
            segments_part, in_cache = self.vad_model(**batch)
            if segments_part:
                for batch_num in range(0, self.batch_size):
                    segments[batch_num] += segments_part[batch_num]
        return fbanks, segments
class Speech2VadSegmentOnline(Speech2VadSegment):
    """Speech2VadSegmentOnline class
@@ -146,13 +128,13 @@
        [[10, 230], [245, 450], ...]
    """
    def __init__(self, **kwargs):
        super(Speech2VadSegmentOnline, self).__init__(**kwargs)
        vad_cmvn_file = kwargs.get('vad_cmvn_file', None)
        self.frontend = None
        if self.vad_infer_args.frontend is not None:
            self.frontend = WavFrontendOnline(cmvn_file=vad_cmvn_file, **self.vad_infer_args.frontend_conf)
    @torch.no_grad()
    def __call__(
@@ -198,5 +180,3 @@
            # in_cache.update(batch['in_cache'])
            # in_cache = {key: value for key, value in batch['in_cache'].items()}
        return fbanks, segments, in_cache