Merge pull request #166 from magicharry/main

magicharry

2023-02-28 939b9fe25d6dd07f2c2215ed78eaff301a71c7f7

Merge pull request #166 from magicharry/main

unit test pr new

 .github/workflows/UnitTest.yml

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name: FunASR Unit Test
run-name: ${{ github.actor }} is testing out FunASR Unit Test 🚀
on:
  pull_request:
      branches:
        - main
  push:
    branches:
      - dev_wjm
      - dev_jy

jobs:
  build:

    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: ["3.7"]

    steps:
      - uses: actions/checkout@v3
      - name: Set up Python ${{ matrix.python-version }}
        uses: actions/setup-python@v4
        with:
          python-version: ${{ matrix.python-version }}
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install torch torchvision torchaudio
          pip install "modelscope[audio_asr]" --upgrade -f \
            https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
          if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
          pip install -e ./
      - name: Testing
        run:
          python tests/run_test.py

 tests/run_test.py

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#!/usr/bin/env python

import argparse
import os
import sys
import unittest
from fnmatch import fnmatch


def gather_test_cases(test_dir, pattern, list_tests):
    case_list = []
    for dirpath, dirnames, filenames in os.walk(test_dir):
        for file in filenames:
            if fnmatch(file, pattern):
                case_list.append(file)

    test_suite = unittest.TestSuite()

    for case in case_list:
        test_case = unittest.defaultTestLoader.discover(start_dir=test_dir, pattern=case)
        test_suite.addTest(test_case)
        if hasattr(test_case, '__iter__'):
            for subcase in test_case:
                if list_tests:
                    print(subcase)
        else:
            if list_tests:
                print(test_case)
    return test_suite


def main(args):
    runner = unittest.TextTestRunner()
    test_suite = gather_test_cases(os.path.abspath(args.test_dir), args.pattern, args.list_tests)
    if not args.list_tests:
        result = runner.run(test_suite)
        if len(result.failures) > 0:
            sys.exit(len(result.failures))
        if len(result.errors) > 0:
            sys.exit(len(result.errors))


if __name__ == '__main__':
    parser = argparse.ArgumentParser('test runner')
    parser.add_argument('--list_tests', action='store_true', help='list all tests')
    parser.add_argument('--pattern', default='test_*.py', help='test file pattern')
    parser.add_argument('--test_dir', default='tests', help='directory to be tested')
    parser.add_argument('--disable_profile', action='store_true', help='disable profiling')
    args = parser.parse_args()
    print(f'working dir: {os.getcwd()}')
    main(args)

 tests/test_inference_pipeline.py

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import unittest

from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.utils.logger import get_logger

logger = get_logger()

class TestInferencePipelines(unittest.TestCase):
    def test_funasr_path(self):
        import funasr
        import os
        logger.info("run_dir:{0} ; funasr_path: {1}".format(os.getcwd(), funasr.__file__))

    def test_asr_inference_pipeline(self):
        inference_pipeline = pipeline(
            task=Tasks.auto_speech_recognition,
            model='damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch')
        rec_result = inference_pipeline(
            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav')
        logger.info("asr inference result: {0}".format(rec_result))

    def test_asr_inference_pipeline_with_vad_punc(self):
        inference_pipeline = pipeline(
            task=Tasks.auto_speech_recognition,
            model='damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
            vad_model='damo/speech_fsmn_vad_zh-cn-16k-common-pytorch',
            vad_model_revision="v1.1.8",
            punc_model='damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch',
            punc_model_revision="v1.1.6")
        rec_result = inference_pipeline(
            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_vad_punc_example.wav')
        logger.info("asr inference with vad punc result: {0}".format(rec_result))

    def test_vad_inference_pipeline(self):
        inference_pipeline = pipeline(
            task=Tasks.voice_activity_detection,
            model='damo/speech_fsmn_vad_zh-cn-16k-common-pytorch',
            model_revision='v1.1.8',
        )
        segments_result = inference_pipeline(
            audio_in='https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/vad_example.wav')
        logger.info("vad inference result: {0}".format(segments_result))


if __name__ == '__main__':
    unittest.main()