| .github/workflows/UnitTest.yml | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| tests/citest.sh | 补丁 | 查看 | 原始文档 | blame | 历史 | |
| tests/run_test.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| tests/test_inference_pipeline.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 |
.github/workflows/UnitTest.yml
New file @@ -0,0 +1,36 @@ 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/citest.sh
tests/run_test.py
New file @@ -0,0 +1,51 @@ #!/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
New file @@ -0,0 +1,47 @@ 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()
