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Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10371244 Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10371244
82 lines
3.5 KiB
Python
82 lines
3.5 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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# NOTICE: Tensorflow 1.15 seems not so compatible with pytorch.
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# A segmentation fault may be raise by pytorch cpp library
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# if 'import tensorflow' in front of 'import torch'.
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# Puting a 'import torch' here can bypass this incompatibility.
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import torch
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from scipy.io.wavfile import write
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from modelscope.models import Model
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from modelscope.outputs import OutputKeys
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.utils.demo_utils import DemoCompatibilityCheck
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from modelscope.utils.logger import get_logger
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from modelscope.utils.test_utils import test_level
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import tensorflow as tf # isort:skip
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logger = get_logger()
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class TextToSpeechSambertHifigan16kPipelineTest(unittest.TestCase,
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DemoCompatibilityCheck):
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def setUp(self) -> None:
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self.task = Tasks.text_to_speech
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self.zhcn_text = '今天北京天气怎么样'
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self.en_text = 'How is the weather in Beijing?'
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self.zhcn_voices = [
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'zhitian_emo', 'zhizhe_emo', 'zhiyan_emo', 'zhibei_emo', 'zhcn'
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]
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self.zhcn_models = [
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'damo/speech_sambert-hifigan_tts_zhitian_emo_zh-cn_16k',
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'damo/speech_sambert-hifigan_tts_zhizhe_emo_zh-cn_16k',
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'damo/speech_sambert-hifigan_tts_zhiyan_emo_zh-cn_16k',
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'damo/speech_sambert-hifigan_tts_zhibei_emo_zh-cn_16k',
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'damo/speech_sambert-hifigan_tts_zh-cn_16k'
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]
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self.en_voices = ['luca', 'luna', 'andy', 'annie', 'engb', 'enus']
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self.en_models = [
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'damo/speech_sambert-hifigan_tts_luca_en-gb_16k',
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'damo/speech_sambert-hifigan_tts_luna_en-gb_16k',
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'damo/speech_sambert-hifigan_tts_andy_en-us_16k',
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'damo/speech_sambert-hifigan_tts_annie_en-us_16k',
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'damo/speech_sambert-hifigan_tts_en-gb_16k',
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'damo/speech_sambert-hifigan_tts_en-us_16k'
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]
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_pipeline(self):
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for i in range(len(self.zhcn_voices)):
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logger.info('test %s' % self.zhcn_voices[i])
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model = Model.from_pretrained(
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model_name_or_path=self.zhcn_models[i], revision='pytorch_am')
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sambert_hifigan_tts = pipeline(task=self.task, model=model)
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self.assertTrue(sambert_hifigan_tts is not None)
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output = sambert_hifigan_tts(input=self.zhcn_text)
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self.assertIsNotNone(output[OutputKeys.OUTPUT_PCM])
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pcm = output[OutputKeys.OUTPUT_PCM]
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write('output_%s.wav' % self.zhcn_voices[i], 16000, pcm)
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for i in range(len(self.en_voices)):
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logger.info('test %s' % self.en_voices[i])
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model = Model.from_pretrained(
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model_name_or_path=self.en_models[i], revision='pytorch_am')
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sambert_hifigan_tts = pipeline(task=self.task, model=model)
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self.assertTrue(sambert_hifigan_tts is not None)
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output = sambert_hifigan_tts(input=self.en_text)
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self.assertIsNotNone(output[OutputKeys.OUTPUT_PCM])
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pcm = output[OutputKeys.OUTPUT_PCM]
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write('output_%s.wav' % self.en_voices[i], 16000, pcm)
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@unittest.skip('demo compatibility test is only enabled on a needed-basis')
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def test_demo_compatibility(self):
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self.compatibility_check()
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if __name__ == '__main__':
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unittest.main()
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