mirror of
https://github.com/modelscope/modelscope.git
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113 lines
4.2 KiB
Python
113 lines
4.2 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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# Putting a 'import torch' here can bypass this incompatibility.
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import torch
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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.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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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.kokr_text = '오늘날씨가어때요'
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self.ru_text = 'Какая сегодня погода?'
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self.test_model_name = [
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'chuangirl', 'jiajia', 'xiaoda', 'kyong', 'masha', 'pretrain_16k',
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'pretrain_24k', 'zhitian_emo', 'zhizhe_emo', 'zhiyan_emo',
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'zhibei_emo', 'zhcn_16k', 'luca', 'luna', 'andy', 'annie',
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'engb_16k', 'enus_16k'
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]
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self.test_models = [{
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'model':
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'speech_tts/speech_sambert-hifigan_tts_chuangirl_Sichuan_16k',
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'text': self.zhcn_text
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}, {
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'model':
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'speech_tts/speech_sambert-hifigan_tts_jiajia_Cantonese_16k',
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'text': self.zhcn_text
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}, {
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'model':
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'speech_tts/speech_sambert-hifigan_tts_xiaoda_WuuShanghai_16k',
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'text': self.zhcn_text
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}, {
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'model': 'speech_tts/speech_sambert-hifigan_tts_kyong_Korean_16k',
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'text': self.kokr_text
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}, {
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'model': 'speech_tts/speech_sambert-hifigan_tts_masha_Russian_16k',
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'text': self.ru_text
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}, {
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'model':
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'speech_tts/speech_sambert-hifigan_tts_zh-cn_multisp_pretrain_16k',
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'text': self.zhcn_text
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}, {
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'model':
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'speech_tts/speech_sambert-hifigan_tts_zh-cn_multisp_pretrain_24k',
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'text': self.zhcn_text,
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_zhitian_emo_zh-cn_16k',
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'text': self.zhcn_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_zhizhe_emo_zh-cn_16k',
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'text': self.zhcn_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_zhiyan_emo_zh-cn_16k',
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'text': self.zhcn_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_zhibei_emo_zh-cn_16k',
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'text': self.zhcn_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_zh-cn_16k',
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'text': self.zhcn_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_luca_en-gb_16k',
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'text': self.en_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_luna_en-gb_16k',
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'text': self.en_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_andy_en-us_16k',
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'text': self.en_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_annie_en-us_16k',
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'text': self.en_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_en-gb_16k',
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'text': self.en_text
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}, {
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'model': 'damo/speech_sambert-hifigan_tts_en-us_16k',
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'text': self.en_text
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}]
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_pipeline(self):
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for i in range(len(self.test_models)):
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logger.info('test %s' % self.test_model_name[i])
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sambert_hifigan_tts = pipeline(
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task=self.task, model=self.test_models[i]['model'])
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self.assertTrue(sambert_hifigan_tts is not None)
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output = sambert_hifigan_tts(input=self.test_models[i]['text'])
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self.assertIsNotNone(output[OutputKeys.OUTPUT_WAV])
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wav = output[OutputKeys.OUTPUT_WAV]
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with open(f'output_{self.test_model_name[i]}', 'wb') as f:
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f.write(wav)
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if __name__ == '__main__':
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unittest.main()
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