[TTS]add fastspeech2 cnndecoder onnx model #1712
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lym0302
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Apr 19, 2022
| full_name = args.am | ||
| elif filed == 'voc': | ||
| full_name = args.voc | ||
| model_dir = str(Path(args.inference_dir) / (full_name + ".onnx")) |
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感觉共用的函数里面用args不是很好，传具体的参数会不会更好，因为万一有的args没有这个参数或者参数名字不一样就不好用。很多共用的函数都用的args
| get_spk_id = True | ||
| spk_id = np.array([args.spk_id]) | ||
| if args.lang == 'zh': | ||
| input_ids = frontend.get_input_ids( |
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感觉 frontend 的相关功能新建一个函数会跟好，更清晰一些，并且单独也可以用
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| # streaming am | ||
| def get_streaming_am_predictor(args): |
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这里需不需要标注下针对的是astspeech2_cnndecoder模型
| return normalized_mel | ||
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| def get_sess(args, filed='am'): |
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这里注释下是onnx推理吧，清晰些。下面是onnx的都可以注释一下
| description="Paddle Infernce with acoustic model & vocoder.") | ||
| # acoustic model | ||
| parser.add_argument( | ||
| '--am', |
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流式am的模型还是写明是fastspeech2_cnndecoder感觉更好
| parser.add_argument( | ||
| '--am', | ||
| type=str, | ||
| default='fastspeech2_csmsc', |
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支持流式am的模型都换成fastspeech2_cnndecoder吧，免得有点混乱
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这个不行，因为现在模型的命名方式是类似于 fastspeech2_csmsc_am_decoder.onnx，我注释歇写清楚一点吧
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