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Added support for npy output from tune-wavegrad
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@@ -37,8 +37,13 @@ def tts(model, vocoder_model, text, CONFIG, use_cuda, ap, use_gl, speaker_fileid
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if CONFIG.model == "Tacotron" and not use_gl:
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mel_postnet_spec = ap.out_linear_to_mel(mel_postnet_spec.T).T
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if not use_gl:
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# Use if not computed noise schedule with tune_wavegrad
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beta = np.linspace(1e-6, 0.01, 50)
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vocoder_model.compute_noise_level(beta)
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# Use alternative when using output npy file from tune_wavegrad
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# beta = np.load("output-tune-wavegrad.npy", allow_pickle=True).item()
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# vocoder_model.compute_noise_level(beta['beta'])
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device_type = "cuda" if use_cuda else "cpu"
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waveform = vocoder_model.inference(torch.FloatTensor(mel_postnet_spec.T).to(device_type).unsqueeze(0))
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