24 lines
688 B
Python
24 lines
688 B
Python
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import torch
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def get_model():
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import whisper
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model = whisper.load_model("small", device="cpu")
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return model.encoder
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def get_content(model=None, wav_16k_tensor=None):
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from whisper import log_mel_spectrogram, pad_or_trim
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dev = next(model.parameters()).device
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mel = log_mel_spectrogram(wav_16k_tensor).to(dev)[:, :3000]
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# if torch.cuda.is_available():
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# mel = mel.to(torch.float16)
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feature_len = mel.shape[-1] // 2
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assert mel.shape[-1] < 3000, "输入音频过长，只允许输入30以内音频"
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with torch.no_grad():
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feature = model(pad_or_trim(mel, 3000).unsqueeze(0))[:1, :feature_len, :].transpose(1, 2)
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return feature
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