29 lines
977 B
Python
29 lines
977 B
Python
import torch
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from vencoder.encoder import SpeechEncoder
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from vencoder.hubert import hubert_model
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class HubertSoft(SpeechEncoder):
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def __init__(self, vec_path="pretrain/hubert-soft-0d54a1f4.pt", device=None):
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super().__init__()
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print("load model(s) from {}".format(vec_path))
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hubert_soft = hubert_model.hubert_soft(vec_path)
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if device is None:
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self.dev = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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else:
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self.dev = torch.device(device)
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self.hidden_dim = 256
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self.model = hubert_soft.to(self.dev)
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def encoder(self, wav):
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feats = wav
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if feats.dim() == 2: # double channels
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feats = feats.mean(-1)
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assert feats.dim() == 1, feats.dim()
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feats = feats[None,None,:]
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with torch.no_grad():
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with torch.inference_mode():
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units = self.model.units(feats)
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return units.transpose(1,2)
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