preprocessing/hubertinfer.py

import os.path
from io import BytesIO
from pathlib import Path

import numpy as np
import torch

from network.hubert.hubert_model import hubert_soft, get_units
from network.hubert.vec_model import load_model, get_vec_units
from utils.hparams import hparams


class Hubertencoder():
    def __init__(self, pt_path=f'.checkpoints/hubert/hubert_soft.pt'):
        if not 'use_vec' in hparams.keys():
            hparams['use_vec'] = False
        if hparams['use_vec']:
            pt_path = f".checkpoints/vec/checkpoint_best_legacy_500.pt"
            self.dev = torch.device("cuda")
            self.hbt_model = load_model(pt_path)
        else:
            pt_path = list(Path(pt_path).parent.rglob('*.pt'))[0]
            if 'hubert_gpu' in hparams.keys():
                self.use_gpu = hparams['hubert_gpu']
            else:
                self.use_gpu = True
            self.dev = torch.device("cuda" if self.use_gpu and torch.cuda.is_available() else "cpu")
            self.hbt_model = hubert_soft(str(pt_path)).to(self.dev)

    def encode(self, wav_path):
        if isinstance(wav_path, BytesIO):
            npy_path = ""
            wav_path.seek(0)
        else:
            npy_path = Path(wav_path).with_suffix('.npy')
        if os.path.exists(npy_path):
            units = np.load(str(npy_path))
        elif hparams['use_vec']:
            units = get_vec_units(self.hbt_model, wav_path, self.dev).cpu().numpy()[0]
        else:
            units = get_units(self.hbt_model, wav_path, self.dev).cpu().numpy()[0]
        return units  # [T,256]