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import sys,os
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import numpy as np
import argparse
import torch
import random
from tqdm import tqdm
from whisper.model import Whisper, ModelDimensions
from whisper.audio import load_audio, pad_or_trim, log_mel_spectrogram
def load_model(path) -> Whisper:
device = "cuda" if torch.cuda.is_available() else "cpu"
checkpoint = torch.load(path, map_location="cpu")
dims = ModelDimensions(**checkpoint["dims"])
print(dims)
model = Whisper(dims)
del model.decoder
cut = len(model.encoder.blocks) // 4
cut = -1 * cut
del model.encoder.blocks[cut:]
model.load_state_dict(checkpoint["model_state_dict"], strict=False)
model.eval()
model.half()
model.to(device)
return model
def pred_ppg(whisper: Whisper, wavPath, ppgPath):
audio = load_audio(wavPath)
audln = audio.shape[0]
ppgln = audln // 320
audio = pad_or_trim(audio)
mel = log_mel_spectrogram(audio).half().to(whisper.device)
with torch.no_grad():
ppg = whisper.encoder(mel.unsqueeze(0)).squeeze().data.cpu().float().numpy()
ppg = ppg[:ppgln,] # [length, dim=1280]
# print(ppg.shape)
np.save(ppgPath, ppg, allow_pickle=False)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-w", "--wav", help="wav", dest="wav", required=True)
parser.add_argument("-p", "--ppg", help="ppg", dest="ppg", required=True)
args = parser.parse_args()
print(args.wav)
print(args.ppg)
os.makedirs(args.ppg, exist_ok=True)
wavPath = args.wav
ppgPath = args.ppg
whisper = load_model(os.path.join("whisper_pretrain", "large-v2.pt"))
spkPaths = os.listdir(wavPath)
random.shuffle(spkPaths)
for spks in spkPaths:
if os.path.isdir(f"./{wavPath}/{spks}"):
os.makedirs(f"./{ppgPath}/{spks}", exist_ok=True)
files = [f for f in os.listdir(f"./{wavPath}/{spks}") if f.endswith(".wav")]
for file in tqdm(files, desc=f'Processing ppg {spks}'):
if file.endswith(".wav"):
# print(file)
file = file[:-4]
path_wav = f"{wavPath}/{spks}/{file}.wav"
path_ppg = f"{ppgPath}/{spks}/{file}.ppg"
if os.path.isfile(f"{path_ppg}.npy"):
continue
pred_ppg(whisper, path_wav, path_ppg)
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