Inference code about dccrn HOT 4 CLOSED

def audiowrite(destpath, audio, sample_rate):
    '''Function to write audio'''
    import soundfile as sf
    destpath = os.path.abspath(destpath)
    destdir = os.path.dirname(destpath)

    if not os.path.exists(destdir):
        os.makedirs(destdir)

    sf.write(destpath, audio, sample_rate)
    return

def predict_torchmodel(model, noisy_path, save_path):
    assert os.path.exists(noisy_path), "noisy path error:" + noisy_path
    noisy_wave, frq = sf.read(noisy_path)
    assert frq == 16000, "sample rate must equal 16000"
    with torch.no_grad():
        net_inp = torch.tensor(noisy_wave)[None].to(torch.float32)
        estimate = model.istft(model(net_inp)).squeeze(1).cpu().data.numpy().flatten()
        audiowrite(save_path, estimate, frq)

def predict_torchmodel(model, noisy_path, save_path):
    assert os.path.exists(noisy_path), "noisy path error:" + noisy_path
    noisy_wave, frq = sf.read(noisy_path)
    assert frq == 16000, "sample rate must equal 16000"
    with torch.no_grad():
        net_inp = torch.tensor(noisy_wave)[None].to(torch.float32)
        estimate = model(net_inp).squeeze(1).cpu().data.numpy().flatten()
        audiowrite(save_path, estimate, frq)