def METHOD_NAME(feat, wav):
    """Pass a single pair of features and waveform"""
    feat = feat.numpy()
    wav = wav.numpy()
    expected_feat_shape = (batch_size, ap.num_mels, seq_len // hop_len + conv_pad * 2)
    # check shapes
    assert np.all(feat.shape == expected_feat_shape), f" [!] {feat.shape} vs {expected_feat_shape}"
    assert (feat.shape[2] - conv_pad * 2) * hop_len == wav.shape[2]
    # check feature vs audio match
    if not use_noise_augment:
        for idx in range(batch_size):
            audio = wav[idx].squeeze()
            feat = feat[idx]
            mel = ap.melspectrogram(audio)
            # the first 2 and the last 2 frames are skipped due to the padding
            # differences in stft
            max_diff = abs((feat - mel[:, : feat.shape[-1]])[:, 2:-2]).max()
            assert max_diff <= 1e-6, f" [!] {max_diff}"