def METHOD_NAME(full_path):
    sampling_rate, data = read(full_path)
    if data.dtype == np.int32:
        norm_fix = 2**31
    elif data.dtype == np.int16:
        norm_fix = 2**15
    elif data.dtype == np.float16 or data.dtype == np.float32:
        norm_fix = 1.0
    else:
        raise NotImplementedError(f"Provided data dtype not supported: {data.dtype}")
    return (torch.FloatTensor(data.astype(np.float32)) / norm_fix, sampling_rate)