def normalize(data, mean, std):
    # transforms.ToTensor, transforms.Normalize的numpy 实现
    if not isinstance(mean, np.ndarray):
        mean = np.array(mean)
    if not isinstance(std, np.ndarray):
        std = np.array(std)
    if mean.ndim == 1:
        mean = np.reshape(mean, (-1, 1, 1))
    if std.ndim == 1:
        std = np.reshape(std, (-1, 1, 1))
    _max = np.max(abs(data))
    _div = np.divide(data, _max)  # i.e. _div = data / _max
    _sub = np.subtract(_div, mean)  # i.e. arrays = _div - mean
    arrays = np.divide(_sub, std)  # i.e. arrays = (_div - mean) / std
    arrays = np.transpose(arrays, (2, 0, 1))
    return arrays