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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def vector_norm(data, axis=None, out=None):
 """Return length, i.e. Euclidean norm, of ndarray along axis. True True True True 0.0 1.0 """

    data = np.array(data, dtype=np.float64, copy=True)
    if out is None:
        if data.ndim == 1:
            return math.sqrt(np.dot(data, data))
        data *= data
        out = np.atleast_1d(np.sum(data, axis=axis))
        np.sqrt(out, out)
        return out
    else:
        data *= data
        np.sum(data, axis=axis, out=out)
        np.sqrt(out, out)