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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 subsample_n(X, n=0, seed=0):
 """Subsample n samples from rows of array. Parameters X : np.ndarray Data array. seed : int Seed for sampling. Returns ------- Xsampled : np.ndarray Subsampled X. rows : np.ndarray Indices of rows that are stored in Xsampled. """

    if n < 0:
        raise ValueError('n must be greater 0')
    np.random.seed(seed)
    n = X.shape[0] if (n == 0 or n > X.shape[0]) else n
    rows = np.random.choice(X.shape[0], size=n, replace=False)
    Xsampled = X[rows]
    return Xsampled, rows