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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 prior_const(C, alpha=0.001):
 r"""Constant prior for given count matrix. Parameters C : (M, M) ndarray or scipy.sparse matrix Count matrix alpha : float (optional) Value of prior counts Returns ------- B : (M, M) ndarray Prior count matrix Notes ----- The prior is defined as .. math:: \begin{array}{rl} b_{ij}= \alpha & \forall i, j \end{array} Examples -------- array([[ 0.001, 0.001, 0.001], [ 0.001, 0.001, 0.001], [ 0.001, 0.001, 0.001]]) """

    if isdense(C):
        return sparse.prior.prior_const(C, alpha=alpha)
    else:
        warnings.warn("Prior will be a dense matrix for sparse input")
        return sparse.prior.prior_const(C, alpha=alpha)