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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 _quic_path( X, path, X_test=None, lam=0.5, tol=1e-6, max_iter=1000, Theta0=None, Sigma0=None, method="quic", verbose=0, score_metric="log_likelihood", init_method="corrcoef", ):
 """Wrapper to compute path for example X. """

    S, lam_scale_ = _init_coefs(X, method=init_method)

    path = path.copy(order="C")

    if method == "quic":
        (precisions_, covariances_, opt_, cputime_, iters_, duality_gap_) = quic(
            S,
            lam,
            mode="path",
            tol=tol,
            max_iter=max_iter,
            Theta0=Theta0,
            Sigma0=Sigma0,
            path=path,
            msg=verbose,
        )
    else:
        raise NotImplementedError("Only method='quic' has been implemented.")

    if X_test is not None:
        S_test, lam_scale_test = _init_coefs(X_test, method=init_method)

        path_errors = []
        for lidx, lam in enumerate(path):
            path_errors.append(
                _compute_error(
                    S_test,
                    covariances_[lidx],
                    precisions_[lidx],
                    score_metric=score_metric,
                )
            )
        scores_ = [-e for e in path_errors]

        return covariances_, precisions_, scores_

    return covariances_, precisions_