syne_tune/optimizer/schedulers/searchers/bayesopt/gpautograd/learncurve/issm.py [427:440]:
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            if ydim < num_res:
                lrvec = anp.array(
                    [np.log(r) for r in range(r_obs, r_max + 1)]) *\
                        alpha_m1 + beta
                c_scal = alpha * anp.exp(logsumexp(lrvec))
                d_scal = anp.square(gamma * alpha) * anp.exp(
                    logsumexp(lrvec * 2.0))
                c_lst.append(c_scal)
                d_lst.append(d_scal)
            else:
                c_lst.append(0.0)
                d_lst.append(0.0)
        if profiler is not None:
            profiler.stop('issm_part1')
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syne_tune/optimizer/schedulers/searchers/bayesopt/gpautograd/learncurve/issm.py [887:901]:
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            if ydim < num_res:
                lrvec = anp.array(
                    [np.log(r) for r in range(r_obs, r_max + 1)]) *\
                        alpha_m1 + beta
                c_scal = alpha * anp.exp(logsumexp(lrvec))
                d_scal = anp.square(gamma * alpha) * anp.exp(
                    logsumexp(lrvec * 2.0))
                c_lst.append(c_scal)
                d_lst.append(d_scal)
            else:
                c_lst.append(0.0)
                d_lst.append(0.0)
        # Inner loop for v_i, w_i
        if profiler is not None:
            profiler.stop('issm_part1')
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