我尝试使用pymc3来估计广义逆高斯分布（GIG）的参数，其中涉及贝塞尔函数（来自scipy.special）。bessel函数的输入应该是数组，而alpha，beta，gamma是pymc3类。如何获得scipy. special函数以pymc3 RV作为输入？运行下面附加的代码会产生错误

import pymc3 as pm
from scipy.special import hankel
import numpy as np

def gig(x, a, b, p):
    # c = p, is the order
    kp = special.hankel1e(p, x)
    y1 = ((a / b) ** (p / 2)) / (2 * kp * np.sqrt(a * b))
    y2 = (x ** (p - 1)) * np.exp(-(a * x + b / x) / 2)
    y = y1 * y2
    return y

with pm.Model() as gig_model:
    alpha = pm.Gamma('alpha', alpha=0.5, beta=2)
    beta = pm.Gamma('beta', alpha=0.5, beta=2)
    gamma = pm.Gamma('gamma', alpha=0.5, beta=2)
    
    def giglogp(x):
        lp = np.log(GIG(x, alpha, beta, gamma))
        return lp
        
    # likelihood
    Like = pm.DensityDist('likelihood', giglogp, observed=dt)

TypeError: ufunc 'hankel1e' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''