Problem encountered while running the student-T process in example

Thanks,the whole error message is here.

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_33164/2673626657.py in <module>
     15 # The latent function values are one sample from a multivariate normal
     16 # Note that we have to call `eval()` because PyMC3 built on top of Theano
---> 17 tp_samples = pm.MvStudentT.dist(mu=mean_func(X), cov=cov_func(X), nu=3).random(size=8)
     18 
     19 ## Plot samples from TP prior

D:\program\anaconda\envs\pymc_env\lib\site-packages\pymc3\distributions\multivariate.py in random(self, point, size)
    395                 dist = MvNormal.dist(mu=np.zeros_like(mu), chol=chol, shape=self.shape)
    396 
--> 397             samples = dist.random(point, size)
    398 
    399         chi2_samples = np.random.chisquare(nu, size)

D:\program\anaconda\envs\pymc_env\lib\site-packages\pymc3\distributions\multivariate.py in random(self, point, size)
    274 
    275         mu = broadcast_dist_samples_to(to_shape=output_shape, samples=[mu], size=size)[0]
--> 276         param = np.broadcast_to(param, shape=output_shape + dist_shape[-1:])
    277 
    278         assert mu.shape == output_shape

<__array_function__ internals> in broadcast_to(*args, **kwargs)

D:\program\anaconda\envs\pymc_env\lib\site-packages\numpy\lib\stride_tricks.py in broadcast_to(array, shape, subok)
    409            [1, 2, 3]])
    410     """
--> 411     return _broadcast_to(array, shape, subok=subok, readonly=True)
    412 
    413 

D:\program\anaconda\envs\pymc_env\lib\site-packages\numpy\lib\stride_tricks.py in _broadcast_to(array, shape, subok, readonly)
    346                          'negative')
    347     extras = []
--> 348     it = np.nditer(
    349         (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
    350         op_flags=['readonly'], itershape=shape, order='C')

ValueError: input operand has more dimensions than allowed by the axis remapping