Error in `examples/survival_analysis/weibull_aft.ipynb`

[williambdean]

The deprecated testval argument is being used.

─────────────────────────────────────────── Error running examples/survival_analysis/weibull_aft.ipynb ───────────────────────────────────────────

---------------------------------------------------------------------------
Exception encountered at "In [12]":
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[12], line 3
      1 with pm.Model() as model_2:
      2     alpha = pm.Normal("alpha", mu=0, sigma=10)
----> 3     r = pm.Gamma("r", alpha=1, beta=0.001, testval=0.25)
      4     beta = pm.Deterministic("beta", pt.exp(-alpha / r))
      6     y_obs = pm.Weibull("y_obs", alpha=r, beta=beta, observed=y[~censored])

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pymc/distributions/distribution.py:511, in Distribution.__new__(cls, name, rng,
dims, initval, observed, total_size, transform, default_transform, *args, **kwargs)
    508     elif observed is not None:
    509         kwargs["shape"] = tuple(observed.shape)
--> 511 rv_out = cls.dist(*args, **kwargs)
    513 rv_out = model.register_rv(
    514     rv_out,
    515     name,
   (...)
    521     initval=initval,
    522 )
    524 # add in pretty-printing support

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pymc/distributions/continuous.py:2371, in Gamma.dist(cls, alpha, beta, mu,
sigma, **kwargs)
   2369 # PyTensor gamma op is parametrized in terms of scale (1/beta)
   2370 scale = pt.reciprocal(beta)
-> 2371 return super().dist(, **kwargs)

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pymc/distributions/distribution.py:580, in Distribution.dist(cls, dist_params,
shape, **kwargs)
    577     ndim_supp = cls.rv_op(*dist_params, **kwargs).owner.op.ndim_supp
    579 create_size = find_size(shape=shape, size=size, ndim_supp=ndim_supp)
--> 580 rv_out = cls.rv_op(*dist_params, size=create_size, **kwargs)
    582 _add_future_warning_tag(rv_out)
    583 return rv_out

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/tensor/random/basic.py:450, in GammaRV.__call__(self, shape, scale,
size, **kwargs)
    429 def __call__(self, shape, scale, size=None, **kwargs):
    430     r"""Draw samples from a gamma distribution.
    431
    432     Signature
   (...)
    448
    449     """
--> 450     return super().__call__(shape, scale, size=size, **kwargs)

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/tensor/random/op.py:312, in RandomVariable.__call__(self, size, name,
rng, dtype, *args, **kwargs)
    310     props["dtype"] = dtype
    311     new_op = type(self)(**props)
--> 312     return new_op.__call__(
    313         *args, size=size, name=name, rng=rng, dtype=dtype, **kwargs
    314     )
    316 res = super().__call__(rng, size, *args, **kwargs)
    318 if name is not None:

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/tensor/random/basic.py:450, in GammaRV.__call__(self, shape, scale,
size, **kwargs)
    429 def __call__(self, shape, scale, size=None, **kwargs):
    430     r"""Draw samples from a gamma distribution.
    431
    432     Signature
   (...)
    448
    449     """
--> 450     return super().__call__(shape, scale, size=size, **kwargs)

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/tensor/random/op.py:316, in RandomVariable.__call__(self, size, name,
rng, dtype, *args, **kwargs)
    311     new_op = type(self)(**props)
    312     return new_op.__call__(
    313         *args, size=size, name=name, rng=rng, dtype=dtype, **kwargs
    314     )
--> 316 res = super().__call__(rng, size, *args, **kwargs)
    318 if name is not None:
    319     res.name = name

File ~/micromamba/envs/pymc-examples/lib/python3.11/site-packages/pytensor/graph/op.py:293, in Op.__call__(self, name, return_list, *inputs,
**kwargs)
    249 def __call__(
    250     self, *inputs: Any, name=None, return_list=False, **kwargs
    251 ) -> Variable | list[Variable]:
    252     r"""Construct an `Apply` node using :meth:`Op.make_node` and return its outputs.
    253
    254     This method is just a wrapper around :meth:`Op.make_node`.
   (...)
    291
    292     """
--> 293     node = self.make_node(*inputs, **kwargs)
    294     if name is not None:
    295         if len(node.outputs) == 1:

TypeError: RandomVariable.make_node() got an unexpected keyword argument 'testval'