xseq = [-2, 2]
shared_N.set_value(np.array(xseq))
with m5_5_draft:
    m5_5_draft_prior_predictive = pm.sample_prior_predictive()

> Sampling: [K, a, bN, sigma]
> ---------------------------------------------------------------------------
> ValueError                                Traceback (most recent call last)
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\compile\function\types.py:971, in Function.__call__(self, *args, **kwargs)
>     969 try:
>     970     outputs = (
> --> 971         self.vm()
>     972         if output_subset is None
>     973         else self.vm(output_subset=output_subset)
>     974     )
>     975 except Exception:
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\graph\op.py:543, in Op.make_py_thunk.<locals>.rval(p, i, o, n, params)
>     539 @is_thunk_type
>     540 def rval(
>     541     p=p, i=node_input_storage, o=node_output_storage, n=node, params=None
>     542 ):
> --> 543     r = p(n, [x[0] for x in i], o)
>     544     for o in node.outputs:
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\tensor\random\op.py:368, in RandomVariable.perform(self, node, inputs, outputs)
>     366 rng_var_out[0] = rng
> --> 368 smpl_val = self.rng_fn(rng, *(args + [size]))
>     370 if (
>     371     not isinstance(smpl_val, np.ndarray)
>     372     or str(smpl_val.dtype) != out_var.type.dtype
>     373 ):
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\tensor\random\op.py:166, in RandomVariable.rng_fn(self, rng, *args, **kwargs)
>     165 """Sample a numeric random variate."""
> --> 166 return getattr(rng, self.name)(*args, **kwargs)
> 
> File _generator.pyx:1220, in numpy.random._generator.Generator.normal()
> 
> File _common.pyx:600, in numpy.random._common.cont()
> 
> File _common.pyx:517, in numpy.random._common.cont_broadcast_2()
> 
> File __init__.cython-30.pxd:780, in numpy.PyArray_MultiIterNew3()
> 
> ValueError: shape mismatch: objects cannot be broadcast to a single shape.  Mismatch is between arg 0 with shape (17,) and arg 1 with shape (2,).
> 
> During handling of the above exception, another exception occurred:
> 
> ValueError                                Traceback (most recent call last)
> Cell In[54], line 4
>       2 shared_N.set_value(np.array(xseq))
>       3 with m5_5_draft:
> ----> 4     m5_5_draft_prior_predictive = pm.sample_prior_predictive()
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\pymc\sampling.py:2169, in sample_prior_predictive(samples, model, var_names, random_seed, return_inferencedata, idata_kwargs, compile_kwargs)
>    2167 # All model variables have a name, but mypy does not know this
>    2168 _log.info(f"Sampling: {list(sorted(volatile_basic_rvs, key=lambda var: var.name))}")  # type: ignore
> -> 2169 values = zip(*(sampler_fn() for i in range(samples)))
>    2171 data = {k: np.stack(v) for k, v in zip(names, values)}
>    2172 if data is None:
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\pymc\sampling.py:2169, in <genexpr>(.0)
>    2167 # All model variables have a name, but mypy does not know this
>    2168 _log.info(f"Sampling: {list(sorted(volatile_basic_rvs, key=lambda var: var.name))}")  # type: ignore
> -> 2169 values = zip(*(sampler_fn() for i in range(samples)))
>    2171 data = {k: np.stack(v) for k, v in zip(names, values)}
>    2172 if data is None:
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\compile\function\types.py:984, in Function.__call__(self, *args, **kwargs)
>     982     if hasattr(self.vm, "thunks"):
>     983         thunk = self.vm.thunks[self.vm.position_of_error]
> --> 984     raise_with_op(
>     985         self.maker.fgraph,
>     986         node=self.vm.nodes[self.vm.position_of_error],
>     987         thunk=thunk,
>     988         storage_map=getattr(self.vm, "storage_map", None),
>     989     )
>     990 else:
>     991     # old-style linkers raise their own exceptions
>     992     raise
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\link\utils.py:534, in raise_with_op(fgraph, node, thunk, exc_info, storage_map)
>     529     warnings.warn(
>     530         f"{exc_type} error does not allow us to add an extra error message"
>     531     )
>     532     # Some exception need extra parameter in inputs. So forget the
>     533     # extra long error message in that case.
> --> 534 raise exc_value.with_traceback(exc_trace)
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\compile\function\types.py:971, in Function.__call__(self, *args, **kwargs)
>     968 t0_fn = time.time()
>     969 try:
>     970     outputs = (
> --> 971         self.vm()
>     972         if output_subset is None
>     973         else self.vm(output_subset=output_subset)
>     974     )
>     975 except Exception:
>     976     restore_defaults()
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\graph\op.py:543, in Op.make_py_thunk.<locals>.rval(p, i, o, n, params)
>     539 @is_thunk_type
>     540 def rval(
>     541     p=p, i=node_input_storage, o=node_output_storage, n=node, params=None
>     542 ):
> --> 543     r = p(n, [x[0] for x in i], o)
>     544     for o in node.outputs:
>     545         compute_map[o][0] = True
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\tensor\random\op.py:368, in RandomVariable.perform(self, node, inputs, outputs)
>     364     rng = copy(rng)
>     366 rng_var_out[0] = rng
> --> 368 smpl_val = self.rng_fn(rng, *(args + [size]))
>     370 if (
>     371     not isinstance(smpl_val, np.ndarray)
>     372     or str(smpl_val.dtype) != out_var.type.dtype
>     373 ):
>     374     smpl_val = _asarray(smpl_val, dtype=out_var.type.dtype)
> 
> File ~\anaconda3\envs\stat-rethink2-pymc_v4\lib\site-packages\aesara\tensor\random\op.py:166, in RandomVariable.rng_fn(self, rng, *args, **kwargs)
>     164 def rng_fn(self, rng, *args, **kwargs):
>     165     """Sample a numeric random variate."""
> --> 166     return getattr(rng, self.name)(*args, **kwargs)
> 
> File _generator.pyx:1220, in numpy.random._generator.Generator.normal()
> 
> File _common.pyx:600, in numpy.random._common.cont()
> 
> File _common.pyx:517, in numpy.random._common.cont_broadcast_2()
> 
> File __init__.cython-30.pxd:780, in numpy.PyArray_MultiIterNew3()


> ValueError: shape mismatch: objects cannot be broadcast to a single shape.  Mismatch is between arg 0 with shape (17,) and arg 1 with shape (2,).
> Apply node that caused the error: normal_rv{0, (0, 0), floatX, True}(RandomGeneratorSharedVariable(<Generator(PCG64) at 0x27DC19E8E40>), TensorConstant{(1,) of 17}, TensorConstant{11}, mu, sigma)
> Toposort index: 6
> Inputs types: [RandomGeneratorType, TensorType(int64, (1,)), TensorType(int64, ()), TensorType(float64, (None,)), TensorType(float64, ())]
> Inputs shapes: ['No shapes', (1,), (), (2,), ()]
> Inputs strides: ['No strides', (8,), (), (8,), ()]
> Inputs values: [Generator(PCG64) at 0x27DC19E8E40, array([17], dtype=int64), array(11, dtype=int64), array([ 1.14271312, -4.0934738 ]), array(0.8151317)]
> Outputs clients: [['output'], ['output']]
> 
> HINT: Re-running with most Aesara optimizations disabled could provide a back-trace showing when this node was created. This can be done by setting the Aesara flag 'optimizer=fast_compile'. If that does not work, Aesara optimizations can be disabled with 'optimizer=None'.
> HINT: Use the Aesara flag `exception_verbosity=high` for a debug print-out and storage map footprint of this Apply node.