I am having trouble implementing Normal distribution with mu that is a shared va…riable. See below example code:
**Please provide a minimal, self-contained, and reproducible example.**
```python
product_mu_shared = shared(0.0)
product_sd = 0.1
total_quantity_shared = shared(np.array([0.0, 0.1, 0.2]))
with pm.Model() as quantity_model:
# Priors
a = pm.Lognormal('a',mu=product_mu_shared, sd=product_sd)
b = pm.Normal('b',mu=0.0, sd=product_sd)
d = pm.Normal('d', mu=product_mu_shared, sd=product_sd)
# Data likelihood
vol = pm.Normal('vol',mu= a+b+d, observed=total_quantity_shared)
# Inference
trace = pm.sample(10,tune=10)
```
**Please provide the full traceback.**
```python
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-6-6131815c61f7> in <module>()
4 a = pm.Lognormal('a',mu=product_mu_shared, sd=product_sd)
5 b = pm.Normal('b',mu=0.0, sd=product_sd)
----> 6 d = pm.Normal('d', mu=product_mu_shared, sd=product_sd)
7
8
C:\ProgramData\Anaconda3\lib\site-packages\pymc3\distributions\distribution.py in __new__(cls, name, *args, **kwargs)
40 total_size = kwargs.pop('total_size', None)
41 dist = cls.dist(*args, **kwargs)
---> 42 return model.Var(name, dist, data, total_size)
43 else:
44 raise TypeError("Name needs to be a string but got: {}".format(name))
C:\ProgramData\Anaconda3\lib\site-packages\pymc3\model.py in Var(self, name, dist, data, total_size)
806 with self:
807 var = FreeRV(name=name, distribution=dist,
--> 808 total_size=total_size, model=self)
809 self.free_RVs.append(var)
810 else:
C:\ProgramData\Anaconda3\lib\site-packages\pymc3\model.py in __init__(self, type, owner, index, name, distribution, total_size, model)
1205 self.distribution = distribution
1206 self.tag.test_value = np.ones(
-> 1207 distribution.shape, distribution.dtype) * distribution.default()
1208 self.logp_elemwiset = distribution.logp(self)
1209 # The logp might need scaling in minibatches.
C:\ProgramData\Anaconda3\lib\site-packages\pymc3\distributions\distribution.py in default(self)
65
66 def default(self):
---> 67 return np.asarray(self.get_test_val(self.testval, self.defaults), self.dtype)
68
69 def get_test_val(self, val, defaults):
C:\ProgramData\Anaconda3\lib\site-packages\pymc3\distributions\distribution.py in get_test_val(self, val, defaults)
70 if val is None:
71 for v in defaults:
---> 72 if hasattr(self, v) and np.all(np.isfinite(self.getattr_value(v))):
73 return self.getattr_value(v)
74 else:
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''```
**Please provide any additional information below.**
## Versions and main components
* PyMC3 Version: 3.5
* Theano Version: 1.0.2
* Python Version: 3.6
* Operating system: Windows 10
* How did you install PyMC3: (conda/pip) conda-forge