X = np.random.normal(size=(1000, 10))
w = np.random.normal(size=10)
y = X.dot(w) + np.random.normal(scale=0.1, size=1000)
with linear_model(X=X, y=y):
sampled_coefs = pm.sample(draws=1000, tune=500)
Traceback (most recent call last):
File "<ipython-input-9-2012d7efa2d1>", line 5, in <module>
with linear_model(X=X, y=y):
File "/home/vr308/anaconda3/lib/python3.6/site-packages/sampled/sampled.py", line 20, in wrapped_f
with ObserverModel(observed) as model:
File "/home/vr308/anaconda3/lib/python3.6/site-packages/pymc3/model.py", line 274, in __call__
instance = cls.__new__(cls, *args, **kwargs)
File "/home/vr308/anaconda3/lib/python3.6/site-packages/pymc3/model.py", line 739, in __new__
instance._parent = cls.get_context(error_if_none=False)
File "/home/vr308/anaconda3/lib/python3.6/site-packages/pymc3/model.py", line 213, in get_context
candidate = cls.get_contexts()[idx] # type: Optional[T]
File "/home/vr308/anaconda3/lib/python3.6/site-packages/pymc3/model.py", line 234, in get_contexts
context_class = cls.context_class
File "/home/vr308/anaconda3/lib/python3.6/site-packages/pymc3/model.py", line 260, in context_class
cls._context_class = resolve_type(cls._context_class)
File "/home/vr308/anaconda3/lib/python3.6/site-packages/pymc3/model.py", line 254, in resolve_type
c = getattr(modules[cls.__module__], c)
AttributeError: module 'sampled.sampled' has no attribute 'Model'
I have been using this deocrator to run the same generative model on datasets of different size but now it suddenly throws the error :
AttributeError: module 'sampled.sampled' has no attribute 'Model'
Can reproduce it with your example:
pymc3 version 3.8