fix potentials in inference

Author: ferrine

pymc3/tests/test_variational_inference.py

@@ -324,6 +324,7 @@ def test_init_from_noize(self):
 
 _model = models.simple_model()[1]
 with _model:
+    pm.Potential('pot', tt.ones((10, 10)))
     _advi = ADVI()
     _fullrank_advi = FullRankADVI()
     _svgd = SVGD()

pymc3/variational/opvi.py

@@ -270,14 +270,17 @@ def __init__(self, approx):
     input = property(lambda self: self.approx.flat_view.input)
 
     def logp(self, z):
-        factors = [tt.sum(var.logpt)for var in self.model.basic_RVs + self.model.potentials]
+        factors = ([tt.sum(var.logpt)for var in self.model.basic_RVs] +
+                   [tt.sum(var) for var in self.model.potentials])
+
         p = self.approx.to_flat_input(tt.add(*factors))
         p = theano.clone(p, {self.input: z})
         return p
 
     def logp_norm(self, z):
         t = self.approx.normalizing_constant
-        factors = [tt.sum(var.logpt) / t for var in self.model.basic_RVs + self.model.potentials]
+        factors = ([tt.sum(var.logpt) / t for var in self.model.basic_RVs] +
+                   [tt.sum(var) / t for var in self.model.potentials])
         logpt = tt.add(*factors)
         p = self.approx.to_flat_input(logpt)
         p = theano.clone(p, {self.input: z})