Cosmetics

demos/meanfield_inference.py

@@ -56,7 +56,8 @@ if __name__ == "__main__":
 
     fc = ift.FullCovarianceVI(position_fc, H, 3, True, initial_sig=0.01)
     mf = ift.MeanFieldVI(position_mf, H, 3, True, initial_sig=0.01)
-    IC = ift.StochasticAbsDeltaEnergyController(10,iteration_limit=1000, name='optimizer')
+    IC = ift.StochasticAbsDeltaEnergyController(10, iteration_limit=1000,
+                                                name='advi')
     minimizer_fc = ift.ADVIOptimizer(IC, eta=0.1)
     minimizer_mf = ift.ADVIOptimizer(IC)
 

src/library/variational_models.py

@@ -139,8 +139,8 @@ class FullCovarianceVI:
         pos = MultiField.from_dict(
                 {'mean': Flat(position),
                  'cov': LT.adjoint(makeField(mat_space, diag_tri))})
-        self._op = hamiltonian(self._generator) + self._entropy
-        self._KL = StochasticEnergyAdapter.make(pos, self._op, ['latent',], n_samples,
+        op = hamiltonian(self._generator) + self._entropy
+        self._KL = StochasticEnergyAdapter.make(pos, op, ['latent',], n_samples,
                                     mirror_samples, nanisinf=nanisinf, comm=comm)
         self._mean = Flat.adjoint @ mean
         self._samdom = lat.domain

src/minimization/iteration_controllers.py

@@ -422,8 +422,9 @@ class AbsDeltaEnergyController(IterationController):
 
         return self.CONTINUE
 
+
 class StochasticAbsDeltaEnergyController(IterationController):
-    """An iteration controller checking the standard deviation over a 
+    """An iteration controller checking the standard deviation over a
      period of iterations. Convergence is reported once this quantity
      falls below the given threshold
 

src/minimization/stochastic_minimizer.py

@@ -48,7 +48,6 @@ class ADVIOptimizer(Minimizer):
         self.epsilon = epsilon
         self.counter = 1
         self._controller = controller
-        # self.steps = steps
         self.s = None
         self.resample = resample