gpytorch/variational/mean_field_variational_distribution.py

Killed 0 out of 2 mutants

Survived

Survived mutation testing. These mutants show holes in your test suite.

Mutant 242

--- gpytorch/variational/mean_field_variational_distribution.py
+++ gpytorch/variational/mean_field_variational_distribution.py
@@ -20,7 +20,7 @@
     :param float mean_init_std: (default=1e-3) Standard deviation of gaussian noise to add to the mean initialization.
     """
 
-    def __init__(self, num_inducing_points, batch_shape=torch.Size([]), mean_init_std=1e-3, **kwargs):
+    def __init__(self, num_inducing_points, batch_shape=torch.Size([]), mean_init_std=1.001, **kwargs):
         super().__init__(num_inducing_points=num_inducing_points, batch_shape=batch_shape, mean_init_std=mean_init_std)
         mean_init = torch.zeros(num_inducing_points)
         covar_init = torch.ones(num_inducing_points)

Mutant 243

--- gpytorch/variational/mean_field_variational_distribution.py
+++ gpytorch/variational/mean_field_variational_distribution.py
@@ -30,7 +30,6 @@
         self.register_parameter(name="variational_mean", parameter=torch.nn.Parameter(mean_init))
         self.register_parameter(name="_variational_stddev", parameter=torch.nn.Parameter(covar_init))
 
-    @property
     def variational_stddev(self):
         # TODO: if we don't multiply self._variational_stddev by a mask of one, Pyro models fail
         # not sure where this bug is occuring (in Pyro or PyTorch)