gpytorch/variational/lmc_variational_strategy.py

Killed 1 out of 6 mutants

Survived

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

Mutant 550

--- gpytorch/variational/lmc_variational_strategy.py
+++ gpytorch/variational/lmc_variational_strategy.py
@@ -78,7 +78,7 @@
     """
 
     def __init__(
-        self, base_variational_strategy, num_tasks, num_latents=1, latent_dim=0,
+        self, base_variational_strategy, num_tasks, num_latents=2, latent_dim=0,
     ):
         Module.__init__(self)
         self.base_variational_strategy = base_variational_strategy

Mutant 552

--- gpytorch/variational/lmc_variational_strategy.py
+++ gpytorch/variational/lmc_variational_strategy.py
@@ -105,7 +105,6 @@
         lmc_coefficients = torch.randn(*batch_shape, self.num_tasks)
         self.register_parameter("lmc_coefficients", torch.nn.Parameter(lmc_coefficients))
 
-    @property
     def prior_distribution(self):
         return self.base_variational_strategy.prior_distribution

Mutant 553

--- gpytorch/variational/lmc_variational_strategy.py
+++ gpytorch/variational/lmc_variational_strategy.py
@@ -109,7 +109,6 @@
     def prior_distribution(self):
         return self.base_variational_strategy.prior_distribution
 
-    @property
     def variational_distribution(self):
         return self.base_variational_strategy.variational_distribution

Mutant 554

--- gpytorch/variational/lmc_variational_strategy.py
+++ gpytorch/variational/lmc_variational_strategy.py
@@ -113,7 +113,6 @@
     def variational_distribution(self):
         return self.base_variational_strategy.variational_distribution
 
-    @property
     def variational_params_initialized(self):
         return self.base_variational_strategy.variational_params_initialized

Mutant 555

--- gpytorch/variational/lmc_variational_strategy.py
+++ gpytorch/variational/lmc_variational_strategy.py
@@ -120,7 +120,7 @@
     def kl_divergence(self):
         return super().kl_divergence().sum(dim=self.latent_dim)
 
-    def __call__(self, x, prior=False):
+    def __call__(self, x, prior=True):
         function_dist = self.base_variational_strategy(x, prior=prior)
         lmc_coefficients = self.lmc_coefficients.expand(*function_dist.batch_shape, self.lmc_coefficients.size(-1))
         num_batch = len(function_dist.batch_shape)