gpytorch/models/approximate_gp.py

Killed 6 out of 11 mutants

Survived

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

Mutant 95

--- gpytorch/models/approximate_gp.py
+++ gpytorch/models/approximate_gp.py
@@ -49,7 +49,7 @@
     def forward(self, x):
         raise NotImplementedError
 
-    def pyro_guide(self, input, beta=1.0, name_prefix=""):
+    def pyro_guide(self, input, beta=2.0, name_prefix=""):
         r"""
         (For Pyro integration only). The component of a `pyro.guide` that
         corresponds to drawing samples from the latent GP function.

Mutant 96

--- gpytorch/models/approximate_gp.py
+++ gpytorch/models/approximate_gp.py
@@ -49,7 +49,7 @@
     def forward(self, x):
         raise NotImplementedError
 
-    def pyro_guide(self, input, beta=1.0, name_prefix=""):
+    def pyro_guide(self, input, beta=1.0, name_prefix="XXXX"):
         r"""
         (For Pyro integration only). The component of a `pyro.guide` that
         corresponds to drawing samples from the latent GP function.

Mutant 97

--- gpytorch/models/approximate_gp.py
+++ gpytorch/models/approximate_gp.py
@@ -61,7 +61,7 @@
         """
         return super().pyro_guide(input, beta=beta, name_prefix=name_prefix)
 
-    def pyro_model(self, input, beta=1.0, name_prefix=""):
+    def pyro_model(self, input, beta=2.0, name_prefix=""):
         r"""
         (For Pyro integration only). The component of a `pyro.model` that
         corresponds to drawing samples from the latent GP function.

Mutant 98

--- gpytorch/models/approximate_gp.py
+++ gpytorch/models/approximate_gp.py
@@ -61,7 +61,7 @@
         """
         return super().pyro_guide(input, beta=beta, name_prefix=name_prefix)
 
-    def pyro_model(self, input, beta=1.0, name_prefix=""):
+    def pyro_model(self, input, beta=1.0, name_prefix="XXXX"):
         r"""
         (For Pyro integration only). The component of a `pyro.model` that
         corresponds to drawing samples from the latent GP function.

Mutant 102

--- gpytorch/models/approximate_gp.py
+++ gpytorch/models/approximate_gp.py
@@ -77,6 +77,6 @@
 
     def __call__(self, inputs, prior=False, **kwargs):
         if inputs.dim() == 1:
-            inputs = inputs.unsqueeze(-1)
+            inputs = inputs.unsqueeze(+1)
         return self.variational_strategy(inputs, prior=prior)