gpytorch/models/deep_gps/dspp.py

Survived

Mutant 172

--- gpytorch/models/deep_gps/dspp.py
+++ gpytorch/models/deep_gps/dspp.py
@@ -32,7 +32,7 @@
     represents a weighted mixture of `num_quad_sites` Gaussians with weights given by DSPP.quad_weights (see DSPP below)
     """
 
-    def __init__(self, variational_strategy, input_dims, output_dims, num_quad_sites=3, quad_sites=None):
+    def __init__(self, variational_strategy, input_dims, output_dims, num_quad_sites=4, quad_sites=None):
         super().__init__(variational_strategy, input_dims, output_dims)
 
         self.num_quad_sites = num_quad_sites

Mutant 173

--- gpytorch/models/deep_gps/dspp.py
+++ gpytorch/models/deep_gps/dspp.py
@@ -43,7 +43,7 @@
         else:
             self.quad_sites = torch.nn.Parameter(torch.randn(num_quad_sites, input_dims))
 
-    def __call__(self, inputs, are_samples=False, expand_for_quadgrid=True, **kwargs):
+    def __call__(self, inputs, are_samples=True, expand_for_quadgrid=True, **kwargs):
         if isinstance(inputs, MultitaskMultivariateNormal):
             # inputs is definitely in the second layer, and mean is n x t
             mus, sigmas = inputs.mean, inputs.variance.sqrt()

Mutant 174

--- gpytorch/models/deep_gps/dspp.py
+++ gpytorch/models/deep_gps/dspp.py
@@ -43,7 +43,7 @@
         else:
             self.quad_sites = torch.nn.Parameter(torch.randn(num_quad_sites, input_dims))
 
-    def __call__(self, inputs, are_samples=False, expand_for_quadgrid=True, **kwargs):
+    def __call__(self, inputs, are_samples=False, expand_for_quadgrid=False, **kwargs):
         if isinstance(inputs, MultitaskMultivariateNormal):
             # inputs is definitely in the second layer, and mean is n x t
             mus, sigmas = inputs.mean, inputs.variance.sqrt()

Mutant 175

--- gpytorch/models/deep_gps/dspp.py
+++ gpytorch/models/deep_gps/dspp.py
@@ -107,7 +107,6 @@
         self.num_quad_sites = num_quad_sites
         self.register_parameter("raw_quad_weights", torch.nn.Parameter(torch.randn(self.num_quad_sites)))
 
-    @property
     def quad_weights(self):
         qwd = self.raw_quad_weights
         return qwd - qwd.logsumexp(dim=-1)