pyro/infer/svgd.py

Survived

Mutant 324

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -41,7 +41,6 @@
     Abstract class for kernels used in the :class:`SVGD` inference algorithm.
     """
 
-    @abstractmethod
     def log_kernel_and_grad(self, particles):
         """
         Compute the component kernels and their gradients.

Mutant 325

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -54,8 +54,6 @@
         """
         raise NotImplementedError
 
-
-@copy_docs_from(SteinKernel)
 class RBFSteinKernel(SteinKernel):
     """
     A RBF kernel for use in the SVGD inference algorithm. The bandwidth of the kernel is chosen from the

Mutant 326

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -89,7 +89,6 @@
         assert median.shape == norm_sq.shape[-1:]
         return median / math.log(num_particles + 1)
 
-    @torch.no_grad()
     def log_kernel_and_grad(self, particles):
         delta_x = particles.unsqueeze(0) - particles.unsqueeze(1)  # N N D
         assert delta_x.dim() == 3

Mutant 328

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -104,7 +104,6 @@
     def bandwidth_factor(self):
         return self._bandwidth_factor
 
-    @bandwidth_factor.setter
     def bandwidth_factor(self, bandwidth_factor):
         """
         :param float bandwidth_factor: Optional factor by which to scale the bandwidth

Mutant 329

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -113,8 +113,6 @@
             assert bandwidth_factor > 0.0, "bandwidth_factor must be positive."
         self._bandwidth_factor = bandwidth_factor
 
-
-@copy_docs_from(SteinKernel)
 class IMQSteinKernel(SteinKernel):
     r"""
     An IMQ (inverse multi-quadratic) kernel for use in the SVGD inference algorithm [1]. The bandwidth of the kernel

Mutant 330

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -135,7 +135,7 @@
     [1] "Stein Points," Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris. J. Oates.
     [2] "Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm," Qiang Liu, Dilin Wang
     """
-    def __init__(self, alpha=0.5, beta=-0.5, bandwidth_factor=None):
+    def __init__(self, alpha=1.5, beta=-0.5, bandwidth_factor=None):
         """
         :param float alpha: Kernel hyperparameter, defaults to 0.5.
         :param float beta: Kernel hyperparameter, defaults to -0.5.

Mutant 331

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -135,7 +135,7 @@
     [1] "Stein Points," Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris. J. Oates.
     [2] "Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm," Qiang Liu, Dilin Wang
     """
-    def __init__(self, alpha=0.5, beta=-0.5, bandwidth_factor=None):
+    def __init__(self, alpha=0.5, beta=+0.5, bandwidth_factor=None):
         """
         :param float alpha: Kernel hyperparameter, defaults to 0.5.
         :param float beta: Kernel hyperparameter, defaults to -0.5.

Mutant 332

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -135,7 +135,7 @@
     [1] "Stein Points," Wilson Ye Chen, Lester Mackey, Jackson Gorham, Francois-Xavier Briol, Chris. J. Oates.
     [2] "Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm," Qiang Liu, Dilin Wang
     """
-    def __init__(self, alpha=0.5, beta=-0.5, bandwidth_factor=None):
+    def __init__(self, alpha=0.5, beta=-1.5, bandwidth_factor=None):
         """
         :param float alpha: Kernel hyperparameter, defaults to 0.5.
         :param float beta: Kernel hyperparameter, defaults to -0.5.

Mutant 333

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -160,7 +160,6 @@
         assert median.shape == norm_sq.shape[-1:]
         return median / math.log(num_particles + 1)
 
-    @torch.no_grad()
     def log_kernel_and_grad(self, particles):
         delta_x = particles.unsqueeze(0) - particles.unsqueeze(1)  # N N D
         assert delta_x.dim() == 3

Mutant 335

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -177,7 +177,6 @@
     def bandwidth_factor(self):
         return self._bandwidth_factor
 
-    @bandwidth_factor.setter
     def bandwidth_factor(self, bandwidth_factor):
         """
         :param float bandwidth_factor: Optional factor by which to scale the bandwidth

Mutant 336

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -224,7 +224,7 @@
     [2] "Kernelized Complete Conditional Stein Discrepancy,"
         Raghav Singhal, Saad Lahlou, Rajesh Ranganath
     """
-    def __init__(self, model, kernel, optim, num_particles, max_plate_nesting, mode="univariate"):
+    def __init__(self, model, kernel, optim, num_particles, max_plate_nesting, mode="XXunivariateXX"):
         assert callable(model)
         assert isinstance(kernel, SteinKernel), "Must provide a valid SteinKernel"
         assert isinstance(optim, pyro.optim.PyroOptim), "Must provide a valid Pyro optimizer"

Mutant 337

--- pyro/infer/svgd.py
+++ pyro/infer/svgd.py
@@ -250,7 +250,6 @@
         return {site["name"]: biject_to(site["fn"].support)(unconstrained_value)
                 for site, unconstrained_value in self.guide._unpack_latent(pyro.param("svgd_particles"))}
 
-    @torch.no_grad()
     def step(self, *args, **kwargs):
         """
         Computes the SVGD gradient, passing args and kwargs to the model,