Update gaussian_likelihood.py

Author: saitcakmak

gpytorch/likelihoods/gaussian_likelihood.py

@@ -130,7 +130,7 @@ def raw_noise(self, value: Tensor) -> None:
         self.noise_covar.initialize(raw_noise=value)
 
     def marginal(self, function_dist: MultivariateNormal, *args: Any, **kwargs: Any) -> MultivariateNormal:
-        """
+        r"""
         :return: Analytic marginal :math:`p(\mathbf y)`.
         """
         return super().marginal(function_dist, *args, **kwargs)
@@ -186,7 +186,7 @@ def log_marginal(
         return res * ~missing_idx
 
     def marginal(self, function_dist: MultivariateNormal, *args: Any, **kwargs: Any) -> MultivariateNormal:
-        """
+        r"""
         :return: Analytic marginal :math:`p(\mathbf y)`.
         """
         return super().marginal(function_dist, *args, **kwargs)
@@ -306,14 +306,14 @@ def _shaped_noise_covar(self, base_shape: torch.Size, *params: Any, **kwargs: An
         return res
 
     def marginal(self, function_dist: MultivariateNormal, *args: Any, **kwargs: Any) -> MultivariateNormal:
-        """
+        r"""
         :return: Analytic marginal :math:`p(\mathbf y)`.
         """
         return super().marginal(function_dist, *args, **kwargs)
 
 
 class DirichletClassificationLikelihood(FixedNoiseGaussianLikelihood):
-    """
+    r"""
     A classification likelihood that treats the labels as regression targets with fixed heteroscedastic noise.
     From Milios et al, NeurIPS, 2018 [https://arxiv.org/abs/1805.10915].
 
@@ -408,7 +408,7 @@ def get_fantasy_likelihood(self, **kwargs: Any) -> "DirichletClassificationLikel
         return fantasy_liklihood
 
     def marginal(self, function_dist: MultivariateNormal, *args: Any, **kwargs: Any) -> MultivariateNormal:
-        """
+        r"""
         :return: Analytic marginal :math:`p(\mathbf y)`.
         """
         return super().marginal(function_dist, *args, **kwargs)