[Refactor] Add Modules for prior distrbutions

prototorch/functions/transforms.py

@@ -1,5 +1,32 @@
 import torch
 
 
-def gaussian(distance, variance):
+# Functions
-    return torch.exp(-(distance * distance) / (2 * variance))
+def gaussian(distances, variance):
+    return torch.exp(-(distances * distances) / (2 * variance))
+
+
+def rank_scaled_gaussian(distances, lambd):
+    order = torch.argsort(distances, dim=1)
+    ranks = torch.argsort(order, dim=1)
+
+    return torch.exp(-torch.exp(-ranks / lambd) * distances)
+
+
+# Modules
+class GaussianPrior(torch.nn.Module):
+    def __init__(self, variance):
+        super().__init__()
+        self.variance = variance
+
+    def forward(self, distances):
+        return gaussian(distances, self.variance)
+
+
+class RankScaledGaussianPrior(torch.nn.Module):
+    def __init__(self, lambd):
+        super().__init__()
+        self.lambd = lambd
+
+    def forward(self, distances):
+        return rank_scaled_gaussian(distances, self.lambd)