Add stratified sum as competition

For example used in RSLVQ

prototorch/functions/competitions.py

@@ -3,7 +3,26 @@
 import torch
 
 
+def stratified_sum(
+        value: torch.Tensor,
+        labels: torch.LongTensor) -> (torch.Tensor, torch.LongTensor):
+    """Group-wise sum"""
+    uniques = labels.unique(sorted=True).tolist()
+    labels = labels.tolist()
+
+    key_val = {key: val for key, val in zip(uniques, range(len(uniques)))}
+    labels = torch.LongTensor(list(map(key_val.get, labels)))
+
+    labels = labels.view(labels.size(0), 1).expand(-1, value.size(1))
+
+    unique_labels = labels.unique(dim=0)
+    result = torch.zeros_like(unique_labels, dtype=torch.float).scatter_add_(
+        0, labels, value)
+    return result.T
+
+
 def stratified_min(distances, labels):
+    """Group-wise minimum"""
     clabels = torch.unique(labels, dim=0)
     num_classes = clabels.size()[0]
     if distances.size()[1] == num_classes: