Added the divide-by-sum importance measure and removed the normalize-by-std importance measure.

code/pruning.py

 import torch
-import copy
-import math
 import os
 import numpy as np
 
@@ -27,15 +25,8 @@ def softmax(inp):
     return torch.softmax(inp, dim=-1)
 
 
-def normalize_std(inp):
-    """
-    Divides by std of the initialization,
-     but because the std is only variable in the term math.sqrt(1/float(fan_in + fan_out)),
-      we divide by that instead
-    """
-    # TODO: this is only for GLOROT UNIFORM, implement the others when needed
-    fan_in, fan_out = torch.nn.init._calculate_fan_in_and_fan_out(inp)
-    return inp / math.sqrt(1 / float(fan_in + fan_out))
+def normalize_sum(inp):
+    return inp/inp.sum()
 
 
 def prune_by_magnitude(model: torch.nn.Module, percentage=0.2, transformation=identity):