amend

backslash.py

@@ -1,4 +1,11 @@
 import torch
+
+rdo = 2e3
+clip = 1
+gamma_table = torch.load("data/gamma_table.pt")
+r_gamma_table = torch.load("data/r_gamma_table.pt")
+
+
 def backslash(model):
     with torch.no_grad():
         device = torch.device("cuda:0")
@@ -11,16 +18,16 @@ def backslash(model):
             var += torch.sum((param ** 2).to(device))
             mean += torch.sum(torch.abs(param).to(device))
         r_gamma = (n * var / mean ** 2).to(device=torch.device("cpu"))
-        pos = torch.argmin(torch.abs(r_gamma - model.r_gamma_table))
-        shape = model.gamma_table[pos]
+        pos = torch.argmin(torch.abs(r_gamma - r_gamma_table))
+        shape = gamma_table[pos]
         std = torch.sqrt(var / n)
         n = torch.tensor(n)
 
         # Rate Constrained Optimization
         for param in model.parameters():
-            constant = model.rdo * shape / n * torch.sign(param.data)
+            constant = rdo * shape / n * torch.sign(param.data)
             param_reg = torch.pow(
-                torch.abs(param.data) + model.clip, shape - 1)
+                torch.abs(param.data) + clip, shape - 1)
             param.data -= constant * param_reg
         distribution = {"shape": shape, "standard": std}
     return distribution

data/gamma_table.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4525076935eaf656655b070bdbb390bf3b48088991b39894024bfca5a2c0225
+size 2352

data/r_gamma_table.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:086241d0f92a1570315b68613c6de94eec3e048bc9fef8e2f3f83ac1180bb718
+size 2362